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Sample records for intel cluster tools

  1. New compilers speed up applications for Intel-based systems; Intel Compilers pave the way for Intel's Hyper-threading technology

    CERN Multimedia

    2002-01-01

    "Intel Corporation today introduced updated tools to help software developers optimize applications for Intel's expanding family of architectures with key innovations such as Intel's Hyper Threading Technology (1 page).

  2. Theorem Proving in Intel Hardware Design

    Science.gov (United States)

    O'Leary, John

    2009-01-01

    For the past decade, a framework combining model checking (symbolic trajectory evaluation) and higher-order logic theorem proving has been in production use at Intel. Our tools and methodology have been used to formally verify execution cluster functionality (including floating-point operations) for a number of Intel products, including the Pentium(Registered TradeMark)4 and Core(TradeMark)i7 processors. Hardware verification in 2009 is much more challenging than it was in 1999 - today s CPU chip designs contain many processor cores and significant firmware content. This talk will attempt to distill the lessons learned over the past ten years, discuss how they apply to today s problems, outline some future directions.

  3. Accessing Intel FPGAs for Acceleration

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    In this presentation, we will discuss the latest tools and products from Intel that enables FPGAs to be deployed as Accelerators. We will first talk about the Acceleration Stack for Intel Xeon CPU with FPGAs which makes it easy to create, verify, and execute functions on the Intel Programmable Acceleration Card in a Data Center. We will then talk about the OpenCL flow which allows parallel software developers to create FPGA systems and deploy them using the OpenCL standard. Next, we will talk about the Intel High-Level Synthesis compiler which can convert C++ code into custom RTL code optimized for Intel FPGAs. Lastly, we will focus on the task of running Machine Learning inference on the FPGA leveraging some of the tools we discussed. About the speaker Karl Qi is Sr. Staff Applications Engineer, Technical Training. He has been with the Customer Training department at Altera/Intel for 8 years. Most recently, he is responsible for all training content relating to High-Level Design tools, including the OpenCL...

  4. Implementation of High-Order Multireference Coupled-Cluster Methods on Intel Many Integrated Core Architecture.

    Science.gov (United States)

    Aprà, E; Kowalski, K

    2016-03-08

    In this paper we discuss the implementation of multireference coupled-cluster formalism with singles, doubles, and noniterative triples (MRCCSD(T)), which is capable of taking advantage of the processing power of the Intel Xeon Phi coprocessor. We discuss the integration of two levels of parallelism underlying the MRCCSD(T) implementation with computational kernels designed to offload the computationally intensive parts of the MRCCSD(T) formalism to Intel Xeon Phi coprocessors. Special attention is given to the enhancement of the parallel performance by task reordering that has improved load balancing in the noniterative part of the MRCCSD(T) calculations. We also discuss aspects regarding efficient optimization and vectorization strategies.

  5. Unlock performance secrets of next-gen Intel hardware

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    Intel® Xeon Phi Product. About the speaker Zakhar is a software architect in Intel SSG group. His current role is Parallel Studio architect with focus on SIMD vector parallelism assistance tools. Before it he was working as Intel Advisor XE software architect and software development team-lead. Before joining Intel he was...

  6. Time-efficient simulations of tight-binding electronic structures with Intel Xeon PhiTM many-core processors

    Science.gov (United States)

    Ryu, Hoon; Jeong, Yosang; Kang, Ji-Hoon; Cho, Kyu Nam

    2016-12-01

    Modelling of multi-million atomic semiconductor structures is important as it not only predicts properties of physically realizable novel materials, but can accelerate advanced device designs. This work elaborates a new Technology-Computer-Aided-Design (TCAD) tool for nanoelectronics modelling, which uses a sp3d5s∗ tight-binding approach to describe multi-million atomic structures, and simulate electronic structures with high performance computing (HPC), including atomic effects such as alloy and dopant disorders. Being named as Quantum simulation tool for Advanced Nanoscale Devices (Q-AND), the tool shows nice scalability on traditional multi-core HPC clusters implying the strong capability of large-scale electronic structure simulations, particularly with remarkable performance enhancement on latest clusters of Intel Xeon PhiTM coprocessors. A review of the recent modelling study conducted to understand an experimental work of highly phosphorus-doped silicon nanowires, is presented to demonstrate the utility of Q-AND. Having been developed via Intel Parallel Computing Center project, Q-AND will be open to public to establish a sound framework of nanoelectronics modelling with advanced HPC clusters of a many-core base. With details of the development methodology and exemplary study of dopant electronics, this work will present a practical guideline for TCAD development to researchers in the field of computational nanoelectronics.

  7. Scientific Computing and Apple's Intel Transition

    CERN Document Server

    CERN. Geneva

    2006-01-01

    Intel's published processor roadmap and how it may affect the future of personal and scientific computing About the speaker: Eric Albert is Senior Software Engineer in Apple's Core Technologies group. During Mac OS X's transition to Intel processors he has worked on almost every part of the operating system, from the OS kernel and compiler tools to appli...

  8. Multi-Kepler GPU vs. multi-Intel MIC for spin systems simulations

    Science.gov (United States)

    Bernaschi, M.; Bisson, M.; Salvadore, F.

    2014-10-01

    We present and compare the performances of two many-core architectures: the Nvidia Kepler and the Intel MIC both in a single system and in cluster configuration for the simulation of spin systems. As a benchmark we consider the time required to update a single spin of the 3D Heisenberg spin glass model by using the Over-relaxation algorithm. We present data also for a traditional high-end multi-core architecture: the Intel Sandy Bridge. The results show that although on the two Intel architectures it is possible to use basically the same code, the performances of a Intel MIC change dramatically depending on (apparently) minor details. Another issue is that to obtain a reasonable scalability with the Intel Phi coprocessor (Phi is the coprocessor that implements the MIC architecture) in a cluster configuration it is necessary to use the so-called offload mode which reduces the performances of the single system. As to the GPU, the Kepler architecture offers a clear advantage with respect to the previous Fermi architecture maintaining exactly the same source code. Scalability of the multi-GPU implementation remains very good by using the CPU as a communication co-processor of the GPU. All source codes are provided for inspection and for double-checking the results.

  9. Intel: High Throughput Computing Collaboration: A CERN openlab / Intel collaboration

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    The Intel/CERN High Throughput Computing Collaboration studies the application of upcoming Intel technologies to the very challenging environment of the LHC trigger and data-acquisition systems. These systems will need to transport and process many terabits of data every second, in some cases with tight latency constraints. Parallelisation and tight integration of accelerators and classical CPU via Intel's OmniPath fabric are the key elements in this project.

  10. Towards Porting a Real-World Seismological Application to the Intel MIC Architecture

    OpenAIRE

    V. Weinberg

    2014-01-01

    This whitepaper aims to discuss first experiences with porting an MPI-based real-world geophysical application to the new Intel Many Integrated Core (MIC) architecture. The selected code SeisSol is an application written in Fortran that can be used to simulate earthquake rupture and radiating seismic wave propagation in complex 3-D heterogeneous materials. The PRACE prototype cluster EURORA at CINECA, Italy, was accessed to analyse the MPI-performance of SeisSol on Intel Xeon Phi on both sing...

  11. Lawrence Livermore National Laboratory selects Intel Itanium 2 processors for world's most powerful Linux cluster

    CERN Multimedia

    2003-01-01

    "Intel Corporation, system manufacturer California Digital and the University of California at Lawrence Livermore National Laboratory (LLNL) today announced they are building one of the world's most powerful supercomputers. The supercomputer project, codenamed "Thunder," uses nearly 4,000 Intel® Itanium® 2 processors... is expected to be complete in January 2004" (1 page).

  12. Protein Alignment on the Intel Xeon Phi Coprocessor

    OpenAIRE

    Ramstad, Jorun

    2015-01-01

    There is an increasing need for sensitive, high perfomance sequence alignemnet tools. With the growing databases of scientificly analyzed protein sequences, more compute power is necessary. Specialized architectures arise, and a transition from serial to specialized implementationsis is required. This thesis is a study of whether Intel 60's cores Xeon Phi coprocessor is a suitable architecture for implementation of a sequence alignment tool. The performance relative to existing tools are eval...

  13. Intel Galileo essentials

    CERN Document Server

    Grimmett, Richard

    2015-01-01

    This book is for anyone who has ever been curious about using the Intel Galileo to create electronics projects. Some programming background is useful, but if you know how to use a personal computer, with the aid of the step-by-step instructions in this book, you can construct complex electronics projects that use the Intel Galileo.

  14. Intel Xeon Phi coprocessor high performance programming

    CERN Document Server

    Jeffers, James

    2013-01-01

    Authors Jim Jeffers and James Reinders spent two years helping educate customers about the prototype and pre-production hardware before Intel introduced the first Intel Xeon Phi coprocessor. They have distilled their own experiences coupled with insights from many expert customers, Intel Field Engineers, Application Engineers and Technical Consulting Engineers, to create this authoritative first book on the essentials of programming for this new architecture and these new products. This book is useful even before you ever touch a system with an Intel Xeon Phi coprocessor. To ensure that your applications run at maximum efficiency, the authors emphasize key techniques for programming any modern parallel computing system whether based on Intel Xeon processors, Intel Xeon Phi coprocessors, or other high performance microprocessors. Applying these techniques will generally increase your program performance on any system, and better prepare you for Intel Xeon Phi coprocessors and the Intel MIC architecture. It off...

  15. Efficient Implementation of Many-body Quantum Chemical Methods on the Intel Xeon Phi Coprocessor

    Energy Technology Data Exchange (ETDEWEB)

    Apra, Edoardo; Klemm, Michael; Kowalski, Karol

    2014-12-01

    This paper presents the implementation and performance of the highly accurate CCSD(T) quantum chemistry method on the Intel Xeon Phi coprocessor within the context of the NWChem computational chemistry package. The widespread use of highly correlated methods in electronic structure calculations is contingent upon the interplay between advances in theory and the possibility of utilizing the ever-growing computer power of emerging heterogeneous architectures. We discuss the design decisions of our implementation as well as the optimizations applied to the compute kernels and data transfers between host and coprocessor. We show the feasibility of adopting the Intel Many Integrated Core Architecture and the Intel Xeon Phi coprocessor for developing efficient computational chemistry modeling tools. Remarkable scalability is demonstrated by benchmarks. Our solution scales up to a total of 62560 cores with the concurrent utilization of Intel Xeon processors and Intel Xeon Phi coprocessors.

  16. Cost/Performance Ratio Achieved by Using a Commodity-Based Cluster

    Science.gov (United States)

    Lopez, Isaac

    2001-01-01

    Researchers at the NASA Glenn Research Center acquired a commodity cluster based on Intel Corporation processors to compare its performance with a traditional UNIX cluster in the execution of aeropropulsion applications. Since the cost differential of the clusters was significant, a cost/performance ratio was calculated. After executing a propulsion application on both clusters, the researchers demonstrated a 9.4 cost/performance ratio in favor of the Intel-based cluster. These researchers utilize the Aeroshark cluster as one of the primary testbeds for developing NPSS parallel application codes and system software. The Aero-shark cluster provides 64 Intel Pentium II 400-MHz processors, housed in 32 nodes. Recently, APNASA - a code developed by a Government/industry team for the design and analysis of turbomachinery systems was used for a simulation on Glenn's Aeroshark cluster.

  17. Home automation with Intel Galileo

    CERN Document Server

    Dundar, Onur

    2015-01-01

    This book is for anyone who wants to learn Intel Galileo for home automation and cross-platform software development. No knowledge of programming with Intel Galileo is assumed, but knowledge of the C programming language is essential.

  18. Investigating the Use of the Intel Xeon Phi for Event Reconstruction

    Science.gov (United States)

    Sherman, Keegan; Gilfoyle, Gerard

    2014-09-01

    The physics goal of Jefferson Lab is to understand how quarks and gluons form nuclei and it is being upgraded to a higher, 12-GeV beam energy. The new CLAS12 detector in Hall B will collect 5-10 terabytes of data per day and will require considerable computing resources. We are investigating tools, such as the Intel Xeon Phi, to speed up the event reconstruction. The Kalman Filter is one of the methods being studied. It is a linear algebra algorithm that estimates the state of a system by combining existing data and predictions of those measurements. The tools required to apply this technique (i.e. matrix multiplication, matrix inversion) are being written using C++ intrinsics for Intel's Xeon Phi Coprocessor, which uses the Many Integrated Cores (MIC) architecture. The Intel MIC is a new high-performance chip that connects to a host machine through the PCIe bus and is built to run highly vectorized and parallelized code making it a well-suited device for applications such as the Kalman Filter. Our tests of the MIC optimized algorithms needed for the filter show significant increases in speed. For example, matrix multiplication of 5x5 matrices on the MIC was able to run up to 69 times faster than the host core. The physics goal of Jefferson Lab is to understand how quarks and gluons form nuclei and it is being upgraded to a higher, 12-GeV beam energy. The new CLAS12 detector in Hall B will collect 5-10 terabytes of data per day and will require considerable computing resources. We are investigating tools, such as the Intel Xeon Phi, to speed up the event reconstruction. The Kalman Filter is one of the methods being studied. It is a linear algebra algorithm that estimates the state of a system by combining existing data and predictions of those measurements. The tools required to apply this technique (i.e. matrix multiplication, matrix inversion) are being written using C++ intrinsics for Intel's Xeon Phi Coprocessor, which uses the Many Integrated Cores (MIC

  19. Parallel solution of the time-dependent Ginzburg-Landau equations and other experiences using BlockComm-Chameleon and PCN on the IBM SP, Intel iPSC/860, and clusters of workstations

    International Nuclear Information System (INIS)

    Coskun, E.

    1995-09-01

    Time-dependent Ginzburg-Landau (TDGL) equations are considered for modeling a thin-film finite size superconductor placed under magnetic field. The problem then leads to the use of so-called natural boundary conditions. Computational domain is partitioned into subdomains and bond variables are used in obtaining the corresponding discrete system of equations. An efficient time-differencing method based on the Forward Euler method is developed. Finally, a variable strength magnetic field resulting in a vortex motion in Type II High T c superconducting films is introduced. The authors tackled the problem using two different state-of-the-art parallel computing tools: BlockComm/Chameleon and PCN. They had access to two high-performance distributed memory supercomputers: the Intel iPSC/860 and IBM SP1. They also tested the codes using, as a parallel computing environment, a cluster of Sun Sparc workstations

  20. Effective SIMD Vectorization for Intel Xeon Phi Coprocessors

    OpenAIRE

    Tian, Xinmin; Saito, Hideki; Preis, Serguei V.; Garcia, Eric N.; Kozhukhov, Sergey S.; Masten, Matt; Cherkasov, Aleksei G.; Panchenko, Nikolay

    2015-01-01

    Efficiently exploiting SIMD vector units is one of the most important aspects in achieving high performance of the application code running on Intel Xeon Phi coprocessors. In this paper, we present several effective SIMD vectorization techniques such as less-than-full-vector loop vectorization, Intel MIC specific alignment optimization, and small matrix transpose/multiplication 2D vectorization implemented in the Intel C/C++ and Fortran production compilers for Intel Xeon Phi coprocessors. A ...

  1. INTEL: Intel based systems move up in supercomputing ranks

    CERN Multimedia

    2002-01-01

    "The TOP500 supercomputer rankings released today at the Supercomputing 2002 conference show a dramatic increase in the number of Intel-based systems being deployed in high-performance computing (HPC) or supercomputing areas" (1/2 page).

  2. Computation cluster for Monte Carlo calculations

    Energy Technology Data Exchange (ETDEWEB)

    Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S. [Dep. Of Nuclear Physics and Technology, Faculty of Electrical Engineering and Information, Technology, Slovak Technical University, Ilkovicova 3, 81219 Bratislava (Slovakia)

    2010-07-01

    Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)

  3. Computation cluster for Monte Carlo calculations

    International Nuclear Information System (INIS)

    Petriska, M.; Vitazek, K.; Farkas, G.; Stacho, M.; Michalek, S.

    2010-01-01

    Two computation clusters based on Rocks Clusters 5.1 Linux distribution with Intel Core Duo and Intel Core Quad based computers were made at the Department of the Nuclear Physics and Technology. Clusters were used for Monte Carlo calculations, specifically for MCNP calculations applied in Nuclear reactor core simulations. Optimization for computation speed was made on hardware and software basis. Hardware cluster parameters, such as size of the memory, network speed, CPU speed, number of processors per computation, number of processors in one computer were tested for shortening the calculation time. For software optimization, different Fortran compilers, MPI implementations and CPU multi-core libraries were tested. Finally computer cluster was used in finding the weighting functions of neutron ex-core detectors of VVER-440. (authors)

  4. Effective SIMD Vectorization for Intel Xeon Phi Coprocessors

    Directory of Open Access Journals (Sweden)

    Xinmin Tian

    2015-01-01

    Full Text Available Efficiently exploiting SIMD vector units is one of the most important aspects in achieving high performance of the application code running on Intel Xeon Phi coprocessors. In this paper, we present several effective SIMD vectorization techniques such as less-than-full-vector loop vectorization, Intel MIC specific alignment optimization, and small matrix transpose/multiplication 2D vectorization implemented in the Intel C/C++ and Fortran production compilers for Intel Xeon Phi coprocessors. A set of workloads from several application domains is employed to conduct the performance study of our SIMD vectorization techniques. The performance results show that we achieved up to 12.5x performance gain on the Intel Xeon Phi coprocessor. We also demonstrate a 2000x performance speedup from the seamless integration of SIMD vectorization and parallelization.

  5. Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

    OpenAIRE

    Koskela, TS; Lobet, M

    2017-01-01

    In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science appl...

  6. Parallel Programming with Intel Parallel Studio XE

    CERN Document Server

    Blair-Chappell , Stephen

    2012-01-01

    Optimize code for multi-core processors with Intel's Parallel Studio Parallel programming is rapidly becoming a "must-know" skill for developers. Yet, where to start? This teach-yourself tutorial is an ideal starting point for developers who already know Windows C and C++ and are eager to add parallelism to their code. With a focus on applying tools, techniques, and language extensions to implement parallelism, this essential resource teaches you how to write programs for multicore and leverage the power of multicore in your programs. Sharing hands-on case studies and real-world examples, the

  7. Optimizing the updated Goddard shortwave radiation Weather Research and Forecasting (WRF) scheme for Intel Many Integrated Core (MIC) architecture

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.

    2015-05-01

    Intel Many Integrated Core (MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our results of optimizing the updated Goddard shortwave radiation Weather Research and Forecasting (WRF) scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The co-processor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of Xeon Phi will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.3x.

  8. Cluster development in the SA tooling industry

    Directory of Open Access Journals (Sweden)

    Von Leipzig, Konrad

    2015-11-01

    Full Text Available This paper explores the concept of clustering in general, analysing research and experiences in different countries and regions, and summarising factors leading to success or contributing to failure of specific cluster initiatives. Based on this, requirements for the establishment of clusters are summarised. Next, initiatives especially in the South African tool and die making (TDM industry are considered. Through a benchmarking approach, the strengths and weaknesses of individual local tool rooms are analysed, and conclusions are drawn particularly about South African characteristics of the industry. From these results, and from structured interviews with individual tool room owners, difficulties in the establishment of a South African tooling cluster are explored, and specific areas of concern are pointed out.

  9. Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme

    Science.gov (United States)

    Mielikainen, J.; Huang, B.; Huang, A. H.-L.

    2014-12-01

    The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same optimizations

  10. BioCluster: Tool for Identification and Clustering of Enterobacteriaceae Based on Biochemical Data

    Directory of Open Access Journals (Sweden)

    Ahmed Abdullah

    2015-06-01

    Full Text Available Presumptive identification of different Enterobacteriaceae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochemical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor-intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and similarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface (GUI tool named BioCluster. This tool was designed for automated clustering and identification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering (HC and the Improved Hierarchical Clustering (IHC, a modified algorithm that was developed specifically for the clustering and identification of Enterobacteriaceae species. IHC takes into account the variability in result of 1–47 biochemical tests within this Enterobacteriaceae family. This tool also provides different options to optimize the clustering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http://microbialgen.du.ac.bd/biocluster/.

  11. [Intel random number generator-based true random number generator].

    Science.gov (United States)

    Huang, Feng; Shen, Hong

    2004-09-01

    To establish a true random number generator on the basis of certain Intel chips. The random numbers were acquired by programming using Microsoft Visual C++ 6.0 via register reading from the random number generator (RNG) unit of an Intel 815 chipset-based computer with Intel Security Driver (ISD). We tested the generator with 500 random numbers in NIST FIPS 140-1 and X(2) R-Squared test, and the result showed that the random number it generated satisfied the demand of independence and uniform distribution. We also compared the random numbers generated by Intel RNG-based true random number generator and those from the random number table statistically, by using the same amount of 7500 random numbers in the same value domain, which showed that the SD, SE and CV of Intel RNG-based random number generator were less than those of the random number table. The result of u test of two CVs revealed no significant difference between the two methods. Intel RNG-based random number generator can produce high-quality random numbers with good independence and uniform distribution, and solves some problems with random number table in acquisition of the random numbers.

  12. Using the Intel Math Kernel Library on Peregrine | High-Performance

    Science.gov (United States)

    Computing | NREL the Intel Math Kernel Library on Peregrine Using the Intel Math Kernel Library on Peregrine Learn how to use the Intel Math Kernel Library (MKL) with Peregrine system software. MKL architectures. Core math functions in MKL include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier

  13. Cluster-based DBMS Management Tool with High-Availability

    Directory of Open Access Journals (Sweden)

    Jae-Woo Chang

    2005-02-01

    Full Text Available A management tool which is needed for monitoring and managing cluster-based DBMSs has been little studied. So, we design and implement a cluster-based DBMS management tool with high-availability that monitors the status of nodes in a cluster system as well as the status of DBMS instances in a node. The tool enables users to recognize a single virtual system image and provides them with the status of all the nodes and resources in the system by using a graphic user interface (GUI. By using a load balancer, our management tool can increase the performance of a cluster-based DBMS as well as can overcome the limitation of the existing parallel DBMSs.

  14. Comparative VME Performance Tests for MEN A20 Intel-L865 and RIO-3 PPC-LynxOS platforms

    CERN Document Server

    Andersen, M; CERN. Geneva. BE Department

    2009-01-01

    This benchmark note presents test results from reading values over VME using different methods and different sizes of data registers, running on two different platforms Intel-L865 and PPC-LynxOS. We find that the PowerPC is a factor 3 faster in accessing an array of contiguous VME memory locations. Block transfer and DMA read accesses are also tested and compared with conventional single access reads.

  15. CERN welcomes Intel Science Fair winners

    CERN Multimedia

    Katarina Anthony

    2012-01-01

    This June, CERN welcomed twelve gifted young scientists aged 15-18 for a week-long visit of the Laboratory. These talented students were the winners of a special award co-funded by CERN and Intel, given yearly at the Intel International Science and Engineering Fair (ISEF).   The CERN award winners at the Intel ISEF 2012 Special Awards Ceremony. © Society for Science & the Public (SSP). The CERN award was set up back in 2009 as an opportunity to bring some of the best and brightest young minds to the Laboratory. The award winners are selected from among 1,500 talented students participating in ISEF – the world's largest pre-university science competition, in which students compete for more than €3 million in awards. “CERN gave an award – which was obviously this trip – to students studying physics, maths, electrical engineering and computer science,” says Benjamin Craig Bartlett, 17, from South Carolina, USA, wh...

  16. Revisiting Intel Xeon Phi optimization of Thompson cloud microphysics scheme in Weather Research and Forecasting (WRF) model

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen

    2015-10-01

    The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large number of improvements. Thus, we have optimized the speed of this important part of WRF. Intel Many Integrated Core (MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our results of optimizing the Thompson microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. New optimizations for an updated Thompson scheme are discusses in this paper. The optimizations improved the performance of the original Thompson code on Xeon Phi 7120P by a factor of 1.8x. Furthermore, the same optimizations improved the performance of the Thompson on a dual socket configuration of eight core Intel Xeon E5-2670 CPUs by a factor of 1.8x compared to the original Thompson code.

  17. Experience with Intel's Many Integrated Core Architecture in ATLAS Software

    CERN Document Server

    Fleischmann, S; The ATLAS collaboration; Lavrijsen, W; Neumann, M; Vitillo, R

    2014-01-01

    Intel recently released the first commercial boards of its Many Integrated Core (MIC) Architecture. MIC is Intel's solution for the domain of throughput computing, currently dominated by general purpose programming on graphics processors (GPGPU). MIC allows the use of the more familiar x86 programming model and supports standard technologies such as OpenMP, MPI, and Intel's Threading Building Blocks. This should make it possible to develop for both throughput and latency devices using a single code base.\

  18. Experience with Intel's Many Integrated Core Architecture in ATLAS Software

    CERN Document Server

    Fleischmann, S; The ATLAS collaboration; Lavrijsen, W; Neumann, M; Vitillo, R

    2013-01-01

    Intel recently released the first commercial boards of its Many Integrated Core (MIC) Architecture. MIC is Intel's solution for the domain of throughput computing, currently dominated by general purpose programming on graphics processors (GPGPU). MIC allows the use of the more familiar x86 programming model and supports standard technologies such as OpenMP, MPI, and Intel's Threading Building Blocks. This should make it possible to develop for both throughput and latency devices using a single code base.\

  19. Game-Based Experiential Learning in Online Management Information Systems Classes Using Intel's IT Manager 3

    Science.gov (United States)

    Bliemel, Michael; Ali-Hassan, Hossam

    2014-01-01

    For several years, we used Intel's flash-based game "IT Manager 3: Unseen Forces" as an experiential learning tool, where students had to act as a manager making real-time prioritization decisions about repairing computer problems, training and upgrading systems with better technologies as well as managing increasing numbers of technical…

  20. Performance of Artificial Intelligence Workloads on the Intel Core 2 Duo Series Desktop Processors

    OpenAIRE

    Abdul Kareem PARCHUR; Kuppangari Krishna RAO; Fazal NOORBASHA; Ram Asaray SINGH

    2010-01-01

    As the processor architecture becomes more advanced, Intel introduced its Intel Core 2 Duo series processors. Performance impact on Intel Core 2 Duo processors are analyzed using SPEC CPU INT 2006 performance numbers. This paper studied the behavior of Artificial Intelligence (AI) benchmarks on Intel Core 2 Duo series processors. Moreover, we estimated the task completion time (TCT) @1 GHz, @2 GHz and @3 GHz Intel Core 2 Duo series processors frequency. Our results show the performance scalab...

  1. Comparison of Processor Performance of SPECint2006 Benchmarks of some Intel Xeon Processors

    Directory of Open Access Journals (Sweden)

    Abdul Kareem PARCHUR

    2012-08-01

    Full Text Available High performance is a critical requirement to all microprocessors manufacturers. The present paper describes the comparison of performance in two main Intel Xeon series processors (Type A: Intel Xeon X5260, X5460, E5450 and L5320 and Type B: Intel Xeon X5140, 5130, 5120 and E5310. The microarchitecture of these processors is implemented using the basis of a new family of processors from Intel starting with the Pentium 4 processor. These processors can provide a performance boost for many key application areas in modern generation. The scaling of performance in two major series of Intel Xeon processors (Type A: Intel Xeon X5260, X5460, E5450 and L5320 and Type B: Intel Xeon X5140, 5130, 5120 and E5310 has been analyzed using the performance numbers of 12 CPU2006 integer benchmarks, performance numbers that exhibit significant differences in performance. The results and analysis can be used by performance engineers, scientists and developers to better understand the performance scaling in modern generation processors.

  2. MPIGeneNet: Parallel Calculation of Gene Co-Expression Networks on Multicore Clusters.

    Science.gov (United States)

    Gonzalez-Dominguez, Jorge; Martin, Maria J

    2017-10-10

    In this work we present MPIGeneNet, a parallel tool that applies Pearson's correlation and Random Matrix Theory to construct gene co-expression networks. It is based on the state-of-the-art sequential tool RMTGeneNet, which provides networks with high robustness and sensitivity at the expenses of relatively long runtimes for large scale input datasets. MPIGeneNet returns the same results as RMTGeneNet but improves the memory management, reduces the I/O cost, and accelerates the two most computationally demanding steps of co-expression network construction by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on two different systems using three typical input datasets shows that MPIGeneNet is significantly faster than RMTGeneNet. As an example, our tool is up to 175.41 times faster on a cluster with eight nodes, each one containing two 12-core Intel Haswell processors. Source code of MPIGeneNet, as well as a reference manual, are available at https://sourceforge.net/projects/mpigenenet/.

  3. Adaptation of MPDATA Heterogeneous Stencil Computation to Intel Xeon Phi Coprocessor

    Directory of Open Access Journals (Sweden)

    Lukasz Szustak

    2015-01-01

    Full Text Available The multidimensional positive definite advection transport algorithm (MPDATA belongs to the group of nonoscillatory forward-in-time algorithms and performs a sequence of stencil computations. MPDATA is one of the major parts of the dynamic core of the EULAG geophysical model. In this work, we outline an approach to adaptation of the 3D MPDATA algorithm to the Intel MIC architecture. In order to utilize available computing resources, we propose the (3 + 1D decomposition of MPDATA heterogeneous stencil computations. This approach is based on combination of the loop tiling and fusion techniques. It allows us to ease memory/communication bounds and better exploit the theoretical floating point efficiency of target computing platforms. An important method of improving the efficiency of the (3 + 1D decomposition is partitioning of available cores/threads into work teams. It permits for reducing inter-cache communication overheads. This method also increases opportunities for the efficient distribution of MPDATA computation onto available resources of the Intel MIC architecture, as well as Intel CPUs. We discuss preliminary performance results obtained on two hybrid platforms, containing two CPUs and Intel Xeon Phi. The top-of-the-line Intel Xeon Phi 7120P gives the best performance results, and executes MPDATA almost 2 times faster than two Intel Xeon E5-2697v2 CPUs.

  4. Comparison of Processor Performance of SPECint2006 Benchmarks of some Intel Xeon Processors

    OpenAIRE

    Abdul Kareem PARCHUR; Ram Asaray SINGH

    2012-01-01

    High performance is a critical requirement to all microprocessors manufacturers. The present paper describes the comparison of performance in two main Intel Xeon series processors (Type A: Intel Xeon X5260, X5460, E5450 and L5320 and Type B: Intel Xeon X5140, 5130, 5120 and E5310). The microarchitecture of these processors is implemented using the basis of a new family of processors from Intel starting with the Pentium 4 processor. These processors can provide a performance boost for many ke...

  5. Intel Many Integrated Core (MIC) architecture optimization strategies for a memory-bound Weather Research and Forecasting (WRF) Goddard microphysics scheme

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

    2014-10-01

    The Goddard cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The WRF is a widely used weather prediction system in the world. It development is a done in collaborative around the globe. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the code of this important part of WRF. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU do. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 4.7x. Furthermore, the same optimizations improved performance on a dual socket Intel Xeon E5-2670 system by a factor of 2.8x compared to the original code.

  6. MILC staggered conjugate gradient performance on Intel KNL

    OpenAIRE

    DeTar, Carleton; Doerfler, Douglas; Gottlieb, Steven; Jha, Ashish; Kalamkar, Dhiraj; Li, Ruizi; Toussaint, Doug

    2016-01-01

    We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second gener- ation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. ...

  7. Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

    Energy Technology Data Exchange (ETDEWEB)

    Koskela, Tuomas S.; Lobet, Mathieu; Deslippe, Jack; Matveev, Zakhar

    2017-05-23

    In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After

  8. Performance tuning Weather Research and Forecasting (WRF) Goddard longwave radiative transfer scheme on Intel Xeon Phi

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

    2015-10-01

    Next-generation mesoscale numerical weather prediction system, the Weather Research and Forecasting (WRF) model, is a designed for dual use for forecasting and research. WRF offers multiple physics options that can be combined in any way. One of the physics options is radiance computation. The major source for energy for the earth's climate is solar radiation. Thus, it is imperative to accurately model horizontal and vertical distribution of the heating. Goddard solar radiative transfer model includes the absorption duo to water vapor,ozone, ozygen, carbon dioxide, clouds and aerosols. The model computes the interactions among the absorption and scattering by clouds, aerosols, molecules and surface. Finally, fluxes are integrated over the entire longwave spectrum.In this paper, we present our results of optimizing the Goddard longwave radiative transfer scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The optimizations improved the performance of the original Goddard longwave radiative transfer scheme on Xeon Phi 7120P by a factor of 2.2x. Furthermore, the same optimizations improved the performance of the Goddard longwave radiative transfer scheme on a dual socket configuration of eight core Intel Xeon E5-2670 CPUs by a factor of 2.1x compared to the original Goddard longwave radiative transfer scheme code.

  9. Performance of Artificial Intelligence Workloads on the Intel Core 2 Duo Series Desktop Processors

    Directory of Open Access Journals (Sweden)

    Abdul Kareem PARCHUR

    2010-12-01

    Full Text Available As the processor architecture becomes more advanced, Intel introduced its Intel Core 2 Duo series processors. Performance impact on Intel Core 2 Duo processors are analyzed using SPEC CPU INT 2006 performance numbers. This paper studied the behavior of Artificial Intelligence (AI benchmarks on Intel Core 2 Duo series processors. Moreover, we estimated the task completion time (TCT @1 GHz, @2 GHz and @3 GHz Intel Core 2 Duo series processors frequency. Our results show the performance scalability in Intel Core 2 Duo series processors. Even though AI benchmarks have similar execution time, they have dissimilar characteristics which are identified using principal component analysis and dendogram. As the processor frequency increased from 1.8 GHz to 3.167 GHz the execution time is decreased by ~370 sec for AI workloads. In the case of Physics/Quantum Computing programs it was ~940 sec.

  10. Parallelization of particle transport using Intel® TBB

    International Nuclear Information System (INIS)

    Apostolakis, J; Brun, R; Carminati, F; Gheata, A; Wenzel, S; Belogurov, S; Ovcharenko, E

    2014-01-01

    One of the current challenges in HEP computing is the development of particle propagation algorithms capable of efficiently use all performance aspects of modern computing devices. The Geant-Vector project at CERN has recently introduced an approach in this direction. This paper describes the implementation of a similar workflow using the Intel(r) Threading Building Blocks (Intel(r) TBB) library. This approach is intended to overcome the potential bottleneck of having a single dispatcher on many-core architectures and to result in better scalability compared to the initial pthreads-based version.

  11. Performance of a plasma fluid code on the Intel parallel computers

    International Nuclear Information System (INIS)

    Lynch, V.E.; Carreras, B.A.; Drake, J.B.; Leboeuf, J.N.; Liewer, P.

    1992-01-01

    One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchtone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchtone Delta machine, the corresponding improvement factor is 16. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel σ machine gives an improvement factor close to 64 over the single-processor CRAY-2

  12. Performance of a plasma fluid code on the Intel parallel computers

    Science.gov (United States)

    Lynch, V. E.; Carreras, B. A.; Drake, J. B.; Leboeuf, J. N.; Liewer, P.

    1992-01-01

    One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchtone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchtone Delta machine, the corresponding improvement factor is 16. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel (sigma) machine gives an improvement factor close to 64 over the single-processor CRAY-2.

  13. Performance Evaluation of Multithreaded Geant4 Simulations Using an Intel Xeon Phi Cluster

    Directory of Open Access Journals (Sweden)

    P. Schweitzer

    2015-01-01

    Full Text Available The objective of this study is to evaluate the performances of Intel Xeon Phi hardware accelerators for Geant4 simulations, especially for multithreaded applications. We present the complete methodology to guide users for the compilation of their Geant4 applications on Phi processors. Then, we propose series of benchmarks to compare the performance of Xeon CPUs and Phi processors for a Geant4 example dedicated to the simulation of electron dose point kernels, the TestEm12 example. First, we compare a distributed execution of a sequential version of the Geant4 example on both architectures before evaluating the multithreaded version of the Geant4 example. If Phi processors demonstrated their ability to accelerate computing time (till a factor 3.83 when distributing sequential Geant4 simulations, we do not reach the same level of speedup when considering the multithreaded version of the Geant4 example.

  14. GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

    Science.gov (United States)

    Wang, Hui; Chen, Huansheng; Wu, Qizhong; Lin, Junmin; Chen, Xueshun; Xie, Xinwei; Wang, Rongrong; Tang, Xiao; Wang, Zifa

    2017-08-01

    The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC), KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1) updating the pure Message Passing Interface (MPI) parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2) fully employing the 512 bit wide vector processing units (VPUs) on the KNL platform; (3) reducing unnecessary memory access to improve cache efficiency; (4) reducing the thread local storage (TLS) in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5) changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined performance and energy

  15. Performance of a plasma fluid code on the Intel parallel computers

    International Nuclear Information System (INIS)

    Lynch, V.E.; Carreras, B.A.; Drake, J.B.; Leboeuf, J.N.; Liewer, P.

    1992-01-01

    One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A parallel algorithm for plasma turbulence calculations was tested on the Intel iPSC/860 hypercube and the Touchtone Delta machine. Using the 128 processors of the Intel iPSC/860 hypercube, a factor of 5 improvement over a single-processor CRAY-2 is obtained. For the Touchtone Delta machine, the corresponding improvement factor is 16. For plasma edge turbulence calculations, an extrapolation of the present results to the Intel (sigma) machine gives an improvement factor close to 64 over the single-processor CRAY-2. 12 refs

  16. Analysis OpenMP performance of AMD and Intel architecture for breaking waves simulation using MPS

    Science.gov (United States)

    Alamsyah, M. N. A.; Utomo, A.; Gunawan, P. H.

    2018-03-01

    Simulation of breaking waves by using Navier-Stokes equation via moving particle semi-implicit method (MPS) over close domain is given. The results show the parallel computing on multicore architecture using OpenMP platform can reduce the computational time almost half of the serial time. Here, the comparison using two computer architectures (AMD and Intel) are performed. The results using Intel architecture is shown better than AMD architecture in CPU time. However, in efficiency, the computer with AMD architecture gives slightly higher than the Intel. For the simulation by 1512 number of particles, the CPU time using Intel and AMD are 12662.47 and 28282.30 respectively. Moreover, the efficiency using similar number of particles, AMD obtains 50.09 % and Intel up to 49.42 %.

  17. Network Analysis Tools: from biological networks to clusters and pathways.

    Science.gov (United States)

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

    2008-01-01

    Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

  18. Intel Corporation osaleb Eesti koolitusprogrammis / Raivo Juurak

    Index Scriptorium Estoniae

    Juurak, Raivo, 1949-

    2001-01-01

    Haridusministeeriumis tutvustati infotehnoloogiaalast koolitusprogrammi, milles osaleb maailma suuremaid arvutifirmasid Intel Corporation. Koolituskursuse käigus õpetatakse aineõpetajaid oma ainetundides interneti võimalusi kasutama. 50-tunnised kursused viiakse läbi kõigis maakondades

  19. CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles

    DEFF Research Database (Denmark)

    G. G. Nielsen, Fiona; Galschiøt Markus, Kasper; Møllegaard Friborg, Rune

    2012-01-01

    IP-profiling data and detect potentially meaningful patterns, the areas of enrichment must be aligned and clustered, which is an algorithmically and computationally challenging task. We have developed CATCHprofiles, a novel tool for exhaustive pattern detection in ChIP profiling data. CATCHprofiles is built upon...... a computationally efficient implementation for the exhaustive alignment and hierarchical clustering of ChIP profiling data. The tool features a graphical interface for examination and browsing of the clustering results. CATCHprofiles requires no prior knowledge about functional sites, detects known binding patterns...... it an invaluable tool for explorative research based on ChIP profiling data. CATCHprofiles and the CATCH algorithm run on all platforms and is available for free through the CATCH website: http://catch.cmbi.ru.nl/. User support is available by subscribing to the mailing list catch-users@bioinformatics.org....

  20. 75 FR 21353 - Intel Corporation, Fab 20 Division, Including On-Site Leased Workers From Volt Technical...

    Science.gov (United States)

    2010-04-23

    ... DEPARTMENT OF LABOR Employment and Training Administration [TA-W-73,642] Intel Corporation, Fab 20... of Intel Corporation, Fab 20 Division, including on-site leased workers of Volt Technical Resources... Precision, Inc. were employed on-site at the Hillsboro, Oregon location of Intel Corporation, Fab 20...

  1. MILC staggered conjugate gradient performance on Intel KNL

    Energy Technology Data Exchange (ETDEWEB)

    Li, Ruiz [Indiana Univ., Bloomington, IN (United States). Dept. of Physics; Detar, Carleton [Univ. of Utah, Salt Lake City, UT (United States). Dept. of Physics and Astronomy; Doerfler, Douglas W. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC); Gottlieb, Steven [Indiana Univ., Bloomington, IN (United States). Dept. of Physics; Jha, Asish [Intel Corp., Hillsboro, OR (United States). Sofware and Services Group; Kalamkar, Dhiraj [Intel Labs., Bangalore (India). Parallel Computing Lab.; Toussaint, Doug [Univ. of Arizona, Tucson, AZ (United States). Physics Dept.

    2016-11-03

    We review our work done to optimize the staggered conjugate gradient (CG) algorithm in the MILC code for use with the Intel Knights Landing (KNL) architecture. KNL is the second gener- ation Intel Xeon Phi processor. It is capable of massive thread parallelism, data parallelism, and high on-board memory bandwidth and is being adopted in supercomputing centers for scientific research. The CG solver consumes the majority of time in production running, so we have spent most of our effort on it. We compare performance of an MPI+OpenMP baseline version of the MILC code with a version incorporating the QPhiX staggered CG solver, for both one-node and multi-node runs.

  2. GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS on Intel Xeon Phi processors

    Directory of Open Access Journals (Sweden)

    H. Wang

    2017-08-01

    Full Text Available The Global Nested Air Quality Prediction Modeling System (GNAQPMS is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS, which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL. Compared with the first-generation Xeon Phi coprocessor (codenamed Knights Corner, KNC, KNL has many new hardware features such as a bootable processor, high-performance in-package memory and ISA compatibility with Intel Xeon processors. In particular, we describe the five optimisations we applied to the key modules of GNAQPMS, including the CBM-Z gas-phase chemistry, advection, convection and wet deposition modules. These optimisations work well on both the KNL 7250 processor and the Intel Xeon E5-2697 V4 processor. They include (1 updating the pure Message Passing Interface (MPI parallel mode to the hybrid parallel mode with MPI and OpenMP in the emission, advection, convection and gas-phase chemistry modules; (2 fully employing the 512 bit wide vector processing units (VPUs on the KNL platform; (3 reducing unnecessary memory access to improve cache efficiency; (4 reducing the thread local storage (TLS in the CBM-Z gas-phase chemistry module to improve its OpenMP performance; and (5 changing the global communication from writing/reading interface files to MPI functions to improve the performance and the parallel scalability. These optimisations greatly improved the GNAQPMS performance. The same optimisations also work well for the Intel Xeon Broadwell processor, specifically E5-2697 v4. Compared with the baseline version of GNAQPMS, the optimised version was 3.51 × faster on KNL and 2.77 × faster on the CPU. Moreover, the optimised version ran at 26 % lower average power on KNL than on the CPU. With the combined

  3. Lattice QCD with Domain Decomposition on Intel Xeon Phi Co-Processors

    Energy Technology Data Exchange (ETDEWEB)

    Heybrock, Simon; Joo, Balint; Kalamkar, Dhiraj D; Smelyanskiy, Mikhail; Vaidyanathan, Karthikeyan; Wettig, Tilo; Dubey, Pradeep

    2014-12-01

    The gap between the cost of moving data and the cost of computing continues to grow, making it ever harder to design iterative solvers on extreme-scale architectures. This problem can be alleviated by alternative algorithms that reduce the amount of data movement. We investigate this in the context of Lattice Quantum Chromodynamics and implement such an alternative solver algorithm, based on domain decomposition, on Intel Xeon Phi co-processor (KNC) clusters. We demonstrate close-to-linear on-chip scaling to all 60 cores of the KNC. With a mix of single- and half-precision the domain-decomposition method sustains 400-500 Gflop/s per chip. Compared to an optimized KNC implementation of a standard solver [1], our full multi-node domain-decomposition solver strong-scales to more nodes and reduces the time-to-solution by a factor of 5.

  4. An INTEL 8080 microprocessor development system

    International Nuclear Information System (INIS)

    Horne, P.J.

    1977-01-01

    The INTEL 8080 has become one of the two most widely used microprocessors at CERN, the other being the MOTOROLA 6800. Even thouth this is the case, there have been, to date, only rudimentary facilities available for aiding the development of application programs for this microprocessor. An ideal development system is one which has a sophisticated editing and filing system, an assembler/compiler, and access to the microprocessor application. In many instances access to a PROM programmer is also required, as the application may utilize only PROMs for program storage. With these thoughts in mind, an INTEL 8080 microprocessor development system was implemented in the Proton Synchrotron (PS) Division. This system utilizes a PDP 11/45 as the editing and file-handling machine, and an MSC 8/MOD 80 microcomputer for assembling, PROM programming and debugging user programs at run time. The two machines are linked by an existing CAMAC crate system which will also provide the means of access to microprocessor applications in CAMAC and the interface of the development system to any other application. (Auth.)

  5. Evaluation of the OpenCL AES Kernel using the Intel FPGA SDK for OpenCL

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Zheming [Argonne National Lab. (ANL), Argonne, IL (United States); Yoshii, Kazutomo [Argonne National Lab. (ANL), Argonne, IL (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-04-20

    The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. In this report, we evaluate the performance of the kernel using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board. Compared to the M506 module, the board provides more hardware resources for a larger design exploration space. The kernel performance is measured with the compute kernel throughput, an upper bound to the FPGA throughput. The report presents the experimental results in details. The Appendix lists the kernel source code.

  6. Vectorization for Molecular Dynamics on Intel Xeon Phi Corpocessors

    Science.gov (United States)

    Yi, Hongsuk

    2014-03-01

    Many modern processors are capable of exploiting data-level parallelism through the use of single instruction multiple data (SIMD) execution. The new Intel Xeon Phi coprocessor supports 512 bit vector registers for the high performance computing. In this paper, we have developed a hierarchical parallelization scheme for accelerated molecular dynamics simulations with the Terfoff potentials for covalent bond solid crystals on Intel Xeon Phi coprocessor systems. The scheme exploits multi-level parallelism computing. We combine thread-level parallelism using a tightly coupled thread-level and task-level parallelism with 512-bit vector register. The simulation results show that the parallel performance of SIMD implementations on Xeon Phi is apparently superior to their x86 CPU architecture.

  7. 75 FR 48338 - Intel Corporation; Analysis of Proposed Consent Order to Aid Public Comment

    Science.gov (United States)

    2010-08-10

    ... product road maps, its compilers, and product benchmarking (Sections VI, VII, and VIII). The Proposed... alleges that Intel's failure to fully disclose the changes it made to its compilers and libraries... benchmarking organizations the effects of its compiler redesign on non-Intel CPUs. Several benchmarking...

  8. A comparison of SuperLU solvers on the intel MIC architecture

    Science.gov (United States)

    Tuncel, Mehmet; Duran, Ahmet; Celebi, M. Serdar; Akaydin, Bora; Topkaya, Figen O.

    2016-10-01

    In many science and engineering applications, problems may result in solving a sparse linear system AX=B. For example, SuperLU_MCDT, a linear solver, was used for the large penta-diagonal matrices for 2D problems and hepta-diagonal matrices for 3D problems, coming from the incompressible blood flow simulation (see [1]). It is important to test the status and potential improvements of state-of-the-art solvers on new technologies. In this work, sequential, multithreaded and distributed versions of SuperLU solvers (see [2]) are examined on the Intel Xeon Phi coprocessors using offload programming model at the EURORA cluster of CINECA in Italy. We consider a portfolio of test matrices containing patterned matrices from UFMM ([3]) and randomly located matrices. This architecture can benefit from high parallelism and large vectors. We find that the sequential SuperLU benefited up to 45 % performance improvement from the offload programming depending on the sparse matrix type and the size of transferred and processed data.

  9. Windows for Intel Macs

    CERN Document Server

    Ogasawara, Todd

    2008-01-01

    Even the most devoted Mac OS X user may need to use Windows XP, or may just be curious about XP and its applications. This Short Cut is a concise guide for OS X users who need to quickly get comfortable and become productive with Windows XP basics on their Macs. It covers: Security Networking ApplicationsMac users can easily install and use Windows thanks to Boot Camp and Parallels Desktop for Mac. Boot Camp lets an Intel-based Mac install and boot Windows XP on its own hard drive partition. Parallels Desktop for Mac uses virtualization technology to run Windows XP (or other operating systems

  10. Optimizing Performance of Combustion Chemistry Solvers on Intel's Many Integrated Core (MIC) Architectures

    Energy Technology Data Exchange (ETDEWEB)

    Sitaraman, Hariswaran [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Grout, Ray W [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-06-09

    This work investigates novel algorithm designs and optimization techniques for restructuring chemistry integrators in zero and multidimensional combustion solvers, which can then be effectively used on the emerging generation of Intel's Many Integrated Core/Xeon Phi processors. These processors offer increased computing performance via large number of lightweight cores at relatively lower clock speeds compared to traditional processors (e.g. Intel Sandybridge/Ivybridge) used in current supercomputers. This style of processor can be productively used for chemistry integrators that form a costly part of computational combustion codes, in spite of their relatively lower clock speeds. Performance commensurate with traditional processors is achieved here through the combination of careful memory layout, exposing multiple levels of fine grain parallelism and through extensive use of vendor supported libraries (Cilk Plus and Math Kernel Libraries). Important optimization techniques for efficient memory usage and vectorization have been identified and quantified. These optimizations resulted in a factor of ~ 3 speed-up using Intel 2013 compiler and ~ 1.5 using Intel 2017 compiler for large chemical mechanisms compared to the unoptimized version on the Intel Xeon Phi. The strategies, especially with respect to memory usage and vectorization, should also be beneficial for general purpose computational fluid dynamics codes.

  11. Connecting Effective Instruction and Technology. Intel-elebration: Safari.

    Science.gov (United States)

    Burton, Larry D.; Prest, Sharon

    Intel-ebration is an attempt to integrate the following research-based instructional frameworks and strategies: (1) dimensions of learning; (2) multiple intelligences; (3) thematic instruction; (4) cooperative learning; (5) project-based learning; and (6) instructional technology. This paper presents a thematic unit on safari, using the…

  12. CAMSHIFT Tracker Design Experiments With Intel OpenCV and SAI

    National Research Council Canada - National Science Library

    Francois, Alexandre R

    2004-01-01

    ... (including multi-modal) systems, must be specifically addressed. This report describes design and implementation experiments for CAMSHIFT-based tracking systems using Intel's Open Computer Vision library and SAI...

  13. Full cycle trigonometric function on Intel Quartus II Verilog

    Science.gov (United States)

    Mustapha, Muhazam; Zulkarnain, Nur Antasha

    2018-02-01

    This paper discusses about an improvement of a previous research on hardware based trigonometric calculations. Tangent function will also be implemented to get a complete set. The functions have been simulated using Quartus II where the result will be compared to the previous work. The number of bits has also been extended for each trigonometric function. The design is based on RTL due to its resource efficient nature. At earlier stage, a technology independent test bench simulation was conducted on ModelSim due to its convenience in capturing simulation data so that accuracy information can be obtained. On second stage, Intel/Altera Quartus II will be used to simulate on technology dependent platform, particularly on the one belonging to Intel/Altera itself. Real data on no. logic elements used and propagation delay have also been obtained.

  14. Accelerating the Pace of Protein Functional Annotation With Intel Xeon Phi Coprocessors.

    Science.gov (United States)

    Feinstein, Wei P; Moreno, Juana; Jarrell, Mark; Brylinski, Michal

    2015-06-01

    Intel Xeon Phi is a new addition to the family of powerful parallel accelerators. The range of its potential applications in computationally driven research is broad; however, at present, the repository of scientific codes is still relatively limited. In this study, we describe the development and benchmarking of a parallel version of eFindSite, a structural bioinformatics algorithm for the prediction of ligand-binding sites in proteins. Implemented for the Intel Xeon Phi platform, the parallelization of the structure alignment portion of eFindSite using pragma-based OpenMP brings about the desired performance improvements, which scale well with the number of computing cores. Compared to a serial version, the parallel code runs 11.8 and 10.1 times faster on the CPU and the coprocessor, respectively; when both resources are utilized simultaneously, the speedup is 17.6. For example, ligand-binding predictions for 501 benchmarking proteins are completed in 2.1 hours on a single Stampede node equipped with the Intel Xeon Phi card compared to 3.1 hours without the accelerator and 36.8 hours required by a serial version. In addition to the satisfactory parallel performance, porting existing scientific codes to the Intel Xeon Phi architecture is relatively straightforward with a short development time due to the support of common parallel programming models by the coprocessor. The parallel version of eFindSite is freely available to the academic community at www.brylinski.org/efindsite.

  15. Extension of the AMBER molecular dynamics software to Intel's Many Integrated Core (MIC) architecture

    Science.gov (United States)

    Needham, Perri J.; Bhuiyan, Ashraf; Walker, Ross C.

    2016-04-01

    We present an implementation of explicit solvent particle mesh Ewald (PME) classical molecular dynamics (MD) within the PMEMD molecular dynamics engine, that forms part of the AMBER v14 MD software package, that makes use of Intel Xeon Phi coprocessors by offloading portions of the PME direct summation and neighbor list build to the coprocessor. We refer to this implementation as pmemd MIC offload and in this paper present the technical details of the algorithm, including basic models for MPI and OpenMP configuration, and analyze the resultant performance. The algorithm provides the best performance improvement for large systems (>400,000 atoms), achieving a ∼35% performance improvement for satellite tobacco mosaic virus (1,067,095 atoms) when 2 Intel E5-2697 v2 processors (2 ×12 cores, 30M cache, 2.7 GHz) are coupled to an Intel Xeon Phi coprocessor (Model 7120P-1.238/1.333 GHz, 61 cores). The implementation utilizes a two-fold decomposition strategy: spatial decomposition using an MPI library and thread-based decomposition using OpenMP. We also present compiler optimization settings that improve the performance on Intel Xeon processors, while retaining simulation accuracy.

  16. Trusted Computing Technologies, Intel Trusted Execution Technology.

    Energy Technology Data Exchange (ETDEWEB)

    Guise, Max Joseph; Wendt, Jeremy Daniel

    2011-01-01

    We describe the current state-of-the-art in Trusted Computing Technologies - focusing mainly on Intel's Trusted Execution Technology (TXT). This document is based on existing documentation and tests of two existing TXT-based systems: Intel's Trusted Boot and Invisible Things Lab's Qubes OS. We describe what features are lacking in current implementations, describe what a mature system could provide, and present a list of developments to watch. Critical systems perform operation-critical computations on high importance data. In such systems, the inputs, computation steps, and outputs may be highly sensitive. Sensitive components must be protected from both unauthorized release, and unauthorized alteration: Unauthorized users should not access the sensitive input and sensitive output data, nor be able to alter them; the computation contains intermediate data with the same requirements, and executes algorithms that the unauthorized should not be able to know or alter. Due to various system requirements, such critical systems are frequently built from commercial hardware, employ commercial software, and require network access. These hardware, software, and network system components increase the risk that sensitive input data, computation, and output data may be compromised.

  17. Radiation Failures in Intel 14nm Microprocessors

    Science.gov (United States)

    Bossev, Dobrin P.; Duncan, Adam R.; Gadlage, Matthew J.; Roach, Austin H.; Kay, Matthew J.; Szabo, Carl; Berger, Tammy J.; York, Darin A.; Williams, Aaron; LaBel, K.; hide

    2016-01-01

    In this study the 14 nm Intel Broadwell 5th generation core series 5005U-i3 and 5200U-i5 was mounted on Dell Inspiron laptops, MSI Cubi and Gigabyte Brix barebones and tested with Windows 8 and CentOS7 at idle. Heavy-ion-induced hard- and catastrophic failures do not appear to be related to the Intel 14nm Tri-Gate FinFET process. They originate from a small (9 m 140 m) area on the 32nm planar PCH die (not the CPU) as initially speculated. The hard failures seem to be due to a SEE but the exact physical mechanism has yet to be identified. Some possibilities include latch-ups, charge ion trapping or implantation, ion channels, or a combination of those (in biased conditions). The mechanism of the catastrophic failures seems related to the presence of electric power (1.05V core voltage). The 1064 nm laser mimics ionization radiation and induces soft- and hard failures as a direct result of electron-hole pair production, not heat. The 14nm FinFET processes continue to look promising for space radiation environments.

  18. Real-time data acquisition and feedback control using Linux Intel computers

    International Nuclear Information System (INIS)

    Penaflor, B.G.; Ferron, J.R.; Piglowski, D.A.; Johnson, R.D.; Walker, M.L.

    2006-01-01

    This paper describes the experiences of the DIII-D programming staff in adapting Linux based Intel computing hardware for use in real-time data acquisition and feedback control systems. Due to the highly dynamic and unstable nature of magnetically confined plasmas in tokamak fusion experiments, real-time data acquisition and feedback control systems are in routine use with all major tokamaks. At DIII-D, plasmas are created and sustained using a real-time application known as the digital plasma control system (PCS). During each experiment, the PCS periodically samples data from hundreds of diagnostic signals and provides these data to control algorithms implemented in software. These algorithms compute the necessary commands to send to various actuators that affect plasma performance. The PCS consists of a group of rack mounted Intel Xeon computer systems running an in-house customized version of the Linux operating system tailored specifically to meet the real-time performance needs of the plasma experiments. This paper provides a more detailed description of the real-time computing hardware and custom developed software, including recent work to utilize dual Intel Xeon equipped computers within the PCS

  19. Analysis of Intel IA-64 Processor Support for Secure Systems

    National Research Council Canada - National Science Library

    Unalmis, Bugra

    2001-01-01

    .... Systems could be constructed for which serious security threats would be eliminated. This thesis explores the Intel IA-64 processor's hardware support and its relationship to software for building a secure system...

  20. Experience with Intel's many integrated core architecture in ATLAS software

    International Nuclear Information System (INIS)

    Fleischmann, S; Neumann, M; Kama, S; Lavrijsen, W; Vitillo, R

    2014-01-01

    Intel recently released the first commercial boards of its Many Integrated Core (MIC) Architecture. MIC is Intel's solution for the domain of throughput computing, currently dominated by general purpose programming on graphics processors (GPGPU). MIC allows the use of the more familiar x86 programming model and supports standard technologies such as OpenMP, MPI, and Intel's Threading Building Blocks (TBB). This should make it possible to develop for both throughput and latency devices using a single code base. In ATLAS Software, track reconstruction has been shown to be a good candidate for throughput computing on GPGPU devices. In addition, the newly proposed offline parallel event-processing framework, GaudiHive, uses TBB for task scheduling. The MIC is thus, in principle, a good fit for this domain. In this paper, we report our experiences of porting to and optimizing ATLAS tracking algorithms for the MIC, comparing the programmability and relative cost/performance of the MIC against those of current GPGPUs and latency-optimized CPUs.

  1. Scaling Deep Learning Workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

    Energy Technology Data Exchange (ETDEWEB)

    Gawande, Nitin A.; Landwehr, Joshua B.; Daily, Jeffrey A.; Tallent, Nathan R.; Vishnu, Abhinav; Kerbyson, Darren J.

    2017-07-03

    Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors --- including NVIDIA, Intel, AMD and IBM --- have architectural road-maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. This paper provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path. Our evaluation consists of a cross section of convolutional neural net workloads: CifarNet, CaffeNet, AlexNet and GoogleNet topologies using the Cifar10 and ImageNet datasets. The workloads are vendor optimized for each architecture. GPUs provide the highest overall raw performance. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and KNL can be competitive when considering performance/watt. Furthermore, NVLink is critical to GPU scaling.

  2. Evaluation of the Intel Westmere-EX server processor

    CERN Document Server

    Jarp, S; Leduc, J; Nowak, A; CERN. Geneva. IT Department

    2011-01-01

    One year after the arrival of the Intel Xeon 7500 systems (“Nehalem-EX”), CERN openlab is presenting a set of benchmark results obtained when running on the new Xeon E7-4870 Processors, representing the “Westmere-EX” family. A modern 4-socket, 40-core system is confronted with the previous generation of expandable (“EX”) platforms, represented by a 4-socket, 32-core Intel Xeon X7560 based system – both being “top of the line” systems. Benchmarking of modern processors is a very complex affair. One has to control (at least) the following features: processor frequency, overclocking via Turbo mode, the number of physical cores in use, the use of logical cores via Symmetric MultiThreading (SMT), the cache sizes available, the configured memory topology, as well as the power configuration if throughput per watt is to be measured. As in previous activities, we have tried to do a good job of comparing like with like. In a “top of the line” comparison based on the HEPSPEC06 benchmark, the “We...

  3. Cluster Flow: A user-friendly bioinformatics workflow tool [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Philip Ewels

    2016-12-01

    Full Text Available Pipeline tools are becoming increasingly important within the field of bioinformatics. Using a pipeline manager to manage and run workflows comprised of multiple tools reduces workload and makes analysis results more reproducible. Existing tools require significant work to install and get running, typically needing pipeline scripts to be written from scratch before running any analysis. We present Cluster Flow, a simple and flexible bioinformatics pipeline tool designed to be quick and easy to install. Cluster Flow comes with 40 modules for common NGS processing steps, ready to work out of the box. Pipelines are assembled using these modules with a simple syntax that can be easily modified as required. Core helper functions automate many common NGS procedures, making running pipelines simple. Cluster Flow is available with an GNU GPLv3 license on GitHub. Documentation, examples and an online demo are available at http://clusterflow.io.

  4. piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

    Science.gov (United States)

    Ray, Rishav; Pandey, Priyanka

    2017-12-19

    With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Performance Analysis of Memory Transfers and GEMM Subroutines on NVIDIA Tesla GPU Cluster

    Energy Technology Data Exchange (ETDEWEB)

    Allada, Veerendra, Benjegerdes, Troy; Bode, Brett

    2009-08-31

    Commodity clusters augmented with application accelerators are evolving as competitive high performance computing systems. The Graphical Processing Unit (GPU) with a very high arithmetic density and performance per price ratio is a good platform for the scientific application acceleration. In addition to the interconnect bottlenecks among the cluster compute nodes, the cost of memory copies between the host and the GPU device have to be carefully amortized to improve the overall efficiency of the application. Scientific applications also rely on efficient implementation of the BAsic Linear Algebra Subroutines (BLAS), among which the General Matrix Multiply (GEMM) is considered as the workhorse subroutine. In this paper, they study the performance of the memory copies and GEMM subroutines that are critical to port the computational chemistry algorithms to the GPU clusters. To that end, a benchmark based on the NetPIPE framework is developed to evaluate the latency and bandwidth of the memory copies between the host and the GPU device. The performance of the single and double precision GEMM subroutines from the NVIDIA CUBLAS 2.0 library are studied. The results have been compared with that of the BLAS routines from the Intel Math Kernel Library (MKL) to understand the computational trade-offs. The test bed is a Intel Xeon cluster equipped with NVIDIA Tesla GPUs.

  6. Performance Analysis of Memory Transfers and GEMM Subroutines on NVIDIA Tesla GPU Cluster

    International Nuclear Information System (INIS)

    Allada, Veerendra; Benjegerdes, Troy; Bode, Brett

    2009-01-01

    Commodity clusters augmented with application accelerators are evolving as competitive high performance computing systems. The Graphical Processing Unit (GPU) with a very high arithmetic density and performance per price ratio is a good platform for the scientific application acceleration. In addition to the interconnect bottlenecks among the cluster compute nodes, the cost of memory copies between the host and the GPU device have to be carefully amortized to improve the overall efficiency of the application. Scientific applications also rely on efficient implementation of the BAsic Linear Algebra Subroutines (BLAS), among which the General Matrix Multiply (GEMM) is considered as the workhorse subroutine. In this paper, they study the performance of the memory copies and GEMM subroutines that are critical to port the computational chemistry algorithms to the GPU clusters. To that end, a benchmark based on the NetPIPE framework is developed to evaluate the latency and bandwidth of the memory copies between the host and the GPU device. The performance of the single and double precision GEMM subroutines from the NVIDIA CUBLAS 2.0 library are studied. The results have been compared with that of the BLAS routines from the Intel Math Kernel Library (MKL) to understand the computational trade-offs. The test bed is a Intel Xeon cluster equipped with NVIDIA Tesla GPUs.

  7. Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture

    OpenAIRE

    Liu, Xu; Chen, Langshi; Firoz, Jesun S.; Qiu, Judy; Jiang, Lei

    2017-01-01

    Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we empirically evaluate various computing platforms including an Intel Xeon E5 CPU, a Nvidia Geforce GTX1070 GPU and an Xeon Phi 7210 processor codenamed Knights Landing (KNL) in the domain of parallel graph processing. We show that the KNL gains encouraging per...

  8. Intel Legend and CERN would build up high speed Internet

    CERN Multimedia

    2002-01-01

    Intel, Legend and China Education and Research Network jointly announced on the 25th of April that they will be cooperating with each other to build up the new generation high speed internet, over the next three years (1/2 page).

  9. Staggered Dslash Performance on Intel Xeon Phi Architecture

    OpenAIRE

    Li, Ruizi; Gottlieb, Steven

    2014-01-01

    The conjugate gradient (CG) algorithm is among the most essential and time consuming parts of lattice calculations with staggered quarks. We test the performance of CG and dslash, the key step in the CG algorithm, on the Intel Xeon Phi, also known as the Many Integrated Core (MIC) architecture. We try different parallelization strategies using MPI, OpenMP, and the vector processing units (VPUs).

  10. Global synchronization algorithms for the Intel iPSC/860

    Science.gov (United States)

    Seidel, Steven R.; Davis, Mark A.

    1992-01-01

    In a distributed memory multicomputer that has no global clock, global processor synchronization can only be achieved through software. Global synchronization algorithms are used in tridiagonal systems solvers, CFD codes, sequence comparison algorithms, and sorting algorithms. They are also useful for event simulation, debugging, and for solving mutual exclusion problems. For the Intel iPSC/860 in particular, global synchronization can be used to ensure the most effective use of the communication network for operations such as the shift, where each processor in a one-dimensional array or ring concurrently sends a message to its right (or left) neighbor. Three global synchronization algorithms are considered for the iPSC/860: the gysnc() primitive provided by Intel, the PICL primitive sync0(), and a new recursive doubling synchronization (RDS) algorithm. The performance of these algorithms is compared to the performance predicted by communication models of both the long and forced message protocols. Measurements of the cost of shift operations preceded by global synchronization show that the RDS algorithm always synchronizes the nodes more precisely and costs only slightly more than the other two algorithms.

  11. Scaling deep learning workloads: NVIDIA DGX-1/Pascal and Intel Knights Landing

    Energy Technology Data Exchange (ETDEWEB)

    Gawande, Nitin A.; Landwehr, Joshua B.; Daily, Jeffrey A.; Tallent, Nathan R.; Vishnu, Abhinav; Kerbyson, Darren J.

    2017-08-24

    Deep Learning (DL) algorithms have become ubiquitous in data analytics. As a result, major computing vendors --- including NVIDIA, Intel, AMD, and IBM --- have architectural road-maps influenced by DL workloads. Furthermore, several vendors have recently advertised new computing products as accelerating large DL workloads. Unfortunately, it is difficult for data scientists to quantify the potential of these different products. This paper provides a performance and power analysis of important DL workloads on two major parallel architectures: NVIDIA DGX-1 (eight Pascal P100 GPUs interconnected with NVLink) and Intel Knights Landing (KNL) CPUs interconnected with Intel Omni-Path or Cray Aries. Our evaluation consists of a cross section of convolutional neural net workloads: CifarNet, AlexNet, GoogLeNet, and ResNet50 topologies using the Cifar10 and ImageNet datasets. The workloads are vendor-optimized for each architecture. Our analysis indicates that although GPUs provide the highest overall performance, the gap can close for some convolutional networks; and the KNL can be competitive in performance/watt. We find that NVLink facilitates scaling efficiency on GPUs. However, its importance is heavily dependent on neural network architecture. Furthermore, for weak-scaling --- sometimes encouraged by restricted GPU memory --- NVLink is less important.

  12. High-performance computing on the Intel Xeon Phi how to fully exploit MIC architectures

    CERN Document Server

    Wang, Endong; Shen, Bo; Zhang, Guangyong; Lu, Xiaowei; Wu, Qing; Wang, Yajuan

    2014-01-01

    The aim of this book is to explain to high-performance computing (HPC) developers how to utilize the Intel® Xeon Phi™ series products efficiently. To that end, it introduces some computing grammar, programming technology and optimization methods for using many-integrated-core (MIC) platforms and also offers tips and tricks for actual use, based on the authors' first-hand optimization experience.The material is organized in three sections. The first section, "Basics of MIC", introduces the fundamentals of MIC architecture and programming, including the specific Intel MIC programming environment

  13. Educational clusters as a tool ofpublic policy on the market of educational services

    OpenAIRE

    M. I. Vorona

    2016-01-01

    Due to the new challenges, the implementation of cluster technology can be considired to be one of the innovative and promising tools of national and regional economy’ competitiveness raise. The cluster approach can be used is in different areas, but most attention in thie article has been paid to the problems of industrial clusters. At the same time, educational clusters remain to be poorly implemented in practice and, consequently, they are less studied theoretically. The aim of the arti...

  14. Exploring synchrotron radiation capabilities: The ALS-Intel CRADA

    International Nuclear Information System (INIS)

    Gozzo, F.; Cossy-Favre, A.; Padmore, H.

    1997-01-01

    Synchrotron radiation spectroscopy and spectromicroscopy were applied, at the Advanced Light Source, to the analysis of materials and problems of interest to the commercial semiconductor industry. The authors discuss some of the results obtained at the ALS using existing capabilities, in particular the small spot ultra-ESCA instrument on beamline 7.0 and the AMS (Applied Material Science) endstation on beamline 9.3.2. The continuing trend towards smaller feature size and increased performance for semiconductor components has driven the semiconductor industry to invest in the development of sophisticated and complex instrumentation for the characterization of microstructures. Among the crucial milestones established by the Semiconductor Industry Association are the needs for high quality, defect free and extremely clean silicon wafers, very thin gate oxides, lithographies near 0.1 micron and advanced material interconnect structures. The requirements of future generations cannot be met with current industrial technologies. The purpose of the ALS-Intel CRADA (Cooperative Research And Development Agreement) is to explore, compare and improve the utility of synchrotron-based techniques for practical analysis of substrates of interest to semiconductor chip manufacturing. The first phase of the CRADA project consisted in exploring existing ALS capabilities and techniques on some problems of interest. Some of the preliminary results obtained on Intel samples are discussed here

  15. Implementation of an Agent-Based Parallel Tissue Modelling Framework for the Intel MIC Architecture

    Directory of Open Access Journals (Sweden)

    Maciej Cytowski

    2017-01-01

    Full Text Available Timothy is a novel large scale modelling framework that allows simulating of biological processes involving different cellular colonies growing and interacting with variable environment. Timothy was designed for execution on massively parallel High Performance Computing (HPC systems. The high parallel scalability of the implementation allows for simulations of up to 109 individual cells (i.e., simulations at tissue spatial scales of up to 1 cm3 in size. With the recent advancements of the Timothy model, it has become critical to ensure appropriate performance level on emerging HPC architectures. For instance, the introduction of blood vessels supplying nutrients to the tissue is a very important step towards realistic simulations of complex biological processes, but it greatly increased the computational complexity of the model. In this paper, we describe the process of modernization of the application in order to achieve high computational performance on HPC hybrid systems based on modern Intel® MIC architecture. Experimental results on the Intel Xeon Phi™ coprocessor x100 and the Intel Xeon Phi processor x200 are presented.

  16. Intel·ligència emocional a maternal

    OpenAIRE

    Missé Cortina, Jordi

    2015-01-01

    Inclusió d'activitats d'intel·ligència emocional a maternal A i B per al treball de l'adquisició de valors com l'autoestima, el respecte, la tolerància, etc. Inclusión de actividades de inteligencia emocional en maternal A y B para el trabajo de la adquisición de valores como la autoestima, el respeto, la tolerancia, etc. Practicum for the Psychology program on Educational Psychology.

  17. Communication overhead on the Intel iPSC-860 hypercube

    Science.gov (United States)

    Bokhari, Shahid H.

    1990-01-01

    Experiments were conducted on the Intel iPSC-860 hypercube in order to evaluate the overhead of interprocessor communication. It is demonstrated that: (1) contrary to popular belief, the distance between two communicating processors has a significant impact on communication time, (2) edge contention can increase communication time by a factor of more than 7, and (3) node contention has no measurable impact.

  18. XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

    Science.gov (United States)

    2015-01-01

    Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

  19. Evaluating the transport layer of the ALFA framework for the Intel® Xeon Phi™ Coprocessor

    Science.gov (United States)

    Santogidis, Aram; Hirstius, Andreas; Lalis, Spyros

    2015-12-01

    The ALFA framework supports the software development of major High Energy Physics experiments. As part of our research effort to optimize the transport layer of ALFA, we focus on profiling its data transfer performance for inter-node communication on the Intel Xeon Phi Coprocessor. In this article we present the collected performance measurements with the related analysis of the results. The optimization opportunities that are discovered, help us to formulate the future plans of enabling high performance data transfer for ALFA on the Intel Xeon Phi architecture.

  20. Parallel Density-Based Clustering for Discovery of Ionospheric Phenomena

    Science.gov (United States)

    Pankratius, V.; Gowanlock, M.; Blair, D. M.

    2015-12-01

    Ionospheric total electron content maps derived from global networks of dual-frequency GPS receivers can reveal a plethora of ionospheric features in real-time and are key to space weather studies and natural hazard monitoring. However, growing data volumes from expanding sensor networks are making manual exploratory studies challenging. As the community is heading towards Big Data ionospheric science, automation and Computer-Aided Discovery become indispensable tools for scientists. One problem of machine learning methods is that they require domain-specific adaptations in order to be effective and useful for scientists. Addressing this problem, our Computer-Aided Discovery approach allows scientists to express various physical models as well as perturbation ranges for parameters. The search space is explored through an automated system and parallel processing of batched workloads, which finds corresponding matches and similarities in empirical data. We discuss density-based clustering as a particular method we employ in this process. Specifically, we adapt Density-Based Spatial Clustering of Applications with Noise (DBSCAN). This algorithm groups geospatial data points based on density. Clusters of points can be of arbitrary shape, and the number of clusters is not predetermined by the algorithm; only two input parameters need to be specified: (1) a distance threshold, (2) a minimum number of points within that threshold. We discuss an implementation of DBSCAN for batched workloads that is amenable to parallelization on manycore architectures such as Intel's Xeon Phi accelerator with 60+ general-purpose cores. This manycore parallelization can cluster large volumes of ionospheric total electronic content data quickly. Potential applications for cluster detection include the visualization, tracing, and examination of traveling ionospheric disturbances or other propagating phenomena. Acknowledgments. We acknowledge support from NSF ACI-1442997 (PI V. Pankratius).

  1. Lattice QCD calculations on commodity clusters at DESY

    International Nuclear Information System (INIS)

    Gellrich, A.; Pop, D.; Wegner, P.; Wittig, H.; Hasenbusch, M.; Jansen, K.

    2003-06-01

    Lattice Gauge Theory is an integral part of particle physics that requires high performance computing in the multi-Tflops regime. These requirements are motivated by the rich research program and the physics milestones to be reached by the lattice community. Over the last years the enormous gains in processor performance, memory bandwidth, and external I/O bandwidth for parallel applications have made commodity clusters exploiting PCs or workstations also suitable for large Lattice Gauge Theory applications. For more than one year two clusters have been operated at the two DESY sites in Hamburg and Zeuthen, consisting of 32 resp. 16 dual-CPU PCs, equipped with Intel Pentium 4 Xeon processors. Interconnection of the nodes is done by way of Myrinet. Linux was chosen as the operating system. In the course of the projects benchmark programs for architectural studies were developed. The performance of the Wilson-Dirac Operator (also in an even-odd preconditioned version) as the inner loop of the Lattice QCD (LQCD) algorithms plays the most important role in classifying the hardware basis to be used. Using the SIMD streaming extensions (SSE/SSE2) on Intel's Pentium 4 Xeon CPUs give promising results for both the single CPU and the parallel version. The parallel performance, in addition to the CPU power and the memory throughput, is nevertheless strongly influenced by the behavior of hardware components like the PC chip-set and the communication interfaces. The paper starts by giving a short explanation about the physics background and the motivation for using PC clusters for Lattice QCD. Subsequently, the concept, implementation, and operating experiences of the two clusters are discussed. Finally, the paper presents benchmark results and discusses comparisons to systems with different hardware components including Myrinet-, GigaBit-Ethernet-, and Infiniband-based interconnects. (orig.)

  2. Modulated modularity clustering as an exploratory tool for functional genomic inference.

    Directory of Open Access Journals (Sweden)

    Eric A Stone

    2009-05-01

    Full Text Available In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC, seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation.

  3. Mesa de coordenadas cartesianas (x,y para la perforación de materiales por medio de un microcontrolador 8051 de intel

    Directory of Open Access Journals (Sweden)

    Omar Yesid Flórez-Prada

    2001-01-01

    Full Text Available In our environment we are surrounded by a number of electronic systems that perform automatic operations according to a number of parameters previously programmed by the operator. This paper presents the prototype of a table of two coordinates (Cartesian plane (X, Y, which uses a development system based on the 8051 microcontroller INTEL (R (computer system, making the system function sending the respective control commands to locate the tool at different points of the work area of the table, the points are previously programmed by the operator, interacting with the keyboard. To make the movements of the table (X, Y, actuator devices responsible for carrying out a linear movement that moves the tool to the specified distance are used.

  4. Porting FEASTFLOW to the Intel Xeon Phi: Lessons Learned

    OpenAIRE

    Georgios Goumas

    2014-01-01

    In this paper we report our experiences in porting the FEASTFLOW software infrastructure to the Intel Xeon Phi coprocessor. Our efforts involved both the evaluation of programming models including OpenCL, POSIX threads and OpenMP and typical optimization strategies like parallelization and vectorization. Since the straightforward porting process of the already existing OpenCL version of the code encountered performance problems that require further analysis, we focused our efforts on the impl...

  5. Single event effect testing of the Intel 80386 family and the 80486 microprocessor

    International Nuclear Information System (INIS)

    Moran, A.; LaBel, K.; Gates, M.; Seidleck, C.; McGraw, R.; Broida, M.; Firer, J.; Sprehn, S.

    1996-01-01

    The authors present single event effect test results for the Intel 80386 microprocessor, the 80387 coprocessor, the 82380 peripheral device, and on the 80486 microprocessor. Both single event upset and latchup conditions were monitored

  6. Evaluation of CHO Benchmarks on the Arria 10 FPGA using Intel FPGA SDK for OpenCL

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Zheming [Argonne National Lab. (ANL), Argonne, IL (United States); Yoshii, Kazutomo [Argonne National Lab. (ANL), Argonne, IL (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-05-23

    The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. Benchmarking of OpenCL-based framework is an effective way for analyzing the performance of system by studying the execution of the benchmark applications. CHO is a suite of benchmark applications that provides support for OpenCL [1]. The authors presented CHO as an OpenCL port of the CHStone benchmark. Using Altera OpenCL (AOCL) compiler to synthesize the benchmark applications, they listed the resource usage and performance of each kernel that can be successfully synthesized by the compiler. In this report, we evaluate the resource usage and performance of the CHO benchmark applications using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board that features an Arria 10 FPGA device. The focus of the report is to have a better understanding of the resource usage and performance of the kernel implementations using Arria-10 FPGA devices compared to Stratix-5 FPGA devices. In addition, we also gain knowledge about the limitations of the current compiler when it fails to synthesize a benchmark

  7. Clustering Algorithm As A Planning Support Tool For Rural Electrification Optimization

    Directory of Open Access Journals (Sweden)

    Ronaldo Pornillosa Parreno Jr

    2015-08-01

    Full Text Available Abstract In this study clustering algorithm was developed to optimize electrification plans by screening and grouping potential customers to be supplied with electricity. The algorithm provided adifferent approach in clustering problem which combines conceptual and distance-based clustering algorithmsto analyze potential clusters using spanning tree with the shortest possible edge weight and creating final cluster trees based on the test of inconsistency for the edges. The clustering criteria consists of commonly used distance measure with the addition of household information as basis for the ability to pay ATP value. The combination of these two parameters resulted to a more significant and realistic clusters since distance measure alone could not take the effect of the household characteristics in screening the most sensible groupings of households. In addition the implications of varying geographical features were incorporated in the algorithm by using routing index across the locations of the households. This new approach of connecting the households in an area was applied in an actual case study of one village or barangay that was not yet energized. The results of clustering algorithm generated cluster trees which could becomethetheoretical basis for power utilities to plan the initial network arrangement of electrification. Scenario analysis conducted on the two strategies of clustering the households provideddifferent alternatives for the optimization of the cost of electrification. Futhermorethe benefits associated with the two strategies formulated from the two scenarios was evaluated using benefit cost ratio BC to determine which is more economically advantageous. The results of the study showed that clustering algorithm proved to be effective in solving electrification optimization problem and serves its purpose as a planning support tool which can facilitate electrification in rural areas and achieve cost-effectiveness.

  8. Heterogeneous Gpu&Cpu Cluster For High Performance Computing In Cryptography

    Directory of Open Access Journals (Sweden)

    Michał Marks

    2012-01-01

    Full Text Available This paper addresses issues associated with distributed computing systems andthe application of mixed GPU&CPU technology to data encryption and decryptionalgorithms. We describe a heterogenous cluster HGCC formed by twotypes of nodes: Intel processor with NVIDIA graphics processing unit and AMDprocessor with AMD graphics processing unit (formerly ATI, and a novel softwareframework that hides the heterogeneity of our cluster and provides toolsfor solving complex scientific and engineering problems. Finally, we present theresults of numerical experiments. The considered case study is concerned withparallel implementations of selected cryptanalysis algorithms. The main goal ofthe paper is to show the wide applicability of the GPU&CPU technology tolarge scale computation and data processing.

  9. Design tool for offshore wind farm cluster planning

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Madsen, Peter Hauge; Giebel, Gregor

    2015-01-01

    In the framework of the FP7 project EERA DTOC: Design Tool for Offshore wind farm Cluster, a new software supporting the planning of offshore wind farms was developed, based on state-of-the-art approaches from large scale wind potential to economic benchmarking. The model portfolio includes WAs......P, FUGA, WRF, Net-Op, LCoE model, CorWind, FarmFlow, EeFarm and grid code compliance calculations. The development is done by members from European Energy Research Alliance (EERA) and guided by several industrial partners. A commercial spin-off from the project is the tool ‘Wind & Economy’. The software...... by the software and several tests were performed. The calculations include the smoothing effect on produced energy between wind farms located in different regional wind zones and the short time scales relevant for assessing balancing power. The grid code compliance was tested for several cases and the results...

  10. Design tool for offshore wind farm clusters

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Giebel, Gregor; Waldl, Igor

    2015-01-01

    . The software includes wind farm wake models, energy yield models, inter-array and long cable and grid component models, grid code compliance and ancillary services models. The common score for evaluation in order to compare different layouts is levelized cost of energy (LCoE). The integrated DTOC software...... Research Alliance (EERA) and a number of industrial partners. The approach has been to develop a robust, efficient, easy to use and flexible tool, which integrates software relevant for planning offshore wind farms and wind farm clusters and supports the user with a clear optimization work flow...... is developed within the project using open interface standards and is now available as the commercial software product Wind&Economy....

  11. GraphCrunch 2: Software tool for network modeling, alignment and clustering.

    Science.gov (United States)

    Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

    2011-01-19

    Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an

  12. GraphCrunch 2: Software tool for network modeling, alignment and clustering

    Directory of Open Access Journals (Sweden)

    Hayes Wayne

    2011-01-01

    Full Text Available Abstract Background Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. Results We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL" for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other

  13. Efficient irregular wavefront propagation algorithms on Intel® Xeon Phi™

    OpenAIRE

    Gomes, Jeremias M.; Teodoro, George; de Melo, Alba; Kong, Jun; Kurc, Tahsin; Saltz, Joel H.

    2015-01-01

    We investigate the execution of the Irregular Wavefront Propagation Pattern (IWPP), a fundamental computing structure used in several image analysis operations, on the Intel® Xeon Phi™ co-processor. An efficient implementation of IWPP on the Xeon Phi is a challenging problem because of IWPP’s irregularity and the use of atomic instructions in the original IWPP algorithm to resolve race conditions. On the Xeon Phi, the use of SIMD and vectorization instructions is critical to attain high perfo...

  14. Clusters of galaxies as tools in observational cosmology : results from x-ray analysis

    International Nuclear Information System (INIS)

    Weratschnig, J.M.

    2009-01-01

    Clusters of galaxies are the largest gravitationally bound structures in the universe. They can be used as ideal tools to study large scale structure formation (e.g. when studying merger clusters) and provide highly interesting environments to analyse several characteristic interaction processes (like ram pressure stripping of galaxies, magnetic fields). In this dissertation thesis, we have studied several clusters of galaxies using X-ray observations. To obtain scientific results, we have applied different data reduction and analysis methods. With a combination of morphological and spectral analysis, the merger cluster Abell 514 was studied in much detail. It has a highly interesting morphology and shows signs for an ongoing merger as well as a shock. using a new method to detect substructure, we have analysed several clusters to determine whether any substructure is present in the X-ray image. This hints towards a real structure in the distribution of the intra-cluster medium (ICM) and is evidence for ongoing mergers. The results from this analysis are extensively used with the cluster of galaxies Abell S1136. Here, we study the ICM distribution and compare its structure with the spatial distribution of star forming galaxies. Cluster magnetic fields are another important topic of my thesis. They can be studied in Radio observations, which can be put into relation with results from X-ray observations. using observational data from several clusters, we could support the theory that cluster magnetic fields are frozen into the ICM. (author)

  15. Optimizing the MapReduce Framework on Intel Xeon Phi Coprocessor

    OpenAIRE

    Lu, Mian; Zhang, Lei; Huynh, Huynh Phung; Ong, Zhongliang; Liang, Yun; He, Bingsheng; Goh, Rick Siow Mong; Huynh, Richard

    2013-01-01

    With the ease-of-programming, flexibility and yet efficiency, MapReduce has become one of the most popular frameworks for building big-data applications. MapReduce was originally designed for distributed-computing, and has been extended to various architectures, e,g, multi-core CPUs, GPUs and FPGAs. In this work, we focus on optimizing the MapReduce framework on Xeon Phi, which is the latest product released by Intel based on the Many Integrated Core Architecture. To the best of our knowledge...

  16. Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wucherl [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Koo, Michelle [Univ. of California, Berkeley, CA (United States); Cao, Yu [California Inst. of Technology (CalTech), Pasadena, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Nugent, Peter [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Wu, Kesheng [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2016-09-17

    Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

  17. Peac – A set of tools to quickly enable Proof on a cluster

    International Nuclear Information System (INIS)

    Ganis, G; Vala, M

    2012-01-01

    With advent of the analysis phase of Lhcdata-processing, interest in Proof technology has considerably increased. While setting up a simple Proof cluster for basic usage is reasonably straightforward, exploiting the several new functionalities added in recent times may be complicated. Peac, standing for Proof Enabled Analysis Cluster, is a set of tools aiming to facilitate the setup and management of a Proof cluster. Peac is based on the experience made by setting up Proof for the Alice analysis facilities. It allows to easily build and configure Root and the additional software needed on the cluster, and may serve as distributor of binaries via Xrootd. Peac uses Proof-On-Demand (PoD) for resource management (start, stop or daemons). Finally, Peac sets-up and configures dataset management (using the Afdsmgrd daemon), as well as cluster monitoring (machine status and Proof query summaries) using MonAlisa. In this respect, a MonAlisa page has been dedicated to Peac users, so that a cluster managed by Peac can be automatically monitored. In this paper we present and describe the status and main components of Peac and show details about its usage.

  18. Does the Intel Xeon Phi processor fit HEP workloads?

    Science.gov (United States)

    Nowak, A.; Bitzes, G.; Dotti, A.; Lazzaro, A.; Jarp, S.; Szostek, P.; Valsan, L.; Botezatu, M.; Leduc, J.

    2014-06-01

    This paper summarizes the five years of CERN openlab's efforts focused on the Intel Xeon Phi co-processor, from the time of its inception to public release. We consider the architecture of the device vis a vis the characteristics of HEP software and identify key opportunities for HEP processing, as well as scaling limitations. We report on improvements and speedups linked to parallelization and vectorization on benchmarks involving software frameworks such as Geant4 and ROOT. Finally, we extrapolate current software and hardware trends and project them onto accelerators of the future, with the specifics of offline and online HEP processing in mind.

  19. Profiling CPU-bound workloads on Intel Haswell-EP platforms

    CERN Document Server

    Guerri, Marco; Cristovao, Cordeiro; CERN. Geneva. IT Department

    2017-01-01

    With the increasing adoption of public and private cloud resources to support the demands in terms of computing capacity of the WLCG, the HEP community has begun studying several benchmarking applications aimed at continuously assessing the performance of virtual machines procured from commercial providers. In order to characterise the behaviour of these benchmarks, in-depth profiling activities have been carried out. In this document we outline our experience in profiling one specific application, the ATLAS Kit Validation, in an attempt to explain an unexpected distribution in the performance samples obtained on systems based on Intel Haswell-EP processors.

  20. Topological clustering as a tool for planning water quality monitoring in water distribution networks

    DEFF Research Database (Denmark)

    Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin

    2015-01-01

    ) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided...... into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers...... particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist...

  1. Evaluation of the Intel Xeon Phi 7120 and NVIDIA K80 as accelerators for two-dimensional panel codes.

    Science.gov (United States)

    Einkemmer, Lukas

    2017-01-01

    To optimize the geometry of airfoils for a specific application is an important engineering problem. In this context genetic algorithms have enjoyed some success as they are able to explore the search space without getting stuck in local optima. However, these algorithms require the computation of aerodynamic properties for a significant number of airfoil geometries. Consequently, for low-speed aerodynamics, panel methods are most often used as the inner solver. In this paper we evaluate the performance of such an optimization algorithm on modern accelerators (more specifically, the Intel Xeon Phi 7120 and the NVIDIA K80). For that purpose, we have implemented an optimized version of the algorithm on the CPU and Xeon Phi (based on OpenMP, vectorization, and the Intel MKL library) and on the GPU (based on CUDA and the MAGMA library). We present timing results for all codes and discuss the similarities and differences between the three implementations. Overall, we observe a speedup of approximately 2.5 for adding an Intel Xeon Phi 7120 to a dual socket workstation and a speedup between 3.4 and 3.8 for adding a NVIDIA K80 to a dual socket workstation.

  2. Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters.

    Science.gov (United States)

    Lan, Haidong; Chan, Yuandong; Xu, Kai; Schmidt, Bertil; Peng, Shaoliang; Liu, Weiguo

    2016-07-19

    Computing alignments between two or more sequences are common operations frequently performed in computational molecular biology. The continuing growth of biological sequence databases establishes the need for their efficient parallel implementation on modern accelerators. This paper presents new approaches to high performance biological sequence database scanning with the Smith-Waterman algorithm and the first stage of progressive multiple sequence alignment based on the ClustalW heuristic on a Xeon Phi-based compute cluster. Our approach uses a three-level parallelization scheme to take full advantage of the compute power available on this type of architecture; i.e. cluster-level data parallelism, thread-level coarse-grained parallelism, and vector-level fine-grained parallelism. Furthermore, we re-organize the sequence datasets and use Xeon Phi shuffle operations to improve I/O efficiency. Evaluations show that our method achieves a peak overall performance up to 220 GCUPS for scanning real protein sequence databanks on a single node consisting of two Intel E5-2620 CPUs and two Intel Xeon Phi 7110P cards. It also exhibits good scalability in terms of sequence length and size, and number of compute nodes for both database scanning and multiple sequence alignment. Furthermore, the achieved performance is highly competitive in comparison to optimized Xeon Phi and GPU implementations. Our implementation is available at https://github.com/turbo0628/LSDBS-mpi .

  3. Why K-12 IT Managers and Administrators Are Embracing the Intel-Based Mac

    Science.gov (United States)

    Technology & Learning, 2007

    2007-01-01

    Over the past year, Apple has dramatically increased its share of the school computer marketplace--especially in the category of notebook computers. A recent study conducted by Grunwald Associates and Rockman et al. reports that one of the major reasons for this growth is Apple's introduction of the Intel processor to the entire line of Mac…

  4. Autonomous controller (JCAM 10) for CAMAC crate with 8080 (INTEL) microprocessor

    International Nuclear Information System (INIS)

    Gallice, P.; Mathis, M.

    1975-01-01

    The CAMAC crate autonomous controller JCAM-10 is designed around an INTEL 8080 microprocessor in association with a 5K RAM and 4K REPROM memory. The concept of the module is described, in which data transfers between CAMAC modules and the memory are optimised from software point of view as well as from execution time. In fact, the JCAM-10 is a microcomputer with a set of 1000 peripheral units represented by the CAMAC modules commercially available

  5. Mashup d'aplicacions basat en un buscador intel·ligent

    OpenAIRE

    Sancho Piqueras, Javier

    2010-01-01

    Mashup de funcionalitats, basat en un cercador intel·ligent, en aquest cas pensat per a cursos, carreres màsters, etc. La finalitat és adjuntar diverses aplicacions amb l'únic propòsit que en aquest cas és un buscador però que també ens permet utilitzar eines per a la connectivitat mitjançant web Services, o xarxes socials. Mashup de funcionalidades, basado en un buscador inteligente, en este caso pensado para cursos, carreras másters, etc. La finalidad es juntar diversas aplicaciones con ...

  6. OpenMP-accelerated SWAT simulation using Intel C and FORTRAN compilers: Development and benchmark

    Science.gov (United States)

    Ki, Seo Jin; Sugimura, Tak; Kim, Albert S.

    2015-02-01

    We developed a practical method to accelerate execution of Soil and Water Assessment Tool (SWAT) using open (free) computational resources. The SWAT source code (rev 622) was recompiled using a non-commercial Intel FORTRAN compiler in Ubuntu 12.04 LTS Linux platform, and newly named iOMP-SWAT in this study. GNU utilities of make, gprof, and diff were used to develop the iOMP-SWAT package, profile memory usage, and check identicalness of parallel and serial simulations. Among 302 SWAT subroutines, the slowest routines were identified using GNU gprof, and later modified using Open Multiple Processing (OpenMP) library in an 8-core shared memory system. In addition, a C wrapping function was used to rapidly set large arrays to zero by cross compiling with the original SWAT FORTRAN package. A universal speedup ratio of 2.3 was achieved using input data sets of a large number of hydrological response units. As we specifically focus on acceleration of a single SWAT run, the use of iOMP-SWAT for parameter calibrations will significantly improve the performance of SWAT optimization.

  7. Performance Evaluation of an Intel Haswell- and Ivy Bridge-Based Supercomputer Using Scientific and Engineering Applications

    Science.gov (United States)

    Saini, Subhash; Hood, Robert T.; Chang, Johnny; Baron, John

    2016-01-01

    We present a performance evaluation conducted on a production supercomputer of the Intel Xeon Processor E5- 2680v3, a twelve-core implementation of the fourth-generation Haswell architecture, and compare it with Intel Xeon Processor E5-2680v2, an Ivy Bridge implementation of the third-generation Sandy Bridge architecture. Several new architectural features have been incorporated in Haswell including improvements in all levels of the memory hierarchy as well as improvements to vector instructions and power management. We critically evaluate these new features of Haswell and compare with Ivy Bridge using several low-level benchmarks including subset of HPCC, HPCG and four full-scale scientific and engineering applications. We also present a model to predict the performance of HPCG and Cart3D within 5%, and Overflow within 10% accuracy.

  8. Does the Intel Xeon Phi processor fit HEP workloads?

    International Nuclear Information System (INIS)

    Nowak, A; Bitzes, G; Dotti, A; Lazzaro, A; Jarp, S; Szostek, P; Valsan, L; Botezatu, M; Leduc, J

    2014-01-01

    This paper summarizes the five years of CERN openlab's efforts focused on the Intel Xeon Phi co-processor, from the time of its inception to public release. We consider the architecture of the device vis a vis the characteristics of HEP software and identify key opportunities for HEP processing, as well as scaling limitations. We report on improvements and speedups linked to parallelization and vectorization on benchmarks involving software frameworks such as Geant4 and ROOT. Finally, we extrapolate current software and hardware trends and project them onto accelerators of the future, with the specifics of offline and online HEP processing in mind.

  9. Evaluation of vectorization potential of Graph500 on Intel's Xeon Phi

    OpenAIRE

    Stanic, Milan; Palomar, Oscar; Ratkovic, Ivan; Duric, Milovan; Unsal, Osman; Cristal, Adrian; Valero, Mateo

    2014-01-01

    Graph500 is a data intensive application for high performance computing and it is an increasingly important workload because graphs are a core part of most analytic applications. So far there is no work that examines if Graph500 is suitable for vectorization mostly due a lack of vector memory instructions for irregular memory accesses. The Xeon Phi is a massively parallel processor recently released by Intel with new features such as a wide 512-bit vector unit and vector scatter/gather instru...

  10. Newsgroups, Activist Publics, and Corporate Apologia: The Case of Intel and Its Pentium Chip.

    Science.gov (United States)

    Hearit, Keith Michael

    1999-01-01

    Applies J. Grunig's theory of publics to the phenomenon of Internet newsgroups using the case of the flawed Intel Pentium chip. Argues that technology facilitates the rapid movement of publics from the theoretical construct stage to the active stage. Illustrates some of the difficulties companies face in establishing their identity in cyberspace.…

  11. 3-D electromagnetic plasma particle simulations on the Intel Delta parallel computer

    International Nuclear Information System (INIS)

    Wang, J.; Liewer, P.C.

    1994-01-01

    A three-dimensional electromagnetic PIC code has been developed on the 512 node Intel Touchstone Delta MIMD parallel computer. This code is based on the General Concurrent PIC algorithm which uses a domain decomposition to divide the computation among the processors. The 3D simulation domain can be partitioned into 1-, 2-, or 3-dimensional sub-domains. Particles must be exchanged between processors as they move among the subdomains. The Intel Delta allows one to use this code for very-large-scale simulations (i.e. over 10 8 particles and 10 6 grid cells). The parallel efficiency of this code is measured, and the overall code performance on the Delta is compared with that on Cray supercomputers. It is shown that their code runs with a high parallel efficiency of ≥ 95% for large size problems. The particle push time achieved is 115 nsecs/particle/time step for 162 million particles on 512 nodes. Comparing with the performance on a single processor Cray C90, this represents a factor of 58 speedup. The code uses a finite-difference leap frog method for field solve which is significantly more efficient than fast fourier transforms on parallel computers. The performance of this code on the 128 node Cray T3D will also be discussed

  12. Server consolidation for heterogeneous computer clusters using Colored Petri Nets and CPN Tools

    Directory of Open Access Journals (Sweden)

    Issam Al-Azzoni

    2015-10-01

    Full Text Available In this paper, we present a new approach to server consolidation in heterogeneous computer clusters using Colored Petri Nets (CPNs. Server consolidation aims to reduce energy costs and improve resource utilization by reducing the number of servers necessary to run the existing virtual machines in the cluster. It exploits the emerging technology of live migration which allows migrating virtual machines between servers without stopping their provided services. Server consolidation approaches attempt to find migration plans that aim to minimize the necessary size of the cluster. Our approach finds plans which not only minimize the overall number of used servers, but also minimize the total data migration overhead. The latter objective is not taken into consideration by other approaches and heuristics. We explore the use of CPN Tools in analyzing the state spaces of the CPNs. Since the state space of the CPN model can grow exponentially with the size of the cluster, we examine different techniques to generate and analyze the state space in order to find good plans to server consolidation within acceptable time and computing power.

  13. Cluster tool for in situ processing and comprehensive characteriza tion of thin films at high temperatures.

    Science.gov (United States)

    Wenisch, Robert; Lungwitz, Frank; Hanf, Daniel; Heller, Rene; Zscharschuch, Jens; Hübner, René; von Borany, Johannes; Abrasonis, Gintautas; Gemming, Sibylle; Escobar-Galindo, Ramon; Krause, Matthias

    2018-05-31

    A new cluster tool for in situ real-time processing and depth-resolved compositional, structural and optical characterization of thin films at temperatures from -100 to 800 °C is described. The implemented techniques comprise magnetron sputtering, ion irradiation, Rutherford backscattering spectrometry, Raman spectroscopy and spectroscopic ellipsometry. The capability of the cluster tool is demonstrated for a layer stack MgO/ amorphous Si (~60 nm)/ Ag (~30 nm), deposited at room temperature and crystallized with partial layer exchange by heating up to 650°C. Its initial and final composition, stacking order and structure were monitored in situ in real time and a reaction progress was defined as a function of time and temperature.

  14. Practical Implementation of Lattice QCD Simulation on Intel Xeon Phi Knights Landing

    OpenAIRE

    Kanamori, Issaku; Matsufuru, Hideo

    2017-01-01

    We investigate implementation of lattice Quantum Chromodynamics (QCD) code on the Intel Xeon Phi Knights Landing (KNL). The most time consuming part of the numerical simulations of lattice QCD is a solver of linear equation for a large sparse matrix that represents the strong interaction among quarks. To establish widely applicable prescriptions, we examine rather general methods for the SIMD architecture of KNL, such as using intrinsics and manual prefetching, to the matrix multiplication an...

  15. Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

    2014-10-01

    The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

  16. Reflective memory recorder upgrade: an opportunity to benchmark PowerPC and Intel architectures for real time

    Science.gov (United States)

    Abuter, Roberto; Tischer, Helmut; Frahm, Robert

    2014-07-01

    Several high frequency loops are required to run the VLTI (Very Large Telescope Interferometer) 2, e.g. for fringe tracking11, 5, angle tracking, vibration cancellation, data capture. All these loops rely on low latency real time computers based on the VME bus, Motorola PowerPC14 hardware architecture. In this context, one highly demanding application in terms of cycle time, latency and data transfer volume is the VLTI centralized recording facility, so called, RMN recorder1 (Reflective Memory Recorder). This application captures and transfers data flowing through the distributed memory of the system in real time. Some of the VLTI data producers are running with frequencies up to 8 KHz. With the evolution from first generation instruments like MIDI3, PRIMA5, and AMBER4 which use one or two baselines, to second generation instruments like MATISSE10 and GRAVITY9 which will use all six baselines simultaneously, the quantity of signals has increased by, at least, a factor of six. This has led to a significant overload of the RMN recorder1 which has reached the natural limits imposed by the underlying hardware. At the same time, new, more powerful computers, based on the Intel multicore families of CPUs and PCI buses have become available. With the purpose of improving the performance of the RMN recorder1 application and in order to make it capable of coping with the demands of the new generation instruments, a slightly modified implementation has been developed and integrated into an Intel based multicore computer15 running the VxWorks17 real time operating system. The core of the application is based on the standard VLT software framework for instruments13. The real time task reads from the reflective memory using the onboard DMA access12 and captured data is transferred to the outside world via a TCP socket on a dedicated Ethernet connection. The diversity of the software and hardware that are involved makes this application suitable as a benchmarking platform. A

  17. DBPQL: A view-oriented query language for the Intel Data Base Processor

    Science.gov (United States)

    Fishwick, P. A.

    1983-01-01

    An interactive query language (BDPQL) for the Intel Data Base Processor (DBP) is defined. DBPQL includes a parser generator package which permits the analyst to easily create and manipulate the query statement syntax and semantics. The prototype language, DBPQL, includes trace and performance commands to aid the analyst when implementing new commands and analyzing the execution characteristics of the DBP. The DBPQL grammar file and associated key procedures are included as an appendix to this report.

  18. OpenMP GNU and Intel Fortran programs for solving the time-dependent Gross-Pitaevskii equation

    Science.gov (United States)

    Young-S., Luis E.; Muruganandam, Paulsamy; Adhikari, Sadhan K.; Lončar, Vladimir; Vudragović, Dušan; Balaž, Antun

    2017-11-01

    six different trap symmetries: axially and radially symmetric traps in 3d, circularly symmetric traps in 2d, fully isotropic (spherically symmetric) and fully anisotropic traps in 2d and 3d, as well as 1d traps, where no spatial symmetry is considered. Solution method: We employ the split-step Crank-Nicolson algorithm to discretize the time-dependent GP equation in space and time. The discretized equation is then solved by imaginary- or real-time propagation, employing adequately small space and time steps, to yield the solution of stationary and non-stationary problems, respectively. Reasons for the new version: Previously published Fortran programs [1,2] have now become popular tools [3] for solving the GP equation. These programs have been translated to the C programming language [4] and later extended to the more complex scenario of dipolar atoms [5]. Now virtually all computers have multi-core processors and some have motherboards with more than one physical computer processing unit (CPU), which may increase the number of available CPU cores on a single computer to several tens. The C programs have been adopted to be very fast on such multi-core modern computers using general-purpose graphic processing units (GPGPU) with Nvidia CUDA and computer clusters using Message Passing Interface (MPI) [6]. Nevertheless, previously developed Fortran programs are also commonly used for scientific computation and most of them use a single CPU core at a time in modern multi-core laptops, desktops, and workstations. Unless the Fortran programs are made aware and capable of making efficient use of the available CPU cores, the solution of even a realistic dynamical 1d problem, not to mention the more complicated 2d and 3d problems, could be time consuming using the Fortran programs. Previously, we published auto-parallel Fortran programs [2] suitable for Intel (but not GNU) compiler for solving the GP equation. Hence, a need for the full OpenMP version of the Fortran programs to

  19. Scalable Algorithms for Clustering Large Geospatiotemporal Data Sets on Manycore Architectures

    Science.gov (United States)

    Mills, R. T.; Hoffman, F. M.; Kumar, J.; Sreepathi, S.; Sripathi, V.

    2016-12-01

    The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery using data sets fused from disparate sources. Traditional algorithms and computing platforms are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of available parallelism in state-of-the-art high-performance computing platforms can enable such analysis. We describe a massively parallel implementation of accelerated k-means clustering and some optimizations to boost computational intensity and utilization of wide SIMD lanes on state-of-the art multi- and manycore processors, including the second-generation Intel Xeon Phi ("Knights Landing") processor based on the Intel Many Integrated Core (MIC) architecture, which includes several new features, including an on-package high-bandwidth memory. We also analyze the code in the context of a few practical applications to the analysis of climatic and remotely-sensed vegetation phenology data sets, and speculate on some of the new applications that such scalable analysis methods may enable.

  20. Techniques and tools for measuring energy efficiency of scientific software applications

    International Nuclear Information System (INIS)

    Abdurachmanov, David; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Niemi, Tapio; Pestana, Gonçalo; Khan, Kashif; Nurminen, Jukka K; Nyback, Filip; Ou, Zhonghong

    2015-01-01

    The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important concern in scientific fields such as High Energy Physics (HEP). There has been a growing interest in utilizing alternate architectures, such as low power ARM processors, to replace traditional Intel x86 architectures. Nevertheless, even though such solutions have been successfully used in mobile applications with low I/O and memory demands, it is unclear if they are suitable and more energy-efficient in the scientific computing environment. Furthermore, there is a lack of tools and experience to derive and compare power consumption between the architectures for various workloads, and eventually to support software optimizations for energy efficiency. To that end, we have performed several physical and software-based measurements of workloads from HEP applications running on ARM and Intel architectures, and compare their power consumption and performance. We leverage several profiling tools (both in hardware and software) to extract different characteristics of the power use. We report the results of these measurements and the experience gained in developing a set of measurement techniques and profiling tools to accurately assess the power consumption for scientific workloads. (paper)

  1. Acceleration of Blender Cycles Path-Tracing Engine Using Intel Many Integrated Core Architecture

    OpenAIRE

    Jaroš , Milan; Říha , Lubomír; Strakoš , Petr; Karásek , Tomáš; Vašatová , Alena; Jarošová , Marta; Kozubek , Tomáš

    2015-01-01

    Part 2: Algorithms; International audience; This paper describes the acceleration of the most computationally intensive kernels of the Blender rendering engine, Blender Cycles, using Intel Many Integrated Core architecture (MIC). The proposed parallelization, which uses OpenMP technology, also improves the performance of the rendering engine when running on multi-core CPUs and multi-socket servers. Although the GPU acceleration is already implemented in Cycles, its functionality is limited. O...

  2. EERA-DTOC Project: Design Tools for Offshore Wind Farm Clusters; Proyecto EERA-DTOC: herramientas para el diseno de clusters de Parques Eolicos Marinos

    Energy Technology Data Exchange (ETDEWEB)

    Palomares, A. M.

    2015-07-01

    In the EERA-DTOC Project an integrated and validated software design tool for the optimization of offshore wind farms and wind farm clusters has been developed. The CIEMAT contribution to this project has change the view on mesoscale wind forecasting models, which were not so far considered capable of modeling wind farm scale phenomena. It has been shown the ability of the WRF model to simulate the wakes caused by the wind turbines on the downwind ones (inter-turbine wakes within a wind farm) as well as the wakes between wind farms within a cluster. (Author)

  3. On the blind use of statistical tools in the analysis of globular cluster stars

    Science.gov (United States)

    D'Antona, Francesca; Caloi, Vittoria; Tailo, Marco

    2018-04-01

    As with most data analysis methods, the Bayesian method must be handled with care. We show that its application to determine stellar evolution parameters within globular clusters can lead to paradoxical results if used without the necessary precautions. This is a cautionary tale on the use of statistical tools for big data analysis.

  4. Optimizing the Betts-Miller-Janjic cumulus parameterization with Intel Many Integrated Core (MIC) architecture

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.-L.

    2015-10-01

    The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.

  5. Application of Intel Many Integrated Core (MIC) accelerators to the Pleim-Xiu land surface scheme

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.

    2015-10-01

    The land-surface model (LSM) is one physics process in the weather research and forecast (WRF) model. The LSM includes atmospheric information from the surface layer scheme, radiative forcing from the radiation scheme, and precipitation forcing from the microphysics and convective schemes, together with internal information on the land's state variables and land-surface properties. The LSM is to provide heat and moisture fluxes over land points and sea-ice points. The Pleim-Xiu (PX) scheme is one LSM. The PX LSM features three pathways for moisture fluxes: evapotranspiration, soil evaporation, and evaporation from wet canopies. To accelerate the computation process of this scheme, we employ Intel Xeon Phi Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.3x and 11.7x as compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670.

  6. Scalability of a Low-Cost Multi-Teraflop Linux Cluster for High-End Classical Atomistic and Quantum Mechanical Simulations

    Science.gov (United States)

    Kikuchi, Hideaki; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya; Shimojo, Fuyuki; Saini, Subhash

    2003-01-01

    Scalability of a low-cost, Intel Xeon-based, multi-Teraflop Linux cluster is tested for two high-end scientific applications: Classical atomistic simulation based on the molecular dynamics method and quantum mechanical calculation based on the density functional theory. These scalable parallel applications use space-time multiresolution algorithms and feature computational-space decomposition, wavelet-based adaptive load balancing, and spacefilling-curve-based data compression for scalable I/O. Comparative performance tests are performed on a 1,024-processor Linux cluster and a conventional higher-end parallel supercomputer, 1,184-processor IBM SP4. The results show that the performance of the Linux cluster is comparable to that of the SP4. We also study various effects, such as the sharing of memory and L2 cache among processors, on the performance.

  7. Acceleration of Cherenkov angle reconstruction with the new Intel Xeon/FPGA compute platform for the particle identification in the LHCb Upgrade

    Science.gov (United States)

    Faerber, Christian

    2017-10-01

    The LHCb experiment at the LHC will upgrade its detector by 2018/2019 to a ‘triggerless’ readout scheme, where all the readout electronics and several sub-detector parts will be replaced. The new readout electronics will be able to readout the detector at 40 MHz. This increases the data bandwidth from the detector down to the Event Filter farm to 40 TBit/s, which also has to be processed to select the interesting proton-proton collision for later storage. The architecture of such a computing farm, which can process this amount of data as efficiently as possible, is a challenging task and several compute accelerator technologies are being considered for use inside the new Event Filter farm. In the high performance computing sector more and more FPGA compute accelerators are used to improve the compute performance and reduce the power consumption (e.g. in the Microsoft Catapult project and Bing search engine). Also for the LHCb upgrade the usage of an experimental FPGA accelerated computing platform in the Event Building or in the Event Filter farm is being considered and therefore tested. This platform from Intel hosts a general CPU and a high performance FPGA linked via a high speed link which is for this platform a QPI link. On the FPGA an accelerator is implemented. The used system is a two socket platform from Intel with a Xeon CPU and an FPGA. The FPGA has cache-coherent memory access to the main memory of the server and can collaborate with the CPU. As a first step, a computing intensive algorithm to reconstruct Cherenkov angles for the LHCb RICH particle identification was successfully ported in Verilog to the Intel Xeon/FPGA platform and accelerated by a factor of 35. The same algorithm was ported to the Intel Xeon/FPGA platform with OpenCL. The implementation work and the performance will be compared. Also another FPGA accelerator the Nallatech 385 PCIe accelerator with the same Stratix V FPGA were tested for performance. The results show that the Intel

  8. Implementation of 5-layer thermal diffusion scheme in weather research and forecasting model with Intel Many Integrated Cores

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.

    2014-10-01

    For weather forecasting and research, the Weather Research and Forecasting (WRF) model has been developed, consisting of several components such as dynamic solvers and physical simulation modules. WRF includes several Land- Surface Models (LSMs). The LSMs use atmospheric information, the radiative and precipitation forcing from the surface layer scheme, the radiation scheme, and the microphysics/convective scheme all together with the land's state variables and land-surface properties, to provide heat and moisture fluxes over land and sea-ice points. The WRF 5-layer thermal diffusion simulation is an LSM based on the MM5 5-layer soil temperature model with an energy budget that includes radiation, sensible, and latent heat flux. The WRF LSMs are very suitable for massively parallel computation as there are no interactions among horizontal grid points. The features, efficient parallelization and vectorization essentials, of Intel Many Integrated Core (MIC) architecture allow us to optimize this WRF 5-layer thermal diffusion scheme. In this work, we present the results of the computing performance on this scheme with Intel MIC architecture. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.1x. Accordingly, the same CPU-based optimizations improved the performance on Intel Xeon E5- 2603 by a factor of 1.6x as compared to the first version of multi-threaded code.

  9. Applying the roofline performance model to the intel xeon phi knights landing processor

    OpenAIRE

    Doerfler, D; Deslippe, J; Williams, S; Oliker, L; Cook, B; Kurth, T; Lobet, M; Malas, T; Vay, JL; Vincenti, H

    2016-01-01

    � Springer International Publishing AG 2016. The Roofline Performance Model is a visually intuitive method used to bound the sustained peak floating-point performance of any given arithmetic kernel on any given processor architecture. In the Roofline, performance is nominally measured in floating-point operations per second as a function of arithmetic intensity (operations per byte of data). In this study we determine the Roofline for the Intel Knights Landing (KNL) processor, determining t...

  10. Performance Engineering for a Medical Imaging Application on the Intel Xeon Phi Accelerator

    OpenAIRE

    Hofmann, Johannes; Treibig, Jan; Hager, Georg; Wellein, Gerhard

    2013-01-01

    We examine the Xeon Phi, which is based on Intel's Many Integrated Cores architecture, for its suitability to run the FDK algorithm--the most commonly used algorithm to perform the 3D image reconstruction in cone-beam computed tomography. We study the challenges of efficiently parallelizing the application and means to enable sensible data sharing between threads despite the lack of a shared last level cache. Apart from parallelization, SIMD vectorization is critical for good performance on t...

  11. Acceleration of Monte Carlo simulation of photon migration in complex heterogeneous media using Intel many-integrated core architecture.

    Science.gov (United States)

    Gorshkov, Anton V; Kirillin, Mikhail Yu

    2015-08-01

    Over two decades, the Monte Carlo technique has become a gold standard in simulation of light propagation in turbid media, including biotissues. Technological solutions provide further advances of this technique. The Intel Xeon Phi coprocessor is a new type of accelerator for highly parallel general purpose computing, which allows execution of a wide range of applications without substantial code modification. We present a technical approach of porting our previously developed Monte Carlo (MC) code for simulation of light transport in tissues to the Intel Xeon Phi coprocessor. We show that employing the accelerator allows reducing computational time of MC simulation and obtaining simulation speed-up comparable to GPU. We demonstrate the performance of the developed code for simulation of light transport in the human head and determination of the measurement volume in near-infrared spectroscopy brain sensing.

  12. Evaluation of the Single-precision Floatingpoint Vector Add Kernel Using the Intel FPGA SDK for OpenCL

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Zheming [Argonne National Lab. (ANL), Argonne, IL (United States); Yoshii, Kazutomo [Argonne National Lab. (ANL), Argonne, IL (United States); Finkel, Hal [Argonne National Lab. (ANL), Argonne, IL (United States); Cappello, Franck [Argonne National Lab. (ANL), Argonne, IL (United States)

    2017-04-20

    Open Computing Language (OpenCL) is a high-level language that enables software programmers to explore Field Programmable Gate Arrays (FPGAs) for application acceleration. The Intel FPGA software development kit (SDK) for OpenCL allows a user to specify applications at a high level and explore the performance of low-level hardware acceleration. In this report, we present the FPGA performance and power consumption results of the single-precision floating-point vector add OpenCL kernel using the Intel FPGA SDK for OpenCL on the Nallatech 385A FPGA board. The board features an Arria 10 FPGA. We evaluate the FPGA implementations using the compute unit duplication and kernel vectorization optimization techniques. On the Nallatech 385A FPGA board, the maximum compute kernel bandwidth we achieve is 25.8 GB/s, approximately 76% of the peak memory bandwidth. The power consumption of the FPGA device when running the kernels ranges from 29W to 42W.

  13. Performance Analysis of an Astrophysical Simulation Code on the Intel Xeon Phi Architecture

    OpenAIRE

    Noormofidi, Vahid; Atlas, Susan R.; Duan, Huaiyu

    2015-01-01

    We have developed the astrophysical simulation code XFLAT to study neutrino oscillations in supernovae. XFLAT is designed to utilize multiple levels of parallelism through MPI, OpenMP, and SIMD instructions (vectorization). It can run on both CPU and Xeon Phi co-processors based on the Intel Many Integrated Core Architecture (MIC). We analyze the performance of XFLAT on configurations with CPU only, Xeon Phi only and both CPU and Xeon Phi. We also investigate the impact of I/O and the multi-n...

  14. Efficient sparse matrix-matrix multiplication for computing periodic responses by shooting method on Intel Xeon Phi

    Science.gov (United States)

    Stoykov, S.; Atanassov, E.; Margenov, S.

    2016-10-01

    Many of the scientific applications involve sparse or dense matrix operations, such as solving linear systems, matrix-matrix products, eigensolvers, etc. In what concerns structural nonlinear dynamics, the computations of periodic responses and the determination of stability of the solution are of primary interest. Shooting method iswidely used for obtaining periodic responses of nonlinear systems. The method involves simultaneously operations with sparse and dense matrices. One of the computationally expensive operations in the method is multiplication of sparse by dense matrices. In the current work, a new algorithm for sparse matrix by dense matrix products is presented. The algorithm takes into account the structure of the sparse matrix, which is obtained by space discretization of the nonlinear Mindlin's plate equation of motion by the finite element method. The algorithm is developed to use the vector engine of Intel Xeon Phi coprocessors. It is compared with the standard sparse matrix by dense matrix algorithm and the one developed by Intel MKL and it is shown that by considering the properties of the sparse matrix better algorithms can be developed.

  15. TreeCluster: Massively scalable transmission clustering using phylogenetic trees

    OpenAIRE

    Moshiri, Alexander

    2018-01-01

    Background: The ability to infer transmission clusters from molecular data is critical to designing and evaluating viral control strategies. Viral sequencing datasets are growing rapidly, but standard methods of transmission cluster inference do not scale well beyond thousands of sequences. Results: I present TreeCluster, a cross-platform tool that performs transmission cluster inference on a given phylogenetic tree orders of magnitude faster than existing inference methods and supports multi...

  16. Transitioning to Intel-based Linux Servers in the Payload Operations Integration Center

    Science.gov (United States)

    Guillebeau, P. L.

    2004-01-01

    The MSFC Payload Operations Integration Center (POIC) is the focal point for International Space Station (ISS) payload operations. The POIC contains the facilities, hardware, software and communication interface necessary to support payload operations. ISS ground system support for processing and display of real-time spacecraft and telemetry and command data has been operational for several years. The hardware components were reaching end of life and vendor costs were increasing while ISS budgets were becoming severely constrained. Therefore it has been necessary to migrate the Unix portions of our ground systems to commodity priced Intel-based Linux servers. hardware architecture including networks, data storage, and highly available resources. This paper will concentrate on the Linux migration implementation for the software portion of our ground system. The migration began with 3.5 million lines of code running on Unix platforms with separate servers for telemetry, command, Payload information management systems, web, system control, remote server interface and databases. The Intel-based system is scheduled to be available for initial operational use by August 2004 The overall migration to Intel-based Linux servers in the control center involves changes to the This paper will address the Linux migration study approach including the proof of concept, criticality of customer buy-in and importance of beginning with POSlX compliant code. It will focus on the development approach explaining the software lifecycle. Other aspects of development will be covered including phased implementation, interim milestones and metrics measurements and reporting mechanisms. This paper will also address the testing approach covering all levels of testing including development, development integration, IV&V, user beta testing and acceptance testing. Test results including performance numbers compared with Unix servers will be included. need for a smooth transition while maintaining

  17. Benchmarking Data Analysis and Machine Learning Applications on the Intel KNL Many-Core Processor

    OpenAIRE

    Byun, Chansup; Kepner, Jeremy; Arcand, William; Bestor, David; Bergeron, Bill; Gadepally, Vijay; Houle, Michael; Hubbell, Matthew; Jones, Michael; Klein, Anna; Michaleas, Peter; Milechin, Lauren; Mullen, Julie; Prout, Andrew; Rosa, Antonio

    2017-01-01

    Knights Landing (KNL) is the code name for the second-generation Intel Xeon Phi product family. KNL has generated significant interest in the data analysis and machine learning communities because its new many-core architecture targets both of these workloads. The KNL many-core vector processor design enables it to exploit much higher levels of parallelism. At the Lincoln Laboratory Supercomputing Center (LLSC), the majority of users are running data analysis applications such as MATLAB and O...

  18. Quantum Chemical Calculations Using Accelerators: Migrating Matrix Operations to the NVIDIA Kepler GPU and the Intel Xeon Phi.

    Science.gov (United States)

    Leang, Sarom S; Rendell, Alistair P; Gordon, Mark S

    2014-03-11

    Increasingly, modern computer systems comprise a multicore general-purpose processor augmented with a number of special purpose devices or accelerators connected via an external interface such as a PCI bus. The NVIDIA Kepler Graphical Processing Unit (GPU) and the Intel Phi are two examples of such accelerators. Accelerators offer peak performances that can be well above those of the host processor. How to exploit this heterogeneous environment for legacy application codes is not, however, straightforward. This paper considers how matrix operations in typical quantum chemical calculations can be migrated to the GPU and Phi systems. Double precision general matrix multiply operations are endemic in electronic structure calculations, especially methods that include electron correlation, such as density functional theory, second order perturbation theory, and coupled cluster theory. The use of approaches that automatically determine whether to use the host or an accelerator, based on problem size, is explored, with computations that are occurring on the accelerator and/or the host. For data-transfers over PCI-e, the GPU provides the best overall performance for data sizes up to 4096 MB with consistent upload and download rates between 5-5.6 GB/s and 5.4-6.3 GB/s, respectively. The GPU outperforms the Phi for both square and nonsquare matrix multiplications.

  19. High-throughput sockets over RDMA for the Intel Xeon Phi coprocessor

    CERN Document Server

    Santogidis, Aram

    2017-01-01

    In this paper we describe the design, implementation and performance of Trans4SCIF, a user-level socket-like transport library for the Intel Xeon Phi coprocessor. Trans4SCIF library is primarily intended for high-throughput applications. It uses RDMA transfers over the native SCIF support, in a way that is transparent for the application, which has the illusion of using conventional stream sockets. We also discuss the integration of Trans4SCIF with the ZeroMQ messaging library, used extensively by several applications running at CERN. We show that this can lead to a substantial, up to 3x, increase of application throughput compared to the default TCP/IP transport option.

  20. ASPECT: A spectra clustering tool for exploration of large spectral surveys

    Science.gov (United States)

    in der Au, A.; Meusinger, H.; Schalldach, P. F.; Newholm, M.

    2012-11-01

    Context. Analysing the empirical output from large surveys is an important challenge in contemporary science. Difficulties arise, in particular, when the database is huge and the properties of the object types to be selected are poorly constrained a priori. Aims: We present the novel, semi-automated clustering tool ASPECT for analysing voluminous archives of spectra. Methods: The heart of the program is a neural network in the form of a Kohonen self-organizing map. The resulting map is designed as an icon map suitable for the inspection by eye. The visual analysis is supported by the option to blend in individual object properties such as redshift, apparent magnitude, or signal-to-noise ratio. In addition, the package provides several tools for the selection of special spectral types, e.g. local difference maps which reflect the deviations of all spectra from one given input spectrum (real or artificial). Results: ASPECT is able to produce a two-dimensional topological map of a huge number of spectra. The software package enables the user to browse and navigate through a huge data pool and helps them to gain an insight into underlying relationships between the spectra and other physical properties and to get the big picture of the entire data set. We demonstrate the capability of ASPECT by clustering the entire data pool of ~6 × 105 spectra from the Data Release 4 of the Sloan Digital Sky Survey (SDSS). To illustrate the results regarding quality and completeness we track objects from existing catalogues of quasars and carbon stars, respectively, and connect the SDSS spectra with morphological information from the GalaxyZoo project. Code is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/547/A115

  1. Evaluation of the Intel Nehalem-EX server processor

    CERN Document Server

    Jarp, S; Leduc, J; Nowak, A; CERN. Geneva. IT Department

    2010-01-01

    In this paper we report on a set of benchmark results recently obtained by the CERN openlab by comparing the 4-socket, 32-core Intel Xeon X7560 server with the previous generation 4-socket server, based on the Xeon X7460 processor. The Xeon X7560 processor represents a major change in many respects, especially the memory sub-system, so it was important to make multiple comparisons. In most benchmarks the two 4-socket servers were compared. It should be underlined that both servers represent the “top of the line” in terms of frequency. However, in some cases, it was important to compare systems that integrated the latest processor features, such as QPI links, Symmetric multithreading and over-clocking via Turbo mode, and in such situations the X7560 server was compared to a dual socket L5520 based system with an identical frequency of 2.26 GHz. Before summarizing the results we must stress the fact that benchmarking of modern processors is a very complex affair. One has to control (at least) the following ...

  2. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2006-01-01

    paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

  3. Cluster fusion algorithm: application to Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2008-01-01

    paths up to the cluster size of 150 atoms. We demonstrate that in this way all known global minima structures of the Lennard-Jones clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence......We present a new general theoretical framework for modelling the cluster structure and apply it to description of the Lennard-Jones clusters. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system and absorbing its energy at each step, we find cluster growing...... for the clusters of noble gas atoms and compare it with experimental observations. We report the striking correspondence of the peaks in the dependence of the second derivative of the binding energy per atom on cluster size calculated for the chain of the Lennard-Jones clusters based on the icosahedral symmetry...

  4. Initial results on computational performance of Intel Many Integrated Core (MIC) architecture: implementation of the Weather and Research Forecasting (WRF) Purdue-Lin microphysics scheme

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

    2014-10-01

    Purdue-Lin scheme is a relatively sophisticated microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme includes six classes of hydro meteors: water vapor, cloud water, raid, cloud ice, snow and graupel. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. In this paper, we accelerate the Purdue Lin scheme using Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi is a high performance coprocessor consists of up to 61 cores. The Xeon Phi is connected to a CPU via the PCI Express (PICe) bus. In this paper, we will discuss in detail the code optimization issues encountered while tuning the Purdue-Lin microphysics Fortran code for Xeon Phi. In particularly, getting a good performance required utilizing multiple cores, the wide vector operations and make efficient use of memory. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 4.2x. Furthermore, the same optimizations improved performance on Intel Xeon E5-2603 CPU by a factor of 1.2x compared to the original code.

  5. Evaluation of the Intel Sandy Bridge-EP server processor

    CERN Document Server

    Jarp, S; Leduc, J; Nowak, A; CERN. Geneva. IT Department

    2012-01-01

    In this paper we report on a set of benchmark results recently obtained by CERN openlab when comparing an 8-core “Sandy Bridge-EP” processor with Intel’s previous microarchitecture, the “Westmere-EP”. The Intel marketing names for these processors are “Xeon E5-2600 processor series” and “Xeon 5600 processor series”, respectively. Both processors are produced in a 32nm process, and both platforms are dual-socket servers. Multiple benchmarks were used to get a good understanding of the performance of the new processor. We used both industry-standard benchmarks, such as SPEC2006, and specific High Energy Physics benchmarks, representing both simulation of physics detectors and data analysis of physics events. Before summarizing the results we must stress the fact that benchmarking of modern processors is a very complex affair. One has to control (at least) the following features: processor frequency, overclocking via Turbo mode, the number of physical cores in use, the use of logical cores ...

  6. Implementation of a 3-D nonlinear MHD [magnetohydrodynamics] calculation on the Intel hypercube

    International Nuclear Information System (INIS)

    Lynch, V.E.; Carreras, B.A.; Drake, J.B.; Hicks, H.R.; Lawkins, W.F.

    1987-01-01

    The optimization of numerical schemes and increasing computer capabilities in the last ten years have improved the efficiency of 3-D nonlinear resistive MHD calculations by about two to three orders of magnitude. However, we are still very limited in performing these types of calculations. Hypercubes have a large number of processors with only local memory and bidirectional links among neighbors. The Intel Hypercube at Oak Ridge has 64 processors with 0.5 megabytes of memory per processor. The multiplicity of processors opens new possibilities for the treatment of such computations. The constraint on time and resources favored the approach of using the existing RSF code which solves as an initial value problem the reduced set of MHD equations for a periodic cylindrical geometry. This code includes minimal physics and geometry, but contains the basic three dimensionality and nonlinear structure of the equations. The code solves the reduced set of MHD equations by Fourier expansion in two angular coordinates and finite differences in the radial one. Due to the continuing interest in these calculations and the likelihood that future supercomputers will take greater advantage of parallelism, the present study was initiated by the ORNL Exploratory Studies Committee and funded entirely by Laboratory Discretionary Funds. The objectives of the study were: to ascertain the suitability of MHD calculation for parallel computation, to design and implement a parallel algorithm to perform the computations, and to evaluate the hypercube, and in particular, ORNL's Intel iPSC, for use in MHD computations

  7. ELT-scale Adaptive Optics real-time control with thes Intel Xeon Phi Many Integrated Core Architecture

    Science.gov (United States)

    Jenkins, David R.; Basden, Alastair; Myers, Richard M.

    2018-05-01

    We propose a solution to the increased computational demands of Extremely Large Telescope (ELT) scale adaptive optics (AO) real-time control with the Intel Xeon Phi Knights Landing (KNL) Many Integrated Core (MIC) Architecture. The computational demands of an AO real-time controller (RTC) scale with the fourth power of telescope diameter and so the next generation ELTs require orders of magnitude more processing power for the RTC pipeline than existing systems. The Xeon Phi contains a large number (≥64) of low power x86 CPU cores and high bandwidth memory integrated into a single socketed server CPU package. The increased parallelism and memory bandwidth are crucial to providing the performance for reconstructing wavefronts with the required precision for ELT scale AO. Here, we demonstrate that the Xeon Phi KNL is capable of performing ELT scale single conjugate AO real-time control computation at over 1.0kHz with less than 20μs RMS jitter. We have also shown that with a wavefront sensor camera attached the KNL can process the real-time control loop at up to 966Hz, the maximum frame-rate of the camera, with jitter remaining below 20μs RMS. Future studies will involve exploring the use of a cluster of Xeon Phis for the real-time control of the MCAO and MOAO regimes of AO. We find that the Xeon Phi is highly suitable for ELT AO real time control.

  8. GW Calculations of Materials on the Intel Xeon-Phi Architecture

    Science.gov (United States)

    Deslippe, Jack; da Jornada, Felipe H.; Vigil-Fowler, Derek; Biller, Ariel; Chelikowsky, James R.; Louie, Steven G.

    Intel Xeon-Phi processors are expected to power a large number of High-Performance Computing (HPC) systems around the United States and the world in the near future. We evaluate the ability of GW and pre-requisite Density Functional Theory (DFT) calculations for materials on utilizing the Xeon-Phi architecture. We describe the optimization process and performance improvements achieved. We find that the GW method, like other higher level Many-Body methods beyond standard local/semilocal approximations to Kohn-Sham DFT, is particularly well suited for many-core architectures due to the ability to exploit a large amount of parallelism over plane-waves, band-pairs and frequencies. Support provided by the SCIDAC program, Department of Energy, Office of Science, Advanced Scientic Computing Research and Basic Energy Sciences. Grant Numbers DE-SC0008877 (Austin) and DE-AC02-05CH11231 (LBNL).

  9. Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

    OpenAIRE

    Rucci, Enzo; De Giusti, Armando Eduardo; Naiouf, Marcelo

    2017-01-01

    Manycores are consolidating in HPC community as a way of improving performance while keeping power efficiency. Knights Landing is the recently released second generation of Intel Xeon Phi architec- ture.While optimizing applications on CPUs, GPUs and first Xeon Phi’s has been largely studied in the last years, the new features in Knights Landing processors require the revision of programming and optimization techniques for these devices. In this work, we selected the Floyd-Warshall algorithm ...

  10. A parallel implementation of particle tracking with space charge effects on an INTEL iPSC/860

    International Nuclear Information System (INIS)

    Chang, L.; Bourianoff, G.; Cole, B.; Machida, S.

    1993-05-01

    Particle-tracking simulation is one of the scientific applications that is well-suited to parallel computations. At the Superconducting Super Collider, it has been theoretically and empirically demonstrated that particle tracking on a designed lattice can achieve very high parallel efficiency on a MIMD Intel iPSC/860 machine. The key to such success is the realization that the particles can be tracked independently without considering their interaction. The perfectly parallel nature of particle tracking is broken if the interaction effects between particles are included. The space charge introduces an electromagnetic force that will affect the motion of tracked particles in 3-D space. For accurate modeling of the beam dynamics with space charge effects, one needs to solve three-dimensional Maxwell field equations, usually by a particle-in-cell (PIC) algorithm. This will require each particle to communicate with its neighbor grids to compute the momentum changes at each time step. It is expected that the 3-D PIC method will degrade parallel efficiency of particle-tracking implementation on any parallel computer. In this paper, we describe an efficient scheme for implementing particle tracking with space charge effects on an INTEL iPSC/860 machine. Experimental results show that a parallel efficiency of 75% can be obtained

  11. Cluster analysis as a tool of guests segmentation by the degree of their demand

    Directory of Open Access Journals (Sweden)

    Damijan Mumel

    2002-01-01

    Full Text Available Authors demonstrate the use of cluster analysis in finding out (ascertaining the homogenity/heterogenity of guests as to the degree of their demand. The degree of guests’ demand is defined according to the importance of perceived service quality components measured by SERVQUAL, which was adopted and adapted, according to the specifics of health spa industry in Slovenia. Goals of the article are: (a the identification of the profile of importance of general health spa service quality components, and (b the identification of groups of guests (segments according to the degree of their demand in the research in 1991 compared with 1999. Cluster analysis serves as useful tool for guest segmentation since it reveals the existence of important differences in the structure of guests in the year 1991 compared with the year 1999. The results serve as a useful database for management in health spas.

  12. Student Intern Ben Freed Competes as Finalist in Intel STS Competition, Three Other Interns Named Semifinalists | Poster

    Science.gov (United States)

    By Ashley DeVine, Staff Writer Werner H. Kirstin (WHK) student intern Ben Freed was one of 40 finalists to compete in the Intel Science Talent Search (STS) in Washington, DC, in March. “It was seven intense days of interacting with amazing judges and incredibly smart and interesting students. We met President Obama, and then the MIT astronomy lab named minor planets after each

  13. Educational program on HPC technologies based on the heterogeneous cluster HybriLIT (LIT JINR

    Directory of Open Access Journals (Sweden)

    Vladimir V. Korenkov

    2017-12-01

    Full Text Available The article highlights the issues of training personnel for work with high-performance computing systems (HPC, as well as of support of the software and information environment which is necessary for the efficient use of heterogeneous computing resources and the development of parallel and hybrid applications. The heterogeneous computing cluster HybriLIT, which is one of the components of the Multifunctional Information and Computing Complex of JINR, is used as the main platform for training and re-training specialists, as well as for training students, graduate students and young scientists. The HybriLIT cluster is a dynamic, actively developing structure, incorporating the most advanced HPC computing architectures (graphics accelerators, Intel Xeon Phi coprocessors, and also it has a developed software and information environment, which in turn, makes it possible to build educational programs on the up-to-date level, and enables the learners to master both modern computing platforms and modern IT technologies.

  14. Les multituds intel·ligents com a generadores de dades massives : la intel·ligència col·lectiva al servei de la innovació social

    Directory of Open Access Journals (Sweden)

    Sanz, Sandra

    2015-06-01

    Full Text Available Les últimes dècades es registra un increment de mobilitzacions socials organitzades, intervingudes, narrades i coordinades a través de les TIC. Són mostra de multituds intel·ligents (smart mobs que s'aprofiten dels nous mitjans de comunicació per organitzar-se. Tant pel nombre de missatges intercanviats i generats com per les pròpies interaccions generades, aquestes multituds intel·ligents es converteixen en objecte de les dades massives. La seva anàlisi a partir de les possibilitats que brinda l'enginyeria de dades pot contribuir a detectar idees construïdes com també sabers compartits fruit de la intel·ligència col·lectiva. Aquest fet afavoriria la reutilització d'aquesta informació per incrementar el coneixement del col·lectiu i contribuir al desenvolupament de la innovació social. És per això que en aquest article s'assenyalen els interrogants i les limitacions que encara presenten aquestes anàlisis i es posa en relleu la necessitat d'aprofundir en el desenvolupament de nous mètodes i tècniques d'anàlisi.En las últimas décadas se registra un incremento de movilizaciones sociales organizadas, mediadas, narradas y coordinadas a través de TICs. Son muestra de smart mobs o multitudes inteligentes que se aprovechan de los nuevos medios de comunicación para organizarse. Tanto por el número de mensajes intercambiados y generados como por las propias interacciones generadas, estas multitudes inteligentes se convierten en objeto del big data. Su análisis a partir de las posibilidades que brinda la ingeniería de datos puede contribuir a detectar ideas construidas así como saberes compartidos fruto de la inteligencia colectiva. Ello favorecería la reutilización de esta información para incrementar el conocimiento del colectivo y contribuir al desarrollo de la innovación social. Es por ello que en este artículo se señalan los interrogantes y limitaciones que todavía presentan estos análisis y se pone de relieve la

  15. A static analysis tool set for assembler code verification

    International Nuclear Information System (INIS)

    Dhodapkar, S.D.; Bhattacharjee, A.K.; Sen, Gopa

    1991-01-01

    Software Verification and Validation (V and V) is an important step in assuring reliability and quality of the software. The verification of program source code forms an important part of the overall V and V activity. The static analysis tools described here are useful in verification of assembler code. The tool set consists of static analysers for Intel 8086 and Motorola 68000 assembly language programs. The analysers examine the program source code and generate information about control flow within the program modules, unreachable code, well-formation of modules, call dependency between modules etc. The analysis of loops detects unstructured loops and syntactically infinite loops. Software metrics relating to size and structural complexity are also computed. This report describes the salient features of the design, implementation and the user interface of the tool set. The outputs generated by the analyser are explained using examples taken from some projects analysed by this tool set. (author). 7 refs., 17 figs

  16. Evaluating the transport layer of the ALFA framework for the Intel(®) Xeon Phi(™) Coprocessor

    OpenAIRE

    Santogidis, Aram; Hirstius, Andreas; Lalis, Spyros

    2015-01-01

    The ALFA framework supports the software development of major High Energy Physics experiments. As part of our research effort to optimize the transport layer of ALFA, we focus on profiling its data transfer performance for inter-node communication on the Intel Xeon Phi Coprocessor. In this article we present the collected performance measurements with the related analysis of the results. The optimization opportunities that are discovered, help us to formulate the future plans of enabling high...

  17. Accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) model on Intel Xeon Phi processors

    OpenAIRE

    Wang, Hui; Chen, Huansheng; Wu, Qizhong; Lin, Junming; Chen, Xueshun; Xie, Xinwei; Wang, Rongrong; Tang, Xiao; Wang, Zifa

    2017-01-01

    The GNAQPMS model is the global version of the Nested Air Quality Prediction Modelling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present our work of porting and optimizing the GNAQPMS model on the second generation Intel Xeon Phi processor codename “Knights Landing” (KNL). Compared with the first generation Xeon Phi coprocessor, KNL introduced many new hardware features such as a boo...

  18. Multi-threaded ATLAS simulation on Intel Knights Landing processors

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00014247; The ATLAS collaboration; Calafiura, Paolo; Leggett, Charles; Tsulaia, Vakhtang; Dotti, Andrea

    2017-01-01

    The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), was delivered to its users in two phases with the first phase online at the end of 2015 and the second phase now online at the end of 2016. Cori Phase 2 is based on the KNL architecture and contains over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a good potential use-case for the KNL architecture and supercomputers like Cori. ATLAS simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this paper we will give an overview of the ATLAS simulation application with detai...

  19. Multi-threaded ATLAS Simulation on Intel Knights Landing Processors

    CERN Document Server

    Farrell, Steven; The ATLAS collaboration; Calafiura, Paolo; Leggett, Charles

    2016-01-01

    The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), will be delivered to its users in two phases with the first phase online now and the second phase expected in mid-2016. Cori Phase 2 will be based on the KNL architecture and will contain over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a great use-case for the KNL architecture and supercomputers like Cori. Simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this presentation we will give an overview of the ATLAS simulation application with details on its multi-thr...

  20. Cluster ion beam facilities

    International Nuclear Information System (INIS)

    Popok, V.N.; Prasalovich, S.V.; Odzhaev, V.B.; Campbell, E.E.B.

    2001-01-01

    A brief state-of-the-art review in the field of cluster-surface interactions is presented. Ionised cluster beams could become a powerful and versatile tool for the modification and processing of surfaces as an alternative to ion implantation and ion assisted deposition. The main effects of cluster-surface collisions and possible applications of cluster ion beams are discussed. The outlooks of the Cluster Implantation and Deposition Apparatus (CIDA) being developed in Guteborg University are shown

  1. Photo fragmentation dynamics of small argon clusters and biological molecular: new tools by trapping and vectorial correlation

    International Nuclear Information System (INIS)

    Lepere, V.

    2006-09-01

    The present work concerns the building up of a complex set-up whose aim being the investigation of the photo fragmentation of ionised clusters and biological molecules. This new tool is based on the association of several techniques. Two ion sources are available: clusters produced in a supersonic beam are ionised by 70 eV electrons while ions of biological interest are produced in an 'electro-spray'. Ro-vibrational cooling is achieved in a 'Zajfman' electrostatic ion trap. The lifetime of ions can also be measured using the trap. Two types of lasers are used to excite the ionised species: the femtosecond laser available at the ELYSE facilities and a nanosecond laser. Both lasers have a repetition rate of 1 kHz. The neutral and ionised fragments are detected in coincidence using a sophisticated detection system allowing time and localisation of the various fragments to be determined. With such a tool, I was able to investigate in details the fragmentation dynamics of ionised clusters and bio-molecules. The first experiments deal with the measurement of the lifetime of the Ar 2+ dimer II(1/2)u metastable state. The relative population of this state was also determined. The Ar 2+ and Ar 3+ photo-fragmentation was then studied and electronic transitions responsible for their dissociation identified. The detailed analysis of our data allowed to distinguish the various fragmentation mechanisms. Finally, a preliminary investigation of the protonated tryptamine fragmentation is presented. (author)

  2. A new shared-memory programming paradigm for molecular dynamics simulations on the Intel Paragon

    International Nuclear Information System (INIS)

    D'Azevedo, E.F.; Romine, C.H.

    1994-12-01

    This report describes the use of shared memory emulation with DOLIB (Distributed Object Library) to simplify parallel programming on the Intel Paragon. A molecular dynamics application is used as an example to illustrate the use of the DOLIB shared memory library. SOTON-PAR, a parallel molecular dynamics code with explicit message-passing using a Lennard-Jones 6-12 potential, is rewritten using DOLIB primitives. The resulting code has no explicit message primitives and resembles a serial code. The new code can perform dynamic load balancing and achieves better performance than the original parallel code with explicit message-passing

  3. Performance Evaluation of Computation and Communication Kernels of the Fast Multipole Method on Intel Manycore Architecture

    KAUST Repository

    AbdulJabbar, Mustafa Abdulmajeed; Al Farhan, Mohammed; Yokota, Rio; Keyes, David E.

    2017-01-01

    Manycore optimizations are essential for achieving performance worthy of anticipated exascale systems. Utilization of manycore chips is inevitable to attain the desired floating point performance of these energy-austere systems. In this work, we revisit ExaFMM, the open source Fast Multiple Method (FMM) library, in light of highly tuned shared-memory parallelization and detailed performance analysis on the new highly parallel Intel manycore architecture, Knights Landing (KNL). We assess scalability and performance gain using task-based parallelism of the FMM tree traversal. We also provide an in-depth analysis of the most computationally intensive part of the traversal kernel (i.e., the particle-to-particle (P2P) kernel), by comparing its performance across KNL and Broadwell architectures. We quantify different configurations that exploit the on-chip 512-bit vector units within different task-based threading paradigms. MPI communication-reducing and NUMA-aware approaches for the FMM’s global tree data exchange are examined with different cluster modes of KNL. By applying several algorithm- and architecture-aware optimizations for FMM, we show that the N-Body kernel on 256 threads of KNL achieves on average 2.8× speedup compared to the non-vectorized version, whereas on 56 threads of Broadwell, it achieves on average 2.9× speedup. In addition, the tree traversal kernel on KNL scales monotonically up to 256 threads with task-based programming models. The MPI-based communication-reducing algorithms show expected improvements of the data locality across the KNL on-chip network.

  4. Performance Evaluation of Computation and Communication Kernels of the Fast Multipole Method on Intel Manycore Architecture

    KAUST Repository

    AbdulJabbar, Mustafa Abdulmajeed

    2017-07-31

    Manycore optimizations are essential for achieving performance worthy of anticipated exascale systems. Utilization of manycore chips is inevitable to attain the desired floating point performance of these energy-austere systems. In this work, we revisit ExaFMM, the open source Fast Multiple Method (FMM) library, in light of highly tuned shared-memory parallelization and detailed performance analysis on the new highly parallel Intel manycore architecture, Knights Landing (KNL). We assess scalability and performance gain using task-based parallelism of the FMM tree traversal. We also provide an in-depth analysis of the most computationally intensive part of the traversal kernel (i.e., the particle-to-particle (P2P) kernel), by comparing its performance across KNL and Broadwell architectures. We quantify different configurations that exploit the on-chip 512-bit vector units within different task-based threading paradigms. MPI communication-reducing and NUMA-aware approaches for the FMM’s global tree data exchange are examined with different cluster modes of KNL. By applying several algorithm- and architecture-aware optimizations for FMM, we show that the N-Body kernel on 256 threads of KNL achieves on average 2.8× speedup compared to the non-vectorized version, whereas on 56 threads of Broadwell, it achieves on average 2.9× speedup. In addition, the tree traversal kernel on KNL scales monotonically up to 256 threads with task-based programming models. The MPI-based communication-reducing algorithms show expected improvements of the data locality across the KNL on-chip network.

  5. Plasma turbulence calculations on the Intel iPSC/860 (rx) hypercube

    International Nuclear Information System (INIS)

    Lynch, V.E.; Ruiter, J.R.

    1990-01-01

    One approach to improving the real-time efficiency of plasma turbulence calculations is to use a parallel algorithm. A serial algorithm used for plasma turbulence calculations was modified to allocate a radial region in each node. In this way, convolutions at a fixed radius are performed in parallel, and communication is limited to boundary values for each radial region. For a semi-implicity numerical scheme (tridiagonal matrix solver), there is a factor of 3 improvement in efficiency with the Intel iPSC/860 machine using 64 processors over a single-processor Cray-II. For block-tridiagonal matrix cases (fully implicit code), a second parallelization takes place. The Fourier components are distributed in nodes. In each node, the block-tridiagonal matrix is inverted for each of allocated Fourier components. The algorithm for this second case has not yet been optimized. 10 refs., 4 figs

  6. Emmarcar el debat: Lliure expressió contra propietat intel·lectual, els propers cinquanta anys

    Directory of Open Access Journals (Sweden)

    Eben Moglen

    2007-02-01

    Full Text Available

    El Prof. Moglen explica i analitza, des d'una perspectiva històrica, la profunda revolució social i legal que resulta de la tecnologia digital quan aquesta s'aplica a tots els camps: programari, música i tot tipus de creacions. En concret, explica la manera en què la tecnologia digital està forçant una modificació substancial (desaparició dels sistemes de propietat intel·lectual i fa prediccions per al futur pròxim dels mercats de la PI.

  7. Using Intel Xeon Phi to accelerate the WRF TEMF planetary boundary layer scheme

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen

    2014-05-01

    The Weather Research and Forecasting (WRF) model is designed for numerical weather prediction and atmospheric research. The WRF software infrastructure consists of several components such as dynamic solvers and physics schemes. Numerical models are used to resolve the large-scale flow. However, subgrid-scale parameterizations are for an estimation of small-scale properties (e.g., boundary layer turbulence and convection, clouds, radiation). Those have a significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. For the cloudy planetary boundary layer (PBL), it is fundamental to parameterize vertical turbulent fluxes and subgrid-scale condensation in a realistic manner. A parameterization based on the Total Energy - Mass Flux (TEMF) that unifies turbulence and moist convection components produces a better result that the other PBL schemes. For that reason, the TEMF scheme is chosen as the PBL scheme we optimized for Intel Many Integrated Core (MIC), which ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our optimization results for TEMF planetary boundary layer scheme. The optimizations that were performed were quite generic in nature. Those optimizations included vectorization of the code to utilize vector units inside each CPU. Furthermore, memory access was improved by scalarizing some of the intermediate arrays. The results show that the optimization improved MIC performance by 14.8x. Furthermore, the optimizations increased CPU performance by 2.6x compared to the original multi-threaded code on quad core Intel Xeon E5-2603 running at 1.8 GHz. Compared to the optimized code running on a single CPU socket the optimized MIC code is 6.2x faster.

  8. A High Performance Computing Framework for Physics-based Modeling and Simulation of Military Ground Vehicles

    Science.gov (United States)

    2011-03-25

    cluster. The co-processing idea is the enabler of the heterogeneous computing concept advertised recently as the paradigm capable of delivering exascale ...Petascale to Exascale : Extending Intel’s HPC Commitment: http://download.intel.com/pressroom/archive/reference/ISC_2010_Skaugen_keynote.pdf in

  9. Applications Performance on NAS Intel Paragon XP/S - 15#

    Science.gov (United States)

    Saini, Subhash; Simon, Horst D.; Copper, D. M. (Technical Monitor)

    1994-01-01

    The Numerical Aerodynamic Simulation (NAS) Systems Division received an Intel Touchstone Sigma prototype model Paragon XP/S- 15 in February, 1993. The i860 XP microprocessor with an integrated floating point unit and operating in dual -instruction mode gives peak performance of 75 million floating point operations (NIFLOPS) per second for 64 bit floating point arithmetic. It is used in the Paragon XP/S-15 which has been installed at NAS, NASA Ames Research Center. The NAS Paragon has 208 nodes and its peak performance is 15.6 GFLOPS. Here, we will report on early experience using the Paragon XP/S- 15. We have tested its performance using both kernels and applications of interest to NAS. We have measured the performance of BLAS 1, 2 and 3 both assembly-coded and Fortran coded on NAS Paragon XP/S- 15. Furthermore, we have investigated the performance of a single node one-dimensional FFT, a distributed two-dimensional FFT and a distributed three-dimensional FFT Finally, we measured the performance of NAS Parallel Benchmarks (NPB) on the Paragon and compare it with the performance obtained on other highly parallel machines, such as CM-5, CRAY T3D, IBM SP I, etc. In particular, we investigated the following issues, which can strongly affect the performance of the Paragon: a. Impact of the operating system: Intel currently uses as a default an operating system OSF/1 AD from the Open Software Foundation. The paging of Open Software Foundation (OSF) server at 22 MB to make more memory available for the application degrades the performance. We found that when the limit of 26 NIB per node out of 32 MB available is reached, the application is paged out of main memory using virtual memory. When the application starts paging, the performance is considerably reduced. We found that dynamic memory allocation can help applications performance under certain circumstances. b. Impact of data cache on the i860/XP: We measured the performance of the BLAS both assembly coded and Fortran

  10. Privacy-preserving distributed clustering

    NARCIS (Netherlands)

    Erkin, Z.; Veugen, T.; Toft, T.; Lagendijk, R.L.

    2013-01-01

    Clustering is a very important tool in data mining and is widely used in on-line services for medical, financial and social environments. The main goal in clustering is to create sets of similar objects in a data set. The data set to be used for clustering can be owned by a single entity, or in some

  11. Genetic algorithm based two-mode clustering of metabolomics data

    NARCIS (Netherlands)

    Hageman, J.A.; van den Berg, R.A.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2008-01-01

    Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering

  12. clusterMaker: a multi-algorithm clustering plugin for Cytoscape

    Directory of Open Access Journals (Sweden)

    Morris John H

    2011-11-01

    Full Text Available Abstract Background In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results. The Cytoscape network is linked to all of the other views, so that a selection in one is immediately reflected in the others. clusterMaker is the first Cytoscape plugin to implement such a wide variety of clustering algorithms and visualizations, including the only implementations of hierarchical clustering, dendrogram plus heat map visualization (tree view, k-means, k-medoid, SCPS, AutoSOME, and native (Java MCL. Results Results are presented in the form of three scenarios of use: analysis of protein expression data using a recently published mouse interactome and a mouse microarray data set of nearly one hundred diverse cell/tissue types; the identification of protein complexes in the yeast Saccharomyces cerevisiae; and the cluster analysis of the vicinal oxygen chelate (VOC enzyme superfamily. For scenario one, we explore functionally enriched mouse interactomes specific to particular cellular phenotypes and apply fuzzy clustering. For scenario two, we explore the prefoldin complex in detail using both physical and genetic interaction clusters. For scenario three, we explore the possible annotation of a protein as a methylmalonyl-CoA epimerase within the VOC superfamily. Cytoscape session files for all three scenarios are provided in the Additional Files section. Conclusions The Cytoscape plugin cluster

  13. Cluster Analysis as an Analytical Tool of Population Policy

    Directory of Open Access Journals (Sweden)

    Oksana Mikhaylovna Shubat

    2017-12-01

    Full Text Available The predicted negative trends in Russian demography (falling birth rates, population decline actualize the need to strengthen measures of family and population policy. Our research purpose is to identify groups of Russian regions with similar characteristics in the family sphere using cluster analysis. The findings should make an important contribution to the field of family policy. We used hierarchical cluster analysis based on the Ward method and the Euclidean distance for segmentation of Russian regions. Clustering is based on four variables, which allowed assessing the family institution in the region. The authors used the data of Federal State Statistics Service from 2010 to 2015. Clustering and profiling of each segment has allowed forming a model of Russian regions depending on the features of the family institution in these regions. The authors revealed four clusters grouping regions with similar problems in the family sphere. This segmentation makes it possible to develop the most relevant family policy measures in each group of regions. Thus, the analysis has shown a high degree of differentiation of the family institution in the regions. This suggests that a unified approach to population problems’ solving is far from being effective. To achieve greater results in the implementation of family policy, a differentiated approach is needed. Methods of multidimensional data classification can be successfully applied as a relevant analytical toolkit. Further research could develop the adaptation of multidimensional classification methods to the analysis of the population problems in Russian regions. In particular, the algorithms of nonparametric cluster analysis may be of relevance in future studies.

  14. Spectral-element simulation of two-dimensional elastic wave propagation in fully heterogeneous media on a GPU cluster

    Science.gov (United States)

    Rudianto, Indra; Sudarmaji

    2018-04-01

    We present an implementation of the spectral-element method for simulation of two-dimensional elastic wave propagation in fully heterogeneous media. We have incorporated most of realistic geological features in the model, including surface topography, curved layer interfaces, and 2-D wave-speed heterogeneity. To accommodate such complexity, we use an unstructured quadrilateral meshing technique. Simulation was performed on a GPU cluster, which consists of 24 core processors Intel Xeon CPU and 4 NVIDIA Quadro graphics cards using CUDA and MPI implementation. We speed up the computation by a factor of about 5 compared to MPI only, and by a factor of about 40 compared to Serial implementation.

  15. Experience with low-power x86 processors (Atom) for HEP usage. An initial analysis of the Intel® dual core Atom™ N330 processor

    CERN Document Server

    Balazs, G; Nowak, A; CERN. Geneva. IT Department

    2009-01-01

    In this paper we compare a system based on an Intel Atom N330 low-power processor to a modern Intel Xeon® dual-socket server using CERN IT’s standard criteria for comparing price-performance and performance per watt. The Xeon server corresponds to what is typically acquired as servers in the LHC Computing Grid. The comparisons used public pricing information from November 2008. After the introduction in section 1, section 2 describes the hardware and software setup. In section 3 we describe the power measurements we did and in section 4 we discuss the throughput performance results. In section 5 we summarize our initial conclusions. We then go on to describe our long term vision and possible future scenarios for using such low-power processors, and finally we list interesting development directions.

  16. A performance study of sparse Cholesky factorization on INTEL iPSC/860

    Science.gov (United States)

    Zubair, M.; Ghose, M.

    1992-01-01

    The problem of Cholesky factorization of a sparse matrix has been very well investigated on sequential machines. A number of efficient codes exist for factorizing large unstructured sparse matrices. However, there is a lack of such efficient codes on parallel machines in general, and distributed machines in particular. Some of the issues that are critical to the implementation of sparse Cholesky factorization on a distributed memory parallel machine are ordering, partitioning and mapping, load balancing, and ordering of various tasks within a processor. Here, we focus on the effect of various partitioning schemes on the performance of sparse Cholesky factorization on the Intel iPSC/860. Also, a new partitioning heuristic for structured as well as unstructured sparse matrices is proposed, and its performance is compared with other schemes.

  17. The Multimorbidity Cluster Analysis Tool: Identifying Combinations and Permutations of Multiple Chronic Diseases Using a Record-Level Computational Analysis

    Directory of Open Access Journals (Sweden)

    Kathryn Nicholson

    2017-12-01

    Full Text Available Introduction: Multimorbidity, or the co-occurrence of multiple chronic health conditions within an individual, is an increasingly dominant presence and burden in modern health care systems.  To fully capture its complexity, further research is needed to uncover the patterns and consequences of these co-occurring health states.  As such, the Multimorbidity Cluster Analysis Tool and the accompanying Multimorbidity Cluster Analysis Toolkit have been created to allow researchers to identify distinct clusters that exist within a sample of participants or patients living with multimorbidity.  Development: The Tool and Toolkit were developed at Western University in London, Ontario, Canada.  This open-access computational program (JAVA code and executable file was developed and tested to support an analysis of thousands of individual records and up to 100 disease diagnoses or categories.  Application: The computational program can be adapted to the methodological elements of a research project, including type of data, type of chronic disease reporting, measurement of multimorbidity, sample size and research setting.  The computational program will identify all existing, and mutually exclusive, combinations and permutations within the dataset.  An application of this computational program is provided as an example, in which more than 75,000 individual records and 20 chronic disease categories resulted in the detection of 10,411 unique combinations and 24,647 unique permutations among female and male patients.  Discussion: The Tool and Toolkit are now available for use by researchers interested in exploring the complexities of multimorbidity.  Its careful use, and the comparison between results, will be valuable additions to the nuanced understanding of multimorbidity.

  18. Computationally efficient implementation of sarse-tap FIR adaptive filters with tap-position control on intel IA-32 processors

    OpenAIRE

    Hirano, Akihiro; Nakayama, Kenji

    2008-01-01

    This paper presents an computationally ef cient implementation of sparse-tap FIR adaptive lters with tapposition control on Intel IA-32 processors with single-instruction multiple-data (SIMD) capability. In order to overcome randomorder memory access which prevents a ectorization, a blockbased processing and a re-ordering buffer are introduced. A dynamic register allocation and the use of memory-to-register operations help the maximization of the loop-unrolling level. Up to 66percent speedup ...

  19. GNAQPMS v1.1: accelerating the Global Nested Air Quality Prediction Modeling System (GNAQPMS) on Intel Xeon Phi processors

    OpenAIRE

    H. Wang; H. Wang; H. Wang; H. Wang; H. Chen; H. Chen; Q. Wu; Q. Wu; J. Lin; X. Chen; X. Xie; R. Wang; R. Wang; X. Tang; Z. Wang

    2017-01-01

    The Global Nested Air Quality Prediction Modeling System (GNAQPMS) is the global version of the Nested Air Quality Prediction Modeling System (NAQPMS), which is a multi-scale chemical transport model used for air quality forecast and atmospheric environmental research. In this study, we present the porting and optimisation of GNAQPMS on a second-generation Intel Xeon Phi processor, codenamed Knights Landing (KNL). Compared with the first-generation Xeon Phi coprocessor (code...

  20. An efficient MPI/OpenMP parallelization of the Hartree–Fock–Roothaan method for the first generation of Intel® Xeon Phi™ processor architecture

    International Nuclear Information System (INIS)

    Mironov, Vladimir; Moskovsky, Alexander; D’Mello, Michael; Alexeev, Yuri

    2017-01-01

    The Hartree-Fock (HF) method in the quantum chemistry package GAMESS represents one of the most irregular algorithms in computation today. Major steps in the calculation are the irregular computation of electron repulsion integrals (ERIs) and the building of the Fock matrix. These are the central components of the main Self Consistent Field (SCF) loop, the key hotspot in Electronic Structure (ES) codes. By threading the MPI ranks in the official release of the GAMESS code, we not only speed up the main SCF loop (4x to 6x for large systems), but also achieve a significant (>2x) reduction in the overall memory footprint. These improvements are a direct consequence of memory access optimizations within the MPI ranks. We benchmark our implementation against the official release of the GAMESS code on the Intel R Xeon PhiTM supercomputer. Here, scaling numbers are reported on up to 7,680 cores on Intel Xeon Phi coprocessors.

  1. Many-core technologies: The move to energy-efficient, high-throughput x86 computing (TFLOPS on a chip)

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms at all levels of integration and programming to achieve higher performance and energy efficiency. Especially in the area of High-Performance Computing (HPC) users can entertain a combination of different hardware and software parallel architectures and programming environments. Those technologies range from vectorization and SIMD computation over shared memory multi-threading (e.g. OpenMP) to distributed memory message passing (e.g. MPI) on cluster systems. We will discuss HPC industry trends and Intel's approach to it from processor/system architectures and research activities to hardware and software tools technologies. This includes the recently announced new Intel(r) Many Integrated Core (MIC) architecture for highly-parallel workloads and general purpose, energy efficient TFLOPS performance, some of its architectural features and its programming environment. At the end we will have a br...

  2. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    CERN Document Server

    Abdurachmanov, David; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

    2014-01-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

  3. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    Science.gov (United States)

    Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Knight, Robert; Muzaffar, Shahzad

    2015-05-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG).

  4. Heterogeneous High Throughput Scientific Computing with APM X-Gene and Intel Xeon Phi

    International Nuclear Information System (INIS)

    Abdurachmanov, David; Bockelman, Brian; Elmer, Peter; Eulisse, Giulio; Muzaffar, Shahzad; Knight, Robert

    2015-01-01

    Electrical power requirements will be a constraint on the future growth of Distributed High Throughput Computing (DHTC) as used by High Energy Physics. Performance-per-watt is a critical metric for the evaluation of computer architectures for cost- efficient computing. Additionally, future performance growth will come from heterogeneous, many-core, and high computing density platforms with specialized processors. In this paper, we examine the Intel Xeon Phi Many Integrated Cores (MIC) co-processor and Applied Micro X-Gene ARMv8 64-bit low-power server system-on-a-chip (SoC) solutions for scientific computing applications. We report our experience on software porting, performance and energy efficiency and evaluate the potential for use of such technologies in the context of distributed computing systems such as the Worldwide LHC Computing Grid (WLCG). (paper)

  5. Evaluation of the Intel iWarp parallel processor for space flight applications

    Science.gov (United States)

    Hine, Butler P., III; Fong, Terrence W.

    1993-01-01

    The potential of a DARPA-sponsored advanced processor, the Intel iWarp, for use in future SSF Data Management Systems (DMS) upgrades is evaluated through integration into the Ames DMS testbed and applications testing. The iWarp is a distributed, parallel computing system well suited for high performance computing applications such as matrix operations and image processing. The system architecture is modular, supports systolic and message-based computation, and is capable of providing massive computational power in a low-cost, low-power package. As a consequence, the iWarp offers significant potential for advanced space-based computing. This research seeks to determine the iWarp's suitability as a processing device for space missions. In particular, the project focuses on evaluating the ease of integrating the iWarp into the SSF DMS baseline architecture and the iWarp's ability to support computationally stressing applications representative of SSF tasks.

  6. Large scale cluster computing workshop

    International Nuclear Information System (INIS)

    Dane Skow; Alan Silverman

    2002-01-01

    Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community

  7. OBSERVED SCALING RELATIONS FOR STRONG LENSING CLUSTERS: CONSEQUENCES FOR COSMOLOGY AND CLUSTER ASSEMBLY

    International Nuclear Information System (INIS)

    Comerford, Julia M.; Moustakas, Leonidas A.; Natarajan, Priyamvada

    2010-01-01

    Scaling relations of observed galaxy cluster properties are useful tools for constraining cosmological parameters as well as cluster formation histories. One of the key cosmological parameters, σ 8 , is constrained using observed clusters of galaxies, although current estimates of σ 8 from the scaling relations of dynamically relaxed galaxy clusters are limited by the large scatter in the observed cluster mass-temperature (M-T) relation. With a sample of eight strong lensing clusters at 0.3 8 , but combining the cluster concentration-mass relation with the M-T relation enables the inclusion of unrelaxed clusters as well. Thus, the resultant gains in the accuracy of σ 8 measurements from clusters are twofold: the errors on σ 8 are reduced and the cluster sample size is increased. Therefore, the statistics on σ 8 determination from clusters are greatly improved by the inclusion of unrelaxed clusters. Exploring cluster scaling relations further, we find that the correlation between brightest cluster galaxy (BCG) luminosity and cluster mass offers insight into the assembly histories of clusters. We find preliminary evidence for a steeper BCG luminosity-cluster mass relation for strong lensing clusters than the general cluster population, hinting that strong lensing clusters may have had more active merging histories.

  8. Co-clustering models, algorithms and applications

    CERN Document Server

    Govaert, Gérard

    2013-01-01

    Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixture

  9. Efficient irregular wavefront propagation algorithms on Intel® Xeon Phi™

    Science.gov (United States)

    Gomes, Jeremias M.; Teodoro, George; de Melo, Alba; Kong, Jun; Kurc, Tahsin; Saltz, Joel H.

    2016-01-01

    We investigate the execution of the Irregular Wavefront Propagation Pattern (IWPP), a fundamental computing structure used in several image analysis operations, on the Intel® Xeon Phi™ co-processor. An efficient implementation of IWPP on the Xeon Phi is a challenging problem because of IWPP’s irregularity and the use of atomic instructions in the original IWPP algorithm to resolve race conditions. On the Xeon Phi, the use of SIMD and vectorization instructions is critical to attain high performance. However, SIMD atomic instructions are not supported. Therefore, we propose a new IWPP algorithm that can take advantage of the supported SIMD instruction set. We also evaluate an alternate storage container (priority queue) to track active elements in the wavefront in an effort to improve the parallel algorithm efficiency. The new IWPP algorithm is evaluated with Morphological Reconstruction and Imfill operations as use cases. Our results show performance improvements of up to 5.63× on top of the original IWPP due to vectorization. Moreover, the new IWPP achieves speedups of 45.7× and 1.62×, respectively, as compared to efficient CPU and GPU implementations. PMID:27298591

  10. Efficient irregular wavefront propagation algorithms on Intel® Xeon Phi™.

    Science.gov (United States)

    Gomes, Jeremias M; Teodoro, George; de Melo, Alba; Kong, Jun; Kurc, Tahsin; Saltz, Joel H

    2015-10-01

    We investigate the execution of the Irregular Wavefront Propagation Pattern (IWPP), a fundamental computing structure used in several image analysis operations, on the Intel ® Xeon Phi ™ co-processor. An efficient implementation of IWPP on the Xeon Phi is a challenging problem because of IWPP's irregularity and the use of atomic instructions in the original IWPP algorithm to resolve race conditions. On the Xeon Phi, the use of SIMD and vectorization instructions is critical to attain high performance. However, SIMD atomic instructions are not supported. Therefore, we propose a new IWPP algorithm that can take advantage of the supported SIMD instruction set. We also evaluate an alternate storage container (priority queue) to track active elements in the wavefront in an effort to improve the parallel algorithm efficiency. The new IWPP algorithm is evaluated with Morphological Reconstruction and Imfill operations as use cases. Our results show performance improvements of up to 5.63 × on top of the original IWPP due to vectorization. Moreover, the new IWPP achieves speedups of 45.7 × and 1.62 × , respectively, as compared to efficient CPU and GPU implementations.

  11. Investigation of Large Scale Cortical Models on Clustered Multi-Core Processors

    Science.gov (United States)

    2013-02-01

    Playstation 3 with 6 available SPU cores outperforms the Intel Xeon processor (with 4 cores) by about 1.9 times for the HTM model and by 2.4 times...runtime breakdowns of the HTM and Dean models respectively on the Cell processor (on the Playstation 3) and the Intel Xeon processor ( 4 thread...YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY) 2. REPORT TYPE 3. DATES COVERED (From - To) 4 . TITLE AND SUBTITLE 5a. CONTRACT NUMBER

  12. Plasma Science and Applications at the Intel Science Fair: A Retrospective

    Science.gov (United States)

    Berry, Lee

    2009-11-01

    For the past five years, the Coalition for Plasma Science (CPS) has presented an award for a plasma project at the Intel International Science and Engineering Fair (ISEF). Eligible projects have ranged from grape-based plasma production in a microwave oven to observation of the effects of viscosity in a fluid model of quark-gluon plasma. Most projects have been aimed at applications, including fusion, thrusters, lighting, materials processing, and GPS improvements. However diagnostics (spectroscopy), technology (magnets), and theory (quark-gluon plasmas) have also been represented. All of the CPS award-winning projects so far have been based on experiments, with two awards going to women students and three to men. Since the award was initiated, both the number and quality of plasma projects has increased. The CPS expects this trend to continue, and looks forward to continuing its work with students who are excited about the possibilities of plasma. You too can share this excitement by judging at the 2010 fair in San Jose on May 11-12.

  13. Fuzzy Clustering

    DEFF Research Database (Denmark)

    Berks, G.; Keyserlingk, Diedrich Graf von; Jantzen, Jan

    2000-01-01

    A symptom is a condition indicating the presence of a disease, especially, when regarded as an aid in diagnosis.Symptoms are the smallest units indicating the existence of a disease. A syndrome on the other hand is an aggregate, set or cluster of concurrent symptoms which together indicate...... and clustering are the basic concerns in medicine. Classification depends on definitions of the classes and their required degree of participant of the elements in the cases' symptoms. In medicine imprecise conditions are the rule and therefore fuzzy methods are much more suitable than crisp ones. Fuzzy c......-mean clustering is an easy and well improved tool, which has been applied in many medical fields. We used c-mean fuzzy clustering after feature extraction from an aphasia database. Factor analysis was applied on a correlation matrix of 26 symptoms of language disorders and led to five factors. The factors...

  14. Cluster analysis as a prediction tool for pregnancy outcomes.

    Science.gov (United States)

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  15. HIV-TRACE (Transmission Cluster Engine): a tool for large scale molecular epidemiology of HIV-1 and other rapidly evolving pathogens.

    Science.gov (United States)

    Kosakovsky Pond, Sergei L; Weaver, Steven; Leigh Brown, Andrew J; Wertheim, Joel O

    2018-01-31

    In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoeleather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, i.e., on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from github.com/veg/hivtrace, along with the accompanying result visualization module from github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens. © The Author 2018. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. Homo-FRET imaging as a tool to quantify protein and lipid clustering.

    Science.gov (United States)

    Bader, Arjen N; Hoetzl, Sandra; Hofman, Erik G; Voortman, Jarno; van Bergen en Henegouwen, Paul M P; van Meer, Gerrit; Gerritsen, Hans C

    2011-02-25

    Homo-FRET, Förster resonance energy transfer between identical fluorophores, can be conveniently measured by observing its effect on the fluorescence anisotropy. This review aims to summarize the possibilities of fluorescence anisotropy imaging techniques to investigate clustering of identical proteins and lipids. Homo-FRET imaging has the ability to determine distances between fluorophores. In addition it can be employed to quantify cluster sizes as well as cluster size distributions. The interpretation of homo-FRET signals is complicated by the fact that both the mutual orientations of the fluorophores and the number of fluorophores per cluster affect the fluorescence anisotropy in a similar way. The properties of the fluorescence probes are very important. Taking these properties into account is critical for the correct interpretation of homo-FRET signals in protein- and lipid-clustering studies. This is be exemplified by studies on the clustering of the lipid raft markers GPI and K-ras, as well as for EGF receptor clustering in the plasma membrane. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Super computer made with Linux cluster

    International Nuclear Information System (INIS)

    Lee, Jeong Hun; Oh, Yeong Eun; Kim, Jeong Seok

    2002-01-01

    This book consists of twelve chapters, which introduce super computer made with Linux cluster. The contents of this book are Linux cluster, the principle of cluster, design of Linux cluster, general things for Linux, building up terminal server and client, Bear wolf cluster by Debian GNU/Linux, cluster system with red hat, Monitoring system, application programming-MPI, on set-up and install application programming-PVM, with PVM programming and XPVM application programming-open PBS with composition and install and set-up and GRID with GRID system, GSI, GRAM, MDS, its install and using of tool kit

  18. Physics development of web-based tools for use in hardware clusters doing lattice physics

    International Nuclear Information System (INIS)

    Dreher, P.; Akers, W.; Chen, J.; Chen, Y.; Watson, C.

    2002-01-01

    Jefferson Lab and MIT are developing a set of web-based tools within the Lattice Hadron Physics Collaboration to allow lattice QCD theorists to treat the computational facilities located at the two sites as a single meta-facility. The prototype Lattice Portal provides researchers the ability to submit jobs to the cluster, browse data caches, and transfer files between cache and off-line storage. The user can view the configuration of the PBS servers and to monitor both the status of all batch queues as well as the jobs in each queue. Work is starting on expanding the present system to include job submissions at the meta-facility level (shared queue), as well as multi-site file transfers and enhanced policy-based data management capabilities

  19. Physics development of web-based tools for use in hardware clusters doing lattice physics

    International Nuclear Information System (INIS)

    Dreher, P.; Akers, Walt; Jian-ping Chen; Chen, Y.; William, A. Watson III

    2001-01-01

    Jefferson Lab and MIT are developing a set of web-based tools within the Lattice Hadron Physics Collaboration to allow lattice QCD theorists to treat the computational facilities located at the two sites as a single meta-facility. The prototype Lattice Portal provides researchers the ability to submit jobs to the cluster, browse data caches, and transfer files between cache and off-line storage. The user can view the configuration of the PBS servers and to monitor both the status of all batch queues as well as the jobs in each queue. Work is starting on expanding the present system to include job submissions at the meta-facility level (shared queue), as well as multi-site file transfers and enhanced policy-based data management capabilities

  20. Physics development of web-based tools for use in hardware clusters doing lattice physics

    Energy Technology Data Exchange (ETDEWEB)

    Dreher, P.; Akers, W.; Chen, J.; Chen, Y.; Watson, C

    2002-03-01

    Jefferson Lab and MIT are developing a set of web-based tools within the Lattice Hadron Physics Collaboration to allow lattice QCD theorists to treat the computational facilities located at the two sites as a single meta-facility. The prototype Lattice Portal provides researchers the ability to submit jobs to the cluster, browse data caches, and transfer files between cache and off-line storage. The user can view the configuration of the PBS servers and to monitor both the status of all batch queues as well as the jobs in each queue. Work is starting on expanding the present system to include job submissions at the meta-facility level (shared queue), as well as multi-site file transfers and enhanced policy-based data management capabilities.

  1. cluML: A markup language for clustering and cluster validity assessment of microarray data.

    Science.gov (United States)

    Bolshakova, Nadia; Cunningham, Pádraig

    2005-01-01

    cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

  2. Multi-threaded ATLAS simulation on Intel Knights Landing processors

    Science.gov (United States)

    Farrell, Steven; Calafiura, Paolo; Leggett, Charles; Tsulaia, Vakhtang; Dotti, Andrea; ATLAS Collaboration

    2017-10-01

    The Knights Landing (KNL) release of the Intel Many Integrated Core (MIC) Xeon Phi line of processors is a potential game changer for HEP computing. With 72 cores and deep vector registers, the KNL cards promise significant performance benefits for highly-parallel, compute-heavy applications. Cori, the newest supercomputer at the National Energy Research Scientific Computing Center (NERSC), was delivered to its users in two phases with the first phase online at the end of 2015 and the second phase now online at the end of 2016. Cori Phase 2 is based on the KNL architecture and contains over 9000 compute nodes with 96GB DDR4 memory. ATLAS simulation with the multithreaded Athena Framework (AthenaMT) is a good potential use-case for the KNL architecture and supercomputers like Cori. ATLAS simulation jobs have a high ratio of CPU computation to disk I/O and have been shown to scale well in multi-threading and across many nodes. In this paper we will give an overview of the ATLAS simulation application with details on its multi-threaded design. Then, we will present a performance analysis of the application on KNL devices and compare it to a traditional x86 platform to demonstrate the capabilities of the architecture and evaluate the benefits of utilizing KNL platforms like Cori for ATLAS production.

  3. La responsabilitat davant la intel·ligència artificial en el comerç electrònic

    OpenAIRE

    Martín i Palomas, Elisabet

    2015-01-01

    Es planteja en aquesta tesi l'efecte produït sobre la responsabilitat derivada de les accions realitzades autònomament per sistemes dotats d'intel·ligència artificial, sense la participació directa de cap ésser humà, en els temes més directament relacionats amb el comerç electrònic. Per a això s'analitzen les activitats realitzades per algunes de les principals empreses internacionals de comerç electrònic, com el grup nord-americà eBay o el grup xinès Alibaba. Després de desenvolupar els prin...

  4. Predicting the mean cycle time as a function of throughput and product mix for cluster tool workstations using EPT-based aggregate modeling

    NARCIS (Netherlands)

    Veeger, C.P.L.; Etman, L.F.P.; Herk, van J.; Rooda, J.E.

    2009-01-01

    Predicting the mean cycle time as a function of throughput and product mix is helpful in making the production planning for cluster tools. To predict the mean cycle time, detailed simulation models may be used. However, detailed models require much development time, and it may not be possible to

  5. Performance Evaluation of Supercomputers using HPCC and IMB Benchmarks

    Science.gov (United States)

    Saini, Subhash; Ciotti, Robert; Gunney, Brian T. N.; Spelce, Thomas E.; Koniges, Alice; Dossa, Don; Adamidis, Panagiotis; Rabenseifner, Rolf; Tiyyagura, Sunil R.; Mueller, Matthias; hide

    2006-01-01

    The HPC Challenge (HPCC) benchmark suite and the Intel MPI Benchmark (IMB) are used to compare and evaluate the combined performance of processor, memory subsystem and interconnect fabric of five leading supercomputers - SGI Altix BX2, Cray XI, Cray Opteron Cluster, Dell Xeon cluster, and NEC SX-8. These five systems use five different networks (SGI NUMALINK4, Cray network, Myrinet, InfiniBand, and NEC IXS). The complete set of HPCC benchmarks are run on each of these systems. Additionally, we present Intel MPI Benchmarks (IMB) results to study the performance of 11 MPI communication functions on these systems.

  6. Macroprocessing is the computing design principle for the times

    CERN Multimedia

    2001-01-01

    In a keynote speech, Intel Corporation CEO Craig Barrett emphasized that "macroprocessing" provides innovative and cost effective solutions to companies that they can customize and scale to match their own data needs. Barrett showcased examples of macroprocessing implementations from business, government and the scientific community, which use the power of Intel Architecture and Oracle9i Real Application Clusters to build large complex and scalable database solutions. A testimonial from CERN explained how the need for high performance computing to perform scientific research on sub-atomic particles was accomplished by using clusters of Xeon processor-based servers.

  7. Communication overhead on the Intel Paragon, IBM SP2 and Meiko CS-2

    Science.gov (United States)

    Bokhari, Shahid H.

    1995-01-01

    Interprocessor communication overhead is a crucial measure of the power of parallel computing systems-its impact can severely limit the performance of parallel programs. This report presents measurements of communication overhead on three contemporary commercial multicomputer systems: the Intel Paragon, the IBM SP2 and the Meiko CS-2. In each case the time to communicate between processors is presented as a function of message length. The time for global synchronization and memory access is discussed. The performance of these machines in emulating hypercubes and executing random pairwise exchanges is also investigated. It is shown that the interprocessor communication time depends heavily on the specific communication pattern required. These observations contradict the commonly held belief that communication overhead on contemporary machines is independent of the placement of tasks on processors. The information presented in this report permits the evaluation of the efficiency of parallel algorithm implementations against standard baselines.

  8. HeinzelCluster: accelerated reconstruction for FORE and OSEM3D.

    Science.gov (United States)

    Vollmar, S; Michel, C; Treffert, J T; Newport, D F; Casey, M; Knöss, C; Wienhard, K; Liu, X; Defrise, M; Heiss, W D

    2002-08-07

    Using iterative three-dimensional (3D) reconstruction techniques for reconstruction of positron emission tomography (PET) is not feasible on most single-processor machines due to the excessive computing time needed, especially so for the large sinogram sizes of our high-resolution research tomograph (HRRT). In our first approach to speed up reconstruction time we transform the 3D scan into the format of a two-dimensional (2D) scan with sinograms that can be reconstructed independently using Fourier rebinning (FORE) and a fast 2D reconstruction method. On our dedicated reconstruction cluster (seven four-processor systems, Intel PIII@700 MHz, switched fast ethernet and Myrinet, Windows NT Server), we process these 2D sinograms in parallel. We have achieved a speedup > 23 using 26 processors and also compared results for different communication methods (RPC, Syngo, Myrinet GM). The other approach is to parallelize OSEM3D (implementation of C Michel), which has produced the best results for HRRT data so far and is more suitable for an adequate treatment of the sinogram gaps that result from the detector geometry of the HRRT. We have implemented two levels of parallelization for four dedicated cluster (a shared memory fine-grain level on each node utilizing all four processors and a coarse-grain level allowing for 15 nodes) reducing the time for one core iteration from over 7 h to about 35 min.

  9. Pain management in cancer center inpatients: a cluster randomized trial to evaluate a systematic integrated approach—The Edinburgh Pain Assessment and Management Tool

    OpenAIRE

    Fallon, M; Walker, J; Colvin, L; Rodriguez, A; Murray, G; Sharpe, M

    2018-01-01

    Purpose Pain is suboptimally managed in patients with cancer. We aimed to compare the effect of a policy of adding a clinician-delivered bedside pain assessment and management tool (Edinburgh Pain Assessment and management Tool [EPAT]) to usual care (UC) versus UC alone on pain outcomes. Patients and Methods In a two-arm, parallel group, cluster randomized (1:1) trial, we observed pain outcomes in 19 cancer centers in the United Kingdom and then randomly assigned the centers to eithe...

  10. New spectroscopic tool for cluster science: Nonexponential laser fluence dependence of photofragmentation

    International Nuclear Information System (INIS)

    Haberland, H.; Issendorff, B.v.

    1996-01-01

    The photodestruction of Hg 7 ++ and Hg 9 ++ has been measured as a function of photon flux. A polarization dependent deviation from a purely exponential intensity decrease was observed in both cases. This effect, which in essence is an alignment phenomenon, can be used to characterize dissociating electronic transitions of molecules and clusters. For the clusters studied it is due to a one-dimensional transition dipole moment having a fixed direction within the cluster. The effect is expected to play a role in many photoabsorption experiments where molecule/cluster ionization or fragmentation is studied under high photon fluxes. copyright 1996 The American Physical Society

  11. The "p"-Median Model as a Tool for Clustering Psychological Data

    Science.gov (United States)

    Kohn, Hans-Friedrich; Steinley, Douglas; Brusco, Michael J.

    2010-01-01

    The "p"-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around "exemplars", that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of…

  12. Deployment of the OSIRIS EM-PIC code on the Intel Knights Landing architecture

    Science.gov (United States)

    Fonseca, Ricardo

    2017-10-01

    Electromagnetic particle-in-cell (EM-PIC) codes such as OSIRIS have found widespread use in modelling the highly nonlinear and kinetic processes that occur in several relevant plasma physics scenarios, ranging from astrophysical settings to high-intensity laser plasma interaction. Being computationally intensive, these codes require large scale HPC systems, and a continuous effort in adapting the algorithm to new hardware and computing paradigms. In this work, we report on our efforts on deploying the OSIRIS code on the new Intel Knights Landing (KNL) architecture. Unlike the previous generation (Knights Corner), these boards are standalone systems, and introduce several new features, include the new AVX-512 instructions and on-package MCDRAM. We will focus on the parallelization and vectorization strategies followed, as well as memory management, and present a detailed performance evaluation of code performance in comparison with the CPU code. This work was partially supported by Fundaçã para a Ciência e Tecnologia (FCT), Portugal, through Grant No. PTDC/FIS-PLA/2940/2014.

  13. Platform computing

    CERN Multimedia

    2002-01-01

    "Platform Computing releases first grid-enabled workload management solution for IBM eServer Intel and UNIX high performance computing clusters. This Out-of-the-box solution maximizes the performance and capability of applications on IBM HPC clusters" (1/2 page) .

  14. Modeling high-temperature superconductors and metallic alloys on the Intel IPSC/860

    Science.gov (United States)

    Geist, G. A.; Peyton, B. W.; Shelton, W. A.; Stocks, G. M.

    Oak Ridge National Laboratory has embarked on several computational Grand Challenges, which require the close cooperation of physicists, mathematicians, and computer scientists. One of these projects is the determination of the material properties of alloys from first principles and, in particular, the electronic structure of high-temperature superconductors. While the present focus of the project is on superconductivity, the approach is general enough to permit study of other properties of metallic alloys such as strength and magnetic properties. This paper describes the progress to date on this project. We include a description of a self-consistent KKR-CPA method, parallelization of the model, and the incorporation of a dynamic load balancing scheme into the algorithm. We also describe the development and performance of a consolidated KKR-CPA code capable of running on CRAYs, workstations, and several parallel computers without source code modification. Performance of this code on the Intel iPSC/860 is also compared to a CRAY 2, CRAY YMP, and several workstations. Finally, some density of state calculations of two perovskite superconductors are given.

  15. Cluster policy in Europe and Asia: A comparison using selected cluster policy characteristics

    Directory of Open Access Journals (Sweden)

    Martina Sopoligová

    2017-10-01

    Full Text Available Currently, cluster concept is one of the most important tools for governments to enhance competitiveness and innovations through sectoral specialization and cooperation. The paper focuses on applications of the cluster policy in the distinct territorial context of Europe and Asia so that to perform a comparison between different approaches to the cluster concept application in real practice. The paper introduces a comparative study of the cluster policy concepts based on the characteristics defined by the authors, such as scope, approach, targeting, autonomy, institutional coordination, policy instruments and evaluation system studied for the selected European and Asian countries such as Denmark, France, Germany, China, Japan, and South Korea. The research draws upon processing the secondary data obtained through content analysis of the related literature, government documents and strategies, and also cluster funding programmes. The findings demonstrate the diversity of cluster policies implemented in the context of European and Asian conditions at the current stage of their development.

  16. Clustering and Flow Conservation Monitoring Tool for Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Jesús Antonio Puente Fernández

    2018-04-01

    Full Text Available Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN is a new concept of network architecture that provides the separation of control plane (controller and data plane (switches in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

  17. Clustering and Flow Conservation Monitoring Tool for Software Defined Networks.

    Science.gov (United States)

    Puente Fernández, Jesús Antonio; García Villalba, Luis Javier; Kim, Tai-Hoon

    2018-04-03

    Prediction systems present some challenges on two fronts: the relation between video quality and observed session features and on the other hand, dynamics changes on the video quality. Software Defined Networks (SDN) is a new concept of network architecture that provides the separation of control plane (controller) and data plane (switches) in network devices. Due to the existence of the southbound interface, it is possible to deploy monitoring tools to obtain the network status and retrieve a statistics collection. Therefore, achieving the most accurate statistics depends on a strategy of monitoring and information requests of network devices. In this paper, we propose an enhanced algorithm for requesting statistics to measure the traffic flow in SDN networks. Such an algorithm is based on grouping network switches in clusters focusing on their number of ports to apply different monitoring techniques. Such grouping occurs by avoiding monitoring queries in network switches with common characteristics and then, by omitting redundant information. In this way, the present proposal decreases the number of monitoring queries to switches, improving the network traffic and preventing the switching overload. We have tested our optimization in a video streaming simulation using different types of videos. The experiments and comparison with traditional monitoring techniques demonstrate the feasibility of our proposal maintaining similar values decreasing the number of queries to the switches.

  18. Balancing Contention and Synchronization on the Intel Paragon

    Science.gov (United States)

    Bokhari, Shahid H.; Nicol, David M.

    1996-01-01

    The Intel Paragon is a mesh-connected distributed memory parallel computer. It uses an oblivious and deterministic message routing algorithm: this permits us to develop highly optimized schedules for frequently needed communication patterns. The complete exchange is one such pattern. Several approaches are available for carrying it out on the mesh. We study an algorithm developed by Scott. This algorithm assumes that a communication link can carry one message at a time and that a node can only transmit one message at a time. It requires global synchronization to enforce a schedule of transmissions. Unfortunately global synchronization has substantial overhead on the Paragon. At the same time the powerful interconnection mechanism of this machine permits 2 or 3 messages to share a communication link with minor overhead. It can also overlap multiple message transmission from the same node to some extent. We develop a generalization of Scott's algorithm that executes complete exchange with a prescribed contention. Schedules that incur greater contention require fewer synchronization steps. This permits us to tradeoff contention against synchronization overhead. We describe the performance of this algorithm and compare it with Scott's original algorithm as well as with a naive algorithm that does not take interconnection structure into account. The Bounded contention algorithm is always better than Scott's algorithm and outperforms the naive algorithm for all but the smallest message sizes. The naive algorithm fails to work on meshes larger than 12 x 12. These results show that due consideration of processor interconnect and machine performance parameters is necessary to obtain peak performance from the Paragon and its successor mesh machines.

  19. jClustering, an open framework for the development of 4D clustering algorithms.

    Directory of Open Access Journals (Sweden)

    José María Mateos-Pérez

    Full Text Available We present jClustering, an open framework for the design of clustering algorithms in dynamic medical imaging. We developed this tool because of the difficulty involved in manually segmenting dynamic PET images and the lack of availability of source code for published segmentation algorithms. Providing an easily extensible open tool encourages publication of source code to facilitate the process of comparing algorithms and provide interested third parties with the opportunity to review code. The internal structure of the framework allows an external developer to implement new algorithms easily and quickly, focusing only on the particulars of the method being implemented and not on image data handling and preprocessing. This tool has been coded in Java and is presented as an ImageJ plugin in order to take advantage of all the functionalities offered by this imaging analysis platform. Both binary packages and source code have been published, the latter under a free software license (GNU General Public License to allow modification if necessary.

  20. Statistical Significance for Hierarchical Clustering

    Science.gov (United States)

    Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

    2017-01-01

    Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

  1. Using Intel's Knight Landing Processor to Accelerate Global Nested Air Quality Prediction Modeling System (GNAQPMS) Model

    Science.gov (United States)

    Wang, H.; Chen, H.; Chen, X.; Wu, Q.; Wang, Z.

    2016-12-01

    The Global Nested Air Quality Prediction Modeling System for Hg (GNAQPMS-Hg) is a global chemical transport model coupled Hg transport module to investigate the mercury pollution. In this study, we present our work of transplanting the GNAQPMS model on Intel Xeon Phi processor, Knights Landing (KNL) to accelerate the model. KNL is the second-generation product adopting Many Integrated Core Architecture (MIC) architecture. Compared with the first generation Knight Corner (KNC), KNL has more new hardware features, that it can be used as unique processor as well as coprocessor with other CPU. According to the Vtune tool, the high overhead modules in GNAQPMS model have been addressed, including CBMZ gas chemistry, advection and convection module, and wet deposition module. These high overhead modules were accelerated by optimizing code and using new techniques of KNL. The following optimized measures was done: 1) Changing the pure MPI parallel mode to hybrid parallel mode with MPI and OpenMP; 2.Vectorizing the code to using the 512-bit wide vector computation unit. 3. Reducing unnecessary memory access and calculation. 4. Reducing Thread Local Storage (TLS) for common variables with each OpenMP thread in CBMZ. 5. Changing the way of global communication from files writing and reading to MPI functions. After optimization, the performance of GNAQPMS is greatly increased both on CPU and KNL platform, the single-node test showed that optimized version has 2.6x speedup on two sockets CPU platform and 3.3x speedup on one socket KNL platform compared with the baseline version code, which means the KNL has 1.29x speedup when compared with 2 sockets CPU platform.

  2. Application of Intel Many Integrated Core (MIC) architecture to the Yonsei University planetary boundary layer scheme in Weather Research and Forecasting model

    Science.gov (United States)

    Huang, Melin; Huang, Bormin; Huang, Allen H.

    2014-10-01

    The Weather Research and Forecasting (WRF) model provided operational services worldwide in many areas and has linked to our daily activity, in particular during severe weather events. The scheme of Yonsei University (YSU) is one of planetary boundary layer (PBL) models in WRF. The PBL is responsible for vertical sub-grid-scale fluxes due to eddy transports in the whole atmospheric column, determines the flux profiles within the well-mixed boundary layer and the stable layer, and thus provide atmospheric tendencies of temperature, moisture (including clouds), and horizontal momentum in the entire atmospheric column. The YSU scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. To accelerate the computation process of the YSU scheme, we employ Intel Many Integrated Core (MIC) Architecture as it is a multiprocessor computer structure with merits of efficient parallelization and vectorization essentials. Our results show that the MIC-based optimization improved the performance of the first version of multi-threaded code on Xeon Phi 5110P by a factor of 2.4x. Furthermore, the same CPU-based optimizations improved the performance on Intel Xeon E5-2603 by a factor of 1.6x as compared to the first version of multi-threaded code.

  3. The concept of cluster- villages as planning tool in the rural districts of Denmark

    DEFF Research Database (Denmark)

    Laursen, Lea Louise Holst; Møller, Jørgen

    on economies of scale, or the decentralised model based on proximity. In the developments and debate relating to these matters, strategic and visionary planning is back in the municipal arena as the only tool capable of handling the many different challenges facing the municipalities. Mellem disse...... and uses each other’s strengths, as well as developing the individual village in addition to the specific potentials of that village. In recent years, rural Denmark has been undergoing a sweeping and very noticeable process of adjustment, Development in municipal service provision plays a particular...... to forskellige positioner ser vi en ny mulighed for landsbyudvikling, som vi kalder Clustervillages. In order to investigate the potentials and possibilities of the cluster-village concept the paper will seek to unfold the concept strategically; looking into the benefits of such concept. Further, the paper seeks...

  4. Performance optimization of Qbox and WEST on Intel Knights Landing

    Science.gov (United States)

    Zheng, Huihuo; Knight, Christopher; Galli, Giulia; Govoni, Marco; Gygi, Francois

    We present the optimization of electronic structure codes Qbox and WEST targeting the Intel®Xeon Phi™processor, codenamed Knights Landing (KNL). Qbox is an ab-initio molecular dynamics code based on plane wave density functional theory (DFT) and WEST is a post-DFT code for excited state calculations within many-body perturbation theory. Both Qbox and WEST employ highly scalable algorithms which enable accurate large-scale electronic structure calculations on leadership class supercomputer platforms beyond 100,000 cores, such as Mira and Theta at the Argonne Leadership Computing Facility. In this work, features of the KNL architecture (e.g. hierarchical memory) are explored to achieve higher performance in key algorithms of the Qbox and WEST codes and to develop a road-map for further development targeting next-generation computing architectures. In particular, the optimizations of the Qbox and WEST codes on the KNL platform will target efficient large-scale electronic structure calculations of nanostructured materials exhibiting complex structures and prediction of their electronic and thermal properties for use in solar and thermal energy conversion device. This work was supported by MICCoM, as part of Comp. Mats. Sci. Program funded by the U.S. DOE, Office of Sci., BES, MSE Division. This research used resources of the ALCF, which is a DOE Office of Sci. User Facility under Contract DE-AC02-06CH11357.

  5. Computational Design of Clusters for Catalysis

    Science.gov (United States)

    Jimenez-Izal, Elisa; Alexandrova, Anastassia N.

    2018-04-01

    When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis.

  6. The parallel processing of EGS4 code on distributed memory scalar parallel computer:Intel Paragon XP/S15-256

    Energy Technology Data Exchange (ETDEWEB)

    Takemiya, Hiroshi; Ohta, Hirofumi; Honma, Ichirou

    1996-03-01

    The parallelization of Electro-Magnetic Cascade Monte Carlo Simulation Code, EGS4 on distributed memory scalar parallel computer: Intel Paragon XP/S15-256 is described. EGS4 has the feature that calculation time for one incident particle is quite different from each other because of the dynamic generation of secondary particles and different behavior of each particle. Granularity for parallel processing, parallel programming model and the algorithm of parallel random number generation are discussed and two kinds of method, each of which allocates particles dynamically or statically, are used for the purpose of realizing high speed parallel processing of this code. Among four problems chosen for performance evaluation, the speedup factors for three problems have been attained to nearly 100 times with 128 processor. It has been found that when both the calculation time for each incident particles and its dispersion are large, it is preferable to use dynamic particle allocation method which can average the load for each processor. And it has also been found that when they are small, it is preferable to use static particle allocation method which reduces the communication overhead. Moreover, it is pointed out that to get the result accurately, it is necessary to use double precision variables in EGS4 code. Finally, the workflow of program parallelization is analyzed and tools for program parallelization through the experience of the EGS4 parallelization are discussed. (author).

  7. Photometric redshifts as a tool for studying the Coma cluster galaxy populations

    Science.gov (United States)

    Adami, C.; Ilbert, O.; Pelló, R.; Cuillandre, J. C.; Durret, F.; Mazure, A.; Picat, J. P.; Ulmer, M. P.

    2008-12-01

    Aims: We apply photometric redshift techniques to an investigation of the Coma cluster galaxy luminosity function (GLF) at faint magnitudes, in particular in the u* band where basically no studies are presently available at these magnitudes. Methods: Cluster members were selected based on probability distribution function from photometric redshift calculations applied to deep u^*, B, V, R, I images covering a region of almost 1 deg2 (completeness limit R ~ 24). In the area covered only by the u* image, the GLF was also derived after a statistical background subtraction. Results: Global and local GLFs in the B, V, R, and I bands obtained with photometric redshift selection are consistent with our previous results based on a statistical background subtraction. The GLF in the u* band shows an increase in the faint end slope towards the outer regions of the cluster. The analysis of the multicolor type spatial distribution reveals that late type galaxies are distributed in clumps in the cluster outskirts, where X-ray substructures are also detected and where the GLF in the u* band is steeper. Conclusions: We can reproduce the GLFs computed with classical statistical subtraction methods by applying a photometric redshift technique. The u* GLF slope is steeper in the cluster outskirts, varying from α ~ -1 in the cluster center to α ~ -2 in the cluster periphery. The concentrations of faint late type galaxies in the cluster outskirts could explain these very steep slopes, assuming a short burst of star formation in these galaxies when entering the cluster. Based on observations obtained with MegaPrime/MegaCam, a joint project of CFHT and CEA/DAPNIA, at the Canada-France-Hawaii Telescope (CFHT) which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique (CNRS) of France, and the University of Hawaii. This work is also partly based on data products produced at

  8. CORECLUSTER: A Degeneracy Based Graph Clustering Framework

    OpenAIRE

    Giatsidis , Christos; Malliaros , Fragkiskos; Thilikos , Dimitrios M. ,; Vazirgiannis , Michalis

    2014-01-01

    International audience; Graph clustering or community detection constitutes an important task forinvestigating the internal structure of graphs, with a plethora of applications in several domains. Traditional tools for graph clustering, such asspectral methods, typically suffer from high time and space complexity. In thisarticle, we present \\textsc{CoreCluster}, an efficient graph clusteringframework based on the concept of graph degeneracy, that can be used along withany known graph clusteri...

  9. Computational Aspects of Nuclear Coupled-Cluster Theory

    International Nuclear Information System (INIS)

    Dean, David Jarvis; Hagen, Gaute; Hjorth-Jensen, M.; Papenbrock, T.F.

    2008-01-01

    Coupled-cluster theory represents an important theoretical tool that we use to solve the quantum many-body problem. Coupled-cluster theory also lends itself to computation in a parallel computing environment. In this article, we present selected results from ab initio studies of stable and weakly bound nuclei utilizing computational techniques that we employ to solve coupled-cluster theory. We also outline several perspectives for future research directions in this area.

  10. Analysis of genetic association using hierarchical clustering and cluster validation indices.

    Science.gov (United States)

    Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

    2017-10-01

    It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Effect of Deep Cryogenic treatment on AISI A8 Tool steel & Development of Wear Mechanism maps using Fuzzy Clustering

    Science.gov (United States)

    Pillai, Nandakumar; Karthikeyan, R., Dr.

    2018-04-01

    Tool steels are widely classified according to their constituents and type of thermal treatments carried out to obtain its properties. Viking a special purpose tool steel coming under AISI A8 cold working steel classification is widely used for heavy duty blanking and forming operations. The optimum combination of wear resistance and toughness as well as ease of machinability in pre-treated condition makes this material accepted in heavy cutting and non cutting tool manufacture. Air or vacuum hardening is recommended as the normal treatment procedure to obtain the desired mechanical and tribological properties for steels under this category. In this study, we are incorporating a deep cryogenic phase within the conventional treatment cycle both before and after tempering. The thermal treatments at sub zero temperatures up to -195°C using cryogenic chamber with liquid nitrogen as medium was conducted. Micro structural changes in its microstructure and the corresponding improvement in the tribological and physical properties are analyzed. The cryogenic treatment leads to more conversion of retained austenite to martensite and also formation of fine secondary carbides. The microstructure is studied using the micrographs taken using optical microscopy. The wear tests are conducted on DUCOM tribometer for different combinations of speed and load under normal temperature. The wear rates and coefficient of friction obtained from these experiments are used to developed wear mechanism maps with the help of fuzzy c means clustering and probabilistic neural network models. Fuzzy C means clustering is an effective algorithm to group data of similar patterns. The wear mechanisms obtained from the computationally developed maps are then compared with the SEM photographs taken and the improvement in properties due to this additional cryogenic treatment is validated.

  12. Clustering methods for the optimization of atomic cluster structure

    Science.gov (United States)

    Bagattini, Francesco; Schoen, Fabio; Tigli, Luca

    2018-04-01

    In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.

  13. X ray emission: a tool and a probe for laser - clusters interaction

    International Nuclear Information System (INIS)

    Prigent, Ch.

    2004-12-01

    In intense laser-cluster interaction, the experimental results show a strong energetic coupling between radiation and matter. We have measured absolute X-ray yields and charge state distributions under well control conditions as a function of physical parameters governing the interaction; namely laser intensity, pulse duration, wavelength or polarization state of the laser light, the size and the species of the clusters (Ar, Kr, Xe). We have highlighted, for the first time, an intensity threshold in the X-ray production very low (∼ 2.10 14 W/cm 2 for a pulse duration of 300 fs) which can results from an effect of the dynamical polarisation of clusters in an intense electric field. A weak dependence with the wavelength (400 nm / 800 nm) on the absolute X-ray yields has been found. Moreover, we have observed a saturation of the X-ray emission probability below a critical cluster size. (author)

  14. Multiscale visual quality assessment for cluster analysis with self-organizing maps

    Science.gov (United States)

    Bernard, Jürgen; von Landesberger, Tatiana; Bremm, Sebastian; Schreck, Tobias

    2011-01-01

    Cluster analysis is an important data mining technique for analyzing large amounts of data, reducing many objects to a limited number of clusters. Cluster visualization techniques aim at supporting the user in better understanding the characteristics and relationships among the found clusters. While promising approaches to visual cluster analysis already exist, these usually fall short of incorporating the quality of the obtained clustering results. However, due to the nature of the clustering process, quality plays an important aspect, as for most practical data sets, typically many different clusterings are possible. Being aware of clustering quality is important to judge the expressiveness of a given cluster visualization, or to adjust the clustering process with refined parameters, among others. In this work, we present an encompassing suite of visual tools for quality assessment of an important visual cluster algorithm, namely, the Self-Organizing Map (SOM) technique. We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar-valued quality scores up to the structural comparison of a given SOM clustering with output of additional supportive clustering methods. The suite of methods allows the user to assess the SOM quality on the appropriate abstraction level, and arrive at improved clustering results. We implement our tools in an integrated system, apply it on experimental data sets, and show its applicability.

  15. Cluster growing process and a sequence of magic numbers

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Solov'yov, Andrey V.; Greiner, Walter

    2003-01-01

    demonstrate that in this way all known global minimum structures of the Lennard-Jones (LJ) clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic number sequence for the clusters of noble gas atoms......We present a new theoretical framework for modeling the cluster growing process. Starting from the initial tetrahedral cluster configuration, adding new atoms to the system, and absorbing its energy at each step, we find cluster growing paths up to the cluster sizes of more than 100 atoms. We...

  16. Multiple Clustering Views via Constrained Projections

    DEFF Research Database (Denmark)

    Dang, Xuan-Hong; Assent, Ira; Bailey, James

    2012-01-01

    Clustering, the grouping of data based on mutual similarity, is often used as one of principal tools to analyze and understand data. Unfortunately, most conventional techniques aim at finding only a single clustering over the data. For many practical applications, especially those being described...... in high dimensional data, it is common to see that the data can be grouped into different yet meaningful ways. This gives rise to the recently emerging research area of discovering alternative clusterings. In this preliminary work, we propose a novel framework to generate multiple clustering views....... The framework relies on a constrained data projection approach by which we ensure that a novel alternative clustering being found is not only qualitatively strong but also distinctively different from a reference clustering solution. We demonstrate the potential of the proposed framework using both synthetic...

  17. Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

    Science.gov (United States)

    Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

    2013-03-01

    Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

  18. Single pass kernel k-means clustering method

    Indian Academy of Sciences (India)

    paper proposes a simple and faster version of the kernel k-means clustering ... It has been considered as an important tool ... On the other hand, kernel-based clustering methods, like kernel k-means clus- ..... able at the UCI machine learning repository (Murphy 1994). ... All the data sets have only numeric valued features.

  19. MILC Code Performance on High End CPU and GPU Supercomputer Clusters

    Science.gov (United States)

    DeTar, Carleton; Gottlieb, Steven; Li, Ruizi; Toussaint, Doug

    2018-03-01

    With recent developments in parallel supercomputing architecture, many core, multi-core, and GPU processors are now commonplace, resulting in more levels of parallelism, memory hierarchy, and programming complexity. It has been necessary to adapt the MILC code to these new processors starting with NVIDIA GPUs, and more recently, the Intel Xeon Phi processors. We report on our efforts to port and optimize our code for the Intel Knights Landing architecture. We consider performance of the MILC code with MPI and OpenMP, and optimizations with QOPQDP and QPhiX. For the latter approach, we concentrate on the staggered conjugate gradient and gauge force. We also consider performance on recent NVIDIA GPUs using the QUDA library.

  20. MILC Code Performance on High End CPU and GPU Supercomputer Clusters

    Directory of Open Access Journals (Sweden)

    DeTar Carleton

    2018-01-01

    Full Text Available With recent developments in parallel supercomputing architecture, many core, multi-core, and GPU processors are now commonplace, resulting in more levels of parallelism, memory hierarchy, and programming complexity. It has been necessary to adapt the MILC code to these new processors starting with NVIDIA GPUs, and more recently, the Intel Xeon Phi processors. We report on our efforts to port and optimize our code for the Intel Knights Landing architecture. We consider performance of the MILC code with MPI and OpenMP, and optimizations with QOPQDP and QPhiX. For the latter approach, we concentrate on the staggered conjugate gradient and gauge force. We also consider performance on recent NVIDIA GPUs using the QUDA library.

  1. Optically-Selected Cluster Catalogs As a Precision Cosmology Tool

    Energy Technology Data Exchange (ETDEWEB)

    Rozo, Eduardo; /Ohio State U. /Chicago U. /KICP, Chicago; Wechsler, Risa H.; /KICP, Chicago /KIPAC, Menlo Park; Koester, Benjamin P.; /Michigan U. /Chicago U., Astron.; Evrard, August E.; McKay, Timothy A.; /Michigan U.

    2007-03-26

    We introduce a framework for describing the halo selection function of optical cluster finders. We treat the problem as being separable into a term that describes the intrinsic galaxy content of a halo (the Halo Occupation Distribution, or HOD) and a term that captures the effects of projection and selection by the particular cluster finding algorithm. Using mock galaxy catalogs tuned to reproduce the luminosity dependent correlation function and the empirical color-density relation measured in the SDSS, we characterize the maxBCG algorithm applied by Koester et al. to the SDSS galaxy catalog. We define and calibrate measures of completeness and purity for this algorithm, and demonstrate successful recovery of the underlying cosmology and HOD when applied to the mock catalogs. We identify principal components--combinations of cosmology and HOD parameters--that are recovered by survey counts as a function of richness, and demonstrate that percent-level accuracies are possible in the first two components, if the selection function can be understood to {approx} 15% accuracy.

  2. Cluster analysis of received constellations for optical performance monitoring

    NARCIS (Netherlands)

    van Weerdenburg, J.J.A.; van Uden, R.; Sillekens, E.; de Waardt, H.; Koonen, A.M.J.; Okonkwo, C.

    2016-01-01

    Performance monitoring based on centroid clustering to investigate constellation generation offsets. The tool allows flexibility in constellation generation tolerances by forwarding centroids to the demapper. The relation of fibre nonlinearities and singular value decomposition of intra-cluster

  3. Parallel computation for biological sequence comparison: comparing a portable model to the native model for the Intel Hypercube.

    Science.gov (United States)

    Nadkarni, P M; Miller, P L

    1991-01-01

    A parallel program for inter-database sequence comparison was developed on the Intel Hypercube using two models of parallel programming. One version was built using machine-specific Hypercube parallel programming commands. The other version was built using Linda, a machine-independent parallel programming language. The two versions of the program provide a case study comparing these two approaches to parallelization in an important biological application area. Benchmark tests with both programs gave comparable results with a small number of processors. As the number of processors was increased, the Linda version was somewhat less efficient. The Linda version was also run without change on Network Linda, a virtual parallel machine running on a network of desktop workstations.

  4. Speckle imaging of globular clusters

    International Nuclear Information System (INIS)

    Sams, B.J. III

    1990-01-01

    Speckle imaging is a powerful tool for high resolution astronomy. Its application to the core regions of globular clusters produces high resolution stellar maps of the bright stars, but is unable to image the faint stars which are most reliable dynamical indicators. The limits on resolving these faint, extended objects are physical, not algorithmic, and cannot be overcome using speckle. High resolution maps may be useful for resolving multicomponent stellar systems in the cluster centers. 30 refs

  5. Perfmon2: a leap forward in performance monitoring

    International Nuclear Information System (INIS)

    Jarp, S; Jurga, R; Nowak, A

    2008-01-01

    This paper describes the software component, perfmon2, that is about to be added to the Linux kernel as the standard interface to the Performance Monitoring Unit (PMU) on common processors, including x86 (AMD and Intel), Sun SPARC, MIPS, IBM Power and Intel Itanium. It also describes a set of tools for doing performance monitoring in practice and details how the CERN openlab team has participated in the testing and development of these tools

  6. Perfmon2: a leap forward in performance monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jarp, S; Jurga, R; Nowak, A [CERN, Geneva (Switzerland)], E-mail: Sverre.Jarp@cern.ch

    2008-07-15

    This paper describes the software component, perfmon2, that is about to be added to the Linux kernel as the standard interface to the Performance Monitoring Unit (PMU) on common processors, including x86 (AMD and Intel), Sun SPARC, MIPS, IBM Power and Intel Itanium. It also describes a set of tools for doing performance monitoring in practice and details how the CERN openlab team has participated in the testing and development of these tools.

  7. Perfmon2 a leap forward in performance monitoring

    CERN Document Server

    Jarp, S; Nowak, A

    2008-01-01

    This paper describes the software component, perfmon2, that is about to be added to the Linux kernel as the standard interface to the Performance Monitoring Unit (PMU) on common processors, including x86 (AMD and Intel), Sun SPARC, MIPS, IBM Power and Intel Itanium. It also describes a set of tools for doing performance monitoring in practice and details how the CERN openlab team has participated in the testing and development of these tools.

  8. Perfmon2: a leap forward in performance monitoring

    Science.gov (United States)

    Jarp, S.; Jurga, R.; Nowak, A.

    2008-07-01

    This paper describes the software component, perfmon2, that is about to be added to the Linux kernel as the standard interface to the Performance Monitoring Unit (PMU) on common processors, including x86 (AMD and Intel), Sun SPARC, MIPS, IBM Power and Intel Itanium. It also describes a set of tools for doing performance monitoring in practice and details how the CERN openlab team has participated in the testing and development of these tools.

  9. Cluster Ion Implantation in Graphite and Diamond

    DEFF Research Database (Denmark)

    Popok, Vladimir

    2014-01-01

    Cluster ion beam technique is a versatile tool which can be used for controllable formation of nanosize objects as well as modification and processing of surfaces and shallow layers on an atomic scale. The current paper present an overview and analysis of data obtained on a few sets of graphite...... and diamond samples implanted by keV-energy size-selected cobalt and argon clusters. One of the emphases is put on pinning of metal clusters on graphite with a possibility of following selective etching of graphene layers. The other topic of concern is related to the development of scaling law for cluster...... implantation. Implantation of cobalt and argon clusters into two different allotropic forms of carbon, namely, graphite and diamond is analysed and compared in order to approach universal theory of cluster stopping in matter....

  10. Clustering by reordering of similarity and Laplacian matrices: Application to galaxy clusters

    Science.gov (United States)

    Mahmoud, E.; Shoukry, A.; Takey, A.

    2018-04-01

    Similarity metrics, kernels and similarity-based algorithms have gained much attention due to their increasing applications in information retrieval, data mining, pattern recognition and machine learning. Similarity Graphs are often adopted as the underlying representation of similarity matrices and are at the origin of known clustering algorithms such as spectral clustering. Similarity matrices offer the advantage of working in object-object (two-dimensional) space where visualization of clusters similarities is available instead of object-features (multi-dimensional) space. In this paper, sparse ɛ-similarity graphs are constructed and decomposed into strong components using appropriate methods such as Dulmage-Mendelsohn permutation (DMperm) and/or Reverse Cuthill-McKee (RCM) algorithms. The obtained strong components correspond to groups (clusters) in the input (feature) space. Parameter ɛi is estimated locally, at each data point i from a corresponding narrow range of the number of nearest neighbors. Although more advanced clustering techniques are available, our method has the advantages of simplicity, better complexity and direct visualization of the clusters similarities in a two-dimensional space. Also, no prior information about the number of clusters is needed. We conducted our experiments on two and three dimensional, low and high-sized synthetic datasets as well as on an astronomical real-dataset. The results are verified graphically and analyzed using gap statistics over a range of neighbors to verify the robustness of the algorithm and the stability of the results. Combining the proposed algorithm with gap statistics provides a promising tool for solving clustering problems. An astronomical application is conducted for confirming the existence of 45 galaxy clusters around the X-ray positions of galaxy clusters in the redshift range [0.1..0.8]. We re-estimate the photometric redshifts of the identified galaxy clusters and obtain acceptable values

  11. bcl::Cluster : A method for clustering biological molecules coupled with visualization in the Pymol Molecular Graphics System.

    Science.gov (United States)

    Alexander, Nathan; Woetzel, Nils; Meiler, Jens

    2011-02-01

    Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.

  12. Clustering of near clusters versus cluster compactness

    International Nuclear Information System (INIS)

    Yu Gao; Yipeng Jing

    1989-01-01

    The clustering properties of near Zwicky clusters are studied by using the two-point angular correlation function. The angular correlation functions for compact and medium compact clusters, for open clusters, and for all near Zwicky clusters are estimated. The results show much stronger clustering for compact and medium compact clusters than for open clusters, and that open clusters have nearly the same clustering strength as galaxies. A detailed study of the compactness-dependence of correlation function strength is worth investigating. (author)

  13. Effects on energetic impact of atomic clusters with surfaces

    International Nuclear Information System (INIS)

    Popok, V.N.; Vuchkovich, S.; Abdela, A.; Campbell, E.E.B.

    2007-01-01

    A brief state-of-the-art review in the field of cluster ion interaction with surface is presented. Cluster beams are efficient tools for manipulating agglomerates of atoms providing control over the synthesis as well as modification of surfaces on the nm-scale. The application of cluster beams for technological purposes requires knowledge of the physics of cluster-surface impact. This has some significant differences compared to monomer ion - surface interactions. The main effects of cluster-surface collisions are discussed. Recent results obtained in experiments on silicon surface nanostructuring using keV-energy implantation of inert gas cluster ions are presented and compared with molecular dynamics simulations. (authors)

  14. Supercomputing for molecular dynamics simulations handling multi-trillion particles in nanofluidics

    CERN Document Server

    Heinecke, Alexander; Horsch, Martin; Bungartz, Hans-Joachim

    2015-01-01

    This work presents modern implementations of relevant molecular dynamics algorithms using ls1 mardyn, a simulation program for engineering applications. The text focuses strictly on HPC-related aspects, covering implementation on HPC architectures, taking Intel Xeon and Intel Xeon Phi clusters as representatives of current platforms. The work describes distributed and shared-memory parallelization on these platforms, including load balancing, with a particular focus on the efficient implementation of the compute kernels. The text also discusses the software-architecture of the resulting code.

  15. Cluster-cluster clustering

    International Nuclear Information System (INIS)

    Barnes, J.; Dekel, A.; Efstathiou, G.; Frenk, C.S.; Yale Univ., New Haven, CT; California Univ., Santa Barbara; Cambridge Univ., England; Sussex Univ., Brighton, England)

    1985-01-01

    The cluster correlation function xi sub c(r) is compared with the particle correlation function, xi(r) in cosmological N-body simulations with a wide range of initial conditions. The experiments include scale-free initial conditions, pancake models with a coherence length in the initial density field, and hybrid models. Three N-body techniques and two cluster-finding algorithms are used. In scale-free models with white noise initial conditions, xi sub c and xi are essentially identical. In scale-free models with more power on large scales, it is found that the amplitude of xi sub c increases with cluster richness; in this case the clusters give a biased estimate of the particle correlations. In the pancake and hybrid models (with n = 0 or 1), xi sub c is steeper than xi, but the cluster correlation length exceeds that of the points by less than a factor of 2, independent of cluster richness. Thus the high amplitude of xi sub c found in studies of rich clusters of galaxies is inconsistent with white noise and pancake models and may indicate a primordial fluctuation spectrum with substantial power on large scales. 30 references

  16. Software and DVFS Tuning for Performance and Energy-Efficiency on Intel KNL Processors

    Directory of Open Access Journals (Sweden)

    Enrico Calore

    2018-06-01

    Full Text Available Energy consumption of processors and memories is quickly becoming a limiting factor in the deployment of large computing systems. For this reason, it is important to understand the energy performance of these processors and to study strategies allowing their use in the most efficient way. In this work, we focus on the computing and energy performance of the Knights Landing Xeon Phi, the latest Intel many-core architecture processor for HPC applications. We consider the 64-core Xeon Phi 7230 and profile its performance and energy efficiency using both its on-chip MCDRAM and the off-chip DDR4 memory as the main storage for application data. As a benchmark application, we use a lattice Boltzmann code heavily optimized for this architecture and implemented using several different arrangements of the application data in memory (data-layouts, in short. We also assess the dependence of energy consumption on data-layouts, memory configurations (DDR4 or MCDRAM and the number of threads per core. We finally consider possible trade-offs between computing performance and energy efficiency, tuning the clock frequency of the processor using the Dynamic Voltage and Frequency Scaling (DVFS technique.

  17. Web-based Quality Control Tool used to validate CERES products on a cluster of Linux servers

    Science.gov (United States)

    Chu, C.; Sun-Mack, S.; Heckert, E.; Chen, Y.; Mlynczak, P.; Mitrescu, C.; Doelling, D.

    2014-12-01

    There have been a few popular desktop tools used in the Earth Science community to validate science data. Because of the limitation on the capacity of desktop hardware such as disk space and CPUs, those softwares are not able to display large amount of data from files.This poster will talk about an in-house developed web-based software built on a cluster of Linux servers. That allows users to take advantage of a few Linux servers working in parallel to generate hundreds images in a short period of time. The poster will demonstrate:(1) The hardware and software architecture is used to provide high throughput of images. (2) The software structure that can incorporate new products and new requirement quickly. (3) The user interface about how users can manipulate the data and users can control how the images are displayed.

  18. Quasi-free experiments as a tool for the study of 6Li cluster structure

    International Nuclear Information System (INIS)

    Lattuada, M.; Riggi, F.; Spitaleri, C.; Vinciguerra, D.

    1984-01-01

    The value of the α-d clustering probability in 6 Li deduced from quasi-free experiments may be influenced by the choice of the inter-cluster wave function. Several functional forms usually taken to describe the relative motion of the two clusters have been examined. The effect of the choice of the intercluster wave function on the information deduced by analysing quasi-free data in the plane-wave impulse approximation was investigated

  19. Cluster analysis of activity-time series in motor learning

    DEFF Research Database (Denmark)

    Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

    2002-01-01

    Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

  20. Clustervision: Visual Supervision of Unsupervised Clustering.

    Science.gov (United States)

    Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam

    2018-01-01

    Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

  1. Control and stimulation tools (cat) for the PC modelers

    International Nuclear Information System (INIS)

    Chan, K.S.; Lea, K.C.

    1990-01-01

    For the last couple of years, the personal computer technology has received a steady stream of improvement in CPU processing power, fast floating coprocessor, super graphics to a very large and fast hard drive. Since Intel began shipping its 80386 version of CPU, it became practical to develop or execute a substantial amount of power plant software on a personal computer. With the introduction of the RISC type personal workstation, complete simulators based on these new generation of computers will soon become a reality. As of today, although almost anybody can afford a personal computer, simulation supporting software is still rare or non-existent at all. The CAST has been designed to support those users who want to develop or debug large power plant simulation programs on a personal computer or workstation. Another separate paper will also be presented to demonstrate the real world development and debugging tools offered by CAST

  2. Improved Ant Colony Clustering Algorithm and Its Performance Study

    Science.gov (United States)

    Gao, Wei

    2016-01-01

    Clustering analysis is used in many disciplines and applications; it is an important tool that descriptively identifies homogeneous groups of objects based on attribute values. The ant colony clustering algorithm is a swarm-intelligent method used for clustering problems that is inspired by the behavior of ant colonies that cluster their corpses and sort their larvae. A new abstraction ant colony clustering algorithm using a data combination mechanism is proposed to improve the computational efficiency and accuracy of the ant colony clustering algorithm. The abstraction ant colony clustering algorithm is used to cluster benchmark problems, and its performance is compared with the ant colony clustering algorithm and other methods used in existing literature. Based on similar computational difficulties and complexities, the results show that the abstraction ant colony clustering algorithm produces results that are not only more accurate but also more efficiently determined than the ant colony clustering algorithm and the other methods. Thus, the abstraction ant colony clustering algorithm can be used for efficient multivariate data clustering. PMID:26839533

  3. ClusterSignificance: A bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data

    DEFF Research Database (Denmark)

    Serviss, Jason T.; Gådin, Jesper R.; Eriksson, Per

    2017-01-01

    , e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical...... significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies....

  4. Automated Parallel Computing Tools for Multicore Machines and Clusters, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to improve productivity of high performance computing for applications on multicore computers and clusters. These machines built from one or more chips...

  5. Evaluation of the Intel Xeon Phi Co-processor to accelerate the sensitivity map calculation for PET imaging

    Science.gov (United States)

    Dey, T.; Rodrigue, P.

    2015-07-01

    We aim to evaluate the Intel Xeon Phi coprocessor for acceleration of 3D Positron Emission Tomography (PET) image reconstruction. We focus on the sensitivity map calculation as one computational intensive part of PET image reconstruction, since it is a promising candidate for acceleration with the Many Integrated Core (MIC) architecture of the Xeon Phi. The computation of the voxels in the field of view (FoV) can be done in parallel and the 103 to 104 samples needed to calculate the detection probability of each voxel can take advantage of vectorization. We use the ray tracing kernels of the Embree project to calculate the hit points of the sample rays with the detector and in a second step the sum of the radiological path taking into account attenuation is determined. The core components are implemented using the Intel single instruction multiple data compiler (ISPC) to enable a portable implementation showing efficient vectorization either on the Xeon Phi and the Host platform. On the Xeon Phi, the calculation of the radiological path is also implemented in hardware specific intrinsic instructions (so-called `intrinsics') to allow manually-optimized vectorization. For parallelization either OpenMP and ISPC tasking (based on pthreads) are evaluated.Our implementation achieved a scalability factor of 0.90 on the Xeon Phi coprocessor (model 5110P) with 60 cores at 1 GHz. Only minor differences were found between parallelization with OpenMP and the ISPC tasking feature. The implementation using intrinsics was found to be about 12% faster than the portable ISPC version. With this version, a speedup of 1.43 was achieved on the Xeon Phi coprocessor compared to the host system (HP SL250s Gen8) equipped with two Xeon (E5-2670) CPUs, with 8 cores at 2.6 to 3.3 GHz each. Using a second Xeon Phi card the speedup could be further increased to 2.77. No significant differences were found between the results of the different Xeon Phi and the Host implementations. The examination

  6. Evaluation of the Intel Xeon Phi Co-processor to accelerate the sensitivity map calculation for PET imaging

    International Nuclear Information System (INIS)

    Dey, T.; Rodrigue, P.

    2015-01-01

    We aim to evaluate the Intel Xeon Phi coprocessor for acceleration of 3D Positron Emission Tomography (PET) image reconstruction. We focus on the sensitivity map calculation as one computational intensive part of PET image reconstruction, since it is a promising candidate for acceleration with the Many Integrated Core (MIC) architecture of the Xeon Phi. The computation of the voxels in the field of view (FoV) can be done in parallel and the 10 3 to 10 4 samples needed to calculate the detection probability of each voxel can take advantage of vectorization. We use the ray tracing kernels of the Embree project to calculate the hit points of the sample rays with the detector and in a second step the sum of the radiological path taking into account attenuation is determined. The core components are implemented using the Intel single instruction multiple data compiler (ISPC) to enable a portable implementation showing efficient vectorization either on the Xeon Phi and the Host platform. On the Xeon Phi, the calculation of the radiological path is also implemented in hardware specific intrinsic instructions (so-called 'intrinsics') to allow manually-optimized vectorization. For parallelization either OpenMP and ISPC tasking (based on pthreads) are evaluated.Our implementation achieved a scalability factor of 0.90 on the Xeon Phi coprocessor (model 5110P) with 60 cores at 1 GHz. Only minor differences were found between parallelization with OpenMP and the ISPC tasking feature. The implementation using intrinsics was found to be about 12% faster than the portable ISPC version. With this version, a speedup of 1.43 was achieved on the Xeon Phi coprocessor compared to the host system (HP SL250s Gen8) equipped with two Xeon (E5-2670) CPUs, with 8 cores at 2.6 to 3.3 GHz each. Using a second Xeon Phi card the speedup could be further increased to 2.77. No significant differences were found between the results of the different Xeon Phi and the Host implementations. The

  7. Open-Source Sequence Clustering Methods Improve the State Of the Art.

    Science.gov (United States)

    Kopylova, Evguenia; Navas-Molina, Jose A; Mercier, Céline; Xu, Zhenjiang Zech; Mahé, Frédéric; He, Yan; Zhou, Hong-Wei; Rognes, Torbjørn; Caporaso, J Gregory; Knight, Rob

    2016-01-01

    Sequence clustering is a common early step in amplicon-based microbial community analysis, when raw sequencing reads are clustered into operational taxonomic units (OTUs) to reduce the run time of subsequent analysis steps. Here, we evaluated the performance of recently released state-of-the-art open-source clustering software products, namely, OTUCLUST, Swarm, SUMACLUST, and SortMeRNA, against current principal options (UCLUST and USEARCH) in QIIME, hierarchical clustering methods in mothur, and USEARCH's most recent clustering algorithm, UPARSE. All the latest open-source tools showed promising results, reporting up to 60% fewer spurious OTUs than UCLUST, indicating that the underlying clustering algorithm can vastly reduce the number of these derived OTUs. Furthermore, we observed that stringent quality filtering, such as is done in UPARSE, can cause a significant underestimation of species abundance and diversity, leading to incorrect biological results. Swarm, SUMACLUST, and SortMeRNA have been included in the QIIME 1.9.0 release. IMPORTANCE Massive collections of next-generation sequencing data call for fast, accurate, and easily accessible bioinformatics algorithms to perform sequence clustering. A comprehensive benchmark is presented, including open-source tools and the popular USEARCH suite. Simulated, mock, and environmental communities were used to analyze sensitivity, selectivity, species diversity (alpha and beta), and taxonomic composition. The results demonstrate that recent clustering algorithms can significantly improve accuracy and preserve estimated diversity without the application of aggressive filtering. Moreover, these tools are all open source, apply multiple levels of multithreading, and scale to the demands of modern next-generation sequencing data, which is essential for the analysis of massive multidisciplinary studies such as the Earth Microbiome Project (EMP) (J. A. Gilbert, J. K. Jansson, and R. Knight, BMC Biol 12:69, 2014, http

  8. Development of a Genetic Algorithm to Automate Clustering of a Dependency Structure Matrix

    Science.gov (United States)

    Rogers, James L.; Korte, John J.; Bilardo, Vincent J.

    2006-01-01

    Much technology assessment and organization design data exists in Microsoft Excel spreadsheets. Tools are needed to put this data into a form that can be used by design managers to make design decisions. One need is to cluster data that is highly coupled. Tools such as the Dependency Structure Matrix (DSM) and a Genetic Algorithm (GA) can be of great benefit. However, no tool currently combines the DSM and a GA to solve the clustering problem. This paper describes a new software tool that interfaces a GA written as an Excel macro with a DSM in spreadsheet format. The results of several test cases are included to demonstrate how well this new tool works.

  9. Analysis of the Intel 386 and i486 microprocessors for the Space Station Freedom Data Management System

    Science.gov (United States)

    Liu, Yuan-Kwei

    1991-01-01

    The feasibility is analyzed of upgrading the Intel 386 microprocessor, which has been proposed as the baseline processor for the Space Station Freedom (SSF) Data Management System (DMS), to the more advanced i486 microprocessors. The items compared between the two processors include the instruction set architecture, power consumption, the MIL-STD-883C Class S (Space) qualification schedule, and performance. The advantages of the i486 over the 386 are (1) lower power consumption; and (2) higher floating point performance. The i486 on-chip cache does not have parity check or error detection and correction circuitry. The i486 with on-chip cache disabled, however, has lower integer performance than the 386 without cache, which is the current DMS design choice. Adding cache to the 386/386 DX memory hierachy appears to be the most beneficial change to the current DMS design at this time.

  10. Evaluating the networking characteristics of the Cray XC-40 Intel Knights Landing-based Cori supercomputer at NERSC

    Energy Technology Data Exchange (ETDEWEB)

    Doerfler, Douglas [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Austin, Brian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Cook, Brandon [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Deslippe, Jack [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Kandalla, Krishna [Cray Inc, Bloomington, MN (United States); Mendygral, Peter [Cray Inc, Bloomington, MN (United States)

    2017-09-12

    There are many potential issues associated with deploying the Intel Xeon Phi™ (code named Knights Landing [KNL]) manycore processor in a large-scale supercomputer. One in particular is the ability to fully utilize the high-speed communications network, given that the serial performance of a Xeon Phi TM core is a fraction of a Xeon®core. In this paper, we take a look at the trade-offs associated with allocating enough cores to fully utilize the Aries high-speed network versus cores dedicated to computation, e.g., the trade-off between MPI and OpenMP. In addition, we evaluate new features of Cray MPI in support of KNL, such as internode optimizations. We also evaluate one-sided programming models such as Unified Parallel C. We quantify the impact of the above trade-offs and features using a suite of National Energy Research Scientific Computing Center applications.

  11. The mass-temperature relation for clusters of galaxies

    DEFF Research Database (Denmark)

    Hjorth, J.; Oukbir, J.; van Kampen, E.

    1998-01-01

    A tight mass-temperature relation, M(r)/r proportional to T-x, is expected in most cosmological models if clusters of galaxies are homologous and the intracluster gas is in global equilibrium with the dark matter. We here calibrate this relation using eight clusters with well-defined global tempe...... redshift, the relation represents a new tool for determination of cosmological parameters, notably the cosmological constant Lambda....

  12. Integrated spectral study of small angular diameter galactic open clusters

    Science.gov (United States)

    Clariá, J. J.; Ahumada, A. V.; Bica, E.; Pavani, D. B.; Parisi, M. C.

    2017-10-01

    This paper presents flux-calibrated integrated spectra obtained at Complejo Astronómico El Leoncito (CASLEO, Argentina) for a sample of 9 Galactic open clusters of small angular diameter. The spectra cover the optical range (3800-6800 Å), with a resolution of ˜14 Å. With one exception (Ruprecht 158), the selected clusters are projected into the fourth Galactic quadrant (282o evaluate their membership status. The current cluster sample complements that of 46 open clusters previously studied by our group in an effort to gather a spectral library with several clusters per age bin. The cluster spectral library that we have been building is an important tool to tie studies of resolved and unresolved stellar content.

  13. A Historical Approach to Clustering in Emerging Economies

    DEFF Research Database (Denmark)

    Giacomin, Valeria

    of external factors. Indeed, researchers have explained clusters as self-contained entities and reduced their success to local exceptionality. In contrast, emerging literature has shown that clusters are integrated in broader structures beyond their location and are rather building blocks of today’s global...... economy. The working paper goes on to present two historical cases from the global south to explain how clusters work as major tools for international business. Particularly in the developing world, multinationals have used clusters as platforms for channeling foreign investment, knowledge, and imported...... inputs. The study concludes by stressing the importance of using historical evidence and data to look at clusters as agglomerations of actors and companies operating not just at the local level but across broader global networks. In doing so the historical perspective provides explanations lacking...

  14. Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster

    Directory of Open Access Journals (Sweden)

    Alberto Cocaña-Fernández

    2016-03-01

    Full Text Available As data and supercomputing centres increase their performance to improve service quality and target more ambitious challenges every day, their carbon footprint also continues to grow, and has already reached the magnitude of the aviation industry. Also, high power consumptions are building up to a remarkable bottleneck for the expansion of these infrastructures in economic terms due to the unavailability of sufficient energy sources. A substantial part of the problem is caused by current energy consumptions of High Performance Computing (HPC clusters. To alleviate this situation, we present in this work EECluster, a tool that integrates with multiple open-source Resource Management Systems to significantly reduce the carbon footprint of clusters by improving their energy efficiency. EECluster implements a dynamic power management mechanism based on Computational Intelligence techniques by learning a set of rules through multi-criteria evolutionary algorithms. This approach enables cluster operators to find the optimal balance between a reduction in the cluster energy consumptions, service quality, and number of reconfigurations. Experimental studies using both synthetic and actual workloads from a real world cluster support the adoption of this tool to reduce the carbon footprint of HPC clusters.

  15. Spectromicroscopy of self-assembled protein clusters

    Energy Technology Data Exchange (ETDEWEB)

    Schonschek, O.; Hormes, J.; Herzog, V. [Univ. of Bonn (Germany)

    1997-04-01

    The aim of this project is to use synchrotron radiation as a tool to study biomedical questions concerned with the thyroid glands. The biological background is outlined in a recent paper. In short, Thyroglobulin (TG), the precursor protein of the hormone thyroxine, forms large (20 - 500 microns in diameter) clusters in the extracellular lumen of thyrocytes. The process of the cluster formation is still not well understood but is thought to be a main storage mechanism of TG and therefore thyroxine inside the thyroid glands. For human thyroids, the interconnections of the proteins inside the clusters are mainly disulfide bondings. Normally, sulfur bridges are catalyzed by an enzyme called Protein Disulfide Bridge Isomerase (PDI). While this enzyme is supposed to be not present in any extracellular space, the cluster formation of TG takes place in the lumen between the thyrocytes. A possible explanation is the autocatalysis of TG.

  16. IntroductionThe Cluster mission

    Directory of Open Access Journals (Sweden)

    M. Fehringer

    Full Text Available The Cluster mission, ESA’s first cornerstone project, together with the SOHO mission, dating back to the first proposals in 1982, was finally launched in the summer of 2000. On 16 July and 9 August, respectively, two Russian Soyuz rockets blasted off from the Russian cosmodrome in Baikonour to deliver two Cluster spacecraft, each into their proper orbit. By the end of August 2000, the four Cluster satellites had reached their final tetrahedral constellation. The commissioning of 44 instruments, both individually and as an ensemble of complementary tools, was completed five months later to ensure the optimal use of their combined observational potential. On 1 February 2001, the mission was declared operational. The main goal of the Cluster mission is to study the small-scale plasma structures in three dimensions in key plasma regions, such as the solar wind, bow shock, magnetopause, polar cusps, magnetotail and the auroral zones. With its unique capabilities of three-dimensional spatial resolution, Cluster plays a major role in the International Solar Terrestrial Program (ISTP, where Cluster and the Solar and Heliospheric Observatory (SOHO are the European contributions. Cluster’s payload consists of state-of-the-art plasma instrumentation to measure electric and magnetic fields from the quasi-static up to high frequencies, and electron and ion distribution functions from energies of nearly 0 eV to a few MeV. The science operations are coordinated by the Joint Science Operations Centre (JSOC, at the Rutherford Appleton Laboratory (UK, and implemented by the European Space Operations Centre (ESOC, in Darmstadt, Germany. A network of eight national data centres has been set up for raw data processing, for the production of physical parameters, and their distribution to end users all over the world. The latest information on the Cluster mission can be found at http://sci.esa.int/cluster/.

  17. IntroductionThe Cluster mission

    Directory of Open Access Journals (Sweden)

    C. P. Escoubet

    2001-09-01

    Full Text Available The Cluster mission, ESA’s first cornerstone project, together with the SOHO mission, dating back to the first proposals in 1982, was finally launched in the summer of 2000. On 16 July and 9 August, respectively, two Russian Soyuz rockets blasted off from the Russian cosmodrome in Baikonour to deliver two Cluster spacecraft, each into their proper orbit. By the end of August 2000, the four Cluster satellites had reached their final tetrahedral constellation. The commissioning of 44 instruments, both individually and as an ensemble of complementary tools, was completed five months later to ensure the optimal use of their combined observational potential. On 1 February 2001, the mission was declared operational. The main goal of the Cluster mission is to study the small-scale plasma structures in three dimensions in key plasma regions, such as the solar wind, bow shock, magnetopause, polar cusps, magnetotail and the auroral zones. With its unique capabilities of three-dimensional spatial resolution, Cluster plays a major role in the International Solar Terrestrial Program (ISTP, where Cluster and the Solar and Heliospheric Observatory (SOHO are the European contributions. Cluster’s payload consists of state-of-the-art plasma instrumentation to measure electric and magnetic fields from the quasi-static up to high frequencies, and electron and ion distribution functions from energies of nearly 0 eV to a few MeV. The science operations are coordinated by the Joint Science Operations Centre (JSOC, at the Rutherford Appleton Laboratory (UK, and implemented by the European Space Operations Centre (ESOC, in Darmstadt, Germany. A network of eight national data centres has been set up for raw data processing, for the production of physical parameters, and their distribution to end users all over the world. The latest information on the Cluster mission can be found at http://sci.esa.int/cluster/.

  18. RSAT matrix-clustering: dynamic exploration and redundancy reduction of transcription factor binding motif collections.

    Science.gov (United States)

    Castro-Mondragon, Jaime Abraham; Jaeger, Sébastien; Thieffry, Denis; Thomas-Chollier, Morgane; van Helden, Jacques

    2017-07-27

    Transcription factor (TF) databases contain multitudes of binding motifs (TFBMs) from various sources, from which non-redundant collections are derived by manual curation. The advent of high-throughput methods stimulated the production of novel collections with increasing numbers of motifs. Meta-databases, built by merging these collections, contain redundant versions, because available tools are not suited to automatically identify and explore biologically relevant clusters among thousands of motifs. Motif discovery from genome-scale data sets (e.g. ChIP-seq) also produces redundant motifs, hampering the interpretation of results. We present matrix-clustering, a versatile tool that clusters similar TFBMs into multiple trees, and automatically creates non-redundant TFBM collections. A feature unique to matrix-clustering is its dynamic visualisation of aligned TFBMs, and its capability to simultaneously treat multiple collections from various sources. We demonstrate that matrix-clustering considerably simplifies the interpretation of combined results from multiple motif discovery tools, and highlights biologically relevant variations of similar motifs. We also ran a large-scale application to cluster ∼11 000 motifs from 24 entire databases, showing that matrix-clustering correctly groups motifs belonging to the same TF families, and drastically reduced motif redundancy. matrix-clustering is integrated within the RSAT suite (http://rsat.eu/), accessible through a user-friendly web interface or command-line for its integration in pipelines. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. tclust: An R Package for a Trimming Approach to Cluster Analysis

    Directory of Open Access Journals (Sweden)

    2012-04-01

    Full Text Available Outlying data can heavily influence standard clustering methods. At the same time, clustering principles can be useful when robustifying statistical procedures. These two reasons motivate the development of feasible robust model-based clustering approaches. With this in mind, an R package for performing non-hierarchical robust clustering, called tclust, is presented here. Instead of trying to “fit” noisy data, a proportion α of the most outlying observations is trimmed. The tclust package efficiently handles different cluster scatter constraints. Graphical exploratory tools are also provided to help the user make sensible choices for the trimming proportion as well as the number of clusters to search for.

  20. Recommending the heterogeneous cluster type multi-processor system computing

    International Nuclear Information System (INIS)

    Iijima, Nobukazu

    2010-01-01

    Real-time reactor simulator had been developed by reusing the equipment of the Musashi reactor and its performance improvement became indispensable for research tools to increase sampling rate with introduction of arithmetic units using multi-Digital Signal Processor(DSP) system (cluster). In order to realize the heterogeneous cluster type multi-processor system computing, combination of two kinds of Control Processor (CP) s, Cluster Control Processor (CCP) and System Control Processor (SCP), were proposed with Large System Control Processor (LSCP) for hierarchical cluster if needed. Faster computing performance of this system was well evaluated by simulation results for simultaneous execution of plural jobs and also pipeline processing between clusters, which showed the system led to effective use of existing system and enhancement of the cost performance. (T. Tanaka)

  1. Star clusters and K2

    Science.gov (United States)

    Dotson, Jessie; Barentsen, Geert; Cody, Ann Marie

    2018-01-01

    The K2 survey has expanded the Kepler legacy by using the repurposed spacecraft to observe over 20 star clusters. The sample includes open and globular clusters at all ages, including very young (1-10 Myr, e.g. Taurus, Upper Sco, NGC 6530), moderately young (0.1-1 Gyr, e.g. M35, M44, Pleiades, Hyades), middle-aged (e.g. M67, Ruprecht 147, NGC 2158), and old globular clusters (e.g. M9, M19, Terzan 5). K2 observations of stellar clusters are exploring the rotation period-mass relationship to significantly lower masses than was previously possible, shedding light on the angular momentum budget and its dependence on mass and circumstellar disk properties, and illuminating the role of multiplicity in stellar angular momentum. Exoplanets discovered by K2 in stellar clusters provides planetary systems ripe for modeling given the extensive information available about their ages and environment. I will review the star clusters sampled by K2 across 16 fields so far, highlighting several characteristics, caveats, and unexplored uses of the public data set along the way. With fuel expected to run out in 2018, I will discuss the closing Campaigns, highlight the final target selection opportunities, and explain the data archive and TESS-compatible software tools the K2 mission intends to leave behind for posterity.

  2. Clustering of experimental data and its application to nuclear data evaluation

    International Nuclear Information System (INIS)

    Abboud, A.; Rashed, R.; Ibrahim, M.

    1997-01-01

    A semi-automatic pre-processing technique has been proposed by Iwasaki to classify the experimental data for a reaction into one or a small number of large data groups, called main cluster(s), and to eliminate some data which deviate from the main body of the data. The classifying method is based on a technique like pattern clustering in the information processing domain. Test of the data clustering formed reasonable main clusters for three activation cross-sections. This technique is a helpful tool in the neutron cross-section evaluation. (author). 4 refs, 1 fig., 3 tabs

  3. Android Malware Classification Using K-Means Clustering Algorithm

    Science.gov (United States)

    Hamid, Isredza Rahmi A.; Syafiqah Khalid, Nur; Azma Abdullah, Nurul; Rahman, Nurul Hidayah Ab; Chai Wen, Chuah

    2017-08-01

    Malware was designed to gain access or damage a computer system without user notice. Besides, attacker exploits malware to commit crime or fraud. This paper proposed Android malware classification approach based on K-Means clustering algorithm. We evaluate the proposed model in terms of accuracy using machine learning algorithms. Two datasets were selected to demonstrate the practicing of K-Means clustering algorithms that are Virus Total and Malgenome dataset. We classify the Android malware into three clusters which are ransomware, scareware and goodware. Nine features were considered for each types of dataset such as Lock Detected, Text Detected, Text Score, Encryption Detected, Threat, Porn, Law, Copyright and Moneypak. We used IBM SPSS Statistic software for data classification and WEKA tools to evaluate the built cluster. The proposed K-Means clustering algorithm shows promising result with high accuracy when tested using Random Forest algorithm.

  4. Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

    Science.gov (United States)

    Joslin, Ronald D.; Zubair, Mohammad

    1993-01-01

    The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

  5. A Cluster Randomized-Controlled Trial of the Impact of the Tools of the Mind Curriculum on Self-Regulation in Canadian Preschoolers.

    Science.gov (United States)

    Solomon, Tracy; Plamondon, Andre; O'Hara, Arland; Finch, Heather; Goco, Geraldine; Chaban, Peter; Huggins, Lorrie; Ferguson, Bruce; Tannock, Rosemary

    2017-01-01

    Early self-regulation predicts school readiness, academic success, and quality of life in adulthood. Its development in the preschool years is rapid and also malleable. Thus, preschool curricula that promote the development of self-regulation may help set children on a more positive developmental trajectory. We conducted a cluster-randomized controlled trial of the Tools of the Mind preschool curriculum, a program that targets self-regulation through imaginative play and self-regulatory language (Tools; clinical trials identifier NCT02462733). Previous research with Tools is limited, with mixed evidence of its effectiveness. Moreover, it is unclear whether it would benefit all preschoolers or primarily those with poorly developed cognitive capacities (e.g., language, executive function, attention). The study goals were to ascertain whether the Tools program leads to greater gains in self-regulation compared to Playing to Learn (YMCA PTL), another play based program that does not target self-regulation specifically, and whether the effects were moderated by children's initial language and hyperactivity/inattention. Two hundred and sixty 3- to 4-year-olds attending 20 largely urban daycares were randomly assigned, at the site level, to receive either Tools or YMCA PTL (the business-as-usual curriculum) for 15 months. We assessed self-regulation at pre-, mid and post intervention, using two executive function tasks, and two questionnaires regarding behavior at home and at school, to capture development in cognitive as well as socio-emotional aspects of self-regulation. Fidelity data showed that only the teachers at the Tools sites implemented Tools, and did so with reasonable success. We found that children who received Tools made greater gains on a behavioral measure of executive function than their YMCA PTL peers, but the difference was significant only for those children whose parents rated them high in hyperactivity/inattention initially. The effect of Tools did

  6. A Cluster Randomized-Controlled Trial of the Impact of the Tools of the Mind Curriculum on Self-Regulation in Canadian Preschoolers

    Directory of Open Access Journals (Sweden)

    Tracy Solomon

    2018-01-01

    Full Text Available Early self-regulation predicts school readiness, academic success, and quality of life in adulthood. Its development in the preschool years is rapid and also malleable. Thus, preschool curricula that promote the development of self-regulation may help set children on a more positive developmental trajectory. We conducted a cluster-randomized controlled trial of the Tools of the Mind preschool curriculum, a program that targets self-regulation through imaginative play and self-regulatory language (Tools; clinical trials identifier NCT02462733. Previous research with Tools is limited, with mixed evidence of its effectiveness. Moreover, it is unclear whether it would benefit all preschoolers or primarily those with poorly developed cognitive capacities (e.g., language, executive function, attention. The study goals were to ascertain whether the Tools program leads to greater gains in self-regulation compared to Playing to Learn (YMCA PTL, another play based program that does not target self-regulation specifically, and whether the effects were moderated by children’s initial language and hyperactivity/inattention. Two hundred and sixty 3- to 4-year-olds attending 20 largely urban daycares were randomly assigned, at the site level, to receive either Tools or YMCA PTL (the business-as-usual curriculum for 15 months. We assessed self-regulation at pre-, mid and post intervention, using two executive function tasks, and two questionnaires regarding behavior at home and at school, to capture development in cognitive as well as socio-emotional aspects of self-regulation. Fidelity data showed that only the teachers at the Tools sites implemented Tools, and did so with reasonable success. We found that children who received Tools made greater gains on a behavioral measure of executive function than their YMCA PTL peers, but the difference was significant only for those children whose parents rated them high in hyperactivity/inattention initially. The

  7. Clustered tuberculosis in a low-burden country

    DEFF Research Database (Denmark)

    Kamper-Jørgensen, Z; Andersen, A B; Kok-Jensen, A

    2012-01-01

    Molecular genotyping of Mycobacterium tuberculosis has proved to be a powerful tool in tuberculosis surveillance, epidemiology, and control. Based on results obtained through 15 years of nationwide IS6110 restriction fragment length polymorphism (RFLP) genotyping of M. tuberculosis cases in Denmark......, a country on the way toward tuberculosis elimination, we discuss M. tuberculosis transmission dynamics and point to areas for control interventions. Cases with 100% identical genotypes (RFLP patterns) were defined as clustered, and a cluster was defined as cases with an identical genotype. Of 4,601 included...... cases, corresponding to 76% of reported and 97% of culture-verified tuberculosis cases in the country, 56% were clustered, of which 69% were Danes. Generally, Danes were more often in large clusters (= 50 persons), older (mean age, 45 years), and male (male/female ratio, 2.5). Also, Danes had a higher...

  8. Techniques for Representation of Regional Clusters in Geographical In-formation Systems

    Directory of Open Access Journals (Sweden)

    Adriana REVEIU

    2011-01-01

    Full Text Available This paper provides an overview of visualization techniques adapted for regional clusters presentation in Geographic Information Systems. Clusters are groups of companies and insti-tutions co-located in a specific geographic region and linked by interdependencies in providing a related group of products and services. The regional clusters can be visualized by projecting the data into two-dimensional space or using parallel coordinates. Cluster membership is usually represented by different colours or by dividing clusters into several panels of a grille display. Taking into consideration regional clusters requirements and the multilevel administrative division of the Romania’s territory, I used two cartograms: NUTS2- regions and NUTS3- counties, to illustrate the tools for regional clusters representation.

  9. Cluster-transfer reactions with radioactive beams: a spectroscopic tool for neutron-rich nuclei

    CERN Document Server

    AUTHOR|(CDS)2086156; Raabe, Riccardo; Bracco, Angela

    In this thesis work, an exploratory experiment to investigate cluster-transfer reactions with radioactive beams in inverse kinematics is presented. The aim of the experiment was to test the potential of cluster-transfer reactions at the Coulomb barrier, as a possible mean to perform $\\gamma$ spectroscopy studies of exotic neutron-rich nuclei at medium-high energies and spins. The experiment was performed at ISOLDE (CERN), employing the heavy-ion reaction $^{98}$Rb + $^{7}$Li at 2.85 MeV/A. Cluster-transfer reaction channels were studied through particle-$\\gamma$ coincidence measurements, using the MINIBALL Ge array coupled to the charged particle Si detectors T-REX. Sr, Y and Zr neutron-rich nuclei with A $\\approx$ 100 were populated by either triton- or $\\alpha$ transfer from $^{7}$Li to the beam nuclei and the emitted complementary charged fragment was detected in coincidence with the $\\gamma$ cascade of the residues, after few neutrons evaporation. The measured $\\gamma$ spectra were studied in detail and t...

  10. m-BIRCH: an online clustering approach for computer vision applications

    Science.gov (United States)

    Madan, Siddharth K.; Dana, Kristin J.

    2015-03-01

    We adapt a classic online clustering algorithm called Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), to incrementally cluster large datasets of features commonly used in multimedia and computer vision. We call the adapted version modified-BIRCH (m-BIRCH). The algorithm uses only a fraction of the dataset memory to perform clustering, and updates the clustering decisions when new data comes in. Modifications made in m-BIRCH enable data driven parameter selection and effectively handle varying density regions in the feature space. Data driven parameter selection automatically controls the level of coarseness of the data summarization. Effective handling of varying density regions is necessary to well represent the different density regions in data summarization. We use m-BIRCH to cluster 840K color SIFT descriptors, and 60K outlier corrupted grayscale patches. We use the algorithm to cluster datasets consisting of challenging non-convex clustering patterns. Our implementation of the algorithm provides an useful clustering tool and is made publicly available.

  11. Topics in modelling of clustered data

    CERN Document Server

    Aerts, Marc; Ryan, Louise M; Geys, Helena

    2002-01-01

    Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It focuses on providing a comprehensive treatment of marginal, conditional, and random effects models using, among others, likelihood, pseudo-likelihood, and generalized estimating equations methods. The authors motivate and illustrate all aspects of these models in a variety of real applications. They discuss several variations and extensions, including individual-level covariates and combined continuous and discrete outcomes. Flexible modelling with fractional and local polynomials, omnibus lack-of-fit tests, robustification against misspecification, exact, and bootstrap inferential procedures all receive extensive treatment. The application...

  12. A semantics-based method for clustering of Chinese web search results

    Science.gov (United States)

    Zhang, Hui; Wang, Deqing; Wang, Li; Bi, Zhuming; Chen, Yong

    2014-01-01

    Information explosion is a critical challenge to the development of modern information systems. In particular, when the application of an information system is over the Internet, the amount of information over the web has been increasing exponentially and rapidly. Search engines, such as Google and Baidu, are essential tools for people to find the information from the Internet. Valuable information, however, is still likely submerged in the ocean of search results from those tools. By clustering the results into different groups based on subjects automatically, a search engine with the clustering feature allows users to select most relevant results quickly. In this paper, we propose an online semantics-based method to cluster Chinese web search results. First, we employ the generalised suffix tree to extract the longest common substrings (LCSs) from search snippets. Second, we use the HowNet to calculate the similarities of the words derived from the LCSs, and extract the most representative features by constructing the vocabulary chain. Third, we construct a vector of text features and calculate snippets' semantic similarities. Finally, we improve the Chameleon algorithm to cluster snippets. Extensive experimental results have shown that the proposed algorithm has outperformed over the suffix tree clustering method and other traditional clustering methods.

  13. Interactive visual exploration and refinement of cluster assignments.

    Science.gov (United States)

    Kern, Michael; Lex, Alexander; Gehlenborg, Nils; Johnson, Chris R

    2017-09-12

    With ever-increasing amounts of data produced in biology research, scientists are in need of efficient data analysis methods. Cluster analysis, combined with visualization of the results, is one such method that can be used to make sense of large data volumes. At the same time, cluster analysis is known to be imperfect and depends on the choice of algorithms, parameters, and distance measures. Most clustering algorithms don't properly account for ambiguity in the source data, as records are often assigned to discrete clusters, even if an assignment is unclear. While there are metrics and visualization techniques that allow analysts to compare clusterings or to judge cluster quality, there is no comprehensive method that allows analysts to evaluate, compare, and refine cluster assignments based on the source data, derived scores, and contextual data. In this paper, we introduce a method that explicitly visualizes the quality of cluster assignments, allows comparisons of clustering results and enables analysts to manually curate and refine cluster assignments. Our methods are applicable to matrix data clustered with partitional, hierarchical, and fuzzy clustering algorithms. Furthermore, we enable analysts to explore clustering results in context of other data, for example, to observe whether a clustering of genomic data results in a meaningful differentiation in phenotypes. Our methods are integrated into Caleydo StratomeX, a popular, web-based, disease subtype analysis tool. We show in a usage scenario that our approach can reveal ambiguities in cluster assignments and produce improved clusterings that better differentiate genotypes and phenotypes.

  14. On the Power and Limits of Sequence Similarity Based Clustering of Proteins Into Families

    DEFF Research Database (Denmark)

    Wiwie, Christian; Röttger, Richard

    2017-01-01

    Over the last decades, we have observed an ongoing tremendous growth of available sequencing data fueled by the advancements in wet-lab technology. The sequencing information is only the beginning of the actual understanding of how organisms survive and prosper. It is, for instance, equally...... important to also unravel the proteomic repertoire of an organism. A classical computational approach for detecting protein families is a sequence-based similarity calculation coupled with a subsequent cluster analysis. In this work we have intensively analyzed various clustering tools on a large scale. We...... used the data to investigate the behavior of the tools' parameters underlining the diversity of the protein families. Furthermore, we trained regression models for predicting the expected performance of a clustering tool for an unknown data set and aimed to also suggest optimal parameters...

  15. Clustering of experimental data and its application to nuclear data evaluation

    International Nuclear Information System (INIS)

    Abboud, A.; Rashed, R.; Ibrahim, M.

    1998-01-01

    A semi-automatic pre-processing technique has been proposed by Iwasaki to classify the experimental data for a reaction into one or a small number of large data groups, called main cluster (s), and to eliminate some data which deviates from the main body of the data. The classifying method is based on technique like pattern clustering in the information processing domain. Test of the data clustering formed reasonable main clusters for three activation cross-sections. This technique is a helpful tool in the neutron cross-section evaluation

  16. Clustering Coefficients for Correlation Networks

    Directory of Open Access Journals (Sweden)

    Naoki Masuda

    2018-03-01

    Full Text Available Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients

  17. Clustering Coefficients for Correlation Networks.

    Science.gov (United States)

    Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

    2018-01-01

    Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

  18. Clustering Coefficients for Correlation Networks

    Science.gov (United States)

    Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

    2018-01-01

    Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly

  19. Continuous Security and Configuration Monitoring of HPC Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Lomeli, H. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Bertsch, A. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Fox, D. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2015-05-08

    Continuous security and configuration monitoring of information systems has been a time consuming and laborious task for system administrators at the High Performance Computing (HPC) center. Prior to this project, system administrators had to manually check the settings of thousands of nodes, which required a significant number of hours rendering the old process ineffective and inefficient. This paper explains the application of Splunk Enterprise, a software agent, and a reporting tool in the development of a user application interface to track and report on critical system updates and security compliance status of HPC Clusters. In conjunction with other configuration management systems, the reporting tool is to provide continuous situational awareness to system administrators of the compliance state of information systems. Our approach consisted of the development, testing, and deployment of an agent to collect any arbitrary information across a massively distributed computing center, and organize that information into a human-readable format. Using Splunk Enterprise, this raw data was then gathered into a central repository and indexed for search, analysis, and correlation. Following acquisition and accumulation, the reporting tool generated and presented actionable information by filtering the data according to command line parameters passed at run time. Preliminary data showed results for over six thousand nodes. Further research and expansion of this tool could lead to the development of a series of agents to gather and report critical system parameters. However, in order to make use of the flexibility and resourcefulness of the reporting tool the agent must conform to specifications set forth in this paper. This project has simplified the way system administrators gather, analyze, and report on the configuration and security state of HPC clusters, maintaining ongoing situational awareness. Rather than querying each cluster independently, compliance checking

  20. Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

    Science.gov (United States)

    Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.

    2015-05-01

    The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

  1. Formation of global energy minimim structures in the growth process of Lennard-Jones clusters

    DEFF Research Database (Denmark)

    Solov'yov, Ilia; Koshelev, Andrey; Shutovich, Andrey

    2003-01-01

    that in this way all known global minimum structures of the Lennard-Jones (LJ) clusters can be found. Our method provides an efficient tool for the calculation and analysis of atomic cluster structure. With its use we justify the magic numbers sequence for the clusters of noble gases atoms and compare...

  2. CAMPAIGN: an open-source library of GPU-accelerated data clustering algorithms.

    Science.gov (United States)

    Kohlhoff, Kai J; Sosnick, Marc H; Hsu, William T; Pande, Vijay S; Altman, Russ B

    2011-08-15

    Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large datasets. Sequential algorithms are inadequate for providing the necessary performance. For this reason, we have created Clustering Algorithms for Massively Parallel Architectures, Including GPU Nodes (CAMPAIGN), a central resource for data clustering algorithms and tools that are implemented specifically for execution on massively parallel processing architectures. CAMPAIGN is a library of data clustering algorithms and tools, written in 'C for CUDA' for Nvidia GPUs. The library provides up to two orders of magnitude speed-up over respective CPU-based clustering algorithms and is intended as an open-source resource. New modules from the community will be accepted into the library and the layout of it is such that it can easily be extended to promising future platforms such as OpenCL. Releases of the CAMPAIGN library are freely available for download under the LGPL from https://simtk.org/home/campaign. Source code can also be obtained through anonymous subversion access as described on https://simtk.org/scm/?group_id=453. kjk33@cantab.net.

  3. Robust multi-scale clustering of large DNA microarray datasets with the consensus algorithm

    DEFF Research Database (Denmark)

    Grotkjær, Thomas; Winther, Ole; Regenberg, Birgitte

    2006-01-01

    Motivation: Hierarchical and relocation clustering (e.g. K-means and self-organizing maps) have been successful tools in the display and analysis of whole genome DNA microarray expression data. However, the results of hierarchical clustering are sensitive to outliers, and most relocation methods...... analysis by collecting re-occurring clustering patterns in a co-occurrence matrix. The results show that consensus clustering obtained from clustering multiple times with Variational Bayes Mixtures of Gaussians or K-means significantly reduces the classification error rate for a simulated dataset...

  4. ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands.

    NARCIS (Netherlands)

    Groeneveld, Geert H; Dalhuijsen, Anton; Kara-Zaïtri, Chakib; Hamilton, Bob; de Waal, Margot W; van Dissel, Jaap T; van Steenbergen, Jim E

    2017-01-01

    Clusters of infectious diseases are frequently detected late. Real-time, detailed information about an evolving cluster and possible associated conditions is essential for local policy makers, travelers planning to visit the area, and the local population. This is currently illustrated in the Zika

  5. Methodologies and Tools for Tuning Parallel Programs: 80% Art, 20% Science, and 10% Luck

    Science.gov (United States)

    Yan, Jerry C.; Bailey, David (Technical Monitor)

    1996-01-01

    The need for computing power has forced a migration from serial computation on a single processor to parallel processing on multiprocessors. However, without effective means to monitor (and analyze) program execution, tuning the performance of parallel programs becomes exponentially difficult as program complexity and machine size increase. In the past few years, the ubiquitous introduction of performance tuning tools from various supercomputer vendors (Intel's ParAide, TMC's PRISM, CRI's Apprentice, and Convex's CXtrace) seems to indicate the maturity of performance instrumentation/monitor/tuning technologies and vendors'/customers' recognition of their importance. However, a few important questions remain: What kind of performance bottlenecks can these tools detect (or correct)? How time consuming is the performance tuning process? What are some important technical issues that remain to be tackled in this area? This workshop reviews the fundamental concepts involved in analyzing and improving the performance of parallel and heterogeneous message-passing programs. Several alternative strategies will be contrasted, and for each we will describe how currently available tuning tools (e.g. AIMS, ParAide, PRISM, Apprentice, CXtrace, ATExpert, Pablo, IPS-2) can be used to facilitate the process. We will characterize the effectiveness of the tools and methodologies based on actual user experiences at NASA Ames Research Center. Finally, we will discuss their limitations and outline recent approaches taken by vendors and the research community to address them.

  6. Comparing the performance of biomedical clustering methods

    DEFF Research Database (Denmark)

    Wiwie, Christian; Baumbach, Jan; Röttger, Richard

    2015-01-01

    expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future......Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene....... This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide...

  7. MARKETING COMMUNICATION TO INDUSTRIAL CLUSTERS OF SLOVAK REPUBLIC

    Directory of Open Access Journals (Sweden)

    Erika Loučanová

    2013-12-01

    Full Text Available Currently, the growing attention is paid to the promotion and development of clusters, i.e. concentration of businesses and other cooperating institutions in a sector and region. Despite of the economy globalization and sophisticated global communications technologies, the factor of geographical concentration should be declined, however the experts highlight the importance of direct contact with local and tacit knowledge. The aim of this paper is analyzing of marketing communication tools in different clusters of Slovakia.

  8. Cluster algebras in mathematical physics

    International Nuclear Information System (INIS)

    Francesco, Philippe Di; Gekhtman, Michael; Kuniba, Atsuo; Yamazaki, Masahito

    2014-01-01

    This special issue of Journal of Physics A: Mathematical and Theoretical contains reviews and original research articles on cluster algebras and their applications to mathematical physics. Cluster algebras were introduced by S Fomin and A Zelevinsky around 2000 as a tool for studying total positivity and dual canonical bases in Lie theory. Since then the theory has found diverse applications in mathematics and mathematical physics. Cluster algebras are axiomatically defined commutative rings equipped with a distinguished set of generators (cluster variables) subdivided into overlapping subsets (clusters) of the same cardinality subject to certain polynomial relations. A cluster algebra of rank n can be viewed as a subring of the field of rational functions in n variables. Rather than being presented, at the outset, by a complete set of generators and relations, it is constructed from the initial seed via an iterative procedure called mutation producing new seeds successively to generate the whole algebra. A seed consists of an n-tuple of rational functions called cluster variables and an exchange matrix controlling the mutation. Relations of cluster algebra type can be observed in many areas of mathematics (Plücker and Ptolemy relations, Stokes curves and wall-crossing phenomena, Feynman integrals, Somos sequences and Hirota equations to name just a few examples). The cluster variables enjoy a remarkable combinatorial pattern; in particular, they exhibit the Laurent phenomenon: they are expressed as Laurent polynomials rather than more general rational functions in terms of the cluster variables in any seed. These characteristic features are often referred to as the cluster algebra structure. In the last decade, it became apparent that cluster structures are ubiquitous in mathematical physics. Examples include supersymmetric gauge theories, Poisson geometry, integrable systems, statistical mechanics, fusion products in infinite dimensional algebras, dilogarithm

  9. Soft landing of size selected clusters in rare gas matrices

    International Nuclear Information System (INIS)

    Lau, J.T; Wurth, W.; Ehrke, H-U.; Achleitner, A.

    2003-01-01

    Soft landing of mass selected clusters in rare gas matrices is a technique used to preserve mass selection in cluster deposition. To prevent fragmentation upon deposition, the substrate is covered with rare gas matrices to dissipate the cluster kinetic energy upon impact. Theoretical and experimental studies demonstrate the power of this technique. Besides STM, optical absorption, excitation, and fluorescence experiments, x-ray absorption at core levels can be used as a tool to study soft landing conditions, as will be shown here. X-ray absorption spectroscopy is also well suited to follow diffusion and agglomeration of clusters on surfaces via energy shifts in core level absorption

  10. Synchronization as Aggregation: Cluster Kinetics of Pulse-Coupled Oscillators.

    Science.gov (United States)

    O'Keeffe, Kevin P; Krapivsky, P L; Strogatz, Steven H

    2015-08-07

    We consider models of identical pulse-coupled oscillators with global interactions. Previous work showed that under certain conditions such systems always end up in sync, but did not quantify how small clusters of synchronized oscillators progressively coalesce into larger ones. Using tools from the study of aggregation phenomena, we obtain exact results for the time-dependent distribution of cluster sizes as the system evolves from disorder to synchrony.

  11. Cluster Computing For Real Time Seismic Array Analysis.

    Science.gov (United States)

    Martini, M.; Giudicepietro, F.

    A seismic array is an instrument composed by a dense distribution of seismic sen- sors that allow to measure the directional properties of the wavefield (slowness or wavenumber vector) radiated by a seismic source. Over the last years arrays have been widely used in different fields of seismological researches. In particular they are applied in the investigation of seismic sources on volcanoes where they can be suc- cessfully used for studying the volcanic microtremor and long period events which are critical for getting information on the volcanic systems evolution. For this reason arrays could be usefully employed for the volcanoes monitoring, however the huge amount of data produced by this type of instruments and the processing techniques which are quite time consuming limited their potentiality for this application. In order to favor a direct application of arrays techniques to continuous volcano monitoring we designed and built a small PC cluster able to near real time computing the kinematics properties of the wavefield (slowness or wavenumber vector) produced by local seis- mic source. The cluster is composed of 8 Intel Pentium-III bi-processors PC working at 550 MHz, and has 4 Gigabytes of RAM memory. It runs under Linux operating system. The developed analysis software package is based on the Multiple SIgnal Classification (MUSIC) algorithm and is written in Fortran. The message-passing part is based upon the LAM programming environment package, an open-source imple- mentation of the Message Passing Interface (MPI). The developed software system includes modules devote to receiving date by internet and graphical applications for the continuous displaying of the processing results. The system has been tested with a data set collected during a seismic experiment conducted on Etna in 1999 when two dense seismic arrays have been deployed on the northeast and the southeast flanks of this volcano. A real time continuous acquisition system has been simulated by

  12. Value, Cost, and Sharing: Open Issues in Constrained Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2006-01-01

    Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, several important open questions have arisen about which constraints are most useful, how they can be actively acquired, and when and how they should be propagated to neighboring points. This position paper describes these open questions and suggests future directions for constrained clustering research.

  13. Clustering-based approaches to SAGE data mining

    Directory of Open Access Journals (Sweden)

    Wang Haiying

    2008-07-01

    Full Text Available Abstract Serial analysis of gene expression (SAGE is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the prediction of new gene functions and the identification of biomarkers in human cancer research. Clustering techniques have become fundamental approaches in these applications. This paper reviews relevant clustering techniques specifically designed for this type of data. It places an emphasis on current limitations and opportunities in this area for supporting biologically-meaningful data mining and visualisation.

  14. A clustering approach to segmenting users of internet-based risk calculators.

    Science.gov (United States)

    Harle, C A; Downs, J S; Padman, R

    2011-01-01

    Risk calculators are widely available Internet applications that deliver quantitative health risk estimates to consumers. Although these tools are known to have varying effects on risk perceptions, little is known about who will be more likely to accept objective risk estimates. To identify clusters of online health consumers that help explain variation in individual improvement in risk perceptions from web-based quantitative disease risk information. A secondary analysis was performed on data collected in a field experiment that measured people's pre-diabetes risk perceptions before and after visiting a realistic health promotion website that provided quantitative risk information. K-means clustering was performed on numerous candidate variable sets, and the different segmentations were evaluated based on between-cluster variation in risk perception improvement. Variation in responses to risk information was best explained by clustering on pre-intervention absolute pre-diabetes risk perceptions and an objective estimate of personal risk. Members of a high-risk overestimater cluster showed large improvements in their risk perceptions, but clusters of both moderate-risk and high-risk underestimaters were much more muted in improving their optimistically biased perceptions. Cluster analysis provided a unique approach for segmenting health consumers and predicting their acceptance of quantitative disease risk information. These clusters suggest that health consumers were very responsive to good news, but tended not to incorporate bad news into their self-perceptions much. These findings help to quantify variation among online health consumers and may inform the targeted marketing of and improvements to risk communication tools on the Internet.

  15. Thread-level parallelization and optimization of NWChem for the Intel MIC architecture

    Energy Technology Data Exchange (ETDEWEB)

    Shan, Hongzhang [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); de Jong, Wibe [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Oliker, Leonid [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-01-01

    In the multicore era it was possible to exploit the increase in on-chip parallelism by simply running multiple MPI processes per chip. Unfortunately, manycore processors' greatly increased thread- and data-level parallelism coupled with a reduced memory capacity demand an altogether different approach. In this paper we explore augmenting two NWChem modules, triples correction of the CCSD(T) and Fock matrix construction, with OpenMP in order that they might run efficiently on future manycore architectures. As the next NERSC machine will be a self-hosted Intel MIC (Xeon Phi) based supercomputer, we leverage an existing MIC testbed at NERSC to evaluate our experiments. In order to proxy the fact that future MIC machines will not have a host processor, we run all of our experiments in native mode. We found that while straightforward application of OpenMP to the deep loop nests associated with the tensor contractions of CCSD(T) was sufficient in attaining high performance, significant e ort was required to safely and efeciently thread the TEXAS integral package when constructing the Fock matrix. Ultimately, our new MPI+OpenMP hybrid implementations attain up to 65× better performance for the triples part of the CCSD(T) due in large part to the fact that the limited on-card memory limits the existing MPI implementation to a single process per card. Additionally, we obtain up to 1.6× better performance on Fock matrix constructions when compared with the best MPI implementations running multiple processes per card.

  16. Thread-Level Parallelization and Optimization of NWChem for the Intel MIC Architecture

    Energy Technology Data Exchange (ETDEWEB)

    Shan, Hongzhang; Williams, Samuel; Jong, Wibe de; Oliker, Leonid

    2014-10-10

    In the multicore era it was possible to exploit the increase in on-chip parallelism by simply running multiple MPI processes per chip. Unfortunately, manycore processors' greatly increased thread- and data-level parallelism coupled with a reduced memory capacity demand an altogether different approach. In this paper we explore augmenting two NWChem modules, triples correction of the CCSD(T) and Fock matrix construction, with OpenMP in order that they might run efficiently on future manycore architectures. As the next NERSC machine will be a self-hosted Intel MIC (Xeon Phi) based supercomputer, we leverage an existing MIC testbed at NERSC to evaluate our experiments. In order to proxy the fact that future MIC machines will not have a host processor, we run all of our experiments in tt native mode. We found that while straightforward application of OpenMP to the deep loop nests associated with the tensor contractions of CCSD(T) was sufficient in attaining high performance, significant effort was required to safely and efficiently thread the TEXAS integral package when constructing the Fock matrix. Ultimately, our new MPI OpenMP hybrid implementations attain up to 65x better performance for the triples part of the CCSD(T) due in large part to the fact that the limited on-card memory limits the existing MPI implementation to a single process per card. Additionally, we obtain up to 1.6x better performance on Fock matrix constructions when compared with the best MPI implementations running multiple processes per card.

  17. Search for Formation Criteria for Globular Cluster Systems

    Science.gov (United States)

    Nuritdinov, S. N.; Mirtadjieva, K. T.; Tadjibaev, I. U.

    2005-01-01

    Star cluster formation is a major mode of star formation in the extreme conditions of interacting galaxies and violent starbursts. By studying ages and metallicities of young metal-enhanced star clusters in mergers / merger remnants we can learn about the violent star formation history of these galaxies and eventually about galaxy formation and evolution. We will present a new set of evolutionary synthesis models of our GALEV code specially developed to account for the gaseous emission of presently forming star clusters and an advanced tool to compare large model grids with multi-color broad-band observations becoming presently available in large amounts. Such observations are an ecomonic way to determine the parameters of young star clusters as will be shown in the presentation. First results of newly-born clusters in mergers and starburst galaxies are presented and compared to the well-studied old globulars and interpreted in the framework of galaxy formation / evolution.

  18. Optimizing 10-Gigabit Ethernet for Networks of Workstations, Clusters, and Grids: A Case Study

    Energy Technology Data Exchange (ETDEWEB)

    Feng, Wu-chun

    2003-10-13

    This paper presents a case study of the 10-Gigabit Ethernet (10GbE) adapter from Intel(reg sign). Specifically, with appropriate optimizations to the configurations of the 10GbE adapter and TCP, we demonstrate that the 10GbE adapter can perform well in local-area, storage-area, system-area, and wide-area networks. For local-area, storage-area, and system-area networks in support of networks of workstations, network-attached storage, and clusters, respectively, we can achieve over 7-Gb/s end-to-end throughput and 12-{micro}s end-to-end latency between applications running on Linux-based PCs. For the wide-area network in support of grids, we broke the recently-set Internet2 Land Speed Record by 2.5 times by sustaining an end-to-end TCP/IP throughput of 2.38 Gb/s between Sunnyvale, California and Geneva, Switzerland (i.e., 10,037 kilometers) to move over a terabyte of data in less than an hour. Thus, the above results indicate that 10GbE may be a cost-effective solution across a multitude of computing environments.

  19. Allergen Sensitization Pattern by Sex: A Cluster Analysis in Korea.

    Science.gov (United States)

    Ohn, Jungyoon; Paik, Seung Hwan; Doh, Eun Jin; Park, Hyun-Sun; Yoon, Hyun-Sun; Cho, Soyun

    2017-12-01

    Allergens tend to sensitize simultaneously. Etiology of this phenomenon has been suggested to be allergen cross-reactivity or concurrent exposure. However, little is known about specific allergen sensitization patterns. To investigate the allergen sensitization characteristics according to gender. Multiple allergen simultaneous test (MAST) is widely used as a screening tool for detecting allergen sensitization in dermatologic clinics. We retrospectively reviewed the medical records of patients with MAST results between 2008 and 2014 in our Department of Dermatology. A cluster analysis was performed to elucidate the allergen-specific immunoglobulin (Ig)E cluster pattern. The results of MAST (39 allergen-specific IgEs) from 4,360 cases were analyzed. By cluster analysis, 39items were grouped into 8 clusters. Each cluster had characteristic features. When compared with female, the male group tended to be sensitized more frequently to all tested allergens, except for fungus allergens cluster. The cluster and comparative analysis results demonstrate that the allergen sensitization is clustered, manifesting allergen similarity or co-exposure. Only the fungus cluster allergens tend to sensitize female group more frequently than male group.

  20. Internet of Things with Intel Galileo

    CERN Document Server

    de Sousa, Miguel

    2015-01-01

    This book employs an incremental, step-by-step approach to get you familiarized with everything from the basic terms, board components, and development environments to developing real projects. Each project will demonstrate how to use specific board components and tools. Both Galileo and Galileo Gen 2 are covered in this book.

  1. Humanitarian Logistics: a Clustering Methodology for Assisting Humanitarian Operations

    Directory of Open Access Journals (Sweden)

    Fabiana santos Lima

    2014-06-01

    Full Text Available In this paper, we propose a methodology to identify and classify regions by the type and frequency of disasters. The data on the clusters allow you to extract information that can be used in the preparedness phase as well as to identify the relief items needed to meet each cluster. Using this approach, the clusters are formed by using a computing tool that uses as the input the history data of the disasters in the Brazilian state of Santa Catarina, with a specific focus on: windstorms, hail, floods, droughts, landslides, and flash floods. The results show that the knowledge provided by the clustering analysis contributes to the decision making process in the response phase of Humanitarian Logistics (HL.

  2. The Stormy Life of Galaxy Clusters

    Science.gov (United States)

    Rudnick, Lawrence

    2018-01-01

    Galaxy clusters, the largest gravitationally bound structures, hold the full history of their baryonic evolution, serve as important cosmological tools and allow us to probe unique physical regimes in their diffuse plasmas. With characteristic dynamical timescales of 107-109 years, these diffuse thermal and relativistic media continue to evolve, as dark matter drives major mergers and more gentle continuing accretion. The history of this assembly is encoded in the plasmas, and a wide range of observational and theoretical investigations are aimed at decoding their signatures. X-ray temperature and density variations, low Mach number shocks, and "cold front" discontinuities all illuminate clusters' continued evolution. Radio structures and spectra are passive indicators of merger shocks, while radio galaxy distortions reveal the complex motions in the intracluster medium. Deep in cluster cores, AGNs associated with brightest cluster galaxies provide ongoing energy, and perhaps even stabilize the intracluster medium. In this talk, we will recount this evolving picture of the stormy ICM, and suggest areas of likely advance in the coming years.

  3. nIFTy galaxy cluster simulations II: radiative models

    CSIR Research Space (South Africa)

    Sembolini, F

    2016-04-01

    Full Text Available Valerio 2, I-34127 Trieste, Italy 12Physics Department, University of the Western Cape, Cape Town 7535, Sotuh Africa 13Physics Department, University of Western Cape, Bellville, Cape Town 7535, South Africa 14South African Astronomical Observatory, PO Box...IFTy cluster comparison project (Sembolini et al., 2015): a study of the latest state-of- the-art hydrodynamical codes using simulated galaxy clusters as a testbed for theories of galaxy formation. Simulations are indis- pensable tools in the interpretation...

  4. Two-Way Regularized Fuzzy Clustering of Multiple Correspondence Analysis.

    Science.gov (United States)

    Kim, Sunmee; Choi, Ji Yeh; Hwang, Heungsun

    2017-01-01

    Multiple correspondence analysis (MCA) is a useful tool for investigating the interrelationships among dummy-coded categorical variables. MCA has been combined with clustering methods to examine whether there exist heterogeneous subclusters of a population, which exhibit cluster-level heterogeneity. These combined approaches aim to classify either observations only (one-way clustering of MCA) or both observations and variable categories (two-way clustering of MCA). The latter approach is favored because its solutions are easier to interpret by providing explicitly which subgroup of observations is associated with which subset of variable categories. Nonetheless, the two-way approach has been built on hard classification that assumes observations and/or variable categories to belong to only one cluster. To relax this assumption, we propose two-way fuzzy clustering of MCA. Specifically, we combine MCA with fuzzy k-means simultaneously to classify a subgroup of observations and a subset of variable categories into a common cluster, while allowing both observations and variable categories to belong partially to multiple clusters. Importantly, we adopt regularized fuzzy k-means, thereby enabling us to decide the degree of fuzziness in cluster memberships automatically. We evaluate the performance of the proposed approach through the analysis of simulated and real data, in comparison with existing two-way clustering approaches.

  5. Techniques and tools for measuring energy efficiency of scientific software applications

    CERN Document Server

    Abdurachmanov, David; Eulisse, Giulio; Knight, Robert; Niemi, Tapio; Nurminen, Jukka K.; Nyback, Filip; Pestana, Goncalo; Ou, Zhonghong; Khan, Kashif

    2014-01-01

    The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important concern in scientific fields such as High Energy Physics (HEP). There has been a growing interest in utilizing alternate architectures, such as low power ARM processors, to replace traditional Intel x86 architectures. Nevertheless, even though such solutions have been successfully used in mobile applications with low I/O and memory demands, it is unclear if they are suitable and more energy-efficient in the scientific computing environment. Furthermore, there is a lack of tools and experience to derive and compare power consumption between the architectures for various workloads, and eventually to support software optimizations for energy efficiency. To that end, we have performed several physical and software-based measurements of workloads from HEP applications running o...

  6. Writing parallel programs that work

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Serial algorithms typically run inefficiently on parallel machines. This may sound like an obvious statement, but it is the root cause of why parallel programming is considered to be difficult. The current state of the computer industry is still that almost all programs in existence are serial. This talk will describe the techniques used in the Intel Parallel Studio to provide a developer with the tools necessary to understand the behaviors and limitations of the existing serial programs. Once the limitations are known the developer can refactor the algorithms and reanalyze the resulting programs with the tools in the Intel Parallel Studio to create parallel programs that work. About the speaker Paul Petersen is a Sr. Principal Engineer in the Software and Solutions Group (SSG) at Intel. He received a Ph.D. degree in Computer Science from the University of Illinois in 1993. After UIUC, he was employed at Kuck and Associates, Inc. (KAI) working on auto-parallelizing compiler (KAP), and was involved in th...

  7. A Distributed Flocking Approach for Information Stream Clustering Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL

    2006-01-01

    Intelligence analysts are currently overwhelmed with the amount of information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the information streams. Document clustering analysis plays an important role in improving the accuracy of information retrieval. However, most clustering technologies can only be applied for analyzing the static document collection because they normally require a large amount of computation resource and long time to get accurate result. It is very difficult to cluster a dynamic changed text information streams on an individual computer. Our early research has resulted in a dynamic reactive flock clustering algorithm which can continually refine the clustering result and quickly react to the change of document contents. This character makes the algorithm suitable for cluster analyzing dynamic changed document information, such as text information stream. Because of the decentralized character of this algorithm, a distributed approach is a very natural way to increase the clustering speed of the algorithm. In this paper, we present a distributed multi-agent flocking approach for the text information stream clustering and discuss the decentralized architectures and communication schemes for load balance and status information synchronization in this approach.

  8. Cluster analysis of spontaneous preterm birth phenotypes identifies potential associations among preterm birth mechanisms.

    Science.gov (United States)

    Esplin, M Sean; Manuck, Tracy A; Varner, Michael W; Christensen, Bryce; Biggio, Joseph; Bukowski, Radek; Parry, Samuel; Zhang, Heping; Huang, Hao; Andrews, William; Saade, George; Sadovsky, Yoel; Reddy, Uma M; Ilekis, John

    2015-09-01

    We sought to use an innovative tool that is based on common biologic pathways to identify specific phenotypes among women with spontaneous preterm birth (SPTB) to enhance investigators' ability to identify and to highlight common mechanisms and underlying genetic factors that are responsible for SPTB. We performed a secondary analysis of a prospective case-control multicenter study of SPTB. All cases delivered a preterm singleton at SPTB ≤34.0 weeks' gestation. Each woman was assessed for the presence of underlying SPTB causes. A hierarchic cluster analysis was used to identify groups of women with homogeneous phenotypic profiles. One of the phenotypic clusters was selected for candidate gene association analysis with the use of VEGAS software. One thousand twenty-eight women with SPTB were assigned phenotypes. Hierarchic clustering of the phenotypes revealed 5 major clusters. Cluster 1 (n = 445) was characterized by maternal stress; cluster 2 (n = 294) was characterized by premature membrane rupture; cluster 3 (n = 120) was characterized by familial factors, and cluster 4 (n = 63) was characterized by maternal comorbidities. Cluster 5 (n = 106) was multifactorial and characterized by infection (INF), decidual hemorrhage (DH), and placental dysfunction (PD). These 3 phenotypes were correlated highly by χ(2) analysis (PD and DH, P cluster 3 of SPTB. We identified 5 major clusters of SPTB based on a phenotype tool and hierarch clustering. There was significant correlation between several of the phenotypes. The INS gene was associated with familial factors that were underlying SPTB. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. ANALISIS SEGMENTASI PELANGGAN MENGGUNAKAN KOMBINASI RFM MODEL DAN TEKNIK CLUSTERING

    Directory of Open Access Journals (Sweden)

    Beta Estri Adiana

    2018-04-01

    Full Text Available Intense competition in the business field motivates a small and medium enterprises (SMEs to manage customer services to the maximal. Improve of customer royalty by grouping cunstomers into some of groups and determining appropriate and effective marketing strategies for each group. Customer segmentation can be performed by data mining approach with clustering method. The main purpose of this paper is customer segmentation and measure their loyalty to a SME’s product. Using CRISP-DM method which consist of six phases, namely business understanding, data understanding, data preparatuin, modeling, evaluation and deployment. The K-Means algorithm is used for cluster formation and RapidMiner as a tool used to evaluate the result of clusters. Cluster formation is based on RFM (recency, frequency, monetary analysis. Davies Bouldin Index (DBI is used to find the optimal number of clusters (k. The customers are divided into 3 clusters, total of customer in first cluster is 30 customers who entered in typical customer category, the second cluster there are 8 customer whho entered in superstar customer and 89 customers in third cluster is dormant cluster category.

  10. Homo-FRET Imaging as a tool to quantify protein and lipid clustering

    NARCIS (Netherlands)

    Bader, A.N.; Hoetzl, S.; Hofman, E.G.; Voortman, J.; van Bergen en Henegouwen, P.M.P.; van Meer, G.; Gerritsen, H.C.

    2010-01-01

    Homo-FRET, Förster resonance energy transfer between identical fluorophores, can be conveniently measured by observing its effect on the fluorescence anisotropy. This review aims to summarize the possibilities of fluorescence anisotropy imaging techniques to investigate clustering of identical

  11. ClusTrack: feature extraction and similarity measures for clustering of genome-wide data sets.

    Directory of Open Access Journals (Sweden)

    Halfdan Rydbeck

    Full Text Available Clustering is a popular technique for explorative analysis of data, as it can reveal subgroupings and similarities between data in an unsupervised manner. While clustering is routinely applied to gene expression data, there is a lack of appropriate general methodology for clustering of sequence-level genomic and epigenomic data, e.g. ChIP-based data. We here introduce a general methodology for clustering data sets of coordinates relative to a genome assembly, i.e. genomic tracks. By defining appropriate feature extraction approaches and similarity measures, we allow biologically meaningful clustering to be performed for genomic tracks using standard clustering algorithms. An implementation of the methodology is provided through a tool, ClusTrack, which allows fine-tuned clustering analyses to be specified through a web-based interface. We apply our methods to the clustering of occupancy of the H3K4me1 histone modification in samples from a range of different cell types. The majority of samples form meaningful subclusters, confirming that the definitions of features and similarity capture biological, rather than technical, variation between the genomic tracks. Input data and results are available, and can be reproduced, through a Galaxy Pages document at http://hyperbrowser.uio.no/hb/u/hb-superuser/p/clustrack. The clustering functionality is available as a Galaxy tool, under the menu option "Specialized analyzis of tracks", and the submenu option "Cluster tracks based on genome level similarity", at the Genomic HyperBrowser server: http://hyperbrowser.uio.no/hb/.

  12. Comparison of two accelerators for Monte Carlo radiation transport calculations, Nvidia Tesla M2090 GPU and Intel Xeon Phi 5110p coprocessor: A case study for X-ray CT imaging dose calculation

    International Nuclear Information System (INIS)

    Liu, T.; Xu, X.G.; Carothers, C.D.

    2015-01-01

    Highlights: • A new Monte Carlo photon transport code ARCHER-CT for CT dose calculations is developed to execute on the GPU and coprocessor. • ARCHER-CT is verified against MCNP. • The GPU code on an Nvidia M2090 GPU is 5.15–5.81 times faster than the parallel CPU code on an Intel X5650 6-core CPU. • The coprocessor code on an Intel Xeon Phi 5110p coprocessor is 3.30–3.38 times faster than the CPU code. - Abstract: Hardware accelerators are currently becoming increasingly important in boosting high performance computing systems. In this study, we tested the performance of two accelerator models, Nvidia Tesla M2090 GPU and Intel Xeon Phi 5110p coprocessor, using a new Monte Carlo photon transport package called ARCHER-CT we have developed for fast CT imaging dose calculation. The package contains three components, ARCHER-CT CPU , ARCHER-CT GPU and ARCHER-CT COP designed to be run on the multi-core CPU, GPU and coprocessor architectures respectively. A detailed GE LightSpeed Multi-Detector Computed Tomography (MDCT) scanner model and a family of voxel patient phantoms are included in the code to calculate absorbed dose to radiosensitive organs under user-specified scan protocols. The results from ARCHER agree well with those from the production code Monte Carlo N-Particle eXtended (MCNPX). It is found that all the code components are significantly faster than the parallel MCNPX run on 12 MPI processes, and that the GPU and coprocessor codes are 5.15–5.81 and 3.30–3.38 times faster than the parallel ARCHER-CT CPU , respectively. The M2090 GPU performs better than the 5110p coprocessor in our specific test. Besides, the heterogeneous computation mode in which the CPU and the hardware accelerator work concurrently can increase the overall performance by 13–18%

  13. The structure of nearby clusters of galaxies Hierarchical clustering and an application to the Leo region

    CERN Document Server

    Materne, J

    1978-01-01

    A new method of classifying groups of galaxies, called hierarchical clustering, is presented as a tool for the investigation of nearby groups of galaxies. The method is free from model assumptions about the groups. The scaling of the different coordinates is necessary, and the level from which one accepts the groups as real has to be determined. Hierarchical clustering is applied to an unbiased sample of galaxies in the Leo region. Five distinct groups result which have reasonable physical properties, such as low crossing times and conservative mass-to-light ratios, and which follow a radial velocity- luminosity relation. Only 4 out of 39 galaxies were adopted as field galaxies. (27 refs).

  14. Mining the National Career Assessment Examination Result Using Clustering Algorithm

    Science.gov (United States)

    Pagudpud, M. V.; Palaoag, T. T.; Padirayon, L. M.

    2018-03-01

    Education is an essential process today which elicits authorities to discover and establish innovative strategies for educational improvement. This study applied data mining using clustering technique for knowledge extraction from the National Career Assessment Examination (NCAE) result in the Division of Quirino. The NCAE is an examination given to all grade 9 students in the Philippines to assess their aptitudes in the different domains. Clustering the students is helpful in identifying students’ learning considerations. With the use of the RapidMiner tool, clustering algorithms such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN), k-means, k-medoid, expectation maximization clustering, and support vector clustering algorithms were analyzed. The silhouette indexes of the said clustering algorithms were compared, and the result showed that the k-means algorithm with k = 3 and silhouette index equal to 0.196 is the most appropriate clustering algorithm to group the students. Three groups were formed having 477 students in the determined group (cluster 0), 310 proficient students (cluster 1) and 396 developing students (cluster 2). The data mining technique used in this study is essential in extracting useful information from the NCAE result to better understand the abilities of students which in turn is a good basis for adopting teaching strategies.

  15. OpenMP Parallelization and Optimization of Graph-based Machine Learning Algorithms

    Science.gov (United States)

    2016-05-01

    Understanding Application Data Movement Characteristics using Intel VTune Amplifier and Software Development Emulator tools, Intel Xeon Phi User Group...sured by a summation of the weights along the graph cut) for this problem. This is equivalent to assigning a scalar or vector value ui to each i th data...graph Laplacian [9]. By projecting all vectors onto this sub-eigenspace, the iteration step reduces to a simple coefficient update. 2.2 Semi-supervised

  16. AN EXAMINATION OF THE OPTICAL SUBSTRUCTURE OF GALAXY CLUSTERS HOSTING RADIO SOURCES

    International Nuclear Information System (INIS)

    Wing, Joshua D.; Blanton, Elizabeth L.

    2013-01-01

    Using radio sources from the Faint Images of the Radio Sky at Twenty-cm survey, and optical counterparts in the Sloan Digital Sky Survey, we have identified a large number of galaxy clusters. The radio sources within these clusters are driven by active galactic nuclei, and our cluster samples include clusters with bent, and straight, double-lobed radio sources. We also included a single-radio-component comparison sample. We examine these galaxy clusters for evidence of optical substructure, testing the possibility that bent double-lobed radio sources are formed as a result of large-scale cluster mergers. We use a suite of substructure analysis tools to determine the location and extent of substructure visible in the optical distribution of cluster galaxies, and compare the rates of substructure in clusters with different types of radio sources. We found no preference for significant substructure in clusters hosting bent double-lobed radio sources compared to those with other types of radio sources.

  17. Gene identification and protein classification in microbial metagenomic sequence data via incremental clustering

    Directory of Open Access Journals (Sweden)

    Li Weizhong

    2008-04-01

    Full Text Available Abstract Background The identification and study of proteins from metagenomic datasets can shed light on the roles and interactions of the source organisms in their communities. However, metagenomic datasets are characterized by the presence of organisms with varying GC composition, codon usage biases etc., and consequently gene identification is challenging. The vast amount of sequence data also requires faster protein family classification tools. Results We present a computational improvement to a sequence clustering approach that we developed previously to identify and classify protein coding genes in large microbial metagenomic datasets. The clustering approach can be used to identify protein coding genes in prokaryotes, viruses, and intron-less eukaryotes. The computational improvement is based on an incremental clustering method that does not require the expensive all-against-all compute that was required by the original approach, while still preserving the remote homology detection capabilities. We present evaluations of the clustering approach in protein-coding gene identification and classification, and also present the results of updating the protein clusters from our previous work with recent genomic and metagenomic sequences. The clustering results are available via CAMERA, (http://camera.calit2.net. Conclusion The clustering paradigm is shown to be a very useful tool in the analysis of microbial metagenomic data. The incremental clustering method is shown to be much faster than the original approach in identifying genes, grouping sequences into existing protein families, and also identifying novel families that have multiple members in a metagenomic dataset. These clusters provide a basis for further studies of protein families.

  18. Analysis and comparison of very large metagenomes with fast clustering and functional annotation

    Directory of Open Access Journals (Sweden)

    Li Weizhong

    2009-10-01

    Full Text Available Abstract Background The remarkable advance of metagenomics presents significant new challenges in data analysis. Metagenomic datasets (metagenomes are large collections of sequencing reads from anonymous species within particular environments. Computational analyses for very large metagenomes are extremely time-consuming, and there are often many novel sequences in these metagenomes that are not fully utilized. The number of available metagenomes is rapidly increasing, so fast and efficient metagenome comparison methods are in great demand. Results The new metagenomic data analysis method Rapid Analysis of Multiple Metagenomes with a Clustering and Annotation Pipeline (RAMMCAP was developed using an ultra-fast sequence clustering algorithm, fast protein family annotation tools, and a novel statistical metagenome comparison method that employs a unique graphic interface. RAMMCAP processes extremely large datasets with only moderate computational effort. It identifies raw read clusters and protein clusters that may include novel gene families, and compares metagenomes using clusters or functional annotations calculated by RAMMCAP. In this study, RAMMCAP was applied to the two largest available metagenomic collections, the "Global Ocean Sampling" and the "Metagenomic Profiling of Nine Biomes". Conclusion RAMMCAP is a very fast method that can cluster and annotate one million metagenomic reads in only hundreds of CPU hours. It is available from http://tools.camera.calit2.net/camera/rammcap/.

  19. Dynamics of cluster structures in a financial market network

    Science.gov (United States)

    Kocheturov, Anton; Batsyn, Mikhail; Pardalos, Panos M.

    2014-11-01

    In the course of recent fifteen years the network analysis has become a powerful tool for studying financial markets. In this work we analyze stock markets of the USA and Sweden. We study cluster structures of a market network constructed from a correlation matrix of returns of the stocks traded in each of these markets. Such cluster structures are obtained by means of the P-Median Problem (PMP) whose objective is to maximize the total correlation between a set of stocks called medians of size p and other stocks. Every cluster structure is an undirected disconnected weighted graph in which every connected component (cluster) is a star, or a tree with one central node (called a median) and several leaf nodes connected with the median by weighted edges. Our main observation is that in non-crisis periods of time cluster structures change more chaotically, while during crises they show more stable behavior and fewer changes. Thus an increasing stability of a market graph cluster structure obtained via the PMP could be used as an indicator of a coming crisis.

  20. Multifractal Approach to Time Clustering of Earthquakes. Application to Mt. Vesuvio Seismicity

    Science.gov (United States)

    Codano, C.; Alonzo, M. L.; Vilardo, G.

    The clustering structure of the Vesuvian earthquakes occurring is investigated by means of statistical tools: the inter-event time distribution, the running mean and the multifractal analysis. The first cannot clearly distinguish between a Poissonian process and a clustered one due to the difficulties of clearly distinguishing between an exponential distribution and a power law one. The running mean test reveals the clustering of the earthquakes, but looses information about the structure of the distribution at global scales. The multifractal approach can enlighten the clustering at small scales, while the global behaviour remains Poissonian. Subsequently the clustering of the events is interpreted in terms of diffusive processes of the stress in the earth crust.

  1. The Whisper Relaxation Sounder onboard Cluster: A Powerful Tool for Space Plasma Diagnosis around the Earth

    International Nuclear Information System (INIS)

    Trotignon, J.G.; Decreau, P.M.E.; Rauch, J.L.; LeGuirriec, E.; Canu, P.; Darrouzet, F.

    2001-01-01

    The WHISPER relaxation sounder that is onboard the four CLUSTER spacecraft has for main scientific objectives to monitor the natural waves in the 2 kHz - 80 kHz frequency range and, mostly, to determine the total plasma density from the solar wind down to the Earth's plasmasphere. To fulfil these objectives, the WHISPER uses the two long double sphere antennae of the Electric Field and Wave experiment as transmitting and receiving sensors. In its active working mode, the WHISPER works according to principles that have been worked out for topside sounding. A radio wave transmitter sends an almost monochromatic and short wave train. A few milliseconds after, a receiver listens to the surrounding plasma response. Strong and long lasting echoes are actually received whenever the transmitting frequencies coincide with characteristic plasma frequencies. Provided that these echoes, also called resonances, may be identified, the WHISPER relaxation sounder becomes a reliable and powerful tool for plasma diagnosis. When the transmitter is off, the WHISPER behaves like a passive receiver, allowing natural waves to be monitored. The paper aims mainly at the resonance identification process description and the WHISPER capabilities and performance highlighting. (author)

  2. Using Vega Linux Cluster at Reactor Physics Dept

    International Nuclear Information System (INIS)

    Zefran, B.; Jeraj, R.; Skvarc, J.; Glumac, B.

    1999-01-01

    Experience using a Linux-based cluster for the reactor physics calculations are presented in this paper. Special attention is paid to the MCNP code in this environment and to practical guidelines how to prepare and use the paralel version of the code. Our results of a time comparison study are presented for two sets of inputs. The results are promising and speedup factor achieved on the Linux cluster agrees with previous tests on other parallel systems. We also tested tools for parallelization of other programs used at our Dept..(author)

  3. Network clustering coefficient approach to DNA sequence analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gerhardt, Guenther J.L. [Universidade Federal do Rio Grande do Sul-Hospital de Clinicas de Porto Alegre, Rua Ramiro Barcelos 2350/sala 2040/90035-003 Porto Alegre (Brazil); Departamento de Fisica e Quimica da Universidade de Caxias do Sul, Rua Francisco Getulio Vargas 1130, 95001-970 Caxias do Sul (Brazil); Lemke, Ney [Programa Interdisciplinar em Computacao Aplicada, Unisinos, Av. Unisinos, 950, 93022-000 Sao Leopoldo, RS (Brazil); Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, Campus Universitario, 59072 970 Natal, RN (Brazil)]. E-mail: corso@dfte.ufrn.br

    2006-05-15

    In this work we propose an alternative DNA sequence analysis tool based on graph theoretical concepts. The methodology investigates the path topology of an organism genome through a triplet network. In this network, triplets in DNA sequence are vertices and two vertices are connected if they occur juxtaposed on the genome. We characterize this network topology by measuring the clustering coefficient. We test our methodology against two main bias: the guanine-cytosine (GC) content and 3-bp (base pairs) periodicity of DNA sequence. We perform the test constructing random networks with variable GC content and imposed 3-bp periodicity. A test group of some organisms is constructed and we investigate the methodology in the light of the constructed random networks. We conclude that the clustering coefficient is a valuable tool since it gives information that is not trivially contained in 3-bp periodicity neither in the variable GC content.

  4. MOLA: a bootable, self-configuring system for virtual screening using AutoDock4/Vina on computer clusters

    Directory of Open Access Journals (Sweden)

    Abreu Rui MV

    2010-10-01

    Full Text Available Abstract Background Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. Implementation MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. Conclusion MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a

  5. Clusters in nonsmooth oscillator networks

    Science.gov (United States)

    Nicks, Rachel; Chambon, Lucie; Coombes, Stephen

    2018-03-01

    For coupled oscillator networks with Laplacian coupling, the master stability function (MSF) has proven a particularly powerful tool for assessing the stability of the synchronous state. Using tools from group theory, this approach has recently been extended to treat more general cluster states. However, the MSF and its generalizations require the determination of a set of Floquet multipliers from variational equations obtained by linearization around a periodic orbit. Since closed form solutions for periodic orbits are invariably hard to come by, the framework is often explored using numerical techniques. Here, we show that further insight into network dynamics can be obtained by focusing on piecewise linear (PWL) oscillator models. Not only do these allow for the explicit construction of periodic orbits, their variational analysis can also be explicitly performed. The price for adopting such nonsmooth systems is that many of the notions from smooth dynamical systems, and in particular linear stability, need to be modified to take into account possible jumps in the components of Jacobians. This is naturally accommodated with the use of saltation matrices. By augmenting the variational approach for studying smooth dynamical systems with such matrices we show that, for a wide variety of networks that have been used as models of biological systems, cluster states can be explicitly investigated. By way of illustration, we analyze an integrate-and-fire network model with event-driven synaptic coupling as well as a diffusively coupled network built from planar PWL nodes, including a reduction of the popular Morris-Lecar neuron model. We use these examples to emphasize that the stability of network cluster states can depend as much on the choice of single node dynamics as it does on the form of network structural connectivity. Importantly, the procedure that we present here, for understanding cluster synchronization in networks, is valid for a wide variety of systems in

  6. SU(3) techniques for angular momentum projected matrix elements in multi-cluster problems

    International Nuclear Information System (INIS)

    Hecht, K.T.; Zahn, W.

    1978-01-01

    In the theory of integral transforms for the evaluation of the resonating group kernels needed for cluster model calculations, the evaluation of matrix elements in an angular momentum coupled basis has proved to be difficult for cluster problems involving more than two fragments. For multi-cluster wave functions SU(3) coupling and recoupling techniques can furnish a tool for the practical evaluation matrix elements in an angular momentum coupled basis if the several relative motion harmonic oscillator functions in Bargmann space have simple SU(3) coupling properties. The method is illustrated by a three-cluster problem, such as 12 C = α + α + α, involving three 1 S clusters. 2 references

  7. Conveyor Performance based on Motor DC 12 Volt Eg-530ad-2f using K-Means Clustering

    Science.gov (United States)

    Arifin, Zaenal; Artini, Sri DP; Much Ibnu Subroto, Imam

    2017-04-01

    To produce goods in industry, a controlled tool to improve production is required. Separation process has become a part of production process. Separation process is carried out based on certain criteria to get optimum result. By knowing the characteristics performance of a controlled tools in separation process the optimum results is also possible to be obtained. Clustering analysis is popular method for clustering data into smaller segments. Clustering analysis is useful to divide a group of object into a k-group in which the member value of the group is homogeny or similar. Similarity in the group is set based on certain criteria. The work in this paper based on K-Means method to conduct clustering of loading in the performance of a conveyor driven by a dc motor 12 volt eg-530-2f. This technique gives a complete clustering data for a prototype of conveyor driven by dc motor to separate goods in term of height. The parameters involved are voltage, current, time of travelling. These parameters give two clusters namely optimal cluster with center of cluster 10.50 volt, 0.3 Ampere, 10.58 second, and unoptimal cluster with center of cluster 10.88 volt, 0.28 Ampere and 40.43 second.

  8. Cluster as a Tool to Increase the Competitiveness and Innovative Activity of Enterprises of the Defense Industry Complex

    Directory of Open Access Journals (Sweden)

    Katrina B. Dobrova

    2017-01-01

    Full Text Available Purpose: the main goal of the publication is to make a comprehensive study of the possible application of the cluster approach to improve the competitiveness and innovation activity of enterprises of the defense industry complex.Methods: the methodology of the research is based on the collection and analysis of initial data and information, the article uses a systematic approach to the study of socio-economic processes and phenomena. The research is based on modern theory of competition, innovation, as well as the modern paradigm of cluster development of the economy. In preparing the study, practical materials from Corporation “Rostec”.Results: the article gives the notion of cluster, the prospects for the use of the cluster approach to enhance competitiveness and innovation enterprises of the military-industrial complex. It is noted that the activation of interaction with the “civil sector” is particularly relevant in the context of the reduction of the state defense order, and the theory and practice of cluster management offers a number of forms of cluster interaction between the enterprises of the defense industry and the civil sector. It is emphasized that the development of cluster mechanisms can solve a number of problems related to the insufficient financial stability of defense industry enterprises in the context of a reduction in the state defense order, low innovation activity and the lack of developed models of interaction with small innovative enterprises. Ultimately, the use of cluster mechanisms in the development of defense enterprises is intended to enhance the competitiveness of the complex, both nationally and globally. It is stated that the existing clusters are not able to fully solve a number of specific tasks related to the diversification of integrated defense industry structures. Attention is drawn to the fact that existing clusters are not able to fully solve a number of specific tasks related to the

  9. Ionized-cluster source based on high-pressure corona discharge

    International Nuclear Information System (INIS)

    Lokuliyanage, K.; Huber, D.; Zappa, F.; Scheier, P.

    2006-01-01

    Full text: It has been demonstrated that energetic beams of large clusters, with thousands of atoms, can be a powerful tool for surface modification. Normally ionized cluster beams are obtained by electron impact on neutral beams produced in a supersonic expansion. At the University of Innsbruck we are pursuing the realization of a high current cluster ion source based on the corona discharge.The idea in the present case is that the ionization should occur prior to the supersonic expansion, thus supersede the need of subsequent electron impact. In this contribution we present the project of our source in its initial stage. The intensity distribution of cluster sizes as a function of the source parameters, such as input pressure, temperature and gap voltage, are investigated with the aid of a custom-built time of flight mass spectrometer. (author)

  10. The OGCleaner: filtering false-positive homology clusters.

    Science.gov (United States)

    Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Snell, Quinn; Bybee, Seth M

    2017-01-01

    Detecting homologous sequences in organisms is an essential step in protein structure and function prediction, gene annotation and phylogenetic tree construction. Heuristic methods are often employed for quality control of putative homology clusters. These heuristics, however, usually only apply to pairwise sequence comparison and do not examine clusters as a whole. We present the Orthology Group Cleaner (the OGCleaner), a tool designed for filtering putative orthology groups as homology or non-homology clusters by considering all sequences in a cluster. The OGCleaner relies on high-quality orthologous groups identified in OrthoDB to train machine learning algorithms that are able to distinguish between true-positive and false-positive homology groups. This package aims to improve the quality of phylogenetic tree construction especially in instances of lower-quality transcriptome assemblies. https://github.com/byucsl/ogcleaner CONTACT: sfujimoto@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. Clustering of Mycobacterium tuberculosis Cases in Acapulco: Spoligotyping and Risk Factors

    Directory of Open Access Journals (Sweden)

    Elizabeth Nava-Aguilera

    2011-01-01

    Full Text Available Recurrence and reinfection of tuberculosis have quite different implications for prevention. We identified 267 spoligotypes of Mycobacterium tuberculosis from consecutive tuberculosis patients in Acapulco, Mexico, to assess the level of clustering and risk factors for clustered strains. Point cluster analysis examined spatial clustering. Risk analysis relied on the Mantel Haenszel procedure to examine bivariate associations, then to develop risk profiles of combinations of risk factors. Supplementary analysis of the spoligotyping data used SpolTools. Spoligotyping identified 85 types, 50 of them previously unreported. The five most common spoligotypes accounted for 55% of tuberculosis cases. One cluster of 70 patients (26% of the series produced a single spoligotype from the Manila Family (Clade EAI2. The high proportion (78% of patients infected with cluster strains is compatible with recent transmission of TB in Acapulco. Geomatic analysis showed no spatial clustering; clustering was associated with a risk profile of uneducated cases who lived in single-room dwellings. The Manila emerging strain accounted for one in every four cases, confirming that one strain can predominate in a hyperendemic area.

  12. Seismicity map tools for earthquake studies

    Science.gov (United States)

    Boucouvalas, Anthony; Kaskebes, Athanasios; Tselikas, Nikos

    2014-05-01

    We report on the development of new and online set of tools for use within Google Maps, for earthquake research. We demonstrate this server based and online platform (developped with PHP, Javascript, MySQL) with the new tools using a database system with earthquake data. The platform allows us to carry out statistical and deterministic analysis on earthquake data use of Google Maps and plot various seismicity graphs. The tool box has been extended to draw on the map line segments, multiple straight lines horizontally and vertically as well as multiple circles, including geodesic lines. The application is demonstrated using localized seismic data from the geographic region of Greece as well as other global earthquake data. The application also offers regional segmentation (NxN) which allows the studying earthquake clustering, and earthquake cluster shift within the segments in space. The platform offers many filters such for plotting selected magnitude ranges or time periods. The plotting facility allows statistically based plots such as cumulative earthquake magnitude plots and earthquake magnitude histograms, calculation of 'b' etc. What is novel for the platform is the additional deterministic tools. Using the newly developed horizontal and vertical line and circle tools we have studied the spatial distribution trends of many earthquakes and we here show for the first time the link between Fibonacci Numbers and spatiotemporal location of some earthquakes. The new tools are valuable for examining visualizing trends in earthquake research as it allows calculation of statistics as well as deterministic precursors. We plan to show many new results based on our newly developed platform.

  13. The GNEMRE Dendro Tool.

    Energy Technology Data Exchange (ETDEWEB)

    Merchant, Bion John

    2007-10-01

    The GNEMRE Dendro Tool provides a previously unrealized analysis capability in the field of nuclear explosion monitoring. Dendro Tool allows analysts to quickly and easily determine the similarity between seismic events using the waveform time-series for each of the events to compute cross-correlation values. Events can then be categorized into clusters of similar events. This analysis technique can be used to characterize historical archives of seismic events in order to determine many of the unique sources that are present. In addition, the source of any new events can be quickly identified simply by comparing the new event to the historical set.

  14. MaRaCluster: A Fragment Rarity Metric for Clustering Fragment Spectra in Shotgun Proteomics.

    Science.gov (United States)

    The, Matthew; Käll, Lukas

    2016-03-04

    Shotgun proteomics experiments generate large amounts of fragment spectra as primary data, normally with high redundancy between and within experiments. Here, we have devised a clustering technique to identify fragment spectra stemming from the same species of peptide. This is a powerful alternative method to traditional search engines for analyzing spectra, specifically useful for larger scale mass spectrometry studies. As an aid in this process, we propose a distance calculation relying on the rarity of experimental fragment peaks, following the intuition that peaks shared by only a few spectra offer more evidence than peaks shared by a large number of spectra. We used this distance calculation and a complete-linkage scheme to cluster data from a recent large-scale mass spectrometry-based study. The clusterings produced by our method have up to 40% more identified peptides for their consensus spectra compared to those produced by the previous state-of-the-art method. We see that our method would advance the construction of spectral libraries as well as serve as a tool for mining large sets of fragment spectra. The source code and Ubuntu binary packages are available at https://github.com/statisticalbiotechnology/maracluster (under an Apache 2.0 license).

  15. High performance electromagnetic simulation tools

    Science.gov (United States)

    Gedney, Stephen D.; Whites, Keith W.

    1994-10-01

    Army Research Office Grant #DAAH04-93-G-0453 has supported the purchase of 24 additional compute nodes that were installed in the Intel iPsC/860 hypercube at the Univesity Of Kentucky (UK), rendering a 32-node multiprocessor. This facility has allowed the investigators to explore and extend the boundaries of electromagnetic simulation for important areas of defense concerns including microwave monolithic integrated circuit (MMIC) design/analysis and electromagnetic materials research and development. The iPSC/860 has also provided an ideal platform for MMIC circuit simulations. A number of parallel methods based on direct time-domain solutions of Maxwell's equations have been developed on the iPSC/860, including a parallel finite-difference time-domain (FDTD) algorithm, and a parallel planar generalized Yee-algorithm (PGY). The iPSC/860 has also provided an ideal platform on which to develop a 'virtual laboratory' to numerically analyze, scientifically study and develop new types of materials with beneficial electromagnetic properties. These materials simulations are capable of assembling hundreds of microscopic inclusions from which an electromagnetic full-wave solution will be obtained in toto. This powerful simulation tool has enabled research of the full-wave analysis of complex multicomponent MMIC devices and the electromagnetic properties of many types of materials to be performed numerically rather than strictly in the laboratory.

  16. Jets from jets: re-clustering as a tool for large radius jet reconstruction and grooming at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Nachman, Benjamin; Nef, Pascal; Schwartzman, Ariel; Swiatlowski, Maximilian [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Wanotayaroj, Chaowaroj [Center for High Energy Physics, University of Oregon,1371 E. 13th Ave, Eugene, OR 97403 (United States)

    2015-02-12

    Jets with a large radius R≳1 and grooming algorithms are widely used to fully capture the decay products of boosted heavy particles at the Large Hadron Collider (LHC). Unlike most discriminating variables used in such studies, the jet radius is usually not optimized for specific physics scenarios. This is because every jet configuration must be calibrated, insitu, to account for detector response and other experimental effects. One solution to enhance the availability of large-R jet configurations used by the LHC experiments is jet re-clustering. Jet re-clustering introduces an intermediate scale rclustering configurations and show that re-clustered large radius jets have essentially the same jet mass performance as large radius groomed jets. Jet re-clustering has the benefit that no additional large-R calibration is necessary, allowing the re-clustered large radius parameter to be optimized in the context of specific precision measurements or searches for new physics.

  17. Jets from jets: re-clustering as a tool for large radius jet reconstruction and grooming at the LHC

    International Nuclear Information System (INIS)

    Nachman, Benjamin; Nef, Pascal; Schwartzman, Ariel; Swiatlowski, Maximilian; Wanotayaroj, Chaowaroj

    2015-01-01

    Jets with a large radius R≳1 and grooming algorithms are widely used to fully capture the decay products of boosted heavy particles at the Large Hadron Collider (LHC). Unlike most discriminating variables used in such studies, the jet radius is usually not optimized for specific physics scenarios. This is because every jet configuration must be calibrated, insitu, to account for detector response and other experimental effects. One solution to enhance the availability of large-R jet configurations used by the LHC experiments is jet re-clustering. Jet re-clustering introduces an intermediate scale rclustering configurations and show that re-clustered large radius jets have essentially the same jet mass performance as large radius groomed jets. Jet re-clustering has the benefit that no additional large-R calibration is necessary, allowing the re-clustered large radius parameter to be optimized in the context of specific precision measurements or searches for new physics.

  18. Country clustering applied to the water and sanitation sector: a new tool with potential applications in research and policy.

    Science.gov (United States)

    Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

    2014-03-01

    The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were distinct from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. Copyright © 2013 Elsevier GmbH. All rights reserved.

  19. Cosmological implication of wide field Sunyaev-Zel'dovich galaxy clusters survey: exploration by simulation

    International Nuclear Information System (INIS)

    Juin, Jean-Baptiste

    2005-01-01

    The goal of my Phd research is to prepare the data analysis of the near future wide-field observations of galaxy clusters detected by Sunyaev Zel'dovitch effect. I set up a complete chain of original tools to carry out this study. These tools allow me to highlight critical and important points of selection effects that has to be taken into account in future analysis. Analysis chain is composed by: a simulation of observed millimeter sky, state-of-the-art algorithms of SZ galaxy clusters extraction from observed maps, a statistical model of selection effects of the whole detection chain and, finally, tools to constrain, from detected SZ sources catalog, the cosmological parameters. I focus myself on multi-channel experiments equipped with large bolometer camera. I use these tools for a prospecting on Olimpo experiment. (author) [fr

  20. MSAProbs-MPI: parallel multiple sequence aligner for distributed-memory systems.

    Science.gov (United States)

    González-Domínguez, Jorge; Liu, Yongchao; Touriño, Juan; Schmidt, Bertil

    2016-12-15

    MSAProbs is a state-of-the-art protein multiple sequence alignment tool based on hidden Markov models. It can achieve high alignment accuracy at the expense of relatively long runtimes for large-scale input datasets. In this work we present MSAProbs-MPI, a distributed-memory parallel version of the multithreaded MSAProbs tool that is able to reduce runtimes by exploiting the compute capabilities of common multicore CPU clusters. Our performance evaluation on a cluster with 32 nodes (each containing two Intel Haswell processors) shows reductions in execution time of over one order of magnitude for typical input datasets. Furthermore, MSAProbs-MPI using eight nodes is faster than the GPU-accelerated QuickProbs running on a Tesla K20. Another strong point is that MSAProbs-MPI can deal with large datasets for which MSAProbs and QuickProbs might fail due to time and memory constraints, respectively. Source code in C ++ and MPI running on Linux systems as well as a reference manual are available at http://msaprobs.sourceforge.net CONTACT: jgonzalezd@udc.esSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Brightest Cluster Galaxies in REXCESS Clusters

    Science.gov (United States)

    Haarsma, Deborah B.; Leisman, L.; Bruch, S.; Donahue, M.

    2009-01-01

    Most galaxy clusters contain a Brightest Cluster Galaxy (BCG) which is larger than the other cluster ellipticals and has a more extended profile. In the hierarchical model, the BCG forms through many galaxy mergers in the crowded center of the cluster, and thus its properties give insight into the assembly of the cluster as a whole. In this project, we are working with the Representative XMM-Newton Cluster Structure Survey (REXCESS) team (Boehringer et al 2007) to study BCGs in 33 X-ray luminous galaxy clusters, 0.055 < z < 0.183. We are imaging the BCGs in R band at the Southern Observatory for Astrophysical Research (SOAR) in Chile. In this poster, we discuss our methods and give preliminary measurements of the BCG magnitudes, morphology, and stellar mass. We compare these BCG properties with the properties of their host clusters, particularly of the X-ray emitting gas.

  2. Methodological Foundations of Clustering and Innovativeness for Establishing the Competitive Production of Biofuels

    Directory of Open Access Journals (Sweden)

    Klymchuk Oleksandr V.

    2016-05-01

    Full Text Available The article is aimed to study the worldwide trends in development of innovative processes and creation of cluster structures for elaborating methodological foundations for establishing the competitive production of biofuels. The article highlights the cluster approaches in conducting the global commercial activities that create effective mechanisms and tools to encourage innovation-investment regional development and can be characterized by their relevance for the Ukrainian economy. Emphasis is made on the matter that clustering is one of the key tools for structuring the energy market, integrated exploiting the potential of bioenergy industry sector, management of the economic policies of redistribution of value added, implementation of the growth of investment attractiveness of the biofuel industry in our country. It has been concluded that cluster development in the biofuel production will stimulate specialization and cooperation processes in the agro-industrial economy sector, bringing together related businesses in the direction of an effective interaction, thereby ensuring a high level of competitiveness of biofuels in both the national and the international markets.

  3. Improved optical mass tracer for galaxy clusters calibrated using weak lensing measurements

    Science.gov (United States)

    Reyes, R.; Mandelbaum, R.; Hirata, C.; Bahcall, N.; Seljak, U.

    2008-11-01

    We develop an improved mass tracer for clusters of galaxies from optically observed parameters, and calibrate the mass relation using weak gravitational lensing measurements. We employ a sample of ~13000 optically selected clusters from the Sloan Digital Sky Survey (SDSS) maxBCG catalogue, with photometric redshifts in the range 0.1-0.3. The optical tracers we consider are cluster richness, cluster luminosity, luminosity of the brightest cluster galaxy (BCG) and combinations of these parameters. We measure the weak lensing signal around stacked clusters as a function of the various tracers, and use it to determine the tracer with the least amount of scatter. We further use the weak lensing data to calibrate the mass normalization. We find that the best mass estimator for massive clusters is a combination of cluster richness, N200, and the luminosity of the BCG, LBCG: , where is the observed mean BCG luminosity at a given richness. This improved mass tracer will enable the use of galaxy clusters as a more powerful tool for constraining cosmological parameters.

  4. Delineation of gravel-bed clusters via factorial kriging

    Science.gov (United States)

    Wu, Fu-Chun; Wang, Chi-Kuei; Huang, Guo-Hao

    2018-05-01

    Gravel-bed clusters are the most prevalent microforms that affect local flows and sediment transport. A growing consensus is that the practice of cluster delineation should be based primarily on bed topography rather than grain sizes. Here we present a novel approach for cluster delineation using patch-scale high-resolution digital elevation models (DEMs). We use a geostatistical interpolation method, i.e., factorial kriging, to decompose the short- and long-range (grain- and microform-scale) DEMs. The required parameters are determined directly from the scales of the nested variograms. The short-range DEM exhibits a flat bed topography, yet individual grains are sharply outlined, making the short-range DEM a useful aid for grain segmentation. The long-range DEM exhibits a smoother topography than the original full DEM, yet groupings of particles emerge as small-scale bedforms, making the contour percentile levels of the long-range DEM a useful tool for cluster identification. Individual clusters are delineated using the segmented grains and identified clusters via a range of contour percentile levels. Our results reveal that the density and total area of delineated clusters decrease with increasing contour percentile level, while the mean grain size of clusters and average size of anchor clast (i.e., the largest particle in a cluster) increase with the contour percentile level. These results support the interpretation that larger particles group as clusters and protrude higher above the bed than other smaller grains. A striking feature of the delineated clusters is that anchor clasts are invariably greater than the D90 of the grain sizes even though a threshold anchor size was not adopted herein. The average areal fractal dimensions (Hausdorff-Besicovich dimensions of the projected areas) of individual clusters, however, demonstrate that clusters delineated with different contour percentile levels exhibit similar planform morphologies. Comparisons with a

  5. Parallel definition of tear film maps on distributed-memory clusters for the support of dry eye diagnosis.

    Science.gov (United States)

    González-Domínguez, Jorge; Remeseiro, Beatriz; Martín, María J

    2017-02-01

    The analysis of the interference patterns on the tear film lipid layer is a useful clinical test to diagnose dry eye syndrome. This task can be automated with a high degree of accuracy by means of the use of tear film maps. However, the time required by the existing applications to generate them prevents a wider acceptance of this method by medical experts. Multithreading has been previously successfully employed by the authors to accelerate the tear film map definition on multicore single-node machines. In this work, we propose a hybrid message-passing and multithreading parallel approach that further accelerates the generation of tear film maps by exploiting the computational capabilities of distributed-memory systems such as multicore clusters and supercomputers. The algorithm for drawing tear film maps is parallelized using Message Passing Interface (MPI) for inter-node communications and the multithreading support available in the C++11 standard for intra-node parallelization. The original algorithm is modified to reduce the communications and increase the scalability. The hybrid method has been tested on 32 nodes of an Intel cluster (with two 12-core Haswell 2680v3 processors per node) using 50 representative images. Results show that maximum runtime is reduced from almost two minutes using the previous only-multithreaded approach to less than ten seconds using the hybrid method. The hybrid MPI/multithreaded implementation can be used by medical experts to obtain tear film maps in only a few seconds, which will significantly accelerate and facilitate the diagnosis of the dry eye syndrome. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  6. Potential Solution of a Hardware-Software System V-Cluster for Big Data Analysis

    Science.gov (United States)

    Morra, G.; Tufo, H.; Yuen, D. A.; Brown, J.; Zihao, S.

    2017-12-01

    Today it cannot be denied that the Big Data revolution is taking place and is replacing HPC and numerical simulation as the main driver in society. Outside the immediate scientific arena, the Big Data market encompass much more than the AGU. There are many sectors in society that Big Data can ably serve, such as governments finances, hospitals, tourism, and, last by not least, scientific and engineering problems. In many countries, education has not kept pace with the demands from students outside computer science to get into Big Data science. Ultimate Vision (UV) in Beijing attempts to address this need in China by focusing part of our energy on education and training outside the immediate university environment. UV plans a strategy to maximize profits in our beginning. Therefore, we will focus on growing markets such as provincial governments, medical sectors, mass media, and education. And will not address issues such as performance for scientific collaboration, such as seismic networks, where the market share and profits are small by comparison. We have developed a software-hardware system, called V-Cluster, built with the latest NVIDIA GPUs and Intel CPUs with ample amounts of RAM (over couple of Tbytes) and local storage. We have put in an internal network with high bandwidth (over 100 Gbits/sec) and each node of V-Cluster can run at around 40 Tflops. Our system can scale linearly with the number of codes. Our main strength in data analytics is the use of graph-computing paradigm for optimizing the transfer rate in collaborative efforts. We focus in training and education with our clients in order to gain experience in learning about new applications. We will present the philosophy of this second generation of our Data Analytic system, whose costs fall far below those offered elsewhere.

  7. Metal cluster compounds - chemistry and importance; clusters containing isolated main group element atoms, large metal cluster compounds, cluster fluxionality

    International Nuclear Information System (INIS)

    Walther, B.

    1988-01-01

    This part of the review on metal cluster compounds deals with clusters containing isolated main group element atoms, with high nuclearity clusters and metal cluster fluxionality. It will be obvious that main group element atoms strongly influence the geometry, stability and reactivity of the clusters. High nuclearity clusters are of interest in there own due to the diversity of the structures adopted, but their intermediate position between molecules and the metallic state makes them a fascinating research object too. These both sites of the metal cluster chemistry as well as the frequently observed ligand and core fluxionality are related to the cluster metal and surface analogy. (author)

  8. CLUSTER ANALYSIS UKRAINIAN REGIONAL DISTRIBUTION BY LEVEL OF INNOVATION

    Directory of Open Access Journals (Sweden)

    Roman Shchur

    2016-07-01

    Full Text Available   SWOT-analysis of the threats and benefits of innovation development strategy of Ivano-Frankivsk region in the context of financial support was сonducted. Methodical approach to determine of public-private partnerships potential that is tool of innovative economic development financing was identified. Cluster analysis of possibilities of forming public-private partnership in a particular region was carried out. Optimal set of problem areas that require urgent solutions and financial security is defined on the basis of cluster approach. It will help to form practical recommendations for the formation of an effective financial mechanism in the regions of Ukraine. Key words: the mechanism of innovation development financial provision, innovation development, public-private partnerships, cluster analysis, innovative development strategy.

  9. Galaxy CloudMan: delivering cloud compute clusters.

    Science.gov (United States)

    Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

    2010-12-21

    Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.

  10. PREFACE: Nuclear Cluster Conference; Cluster'07

    Science.gov (United States)

    Freer, Martin

    2008-05-01

    The Cluster Conference is a long-running conference series dating back to the 1960's, the first being initiated by Wildermuth in Bochum, Germany, in 1969. The most recent meeting was held in Nara, Japan, in 2003, and in 2007 the 9th Cluster Conference was held in Stratford-upon-Avon, UK. As the name suggests the town of Stratford lies upon the River Avon, and shortly before the conference, due to unprecedented rainfall in the area (approximately 10 cm within half a day), lay in the River Avon! Stratford is the birthplace of the `Bard of Avon' William Shakespeare, and this formed an intriguing conference backdrop. The meeting was attended by some 90 delegates and the programme contained 65 70 oral presentations, and was opened by a historical perspective presented by Professor Brink (Oxford) and closed by Professor Horiuchi (RCNP) with an overview of the conference and future perspectives. In between, the conference covered aspects of clustering in exotic nuclei (both neutron and proton-rich), molecular structures in which valence neutrons are exchanged between cluster cores, condensates in nuclei, neutron-clusters, superheavy nuclei, clusters in nuclear astrophysical processes and exotic cluster decays such as 2p and ternary cluster decay. The field of nuclear clustering has become strongly influenced by the physics of radioactive beam facilities (reflected in the programme), and by the excitement that clustering may have an important impact on the structure of nuclei at the neutron drip-line. It was clear that since Nara the field had progressed substantially and that new themes had emerged and others had crystallized. Two particular topics resonated strongly condensates and nuclear molecules. These topics are thus likely to be central in the next cluster conference which will be held in 2011 in the Hungarian city of Debrechen. Martin Freer Participants and Cluster'07

  11. The k-means clustering technique: General considerations and implementation in Mathematica

    Directory of Open Access Journals (Sweden)

    Laurence Morissette

    2013-02-01

    Full Text Available Data clustering techniques are valuable tools for researchers working with large databases of multivariate data. In this tutorial, we present a simple yet powerful one: the k-means clustering technique, through three different algorithms: the Forgy/Lloyd, algorithm, the MacQueen algorithm and the Hartigan and Wong algorithm. We then present an implementation in Mathematica and various examples of the different options available to illustrate the application of the technique.

  12. An improved K-means clustering method for cDNA microarray image segmentation.

    Science.gov (United States)

    Wang, T N; Li, T J; Shao, G F; Wu, S X

    2015-07-14

    Microarray technology is a powerful tool for human genetic research and other biomedical applications. Numerous improvements to the standard K-means algorithm have been carried out to complete the image segmentation step. However, most of the previous studies classify the image into two clusters. In this paper, we propose a novel K-means algorithm, which first classifies the image into three clusters, and then one of the three clusters is divided as the background region and the other two clusters, as the foreground region. The proposed method was evaluated on six different data sets. The analyses of accuracy, efficiency, expression values, special gene spots, and noise images demonstrate the effectiveness of our method in improving the segmentation quality.

  13. Radiation-Induced Chemical Dynamics in Ar Clusters Exposed to Strong X-Ray Pulses

    Science.gov (United States)

    Kumagai, Yoshiaki; Jurek, Zoltan; Xu, Weiqing; Fukuzawa, Hironobu; Motomura, Koji; Iablonskyi, Denys; Nagaya, Kiyonobu; Wada, Shin-ichi; Mondal, Subhendu; Tachibana, Tetsuya; Ito, Yuta; Sakai, Tsukasa; Matsunami, Kenji; Nishiyama, Toshiyuki; Umemoto, Takayuki; Nicolas, Christophe; Miron, Catalin; Togashi, Tadashi; Ogawa, Kanade; Owada, Shigeki; Tono, Kensuke; Yabashi, Makina; Son, Sang-Kil; Ziaja, Beata; Santra, Robin; Ueda, Kiyoshi

    2018-06-01

    We show that electron and ion spectroscopy reveals the details of the oligomer formation in Ar clusters exposed to an x-ray free electron laser (XFEL) pulse, i.e., chemical dynamics triggered by x rays. With guidance from a dedicated molecular dynamics simulation tool, we find that van der Waals bonding, the oligomer formation mechanism, and charge transfer among the cluster constituents significantly affect ionization dynamics induced by an XFEL pulse of moderate fluence. Our results clearly demonstrate that XFEL pulses can be used not only to "damage and destroy" molecular assemblies but also to modify and transform their molecular structure. The accuracy of the predictions obtained makes it possible to apply the cluster spectroscopy, in connection with the respective simulations, for estimation of the XFEL pulse fluence in the fluence regime below single-atom multiple-photon absorption, which is hardly accessible with other diagnostic tools.

  14. Appropriate tools and methods for tropical microepidemiology: a ...

    African Journals Online (AJOL)

    Appropriate tools and methods for tropical microepidemiology: a case-study of malaria clustering in Ethiopia. Tedros A Ghebreyesus, Peter Byass, Karen H Witten, Asfaw Getachew, Mitiku Haile, Mekonnen Yohannes, Steven W Lindsay ...

  15. Homological methods, representation theory, and cluster algebras

    CERN Document Server

    Trepode, Sonia

    2018-01-01

    This text presents six mini-courses, all devoted to interactions between representation theory of algebras, homological algebra, and the new ever-expanding theory of cluster algebras. The interplay between the topics discussed in this text will continue to grow and this collection of courses stands as a partial testimony to this new development. The courses are useful for any mathematician who would like to learn more about this rapidly developing field; the primary aim is to engage graduate students and young researchers. Prerequisites include knowledge of some noncommutative algebra or homological algebra. Homological algebra has always been considered as one of the main tools in the study of finite-dimensional algebras. The strong relationship with cluster algebras is more recent and has quickly established itself as one of the important highlights of today’s mathematical landscape. This connection has been fruitful to both areas—representation theory provides a categorification of cluster algebras, wh...

  16. Formation of stable products from cluster-cluster collisions

    International Nuclear Information System (INIS)

    Alamanova, Denitsa; Grigoryan, Valeri G; Springborg, Michael

    2007-01-01

    The formation of stable products from copper cluster-cluster collisions is investigated by using classical molecular-dynamics simulations in combination with an embedded-atom potential. The dependence of the product clusters on impact energy, relative orientation of the clusters, and size of the clusters is studied. The structures and total energies of the product clusters are analysed and compared with those of the colliding clusters before impact. These results, together with the internal temperature, are used in obtaining an increased understanding of cluster fusion processes

  17. Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

    Science.gov (United States)

    Youroukova, Vania M; Dimitrova, Denitsa G; Valerieva, Anna D; Lesichkova, Spaska S; Velikova, Tsvetelina V; Ivanova-Todorova, Ekaterina I; Tumangelova-Yuzeir, Kalina D

    2017-06-01

    Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.

  18. Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

    Directory of Open Access Journals (Sweden)

    Lauren Hund

    Full Text Available Lot quality assurance sampling (LQAS surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

  19. Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

    Science.gov (United States)

    Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

    2015-01-01

    Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

  20. DIMM-SC: a Dirichlet mixture model for clustering droplet-based single cell transcriptomic data.

    Science.gov (United States)

    Sun, Zhe; Wang, Ting; Deng, Ke; Wang, Xiao-Feng; Lafyatis, Robert; Ding, Ying; Hu, Ming; Chen, Wei

    2018-01-01

    Single cell transcriptome sequencing (scRNA-Seq) has become a revolutionary tool to study cellular and molecular processes at single cell resolution. Among existing technologies, the recently developed droplet-based platform enables efficient parallel processing of thousands of single cells with direct counting of transcript copies using Unique Molecular Identifier (UMI). Despite the technology advances, statistical methods and computational tools are still lacking for analyzing droplet-based scRNA-Seq data. Particularly, model-based approaches for clustering large-scale single cell transcriptomic data are still under-explored. We developed DIMM-SC, a Dirichlet Mixture Model for clustering droplet-based Single Cell transcriptomic data. This approach explicitly models UMI count data from scRNA-Seq experiments and characterizes variations across different cell clusters via a Dirichlet mixture prior. We performed comprehensive simulations to evaluate DIMM-SC and compared it with existing clustering methods such as K-means, CellTree and Seurat. In addition, we analyzed public scRNA-Seq datasets with known cluster labels and in-house scRNA-Seq datasets from a study of systemic sclerosis with prior biological knowledge to benchmark and validate DIMM-SC. Both simulation studies and real data applications demonstrated that overall, DIMM-SC achieves substantially improved clustering accuracy and much lower clustering variability compared to other existing clustering methods. More importantly, as a model-based approach, DIMM-SC is able to quantify the clustering uncertainty for each single cell, facilitating rigorous statistical inference and biological interpretations, which are typically unavailable from existing clustering methods. DIMM-SC has been implemented in a user-friendly R package with a detailed tutorial available on www.pitt.edu/∼wec47/singlecell.html. wei.chen@chp.edu or hum@ccf.org. Supplementary data are available at Bioinformatics online. © The Author

  1. Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture

    Science.gov (United States)

    Sanfilippo, Antonio [Richland, WA; Calapristi, Augustin J [West Richland, WA; Crow, Vernon L [Richland, WA; Hetzler, Elizabeth G [Kennewick, WA; Turner, Alan E [Kennewick, WA

    2009-12-22

    Document clustering methods, document cluster label disambiguation methods, document clustering apparatuses, and articles of manufacture are described. In one aspect, a document clustering method includes providing a document set comprising a plurality of documents, providing a cluster comprising a subset of the documents of the document set, using a plurality of terms of the documents, providing a cluster label indicative of subject matter content of the documents of the cluster, wherein the cluster label comprises a plurality of word senses, and selecting one of the word senses of the cluster label.

  2. Benchmarking and tuning the MILC code on clusters and supercomputers

    International Nuclear Information System (INIS)

    Gottlieb, Steven

    2002-01-01

    Recently, we have benchmarked and tuned the MILC code on a number of architectures including Intel Itanium and Pentium IV (PIV), dual-CPU Athlon, and the latest Compaq Alpha nodes. Results will be presented for many of these, and we shall discuss some simple code changes that can result in a very dramatic speedup of the KS conjugate gradient on processors with more advanced memory systems such as PIV, IBM SP and Alpha

  3. Benchmarking and tuning the MILC code on clusters and supercomputers

    International Nuclear Information System (INIS)

    Steven A. Gottlieb

    2001-01-01

    Recently, we have benchmarked and tuned the MILC code on a number of architectures including Intel Itanium and Pentium IV (PIV), dual-CPU Athlon, and the latest Compaq Alpha nodes. Results will be presented for many of these, and we shall discuss some simple code changes that can result in a very dramatic speedup of the KS conjugate gradient on processors with more advanced memory systems such as PIV, IBM SP and Alpha

  4. Benchmarking and tuning the MILC code on clusters and supercomputers

    Science.gov (United States)

    Gottlieb, Steven

    2002-03-01

    Recently, we have benchmarked and tuned the MILC code on a number of architectures including Intel Itanium and Pentium IV (PIV), dual-CPU Athlon, and the latest Compaq Alpha nodes. Results will be presented for many of these, and we shall discuss some simple code changes that can result in a very dramatic speedup of the KS conjugate gradient on processors with more advanced memory systems such as PIV, IBM SP and Alpha.

  5. Fragmentation of percolation cluster perimeters

    Science.gov (United States)

    Debierre, Jean-Marc; Bradley, R. Mark

    1996-05-01

    We introduce a model for the fragmentation of porous random solids under the action of an external agent. In our model, the solid is represented by a bond percolation cluster on the square lattice and bonds are removed only at the external perimeter (or `hull') of the cluster. This model is shown to be related to the self-avoiding walk on the Manhattan lattice and to the disconnection events at a diffusion front. These correspondences are used to predict the leading and the first correction-to-scaling exponents for several quantities defined for hull fragmentation. Our numerical results support these predictions. In addition, the algorithm used to construct the perimeters reveals itself to be a very efficient tool for detecting subtle correlations in the pseudo-random number generator used. We present a quantitative test of two generators which supports recent results reported in more systematic studies.

  6. Nuclear clustering - a cluster core model study

    International Nuclear Information System (INIS)

    Paul Selvi, G.; Nandhini, N.; Balasubramaniam, M.

    2015-01-01

    Nuclear clustering, similar to other clustering phenomenon in nature is a much warranted study, since it would help us in understanding the nature of binding of the nucleons inside the nucleus, closed shell behaviour when the system is highly deformed, dynamics and structure at extremes. Several models account for the clustering phenomenon of nuclei. We present in this work, a cluster core model study of nuclear clustering in light mass nuclei

  7. Jets from jets: re-clustering as a tool for large radius jet reconstruction and grooming at the LHC

    Science.gov (United States)

    Nachman, Benjamin; Nef, Pascal; Schwartzman, Ariel; Swiatlowski, Maximilian; Wanotayaroj, Chaowaroj

    2015-02-01

    Jets with a large radius R ≳ 1 and grooming algorithms are widely used to fully capture the decay products of boosted heavy particles at the Large Hadron Collider (LHC). Unlike most discriminating variables used in such studies, the jet radius is usually not optimized for specific physics scenarios. This is because every jet configuration must be calibrated, insitu, to account for detector response and other experimental effects. One solution to enhance the availability of large- R jet configurations used by the LHC experiments is jet re-clustering. Jet re-clustering introduces an intermediate scale r groomed jets. Jet re-clustering has the benefit that no additional large-R calibration is necessary, allowing the re-clustered large radius parameter to be optimized in the context of specific precision measurements or searches for new physics.

  8. A Clustering-Based Automatic Transfer Function Design for Volume Visualization

    Directory of Open Access Journals (Sweden)

    Tianjin Zhang

    2016-01-01

    Full Text Available The two-dimensional transfer functions (TFs designed based on intensity-gradient magnitude (IGM histogram are effective tools for the visualization and exploration of 3D volume data. However, traditional design methods usually depend on multiple times of trial-and-error. We propose a novel method for the automatic generation of transfer functions by performing the affinity propagation (AP clustering algorithm on the IGM histogram. Compared with previous clustering algorithms that were employed in volume visualization, the AP clustering algorithm has much faster convergence speed and can achieve more accurate clustering results. In order to obtain meaningful clustering results, we introduce two similarity measurements: IGM similarity and spatial similarity. These two similarity measurements can effectively bring the voxels of the same tissue together and differentiate the voxels of different tissues so that the generated TFs can assign different optical properties to different tissues. Before performing the clustering algorithm on the IGM histogram, we propose to remove noisy voxels based on the spatial information of voxels. Our method does not require users to input the number of clusters, and the classification and visualization process is automatic and efficient. Experiments on various datasets demonstrate the effectiveness of the proposed method.

  9. Using cluster analysis to organize and explore regional GPS velocities

    Science.gov (United States)

    Simpson, Robert W.; Thatcher, Wayne; Savage, James C.

    2012-01-01

    Cluster analysis offers a simple visual exploratory tool for the initial investigation of regional Global Positioning System (GPS) velocity observations, which are providing increasingly precise mappings of actively deforming continental lithosphere. The deformation fields from dense regional GPS networks can often be concisely described in terms of relatively coherent blocks bounded by active faults, although the choice of blocks, their number and size, can be subjective and is often guided by the distribution of known faults. To illustrate our method, we apply cluster analysis to GPS velocities from the San Francisco Bay Region, California, to search for spatially coherent patterns of deformation, including evidence of block-like behavior. The clustering process identifies four robust groupings of velocities that we identify with four crustal blocks. Although the analysis uses no prior geologic information other than the GPS velocities, the cluster/block boundaries track three major faults, both locked and creeping.

  10. Cluster mislocation in kinematic Sunyaev-Zel'dovich effect extraction

    Science.gov (United States)

    Calafut, Victoria; Bean, Rachel; Yu, Byeonghee

    2017-12-01

    We investigate the impact of a variety of analysis assumptions that influence cluster identification and location on the kinematic Sunyaev-Zel'dovich (kSZ) pairwise momentum signal and covariance estimation. Photometric and spectroscopic galaxy tracers from SDSS, WISE, and DECaLs, spanning redshifts 0.05 surveys the statistical and photometric errors will shrink markedly. Our results demonstrate that uncertainties introduced through using galaxy proxies for cluster locations will need to be fully incorporated, and actively mitigated, for the kSZ to reach its full potential as a cosmological constraining tool for dark energy and neutrino physics.

  11. High-Performance Data Analysis Tools for Sun-Earth Connection Missions

    Science.gov (United States)

    Messmer, Peter

    2011-01-01

    The data analysis tool of choice for many Sun-Earth Connection missions is the Interactive Data Language (IDL) by ITT VIS. The increasing amount of data produced by these missions and the increasing complexity of image processing algorithms requires access to higher computing power. Parallel computing is a cost-effective way to increase the speed of computation, but algorithms oftentimes have to be modified to take advantage of parallel systems. Enhancing IDL to work on clusters gives scientists access to increased performance in a familiar programming environment. The goal of this project was to enable IDL applications to benefit from both computing clusters as well as graphics processing units (GPUs) for accelerating data analysis tasks. The tool suite developed in this project enables scientists now to solve demanding data analysis problems in IDL that previously required specialized software, and it allows them to be solved orders of magnitude faster than on conventional PCs. The tool suite consists of three components: (1) TaskDL, a software tool that simplifies the creation and management of task farms, collections of tasks that can be processed independently and require only small amounts of data communication; (2) mpiDL, a tool that allows IDL developers to use the Message Passing Interface (MPI) inside IDL for problems that require large amounts of data to be exchanged among multiple processors; and (3) GPULib, a tool that simplifies the use of GPUs as mathematical coprocessors from within IDL. mpiDL is unique in its support for the full MPI standard and its support of a broad range of MPI implementations. GPULib is unique in enabling users to take advantage of an inexpensive piece of hardware, possibly already installed in their computer, and achieve orders of magnitude faster execution time for numerically complex algorithms. TaskDL enables the simple setup and management of task farms on compute clusters. The products developed in this project have the

  12. Exploring Undergraduates' Understanding of Photosynthesis Using Diagnostic Question Clusters

    Science.gov (United States)

    Parker, Joyce M.; Anderson, Charles W.; Heidemann, Merle; Merrill, John; Merritt, Brett; Richmond, Gail; Urban-Lurain, Mark

    2012-01-01

    We present a diagnostic question cluster (DQC) that assesses undergraduates' thinking about photosynthesis. This assessment tool is not designed to identify individual misconceptions. Rather, it is focused on students' abilities to apply basic concepts about photosynthesis by reasoning with a coordinated set of practices based on a few scientific…

  13. Clustering Trajectories by Relevant Parts for Air Traffic Analysis.

    Science.gov (United States)

    Andrienko, Gennady; Andrienko, Natalia; Fuchs, Georg; Garcia, Jose Manuel Cordero

    2018-01-01

    Clustering of trajectories of moving objects by similarity is an important technique in movement analysis. Existing distance functions assess the similarity between trajectories based on properties of the trajectory points or segments. The properties may include the spatial positions, times, and thematic attributes. There may be a need to focus the analysis on certain parts of trajectories, i.e., points and segments that have particular properties. According to the analysis focus, the analyst may need to cluster trajectories by similarity of their relevant parts only. Throughout the analysis process, the focus may change, and different parts of trajectories may become relevant. We propose an analytical workflow in which interactive filtering tools are used to attach relevance flags to elements of trajectories, clustering is done using a distance function that ignores irrelevant elements, and the resulting clusters are summarized for further analysis. We demonstrate how this workflow can be useful for different analysis tasks in three case studies with real data from the domain of air traffic. We propose a suite of generic techniques and visualization guidelines to support movement data analysis by means of relevance-aware trajectory clustering.

  14. Characteristics of multiprocessing MCNP5 on small personal computer clusters

    International Nuclear Information System (INIS)

    Robinson, S M; Mc Conn, R J Jr; Pagh, R T; Schweppe, J E; Siciliano, E R

    2006-01-01

    The feasibility and efficiency of performing MCNP5 calculations with a small, heterogeneous computing cluster built from Microsoft ( R) Windows TM personal computers (PC) are explored. The performance increases that may be expected with such clusters are estimated for cases that typify general radiation-shielding calculations. Our results show that the speed increase from additional slave PCs is nearly linear up to 10 processors. Guidance is given as to the specific advantages of changing various parameters present in the system. Implementing load balancing, and reducing the overhead from the MCNP rendezvous mechanism add to heterogeneous cluster efficiency. Hyper-threading technology and matching the total number of slave processes to the total number of logical processors also yield modest speed increases in the range below 7 processors. Because of the ease of acquisition of heterogeneous desktop computers, and the peak in efficiency at the level of a few physical processors, a strong case is made for the use of small clusters as a tool for producing MCNP5 calculations rapidly, and detailed instructions for constructing such clusters are provided

  15. Computer-Based Driving in Dementia Decision Tool With Mail Support: Cluster Randomized Controlled Trial.

    Science.gov (United States)

    Rapoport, Mark J; Zucchero Sarracini, Carla; Kiss, Alex; Lee, Linda; Byszewski, Anna; Seitz, Dallas P; Vrkljan, Brenda; Molnar, Frank; Herrmann, Nathan; Tang-Wai, David F; Frank, Christopher; Henry, Blair; Pimlott, Nicholas; Masellis, Mario; Naglie, Gary

    2018-05-25

    Physicians often find significant challenges in assessing automobile driving in persons with mild cognitive impairment and mild dementia and deciding when to report to transportation administrators. Care must be taken to balance the safety of patients and other road users with potential negative effects of issuing such reports. The aim of this study was to assess whether a computer-based Driving in Dementia Decision Tool (DD-DT) increased appropriate reporting of patients with mild dementia or mild cognitive impairment to transportation administrators. The study used a parallel-group cluster nonblinded randomized controlled trial design to test a multifaceted knowledge translation intervention. The intervention included a computer-based decision support system activated by the physician-user, which provides a recommendation about whether to report patients with mild dementia or mild cognitive impairment to transportation administrators, based on an algorithm derived from earlier work. The intervention also included a mailed educational package and Web-based specialized reporting forms. Specialists and family physicians with expertise in dementia or care of the elderly were stratified by sex and randomized to either use the DD-DT or a control version of the tool that required identical data input as the intervention group, but instead generated a generic reminder about the reporting legislation in Ontario, Canada. The trial ran from September 9, 2014 to January 29, 2016, and the primary outcome was the number of reports made to the transportation administrators concordant with the algorithm. A total of 69 participating physicians were randomized, and 36 of these used the DD-DT; 20 of the 35 randomized to the intervention group used DD-DT with 114 patients, and 16 of the 34 randomized to the control group used it with 103 patients. The proportion of all assessed patients reported to the transportation administrators concordant with recommendation did not differ

  16. Performance Analysis of Unsupervised Clustering Methods for Brain Tumor Segmentation

    Directory of Open Access Journals (Sweden)

    Tushar H Jaware

    2013-10-01

    Full Text Available Medical image processing is the most challenging and emerging field of neuroscience. The ultimate goal of medical image analysis in brain MRI is to extract important clinical features that would improve methods of diagnosis & treatment of disease. This paper focuses on methods to detect & extract brain tumour from brain MR images. MATLAB is used to design, software tool for locating brain tumor, based on unsupervised clustering methods. K-Means clustering algorithm is implemented & tested on data base of 30 images. Performance evolution of unsupervised clusteringmethods is presented.

  17. Comprehensive cluster analysis with Transitivity Clustering.

    Science.gov (United States)

    Wittkop, Tobias; Emig, Dorothea; Truss, Anke; Albrecht, Mario; Böcker, Sebastian; Baumbach, Jan

    2011-03-01

    Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins. In this paper, we describe three major workflows: (i) protein (super)family detection with Cytoscape, (ii) protein homology detection with incomplete gold standards and (iii) clustering of gene expression data. This protocol guides the user through the most important features of Transitivity Clustering and takes ∼1 h to complete.

  18. Centroid based clustering of high throughput sequencing reads based on n-mer counts.

    Science.gov (United States)

    Solovyov, Alexander; Lipkin, W Ian

    2013-09-08

    Many problems in computational biology require alignment-free sequence comparisons. One of the common tasks involving sequence comparison is sequence clustering. Here we apply methods of alignment-free comparison (in particular, comparison using sequence composition) to the challenge of sequence clustering. We study several centroid based algorithms for clustering sequences based on word counts. Study of their performance shows that using k-means algorithm with or without the data whitening is efficient from the computational point of view. A higher clustering accuracy can be achieved using the soft expectation maximization method, whereby each sequence is attributed to each cluster with a specific probability. We implement an open source tool for alignment-free clustering. It is publicly available from github: https://github.com/luscinius/afcluster. We show the utility of alignment-free sequence clustering for high throughput sequencing analysis despite its limitations. In particular, it allows one to perform assembly with reduced resources and a minimal loss of quality. The major factor affecting performance of alignment-free read clustering is the length of the read.

  19. Cluster-cluster correlations and constraints on the correlation hierarchy

    Science.gov (United States)

    Hamilton, A. J. S.; Gott, J. R., III

    1988-01-01

    The hypothesis that galaxies cluster around clusters at least as strongly as they cluster around galaxies imposes constraints on the hierarchy of correlation amplitudes in hierachical clustering models. The distributions which saturate these constraints are the Rayleigh-Levy random walk fractals proposed by Mandelbrot; for these fractal distributions cluster-cluster correlations are all identically equal to galaxy-galaxy correlations. If correlation amplitudes exceed the constraints, as is observed, then cluster-cluster correlations must exceed galaxy-galaxy correlations, as is observed.

  20. CONSTRAINING CLUSTER PHYSICS WITH THE SHAPE OF X-RAY CLUSTERS: COMPARISON OF LOCAL X-RAY CLUSTERS VERSUS ΛCDM CLUSTERS

    International Nuclear Information System (INIS)

    Lau, Erwin T.; Nagai, Daisuke; Kravtsov, Andrey V.; Vikhlinin, Alexey; Zentner, Andrew R.

    2012-01-01

    Recent simulations of cluster formation have demonstrated that condensation of baryons into central galaxies during cluster formation can drive the shape of the gas distribution in galaxy clusters significantly rounder out to their virial radius. These simulations generally predict stellar fractions within cluster virial radii that are ∼2-3 times larger than the stellar masses deduced from observations. In this paper, we compare ellipticity profiles of simulated clusters performed with varying input physics (radiative cooling, star formation, and supernova feedback) to the cluster ellipticity profiles derived from Chandra and ROSAT observations, in an effort to constrain the fraction of gas that cools and condenses into the central galaxies within clusters. We find that local relaxed clusters have an average ellipticity of ε = 0.18 ± 0.05 in the radial range of 0.04 ≤ r/r 500 ≤ 1. At larger radii r > 0.1r 500 , the observed ellipticity profiles agree well with the predictions of non-radiative simulations. In contrast, the ellipticity profiles of simulated clusters that include dissipative gas physics deviate significantly from the observed ellipticity profiles at all radii. The dissipative simulations overpredict (underpredict) ellipticity in the inner (outer) regions of galaxy clusters. By comparing simulations with and without dissipative gas physics, we show that gas cooling causes the gas distribution to be more oblate in the central regions, but makes the outer gas distribution more spherical. We find that late-time gas cooling and star formation are responsible for the significantly oblate gas distributions in cluster cores, but the gas shapes outside of cluster cores are set primarily by baryon dissipation at high redshift (z ≥ 2). Our results indicate that the shapes of X-ray emitting gas in galaxy clusters, especially at large radii, can be used to place constraints on cluster gas physics, making it potential probes of the history of baryonic

  1. Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

    Science.gov (United States)

    Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

    2018-01-01

    Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

  2. Convex Clustering: An Attractive Alternative to Hierarchical Clustering

    Science.gov (United States)

    Chen, Gary K.; Chi, Eric C.; Ranola, John Michael O.; Lange, Kenneth

    2015-01-01

    The primary goal in cluster analysis is to discover natural groupings of objects. The field of cluster analysis is crowded with diverse methods that make special assumptions about data and address different scientific aims. Despite its shortcomings in accuracy, hierarchical clustering is the dominant clustering method in bioinformatics. Biologists find the trees constructed by hierarchical clustering visually appealing and in tune with their evolutionary perspective. Hierarchical clustering operates on multiple scales simultaneously. This is essential, for instance, in transcriptome data, where one may be interested in making qualitative inferences about how lower-order relationships like gene modules lead to higher-order relationships like pathways or biological processes. The recently developed method of convex clustering preserves the visual appeal of hierarchical clustering while ameliorating its propensity to make false inferences in the presence of outliers and noise. The solution paths generated by convex clustering reveal relationships between clusters that are hidden by static methods such as k-means clustering. The current paper derives and tests a novel proximal distance algorithm for minimizing the objective function of convex clustering. The algorithm separates parameters, accommodates missing data, and supports prior information on relationships. Our program CONVEXCLUSTER incorporating the algorithm is implemented on ATI and nVidia graphics processing units (GPUs) for maximal speed. Several biological examples illustrate the strengths of convex clustering and the ability of the proximal distance algorithm to handle high-dimensional problems. CONVEXCLUSTER can be freely downloaded from the UCLA Human Genetics web site at http://www.genetics.ucla.edu/software/ PMID:25965340

  3. Computationally inexpensive interpretation of magnetic data for finite spin clusters

    DEFF Research Database (Denmark)

    Thuesen, Christian Aagaard; Weihe, Høgni; Bendix, Jesper

    2010-01-01

    We show that high-temperature expansion of the partition function is a computationally convenient tool to interpretation of magnetic properties of spin clusters wherein the spin centers are interacting via an isotropic Heisenberg exchange operator. High-temperature expansions up to order 12 are u...

  4. Metaobjects as a programming tool / Robert William Lemke

    OpenAIRE

    Lemke, Robert William

    2010-01-01

    Computer applications can be described as largely rigid structures within which an information seeker must navigate in search of information - each screen, each transaction having underlying unique code. The larger the application, the higher the number of lines of code and the larger the size of the application executable. This study suggests an alternative pattern based approach, an approach driven by the information seeker. This alternative approach makes use of value embedded in intell...

  5. A new tool for supervised classification of satellite images available on web servers: Google Maps as a case study

    Science.gov (United States)

    García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun

    2016-10-01

    This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.

  6. Full text clustering and relationship network analysis of biomedical publications.

    Directory of Open Access Journals (Sweden)

    Renchu Guan

    Full Text Available Rapid developments in the biomedical sciences have increased the demand for automatic clustering of biomedical publications. In contrast to current approaches to text clustering, which focus exclusively on the contents of abstracts, a novel method is proposed for clustering and analysis of complete biomedical article texts. To reduce dimensionality, Cosine Coefficient is used on a sub-space of only two vectors, instead of computing the Euclidean distance within the space of all vectors. Then a strategy and algorithm is introduced for Semi-supervised Affinity Propagation (SSAP to improve analysis efficiency, using biomedical journal names as an evaluation background. Experimental results show that by avoiding high-dimensional sparse matrix computations, SSAP outperforms conventional k-means methods and improves upon the standard Affinity Propagation algorithm. In constructing a directed relationship network and distribution matrix for the clustering results, it can be noted that overlaps in scope and interests among BioMed publications can be easily identified, providing a valuable analytical tool for editors, authors and readers.

  7. Full text clustering and relationship network analysis of biomedical publications.

    Science.gov (United States)

    Guan, Renchu; Yang, Chen; Marchese, Maurizio; Liang, Yanchun; Shi, Xiaohu

    2014-01-01

    Rapid developments in the biomedical sciences have increased the demand for automatic clustering of biomedical publications. In contrast to current approaches to text clustering, which focus exclusively on the contents of abstracts, a novel method is proposed for clustering and analysis of complete biomedical article texts. To reduce dimensionality, Cosine Coefficient is used on a sub-space of only two vectors, instead of computing the Euclidean distance within the space of all vectors. Then a strategy and algorithm is introduced for Semi-supervised Affinity Propagation (SSAP) to improve analysis efficiency, using biomedical journal names as an evaluation background. Experimental results show that by avoiding high-dimensional sparse matrix computations, SSAP outperforms conventional k-means methods and improves upon the standard Affinity Propagation algorithm. In constructing a directed relationship network and distribution matrix for the clustering results, it can be noted that overlaps in scope and interests among BioMed publications can be easily identified, providing a valuable analytical tool for editors, authors and readers.

  8. Dynamical Mass Measurements of Contaminated Galaxy Clusters Using Support Distribution Machines

    Science.gov (United States)

    Ntampaka, Michelle; Trac, Hy; Sutherland, Dougal; Fromenteau, Sebastien; Poczos, Barnabas; Schneider, Jeff

    2018-01-01

    We study dynamical mass measurements of galaxy clusters contaminated by interlopers and show that a modern machine learning (ML) algorithm can predict masses by better than a factor of two compared to a standard scaling relation approach. We create two mock catalogs from Multidark’s publicly available N-body MDPL1 simulation, one with perfect galaxy cluster membership infor- mation and the other where a simple cylindrical cut around the cluster center allows interlopers to contaminate the clusters. In the standard approach, we use a power-law scaling relation to infer cluster mass from galaxy line-of-sight (LOS) velocity dispersion. Assuming perfect membership knowledge, this unrealistic case produces a wide fractional mass error distribution, with a width E=0.87. Interlopers introduce additional scatter, significantly widening the error distribution further (E=2.13). We employ the support distribution machine (SDM) class of algorithms to learn from distributions of data to predict single values. Applied to distributions of galaxy observables such as LOS velocity and projected distance from the cluster center, SDM yields better than a factor-of-two improvement (E=0.67) for the contaminated case. Remarkably, SDM applied to contaminated clusters is better able to recover masses than even the scaling relation approach applied to uncon- taminated clusters. We show that the SDM method more accurately reproduces the cluster mass function, making it a valuable tool for employing cluster observations to evaluate cosmological models.

  9. Clustering Multivariate Time Series Using Hidden Markov Models

    Directory of Open Access Journals (Sweden)

    Shima Ghassempour

    2014-03-01

    Full Text Available In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs, where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers.

  10. Statistical analysis of the spatial distribution of galaxies and clusters

    International Nuclear Information System (INIS)

    Cappi, Alberto

    1993-01-01

    This thesis deals with the analysis of the distribution of galaxies and clusters, describing some observational problems and statistical results. First chapter gives a theoretical introduction, aiming to describe the framework of the formation of structures, tracing the history of the Universe from the Planck time, t_p = 10"-"4"3 sec and temperature corresponding to 10"1"9 GeV, to the present epoch. The most usual statistical tools and models of the galaxy distribution, with their advantages and limitations, are described in chapter two. A study of the main observed properties of galaxy clustering, together with a detailed statistical analysis of the effects of selecting galaxies according to apparent magnitude or diameter, is reported in chapter three. Chapter four delineates some properties of groups of galaxies, explaining the reasons of discrepant results on group distributions. Chapter five is a study of the distribution of galaxy clusters, with different statistical tools, like correlations, percolation, void probability function and counts in cells; it is found the same scaling-invariant behaviour of galaxies. Chapter six describes our finding that rich galaxy clusters too belong to the fundamental plane of elliptical galaxies, and gives a discussion of its possible implications. Finally chapter seven reviews the possibilities offered by multi-slit and multi-fibre spectrographs, and I present some observational work on nearby and distant galaxy clusters. In particular, I show the opportunities offered by ongoing surveys of galaxies coupled with multi-object fibre spectrographs, focusing on the ESO Key Programme A galaxy redshift survey in the south galactic pole region to which I collaborate and on MEFOS, a multi-fibre instrument with automatic positioning. Published papers related to the work described in this thesis are reported in the last appendix. (author) [fr

  11. antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

    DEFF Research Database (Denmark)

    Weber, Tilmann; Blin, Kai; Duddela, Srikanth

    2015-01-01

    Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we...... introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration...... of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products...

  12. Cluster management.

    Science.gov (United States)

    Katz, R

    1992-11-01

    Cluster management is a management model that fosters decentralization of management, develops leadership potential of staff, and creates ownership of unit-based goals. Unlike shared governance models, there is no formal structure created by committees and it is less threatening for managers. There are two parts to the cluster management model. One is the formation of cluster groups, consisting of all staff and facilitated by a cluster leader. The cluster groups function for communication and problem-solving. The second part of the cluster management model is the creation of task forces. These task forces are designed to work on short-term goals, usually in response to solving one of the unit's goals. Sometimes the task forces are used for quality improvement or system problems. Clusters are groups of not more than five or six staff members, facilitated by a cluster leader. A cluster is made up of individuals who work the same shift. For example, people with job titles who work days would be in a cluster. There would be registered nurses, licensed practical nurses, nursing assistants, and unit clerks in the cluster. The cluster leader is chosen by the manager based on certain criteria and is trained for this specialized role. The concept of cluster management, criteria for choosing leaders, training for leaders, using cluster groups to solve quality improvement issues, and the learning process necessary for manager support are described.

  13. CERN helps Grid cmputing into the mainstream

    CERN Multimedia

    Moran, Nuala

    2006-01-01

    CERN, the European Laboratory for Particle Physics, has launched the seocnd phase of Openlab, its partnership with IT companies for the development of advanced computing facilities. The industrial partners in this phase, Hewlett Packard, Intel and Oracle, will help build on the experience from the last three years when Openlab worked on cluster and Grid computing (1 page)

  14. A Monte Carlo study of the ''minus sign problem'' in the t-J model using an intel IPSC/860 hypercube

    International Nuclear Information System (INIS)

    Kovarik, M.D.; Barnes, T.; Tennessee Univ., Knoxville, TN

    1993-01-01

    We describe a Monte Carlo simulation of the 2-dimensional t-J model on an Intel iPSC/860 hypercube. The problem studied is the determination of the dispersion relation of a dynamical hole in the t-J model of the high temperature superconductors. Since this problem involves the motion of many fermions in more than one spatial dimensions, it is representative of the class of systems that suffer from the ''minus sign problem'' of dynamical fermions which has made Monte Carlo simulation very difficult. We demonstrate that for small values of the hole hopping parameter one can extract the entire hole dispersion relation using the GRW Monte Carlo algorithm, which is a simulation of the Euclidean time Schroedinger equation, and present results on 4 x 4 and 6 x 6 lattices. We demonstrate that a qualitative picture at higher hopping parameters may be found by extrapolating weak hopping results where the minus sign problem is less severe. Generalization to physical hopping parameter values will only require use of an improved trial wavefunction for importance sampling

  15. A note on the kappa statistic for clustered dichotomous data.

    Science.gov (United States)

    Zhou, Ming; Yang, Zhao

    2014-06-30

    The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

  16. Extension of K-Means Algorithm for clustering mixed data | Onuodu ...

    African Journals Online (AJOL)

    Also proposed is a new dissimilarity measure that uses relative cumulative frequency-based method in clustering objects with mixed values. The dissimilarity model developed could serve as a predictive tool for identifying attributes of objects in mixed datasets. It has been implemented using JAVA programming language ...

  17. A Science Portal and Archive for Extragalactic Globular Cluster Systems Data

    Science.gov (United States)

    Young, Michael; Rhode, Katherine L.; Gopu, Arvind

    2015-01-01

    For several years we have been carrying out a wide-field imaging survey of the globular cluster populations of a sample of giant spiral, S0, and elliptical galaxies with distances of ~10-30 Mpc. We use mosaic CCD cameras on the WIYN 3.5-m and Kitt Peak 4-m telescopes to acquire deep BVR imaging of each galaxy and then analyze the data to derive global properties of the globular cluster system. In addition to measuring the total numbers, specific frequencies, spatial distributions, and color distributions for the globular cluster populations, we have produced deep, high-quality images and lists of tens to thousands of globular cluster candidates for the ~40 galaxies included in the survey.With the survey nearing completion, we have been exploring how to efficiently disseminate not only the overall results, but also all of the relevant data products, to the astronomical community. Here we present our solution: a scientific portal and archive for extragalactic globular cluster systems data. With a modern and intuitive web interface built on the same framework as the WIYN One Degree Imager Portal, Pipeline, and Archive (ODI-PPA), our system will provide public access to the survey results and the final stacked mosaic images of the target galaxies. In addition, the astrometric and photometric data for thousands of identified globular cluster candidates, as well as for all point sources detected in each field, will be indexed and searchable. Where available, spectroscopic follow-up data will be paired with the candidates. Advanced imaging tools will enable users to overlay the cluster candidates and other sources on the mosaic images within the web interface, while metadata charting tools will allow users to rapidly and seamlessly plot the survey results for each galaxy and the data for hundreds of thousands of individual sources. Finally, we will appeal to other researchers with similar data products and work toward making our portal a central repository for data

  18. Lifting to cluster-tilting objects in higher cluster categories

    OpenAIRE

    Liu, Pin

    2008-01-01

    In this note, we consider the $d$-cluster-tilted algebras, the endomorphism algebras of $d$-cluster-tilting objects in $d$-cluster categories. We show that a tilting module over such an algebra lifts to a $d$-cluster-tilting object in this $d$-cluster category.

  19. Sleep stages identification in patients with sleep disorder using k-means clustering

    Science.gov (United States)

    Fadhlullah, M. U.; Resahya, A.; Nugraha, D. F.; Yulita, I. N.

    2018-05-01

    Data mining is a computational intelligence discipline where a large dataset processed using a certain method to look for patterns within the large dataset. This pattern then used for real time application or to develop some certain knowledge. This is a valuable tool to solve a complex problem, discover new knowledge, data analysis and decision making. To be able to get the pattern that lies inside the large dataset, clustering method is used to get the pattern. Clustering is basically grouping data that looks similar so a certain pattern can be seen in the large data set. Clustering itself has several algorithms to group the data into the corresponding cluster. This research used data from patients who suffer sleep disorders and aims to help people in the medical world to reduce the time required to classify the sleep stages from a patient who suffers from sleep disorders. This study used K-Means algorithm and silhouette evaluation to find out that 3 clusters are the optimal cluster for this dataset which means can be divided to 3 sleep stages.

  20. Data Clustering

    Science.gov (United States)

    Wagstaff, Kiri L.

    2012-03-01

    On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained

  1. MANAGING THE DEVELOPMENT OF AGRO-INDUSTRIAL CLUSTERS

    Directory of Open Access Journals (Sweden)

    D. V. Zavyalov

    2018-01-01

    Full Text Available Purpose: the purpose of the research is to design a concept of management system for agro-industrial clusters as self-organizing systems. The transition to a new technological way was marked not only by breakthrough solutions in the organization of production of goods, works and services, but also by the emergence of new (in some cases unique forms of inter-firm cooperation and interaction of economic agents in the real and financial sector of the economy. The concept of "digital economy" becomes the most important in economic research, and moreover - from a practical point of view, modern digitalization technologies in managing the activities of economic entities form new information and communication platforms for economic and scientific exchange. The penetration of digital technologies into life is one of the characteristic features of the future world. Not an exception is the agro-industrial sector, which is both strategically important for ensuring food security and has a high export potential. The article presents the concept of managing the development of agro-industrial clusters as self-organizing systems capable of integrating the activities of small and medium-sized businesses into the value-added chain based on modern information technologies. The obligatory and providing tools, mechanisms for implementing the concept, aimed at eliminating existing problems on the way of forming agro-industrial clusters, are disclosed.Methods: the agro-industrial cluster management model is developed using the methods of economic analysis and synthesis, and functional modelling.Results: conceptual model of cluster development management is presented to be used for the nascent clusters and the development of existing agro-industrial clusters.Conclusions and Relevance: as a result of the conducted research the reasons interfering development of cluster approach in the agroindustrial sector of economy are defined. Among them the main are: lack of

  2. SECIMTools: a suite of metabolomics data analysis tools.

    Science.gov (United States)

    Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

    2018-04-20

    Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

  3. Dense Fe cluster-assembled films by energetic cluster deposition

    International Nuclear Information System (INIS)

    Peng, D.L.; Yamada, H.; Hihara, T.; Uchida, T.; Sumiyama, K.

    2004-01-01

    High-density Fe cluster-assembled films were produced at room temperature by an energetic cluster deposition. Though cluster-assemblies are usually sooty and porous, the present Fe cluster-assembled films are lustrous and dense, revealing a soft magnetic behavior. Size-monodispersed Fe clusters with the mean cluster size d=9 nm were synthesized using a plasma-gas-condensation technique. Ionized clusters are accelerated electrically and deposited onto the substrate together with neutral clusters from the same cluster source. Packing fraction and saturation magnetic flux density increase rapidly and magnetic coercivity decreases remarkably with increasing acceleration voltage. The Fe cluster-assembled film obtained at the acceleration voltage of -20 kV has a packing fraction of 0.86±0.03, saturation magnetic flux density of 1.78±0.05 Wb/m 2 , and coercivity value smaller than 80 A/m. The resistivity at room temperature is ten times larger than that of bulk Fe metal

  4. CRISPR-Cpf1: A New Tool for Plant Genome Editing

    KAUST Repository

    Zaidi, Syed Shan-e-Ali; Mahfouz, Magdy M.; Mansoor, Shahid

    2017-01-01

    Clustered regularly interspaced palindromic repeats (CRISPR)-CRISPR-associated proteins (CRISPR-Cas), a groundbreaking genome-engineering tool, has facilitated targeted trait improvement in plants. Recently, CRISPR-CRISPR from Prevotella and Francisella 1 (Cpf1) has emerged as a new tool for efficient genome editing, including DNA-free editing in plants, with higher efficiency, specificity, and potentially wider applications than CRISPR-Cas9.

  5. CRISPR-Cpf1: A New Tool for Plant Genome Editing

    KAUST Repository

    Zaidi, Syed Shan-e-Ali

    2017-05-19

    Clustered regularly interspaced palindromic repeats (CRISPR)-CRISPR-associated proteins (CRISPR-Cas), a groundbreaking genome-engineering tool, has facilitated targeted trait improvement in plants. Recently, CRISPR-CRISPR from Prevotella and Francisella 1 (Cpf1) has emerged as a new tool for efficient genome editing, including DNA-free editing in plants, with higher efficiency, specificity, and potentially wider applications than CRISPR-Cas9.

  6. Fragmentation of neutral carbon clusters formed by high velocity atomic collision

    International Nuclear Information System (INIS)

    Martinet, G.

    2004-05-01

    The aim of this work is to understand the fragmentation of small neutral carbon clusters formed by high velocity atomic collision on atomic gas. In this experiment, the main way of deexcitation of neutral clusters formed by electron capture with ionic species is the fragmentation. To measure the channels of fragmentation, a new detection tool based on shape analysis of current pulse delivered by semiconductor detectors has been developed. For the first time, all branching ratios of neutral carbon clusters are measured in an unambiguous way for clusters size up to 10 atoms. The measurements have been compared to a statistical model in microcanonical ensemble (Microcanonical Metropolis Monte Carlo). In this model, various structural properties of carbon clusters are required. These data have been calculated with Density Functional Theory (DFT-B3LYP) to find the geometries of the clusters and then with Coupled Clusters (CCSD(T)) formalism to obtain dissociation energies and other quantities needed to compute fragmentation calculations. The experimental branching ratios have been compared to the fragmentation model which has allowed to find an energy distribution deposited in the collision. Finally, specific cluster effect has been found namely a large population of excited states. This behaviour is completely different of the atomic carbon case for which the electron capture in the ground states predominates. (author)

  7. Cluster Physics with Merging Galaxy Clusters

    Directory of Open Access Journals (Sweden)

    Sandor M. Molnar

    2016-02-01

    Full Text Available Collisions between galaxy clusters provide a unique opportunity to study matter in a parameter space which cannot be explored in our laboratories on Earth. In the standard LCDM model, where the total density is dominated by the cosmological constant ($Lambda$ and the matter density by cold dark matter (CDM, structure formation is hierarchical, and clusters grow mostly by merging.Mergers of two massive clusters are the most energetic events in the universe after the Big Bang,hence they provide a unique laboratory to study cluster physics.The two main mass components in clusters behave differently during collisions:the dark matter is nearly collisionless, responding only to gravity, while the gas is subject to pressure forces and dissipation, and shocks and turbulenceare developed during collisions. In the present contribution we review the different methods used to derive the physical properties of merging clusters. Different physical processes leave their signatures on different wavelengths, thusour review is based on a multifrequency analysis. In principle, the best way to analyze multifrequency observations of merging clustersis to model them using N-body/HYDRO numerical simulations. We discuss the results of such detailed analyses.New high spatial and spectral resolution ground and space based telescopeswill come online in the near future. Motivated by these new opportunities,we briefly discuss methods which will be feasible in the near future in studying merging clusters.

  8. Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

    Science.gov (United States)

    Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

    2018-06-01

    Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

  9. Lean Manufacturing Auto Cluster at Chennai

    Science.gov (United States)

    Bhaskaran, E.

    2012-10-01

    Due the presence of lot of automotive Industry, Chennai is known as Detroit of India, that producing over 40 % of the Indian vehicle and components. Lean manufacturing concepts have been widely recognized as an important tool in improving the competitiveness of industries. This is a continuous process involving everyone, starting from management to the shop floor. Automotive Component Industries (ACIs) in Ambattur Industrial Estate, Chennai has formed special purpose vehicle (SPV) society namely Ambattur Industrial Estate Manufacturers Association (AIEMA) Technology Centre (ATC) lean manufacturing cluster (ATC-LMC) during July 2010 under lean manufacturing competitiveness scheme, that comes under National Manufacturing Competitiveness Programme of Government of India. The Tripartite Agreement is taken place between National Productivity Council, consultants and cluster (ATC-LMC). The objective is to conduct diagnostic study, study on training and application of various lean manufacturing techniques and auditing in ten ACIs. The methodology adopted is collection of primary data/details from ten ACIs. In the first phase, diagnostic study is done and the areas for improvement in each of the cluster member companies are identified. In the second phase, training programs and implementation is done on 5S and other areas. In the third phase auditing is done and found that the lean manufacturing techniques implementation in ATC-LMC is sustainable and successful in every cluster companies, which will not only enhance competitiveness but also decrease cost, time and increase productivity. The technical efficiency of LMC companies also increases significantly.

  10. ANALYSIS OF DEVELOPING BATIK INDUSTRY CLUSTER IN BAKARAN VILLAGE CENTRAL JAVA PROVINCE

    Directory of Open Access Journals (Sweden)

    Hermanto Hermanto

    2017-06-01

    Full Text Available SMEs grow in a cluster in a certain geographical area. The entrepreneurs grow and thrive through the business cluster. Central Java Province has a lot of business clusters in improving the regional economy, one of which is batik industry cluster. Pati Regency is one of regencies / city in Central Java that has the lowest turnover. Batik industy cluster in Pati develops quite well, which can be seen from the increasing number of batik industry incorporated in the cluster. This research examines the strategy of developing the batik industry cluster in Pati Regency. The purpose of this research is to determine the proper strategy for developing the batik industry clusters in Pati. The method of research is quantitative. The analysis tool of this research is the Strengths, Weakness, Opportunity, Threats (SWOT analysis. The result of SWOT analysis in this research shows that the proper strategy for developing the batik industry cluster in Pati is optimizing the management of batik business cluster in Bakaran Village; the local government provides information of the facility of business capital loans; the utilization of labors from Bakaran Village while improving the quality of labors by training, and marketing the Bakaran batik to the broader markets while maintaining the quality of batik. Advice that can be given from this research is that the parties who have a role in batik industry cluster development in Bakaran Village, Pati Regency, such as the Local Government.

  11. Genome cluster database. A sequence family analysis platform for Arabidopsis and rice.

    Science.gov (United States)

    Horan, Kevin; Lauricha, Josh; Bailey-Serres, Julia; Raikhel, Natasha; Girke, Thomas

    2005-05-01

    The genome-wide protein sequences from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) spp. japonica were clustered into families using sequence similarity and domain-based clustering. The two fundamentally different methods resulted in separate cluster sets with complementary properties to compensate the limitations for accurate family analysis. Functional names for the identified families were assigned with an efficient computational approach that uses the description of the most common molecular function gene ontology node within each cluster. Subsequently, multiple alignments and phylogenetic trees were calculated for the assembled families. All clustering results and their underlying sequences were organized in the Web-accessible Genome Cluster Database (http://bioinfo.ucr.edu/projects/GCD) with rich interactive and user-friendly sequence family mining tools to facilitate the analysis of any given family of interest for the plant science community. An automated clustering pipeline ensures current information for future updates in the annotations of the two genomes and clustering improvements. The analysis allowed the first systematic identification of family and singlet proteins present in both organisms as well as those restricted to one of them. In addition, the established Web resources for mining these data provide a road map for future studies of the composition and structure of protein families between the two species.

  12. Russian Pharmaceutical Companies Export Potential in Emerging Regional Clusters

    Directory of Open Access Journals (Sweden)

    Elena Vladimirovna Sapir

    2016-12-01

    Full Text Available This article analyzes a diverse range of the enterprise’s export potential growth factors in emerging pharmaceutical clusters of Central European Russia. Classification and comparative analysis were used to identify export potential attributes (production, finance, labor and marketing, which have allowed to reveal the strong connection of cluster and regional factor groups with the results of export performance. The purpose of the study is to provide exports-seeking pharmaceutical companies with a set of tools to enhance their export potential. The hypothesis that the cumulative impact of the specified attributes leads to the strengthening of pharmaceutical cluster export potential and promotes an effective integration of the region in the world economic space, is developed and tested. The methodology combines the geo-economy-based theory with the theory of clusters competitive advantages. The impacts of export potential growth factors are estimated by using an econometric model based on math statistics. Thus, five Russian regional pharmaceutical clusters (Belgorod, Kaluga, Moscow, Oryol, Yaroslavl are shown. Findings identify an objective causal link between enterprise export potential growth and competitiveness factors of cluster origin (network business chains, production functions interconnectedness and flexibility, production localization. An action plan for the purpose of the maximum use of competitive advantages of the cluster organization for export activities of the entities of the pharmaceutical industry is developed. Conclusions and recommendations of the study are intended to enterprises in pharmaceutical industry and regions’ public authorities, implementing cluster development strategies. It is thus essential to improve marketing and organizational innovations, reduction of commercial expenses under the cluster environment, development of drugs production and delivery chains from R&D to end-users in order to enjoy greater

  13. Clustering and Recurring Anomaly Identification: Recurring Anomaly Detection System (ReADS)

    Science.gov (United States)

    McIntosh, Dawn

    2006-01-01

    This viewgraph presentation reviews the Recurring Anomaly Detection System (ReADS). The Recurring Anomaly Detection System is a tool to analyze text reports, such as aviation reports and maintenance records: (1) Text clustering algorithms group large quantities of reports and documents; Reduces human error and fatigue (2) Identifies interconnected reports; Automates the discovery of possible recurring anomalies; (3) Provides a visualization of the clusters and recurring anomalies We have illustrated our techniques on data from Shuttle and ISS discrepancy reports, as well as ASRS data. ReADS has been integrated with a secure online search

  14. Are clusters of dietary patterns and cluster membership stable over time? Results of a longitudinal cluster analysis study.

    Science.gov (United States)

    Walthouwer, Michel Jean Louis; Oenema, Anke; Soetens, Katja; Lechner, Lilian; de Vries, Hein

    2014-11-01

    Developing nutrition education interventions based on clusters of dietary patterns can only be done adequately when it is clear if distinctive clusters of dietary patterns can be derived and reproduced over time, if cluster membership is stable, and if it is predictable which type of people belong to a certain cluster. Hence, this study aimed to: (1) identify clusters of dietary patterns among Dutch adults, (2) test the reproducibility of these clusters and stability of cluster membership over time, and (3) identify sociodemographic predictors of cluster membership and cluster transition. This study had a longitudinal design with online measurements at baseline (N=483) and 6 months follow-up (N=379). Dietary intake was assessed with a validated food frequency questionnaire. A hierarchical cluster analysis was performed, followed by a K-means cluster analysis. Multinomial logistic regression analyses were conducted to identify the sociodemographic predictors of cluster membership and cluster transition. At baseline and follow-up, a comparable three-cluster solution was derived, distinguishing a healthy, moderately healthy, and unhealthy dietary pattern. Male and lower educated participants were significantly more likely to have a less healthy dietary pattern. Further, 251 (66.2%) participants remained in the same cluster, 45 (11.9%) participants changed to an unhealthier cluster, and 83 (21.9%) participants shifted to a healthier cluster. Men and people living alone were significantly more likely to shift toward a less healthy dietary pattern. Distinctive clusters of dietary patterns can be derived. Yet, cluster membership is unstable and only few sociodemographic factors were associated with cluster membership and cluster transition. These findings imply that clusters based on dietary intake may not be suitable as a basis for nutrition education interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

  15. Investigating the temporal variations of the time-clustering behavior of the Koyna-Warna (India) reservoir-triggered seismicity

    International Nuclear Information System (INIS)

    Telesca, Luciano

    2011-01-01

    Research highlights: → Time-clustering behaviour in seismicity can be detected by applying the Allan Factor. → The reservoir-induced seismicity at Koyna-Warna (India) is time-clusterized. → Pre- and co-seismic increases of the time-clustering degree are revealed. - Abstract: The time-clustering behavior of the 1996-2005 seismicity of Koyna-Warna region (India), a unique site where reservoir-triggered earthquakes have been continuously occurring over the last about 50 year, has been analyzed. The scaling exponent α, estimated by using the Allan Factor method, a powerful tool to investigate clusterization in point processes, shows co-seismic and pre-seismic enhancements associated with the occurrence of the major events.

  16. Disk cloning program 'Dolly+' for system management of PC Linux cluster

    International Nuclear Information System (INIS)

    Atsushi Manabe

    2001-01-01

    The Dolly+ is a Linux application program to clone files and disk partition image from a PC to many others. By using several techniques such as logical ring connection, multi threading and pipelining, it could achieve high performance and scalability. For example, in typical condition, installations to a hundred PCs takes almost equivalent time for two PCs. Together with the Intel PXE and the RedHat kickstart, automatic and very fast system installation and upgrading could be performed

  17. Educational clusters as a tool ofpublic policy on the market of educational services

    Directory of Open Access Journals (Sweden)

    M. I. Vorona

    2016-08-01

    Due to this, the innovative educational cluster has been determined as a voluntary association of geographically close interacting entities, educational institutions, government, banking and private sector, innovative enterprises/organizations infrastructure. Such interaction is characterized by the production of competitive educational, cultural, social services, the availability of the agreed development strategy aimed at the interests of each participant and the region being a territory of cluster’s localization.

  18. Clusters and how to make it work : Cluster Strategy Toolkit

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2014-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  19. Cluster dynamics at different cluster size and incident laser wavelengths

    International Nuclear Information System (INIS)

    Desai, Tara; Bernardinello, Andrea

    2002-01-01

    X-ray emission spectra from aluminum clusters of diameter -0.4 μm and gold clusters of dia. ∼1.25 μm are experimentally studied by irradiating the cluster foil targets with 1.06 μm laser, 10 ns (FWHM) at an intensity ∼10 12 W/cm 2 . Aluminum clusters show a different spectra compared to bulk material whereas gold cluster evolve towards bulk gold. Experimental data are analyzed on the basis of cluster dimension, laser wavelength and pulse duration. PIC simulations are performed to study the behavior of clusters at higher intensity I≥10 17 W/cm 2 for different size of the clusters irradiated at different laser wavelengths. Results indicate the dependence of cluster dynamics on cluster size and incident laser wavelength

  20. Text Clustering Algorithm Based on Random Cluster Core

    Directory of Open Access Journals (Sweden)

    Huang Long-Jun

    2016-01-01

    Full Text Available Nowadays clustering has become a popular text mining algorithm, but the huge data can put forward higher requirements for the accuracy and performance of text mining. In view of the performance bottleneck of traditional text clustering algorithm, this paper proposes a text clustering algorithm with random features. This is a kind of clustering algorithm based on text density, at the same time using the neighboring heuristic rules, the concept of random cluster is introduced, which effectively reduces the complexity of the distance calculation.

  1. Hough transform for clustered microcalcifications detection in full-field digital mammograms

    Science.gov (United States)

    Fanizzi, A.; Basile, T. M. A.; Losurdo, L.; Amoroso, N.; Bellotti, R.; Bottigli, U.; Dentamaro, R.; Didonna, V.; Fausto, A.; Massafra, R.; Moschetta, M.; Tamborra, P.; Tangaro, S.; La Forgia, D.

    2017-09-01

    Many screening programs use mammography as principal diagnostic tool for detecting breast cancer at a very early stage. Despite the efficacy of the mammograms in highlighting breast diseases, the detection of some lesions is still doubtless for radiologists. In particular, the extremely minute and elongated salt-like particles of microcalcifications are sometimes no larger than 0.1 mm and represent approximately half of all cancer detected by means of mammograms. Hence the need for automatic tools able to support radiologists in their work. Here, we propose a computer assisted diagnostic tool to support radiologists in identifying microcalcifications in full (native) digital mammographic images. The proposed CAD system consists of a pre-processing step, that improves contrast and reduces noise by applying Sobel edge detection algorithm and Gaussian filter, followed by a microcalcification detection step performed by exploiting the circular Hough transform. The procedure performance was tested on 200 images coming from the Breast Cancer Digital Repository (BCDR), a publicly available database. The automatically detected clusters of microcalcifications were evaluated by skilled radiologists which asses the validity of the correctly identified regions of interest as well as the system error in case of missed clustered microcalcifications. The system performance was evaluated in terms of Sensitivity and False Positives per images (FPi) rate resulting comparable to the state-of-art approaches. The proposed model was able to accurately predict the microcalcification clusters obtaining performances (sensibility = 91.78% and FPi rate = 3.99) which favorably compare to other state-of-the-art approaches.

  2. Attitude Estimation in Fractionated Spacecraft Cluster Systems

    Science.gov (United States)

    Hadaegh, Fred Y.; Blackmore, James C.

    2011-01-01

    An attitude estimation was examined in fractioned free-flying spacecraft. Instead of a single, monolithic spacecraft, a fractionated free-flying spacecraft uses multiple spacecraft modules. These modules are connected only through wireless communication links and, potentially, wireless power links. The key advantage of this concept is the ability to respond to uncertainty. For example, if a single spacecraft module in the cluster fails, a new one can be launched at a lower cost and risk than would be incurred with onorbit servicing or replacement of the monolithic spacecraft. In order to create such a system, however, it is essential to know what the navigation capabilities of the fractionated system are as a function of the capabilities of the individual modules, and to have an algorithm that can perform estimation of the attitudes and relative positions of the modules with fractionated sensing capabilities. Looking specifically at fractionated attitude estimation with startrackers and optical relative attitude sensors, a set of mathematical tools has been developed that specify the set of sensors necessary to ensure that the attitude of the entire cluster ( cluster attitude ) can be observed. Also developed was a navigation filter that can estimate the cluster attitude if these conditions are satisfied. Each module in the cluster may have either a startracker, a relative attitude sensor, or both. An extended Kalman filter can be used to estimate the attitude of all modules. A range of estimation performances can be achieved depending on the sensors used and the topology of the sensing network.

  3. Heat dissipation for the Intel Core i5 processor using multiwalled carbon-nanotube-based ethylene glycol

    Energy Technology Data Exchange (ETDEWEB)

    Thang, Bui Hung; Trinh, Pham Van; Quang, Le Dinh; Khoi, Phan Hong; Minh, Phan Ngoc [Vietnam Academy of Science and Technology, Ho Chi Minh CIty (Viet Nam); Huong, Nguyen Thi [Hanoi University of Science, Hanoi (Viet Nam); Vietnam National University, Hanoi (Viet Nam)

    2014-08-15

    Carbon nanotubes (CNTs) are some of the most valuable materials with high thermal conductivity. The thermal conductivity of individual multiwalled carbon nanotubes (MWCNTs) grown by using chemical vapor deposition is 600 ± 100 Wm{sup -1}K{sup -1} compared with the thermal conductivity 419 Wm{sup -1}K{sup -1} of Ag. Carbon-nanotube-based liquids - a new class of nanomaterials, have shown many interesting properties and distinctive features offering potential in heat dissipation applications for electronic devices, such as computer microprocessor, high power LED, etc. In this work, a multiwalled carbon-nanotube-based liquid was made of well-dispersed hydroxyl-functional multiwalled carbon nanotubes (MWCNT-OH) in ethylene glycol (EG)/distilled water (DW) solutions by using Tween-80 surfactant and an ultrasonication method. The concentration of MWCNT-OH in EG/DW solutions ranged from 0.1 to 1.2 gram/liter. The dispersion of the MWCNT-OH-based EG/DW solutions was evaluated by using a Zeta-Sizer analyzer. The MWCNT-OH-based EG/DW solutions were used as coolants in the liquid cooling system for the Intel Core i5 processor. The thermal dissipation efficiency and the thermal response of the system were evaluated by directly measuring the temperature of the micro-processor using the Core Temp software and the temperature sensors built inside the micro-processor. The results confirmed the advantages of CNTs in thermal dissipation systems for computer processors and other high-power electronic devices.

  4. Heat dissipation for the Intel Core i5 processor using multiwalled carbon-nanotube-based ethylene glycol

    International Nuclear Information System (INIS)

    Thang, Bui Hung; Trinh, Pham Van; Quang, Le Dinh; Khoi, Phan Hong; Minh, Phan Ngoc; Huong, Nguyen Thi

    2014-01-01

    Carbon nanotubes (CNTs) are some of the most valuable materials with high thermal conductivity. The thermal conductivity of individual multiwalled carbon nanotubes (MWCNTs) grown by using chemical vapor deposition is 600 ± 100 Wm -1 K -1 compared with the thermal conductivity 419 Wm -1 K -1 of Ag. Carbon-nanotube-based liquids - a new class of nanomaterials, have shown many interesting properties and distinctive features offering potential in heat dissipation applications for electronic devices, such as computer microprocessor, high power LED, etc. In this work, a multiwalled carbon-nanotube-based liquid was made of well-dispersed hydroxyl-functional multiwalled carbon nanotubes (MWCNT-OH) in ethylene glycol (EG)/distilled water (DW) solutions by using Tween-80 surfactant and an ultrasonication method. The concentration of MWCNT-OH in EG/DW solutions ranged from 0.1 to 1.2 gram/liter. The dispersion of the MWCNT-OH-based EG/DW solutions was evaluated by using a Zeta-Sizer analyzer. The MWCNT-OH-based EG/DW solutions were used as coolants in the liquid cooling system for the Intel Core i5 processor. The thermal dissipation efficiency and the thermal response of the system were evaluated by directly measuring the temperature of the micro-processor using the Core Temp software and the temperature sensors built inside the micro-processor. The results confirmed the advantages of CNTs in thermal dissipation systems for computer processors and other high-power electronic devices.

  5. Stereoscopic-3D display design: a new paradigm with Intel Adaptive Stable Image Technology [IA-SIT

    Science.gov (United States)

    Jain, Sunil

    2012-03-01

    Stereoscopic-3D (S3D) proliferation on personal computers (PC) is mired by several technical and business challenges: a) viewing discomfort due to cross-talk amongst stereo images; b) high system cost; and c) restricted content availability. Users expect S3D visual quality to be better than, or at least equal to, what they are used to enjoying on 2D in terms of resolution, pixel density, color, and interactivity. Intel Adaptive Stable Image Technology (IA-SIT) is a foundational technology, successfully developed to resolve S3D system design challenges and deliver high quality 3D visualization at PC price points. Optimizations in display driver, panel timing firmware, backlight hardware, eyewear optical stack, and synch mechanism combined can help accomplish this goal. Agnostic to refresh rate, IA-SIT will scale with shrinking of display transistors and improvements in liquid crystal and LED materials. Industry could profusely benefit from the following calls to action:- 1) Adopt 'IA-SIT S3D Mode' in panel specs (via VESA) to help panel makers monetize S3D; 2) Adopt 'IA-SIT Eyewear Universal Optical Stack' and algorithm (via CEA) to help PC peripheral makers develop stylish glasses; 3) Adopt 'IA-SIT Real Time Profile' for sub-100uS latency control (via BT Sig) to extend BT into S3D; and 4) Adopt 'IA-SIT Architecture' for Monitors and TVs to monetize via PC attach.

  6. On clusters and clustering from atoms to fractals

    CERN Document Server

    Reynolds, PJ

    1993-01-01

    This book attempts to answer why there is so much interest in clusters. Clusters occur on all length scales, and as a result occur in a variety of fields. Clusters are interesting scientifically, but they also have important consequences technologically. The division of the book into three parts roughly separates the field into small, intermediate, and large-scale clusters. Small clusters are the regime of atomic and molecular physics and chemistry. The intermediate regime is the transitional regime, with its characteristics including the onset of bulk-like behavior, growth and aggregation, a

  7. Towards Development of Clustering Applications for Large-Scale Comparative Genotyping and Kinship Analysis Using Y-Short Tandem Repeats.

    Science.gov (United States)

    Seman, Ali; Sapawi, Azizian Mohd; Salleh, Mohd Zaki

    2015-06-01

    Y-chromosome short tandem repeats (Y-STRs) are genetic markers with practical applications in human identification. However, where mass identification is required (e.g., in the aftermath of disasters with significant fatalities), the efficiency of the process could be improved with new statistical approaches. Clustering applications are relatively new tools for large-scale comparative genotyping, and the k-Approximate Modal Haplotype (k-AMH), an efficient algorithm for clustering large-scale Y-STR data, represents a promising method for developing these tools. In this study we improved the k-AMH and produced three new algorithms: the Nk-AMH I (including a new initial cluster center selection), the Nk-AMH II (including a new dominant weighting value), and the Nk-AMH III (combining I and II). The Nk-AMH III was the superior algorithm, with mean clustering accuracy that increased in four out of six datasets and remained at 100% in the other two. Additionally, the Nk-AMH III achieved a 2% higher overall mean clustering accuracy score than the k-AMH, as well as optimal accuracy for all datasets (0.84-1.00). With inclusion of the two new methods, the Nk-AMH III produced an optimal solution for clustering Y-STR data; thus, the algorithm has potential for further development towards fully automatic clustering of any large-scale genotypic data.

  8. GibbsCluster: unsupervised clustering and alignment of peptide sequences

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

    2017-01-01

    motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large......-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0....

  9. Clustering of Cochlear Oscillations in Frequency Plateaus as a Tool to Investigate SOAE Generation

    DEFF Research Database (Denmark)

    Epp, Bastian; Wit, Hero; van Dijk, Pim

    2016-01-01

    of coupled oscillators (OAM) [7] are also found in a transmission line model (TLM) which is able to generate realistic SOAEs [2] and if these frequency plateaus can be used to explain the formation of SOAEs. The simulations showed a clustering of oscillators along the simulated basilar membrane Both, the OAM...

  10. Diametrical clustering for identifying anti-correlated gene clusters.

    Science.gov (United States)

    Dhillon, Inderjit S; Marcotte, Edward M; Roshan, Usman

    2003-09-01

    Clustering genes based upon their expression patterns allows us to predict gene function. Most existing clustering algorithms cluster genes together when their expression patterns show high positive correlation. However, it has been observed that genes whose expression patterns are strongly anti-correlated can also be functionally similar. Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways. We present a new diametrical clustering algorithm that explicitly identifies anti-correlated clusters of genes. Our algorithm proceeds by iteratively (i). re-partitioning the genes and (ii). computing the dominant singular vector of each gene cluster; each singular vector serving as the prototype of a 'diametric' cluster. We empirically show the effectiveness of the algorithm in identifying diametrical or anti-correlated clusters. Testing the algorithm on yeast cell cycle data, fibroblast gene expression data, and DNA microarray data from yeast mutants reveals that opposed cellular pathways can be discovered with this method. We present systems whose mRNA expression patterns, and likely their functions, oppose the yeast ribosome and proteosome, along with evidence for the inverse transcriptional regulation of a number of cellular systems.

  11. Partitional clustering algorithms

    CERN Document Server

    2015-01-01

    This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

  12. Near-Edge X-ray Absorption Fine Structure within Multilevel Coupled Cluster Theory.

    Science.gov (United States)

    Myhre, Rolf H; Coriani, Sonia; Koch, Henrik

    2016-06-14

    Core excited states are challenging to calculate, mainly because they are embedded in a manifold of high-energy valence-excited states. However, their locality makes their determination ideal for local correlation methods. In this paper, we demonstrate the performance of multilevel coupled cluster theory in computing core spectra both within the core-valence separated and the asymmetric Lanczos implementations of coupled cluster linear response theory. We also propose a visualization tool to analyze the excitations using the difference between the ground-state and excited-state electron densities.

  13. Topic modeling for cluster analysis of large biological and medical datasets.

    Science.gov (United States)

    Zhao, Weizhong; Zou, Wen; Chen, James J

    2014-01-01

    The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors. Although multivariate techniques such as cluster analysis may allow researchers to identify groups, or clusters, of related variables, the accuracies and effectiveness of traditional clustering methods diminish for large and hyper dimensional datasets. Topic modeling is an active research field in machine learning and has been mainly used as an analytical tool to structure large textual corpora for data mining. Its ability to reduce high dimensionality to a small number of latent variables makes it suitable as a means for clustering or overcoming clustering difficulties in large biological and medical datasets. In this study, three topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, are proposed and tested on the cluster analysis of three large datasets: Salmonella pulsed-field gel electrophoresis (PFGE) dataset, lung cancer dataset, and breast cancer dataset, which represent various types of large biological or medical datasets. All three various methods are shown to improve the efficacy/effectiveness of clustering results on the three datasets in comparison to traditional methods. A preferable cluster analysis method emerged for each of the three datasets on the basis of replicating known biological truths. Topic modeling could be advantageously applied to the large datasets of biological or medical research. The three proposed topic model-derived clustering methods, highest probable topic assignment, feature selection and feature extraction, yield clustering improvements for the three different data types. Clusters more efficaciously represent truthful groupings and subgroupings in the data than traditional methods, suggesting

  14. Dynamic parallel ROOT facility clusters on the Alice Environment

    International Nuclear Information System (INIS)

    Luzzi, C; Betev, L; Carminati, F; Grigoras, C; Saiz, P; Manafov, A

    2012-01-01

    The ALICE collaboration has developed a production environment (AliEn) that implements the full set of the Grid tools enabling the full offline computational work-flow of the experiment, simulation, reconstruction and data analysis, in a distributed and heterogeneous computing environment. In addition to the analysis on the Grid, ALICE uses a set of local interactive analysis facilities installed with the Parallel ROOT Facility (PROOF). PROOF enables physicists to analyze medium-sized (order of 200-300 TB) data sets on a short time scale. The default installation of PROOF is on a static dedicated cluster, typically 200-300 cores. This well-proven approach, has its limitations, more specifically for analysis of larger datasets or when the installation of a dedicated cluster is not possible. Using a new framework called PoD (Proof on Demand), PROOF can be used directly on Grid-enabled clusters, by dynamically assigning interactive nodes on user request. The integration of Proof on Demand in the AliEn framework provides private dynamic PROOF clusters as a Grid service. This functionality is transparent to the user who will submit interactive jobs to the AliEn system.

  15. Installing, Running and Maintaining Large Linux Clusters at CERN

    CERN Document Server

    Bahyl, V; van Eldik, Jan; Fuchs, Ulrich; Kleinwort, Thorsten; Murth, Martin; Smith, Tim; Bahyl, Vladimir; Chardi, Benjamin; Eldik, Jan van; Fuchs, Ulrich; Kleinwort, Thorsten; Murth, Martin; Smith, Tim

    2003-01-01

    Having built up Linux clusters to more than 1000 nodes over the past five years, we already have practical experience confronting some of the LHC scale computing challenges: scalability, automation, hardware diversity, security, and rolling OS upgrades. This paper describes the tools and processes we have implemented, working in close collaboration with the EDG project [1], especially with the WP4 subtask, to improve the manageability of our clusters, in particular in the areas of system installation, configuration, and monitoring. In addition to the purely technical issues, providing shared interactive and batch services which can adapt to meet the diverse and changing requirements of our users is a significant challenge. We describe the developments and tuning that we have introduced on our LSF based systems to maximise both responsiveness to users and overall system utilisation. Finally, this paper will describe the problems we are facing in enlarging our heterogeneous Linux clusters, the progress we have ...

  16. Open Clusters as Tracers of the Galactic Disk

    Science.gov (United States)

    Cantat-Gaudin, Tristan

    2015-01-01

    Open clusters (OCs) are routinely used as reliable tracers of the properties and evolution of the galactic disk, as they can be found at all galactocentric distances and span a wide range of ages. More than 3000 OCs are listed in catalogues, although few have been studied in details. The goal of this work is to study the properties of open clusters. This work was conducted in the framework of the Gaia-ESO Survey (GES). GES is an observational campaign targeting more than 100,000 stars in all major components of the Milky Way, including stars in a hundred open clusters. It uses the FLAMES instrument at the VLT to produce high and medium-resolution spectra, which provide accurate radial velocities and individual elemental abundances. In this framework, the goals of the Thesis are: * to study the properties of OCs and of their stars from photometry and spectroscopy to derive their age, the extinction and the chemical composition of the stars, to begin to build a homogeneous data base. Looking at literature data it is clear that different authors derive substantially different chemical compositions, and in general OC parameters. * the study of OCs and their chemical homogeneity (or inhomogeneity) can cast light on what is still an open issue: the presence of multiple populations in clusters. While multiple generations of stars are now ubiquitously found in globular clusters in the Milky Way and in the Magellanic Clouds, they have not been yet detected in open clusters. What is the main driver of the self-pollution process? * to study the cluster formation process. All, or at least a significant fraction of stars form in clusters. Young clusters (a few Myr) can retain some of the properties of the molecular cloud they originate from and give us insight about the cluster assembly process. The first GES data release contains data for the young OC Gamma Velorum, in which two (dynamically different) subpopulations have been identified. This cluster can serve as a test case

  17. WinHPC System Configuration | High-Performance Computing | NREL

    Science.gov (United States)

    ), login node (WinHPC02) and worker/compute nodes. The head node acts as the file, DNS, and license server . The login node is where the users connect to access the cluster. Node 03 has dual Intel Xeon E5530 2008 R2 HPC Edition. The login node, WinHPC02, is where users login to access the system. This is where

  18. Using the GeoFEST Faulted Region Simulation System

    Science.gov (United States)

    Parker, Jay W.; Lyzenga, Gregory A.; Donnellan, Andrea; Judd, Michele A.; Norton, Charles D.; Baker, Teresa; Tisdale, Edwin R.; Li, Peggy

    2004-01-01

    GeoFEST (the Geophysical Finite Element Simulation Tool) simulates stress evolution, fault slip and plastic/elastic processes in realistic materials, and so is suitable for earthquake cycle studies in regions such as Southern California. Many new capabilities and means of access for GeoFEST are now supported. New abilities include MPI-based cluster parallel computing using automatic PYRAMID/Parmetis-based mesh partitioning, automatic mesh generation for layered media with rectangular faults, and results visualization that is integrated with remote sensing data. The parallel GeoFEST application has been successfully run on over a half-dozen computers, including Intel Xeon clusters, Itanium II and Altix machines, and the Apple G5 cluster. It is not separately optimized for different machines, but relies on good domain partitioning for load-balance and low communication, and careful writing of the parallel diagonally preconditioned conjugate gradient solver to keep communication overhead low. Demonstrated thousand-step solutions for over a million finite elements on 64 processors require under three hours, and scaling tests show high efficiency when using more than (order of) 4000 elements per processor. The source code and documentation for GeoFEST is available at no cost from Open Channel Foundation. In addition GeoFEST may be used through a browser-based portal environment available to approved users. That environment includes semi-automated geometry creation and mesh generation tools, GeoFEST, and RIVA-based visualization tools that include the ability to generate a flyover animation showing deformations and topography. Work is in progress to support simulation of a region with several faults using 16 million elements, using a strain energy metric to adapt the mesh to faithfully represent the solution in a region of widely varying strain.

  19. In vivo fluorescent detection of Fe-S clusters coordinated by human GRX2.

    Science.gov (United States)

    Hoff, Kevin G; Culler, Stephanie J; Nguyen, Peter Q; McGuire, Ryan M; Silberg, Jonathan J; Smolke, Christina D

    2009-12-24

    A major challenge to studying Fe-S cluster biosynthesis in higher eukaryotes is the lack of simple tools for imaging metallocluster binding to proteins. We describe the first fluorescent approach for in vivo detection of 2Fe2S clusters that is based upon the complementation of Venus fluorescent protein fragments via human glutaredoxin 2 (GRX2) coordination of a 2Fe2S cluster. We show that Escherichia coli and mammalian cells expressing Venus fragments fused to GRX2 exhibit greater fluorescence than cells expressing fragments fused to a C37A mutant that cannot coordinate a metallocluster. In addition, we find that maximal fluorescence in the cytosol of mammalian cells requires the iron-sulfur cluster assembly proteins ISCU and NFS1. These findings provide evidence that glutaredoxins can dimerize within mammalian cells through coordination of a 2Fe2S cluster as observed with purified recombinant proteins. Copyright 2009 Elsevier Ltd. All rights reserved.

  20. Navier-Stokes Aerodynamic Simulation of the V-22 Osprey on the Intel Paragon MPP

    Science.gov (United States)

    Vadyak, Joseph; Shrewsbury, George E.; Narramore, Jim C.; Montry, Gary; Holst, Terry; Kwak, Dochan (Technical Monitor)

    1995-01-01

    The paper will describe the Development of a general three-dimensional multiple grid zone Navier-Stokes flowfield simulation program (ENS3D-MPP) designed for efficient execution on the Intel Paragon Massively Parallel Processor (MPP) supercomputer, and the subsequent application of this method to the prediction of the viscous flowfield about the V-22 Osprey tiltrotor vehicle. The flowfield simulation code solves the thin Layer or full Navier-Stoke's equation - for viscous flow modeling, or the Euler equations for inviscid flow modeling on a structured multi-zone mesh. In the present paper only viscous simulations will be shown. The governing difference equations are solved using a time marching implicit approximate factorization method with either TVD upwind or central differencing used for the convective terms and central differencing used for the viscous diffusion terms. Steady state or Lime accurate solutions can be calculated. The present paper will focus on steady state applications, although time accurate solution analysis is the ultimate goal of this effort. Laminar viscosity is calculated using Sutherland's law and the Baldwin-Lomax two layer algebraic turbulence model is used to compute the eddy viscosity. The Simulation method uses an arbitrary block, curvilinear grid topology. An automatic grid adaption scheme is incorporated which concentrates grid points in high density gradient regions. A variety of user-specified boundary conditions are available. This paper will present the application of the scalable and superscalable versions to the steady state viscous flow analysis of the V-22 Osprey using a multiple zone global mesh. The mesh consists of a series of sheared cartesian grid blocks with polar grids embedded within to better simulate the wing tip mounted nacelle. MPP solutions will be shown in comparison to equivalent Cray C-90 results and also in comparison to experimental data. Discussions on meshing considerations, wall clock execution time

  1. Seminal Quality Prediction Using Clustering-Based Decision Forests

    Directory of Open Access Journals (Sweden)

    Hong Wang

    2014-08-01

    Full Text Available Prediction of seminal quality with statistical learning tools is an emerging methodology in decision support systems in biomedical engineering and is very useful in early diagnosis of seminal patients and selection of semen donors candidates. However, as is common in medical diagnosis, seminal quality prediction faces the class imbalance problem. In this paper, we propose a novel supervised ensemble learning approach, namely Clustering-Based Decision Forests, to tackle unbalanced class learning problem in seminal quality prediction. Experiment results on real fertility diagnosis dataset have shown that Clustering-Based Decision Forests outperforms decision tree, Support Vector Machines, random forests, multilayer perceptron neural networks and logistic regression by a noticeable margin. Clustering-Based Decision Forests can also be used to evaluate variables’ importance and the top five important factors that may affect semen concentration obtained in this study are age, serious trauma, sitting time, the season when the semen sample is produced, and high fevers in the last year. The findings could be helpful in explaining seminal concentration problems in infertile males or pre-screening semen donor candidates.

  2. Cluster Matters

    DEFF Research Database (Denmark)

    Gulati, Mukesh; Lund-Thomsen, Peter; Suresh, Sangeetha

    2018-01-01

    sell their products successfully in international markets, but there is also an increasingly large consumer base within India. Indeed, Indian industrial clusters have contributed to a substantial part of this growth process, and there are several hundred registered clusters within the country...... of this handbook, which focuses on the role of CSR in MSMEs. Hence we contribute to the literature on CSR in industrial clusters and specifically CSR in Indian industrial clusters by investigating the drivers of CSR in India’s industrial clusters....

  3. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  4. Support Policies in Clusters: Prioritization of Support Needs by Cluster Members According to Cluster Life Cycle

    Directory of Open Access Journals (Sweden)

    Gulcin Salıngan

    2012-07-01

    Full Text Available Economic development has always been a moving target. Both the national and local governments have been facing the challenge of implementing the effective and efficient economic policy and program in order to best utilize their limited resources. One of the recent approaches in this area is called cluster-based economic analysis and strategy development. This study reviews key literature and some of the cluster based economic policies adopted by different governments. Based on this review, it proposes “the cluster life cycle” as a determining factor to identify the support requirements of clusters. A survey, designed based on literature review of International Cluster support programs, was conducted with 30 participants from 3 clusters with different maturity stage. This paper discusses the results of this study conducted among the cluster members in Eskişehir- Bilecik-Kütahya Region in Turkey on the requirement of the support to foster the development of related clusters.

  5. Cluster mislocation in kinematic Sunyaev-Zel'dovich (kSZ) effect extraction

    Science.gov (United States)

    Calafut, Victoria Rose; Bean, Rachel; Yu, Byeonghee

    2018-01-01

    We investigate the impact of a variety of analysis assumptions that influence cluster identification and location on the kSZ pairwise momentum signal and covariance estimation. Photometric and spectroscopic galaxy tracers from SDSS, WISE, and DECaLs, spanning redshifts 0.05zgeneration of CMB and LSS surveys the statistical and photometric errors will shrink markedly. Our results demonstrate that uncertainties introduced through using galaxy proxies for cluster locations will need to be fully incorporated, and actively mitigated, for the kSZ to reach its full potential as a cosmological constraining tool for dark energy and neutrino physics.

  6. Covering Image Segmentation via Matrix X-means and J-means Clustering

    Directory of Open Access Journals (Sweden)

    Volodymyr MASHTALIR

    2015-12-01

    Full Text Available To provide tools for image understanding, non-trivial task of image segmentation is now put on a new semantic level of object detection. Internal, external and contextual region properties often can adequately represent image content but there arises field of view coverings due shape ambiguities on blurred images. Truthful image interpretation strictly depends on valid number of regions. The goal is an attempt to solve image clustering problem under fuzzy conditions of overlapping classes, more specifically, to find estimation of meaningful region number with following refining of fuzzy clustering data in matrix form.

  7. Simulating the Euclidean time Schroedinger equations using an Intel iPSC/860 hypercube: Application to the t-J model of high-Tc superconductivity

    International Nuclear Information System (INIS)

    Kovarik, M.D.; Barnes, T.; Tennessee Univ., Knoxville, TN

    1993-01-01

    We describe a Monte Carlo simulation of a dynamical fermion problem in two spatial dimensions on an Intel iPSC/860 hypercube. The problem studied is the determination of the dispersion relation of a dynamical hole in the t-J model of the high temperature superconductors. Since this problem involves the motion of many fermions in more than one spatial dimensions, it is representative of the class of systems that suffer from the ''minus sign problem'' of dynamical fermions which has made Monte Carlo simulation very difficult. We demonstrate that for small values of the hole hopping parameter one can extract the entire hole dispersion relation using the GRW Monte Carlo algorithm, which is a simulation of the Euclidean time Schroedinger equation, and present results on 4 x 4 and 6 x 6 lattices. Generalization to physical hopping parameter values wig only require use of an improved trial wavefunction for importance sampling

  8. Clusters and how to make it work : toolkit for cluster strategy

    NARCIS (Netherlands)

    Manickam, Anu; van Berkel, Karel

    2013-01-01

    Clusters are the magic answer to regional economic development. Firms in clusters are more innovative; cluster policy dominates EU policy; ‘top-sectors’ and excellence are the choice of national policy makers; clusters are ‘in’. But, clusters are complex, clusters are ‘messy’; there is no clear

  9. Reconstruction of Cluster Positions in the LHCb Velo

    CERN Document Server

    Parkes, C; Szumlak, T

    2007-01-01

    This note describes the `Velo Cluster Position Tool'. This software is used in the GAUDI framework to estimate the hit position of a particle traversing the silicon sensors of the LHCb VELO and to estimate the uncertainty on this position. This estimate and its uncertainty are used in the LHCb track fit. The definition of the cluster centre is given and the baseline linear approximation method presented. The position error is strongly dependent on the angle of incidence of the particle on the silicon sensors measured perpendicularly to the strips -- known as the projected angle -- and on the silicon sensor pitch at the point of incidence, and is parametrised in terms of these variables. Pull plots are presented to show the quality of the current tuning implemented for simulation events.

  10. Helium clusters as cold, liquid matrix for the laser spectroscopy of silver atoms, silver clusters and C60 fullerenes

    International Nuclear Information System (INIS)

    Hoffmann, K.

    1999-01-01

    One of the main obstacles in the study of gas phase metal clusters is their high temperature. Even cooling in a seeded beam is only of limited used, since the condensation continuously releases energy into the system. As a consequence, spectroscopic studies of free metal clusters typically yield broad structures, which are interpreted as plasma resonances of a free electron gas. An experiment on ionic sodium clusters has shown that low temperatures lead to a narrowing of the absorption bands and the appearance of additional structure, that can not be explained within the free electron model. Thus the need for cold clusters is evident. In principle the deposition of metal clusters into inert matrices eliminates the temperature problem but it can also inflict strong changes on the electronic spectra. Droplets of liquid helium serve as a much more gentle matrix that avoids many of the above problems. In this thesis the new technique of helium droplet spectroscopy is presented as a tool for the study of extremely cold metal clusters. Clusters of silver up to a mass greater than 7000 amu have been produced by pickup of single atoms by a beam of helium droplets. The droplets are formed in a supersonic expansion. The cluster's binding energy is removed by evaporative cooling and the system remains at 0.4 K. The doped droplets are probed by laser spectroscopy with a depletion technique or resonant two photon ionization. We were able to measure the first UV absorption spectrum of metal atoms (silver) inside helium droplets. Another experiment shows that a small fraction of the captured silver atoms resides on the surface of the droplet like alkali atoms. In a two photon process previously unobserved s- and d-Rydberg states of the free silver atom (20 left angle n left angle 80) were excited. The silver atoms, initially embedded in the helium droplets, are found to move to the surface and desorb when excited to the broadened 5p level. This is the first result showing laser

  11. Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data.

    Science.gov (United States)

    Kim, Sehwi; Jung, Inkyung

    2017-01-01

    The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns.

  12. Determination of atomic cluster structure with cluster fusion algorithm

    DEFF Research Database (Denmark)

    Obolensky, Oleg I.; Solov'yov, Ilia; Solov'yov, Andrey V.

    2005-01-01

    We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters.......We report an efficient scheme of global optimization, called cluster fusion algorithm, which has proved its reliability and high efficiency in determination of the structure of various atomic clusters....

  13. Large-Scale Multi-Dimensional Document Clustering on GPU Clusters

    Energy Technology Data Exchange (ETDEWEB)

    Cui, Xiaohui [ORNL; Mueller, Frank [North Carolina State University; Zhang, Yongpeng [ORNL; Potok, Thomas E [ORNL

    2010-01-01

    Document clustering plays an important role in data mining systems. Recently, a flocking-based document clustering algorithm has been proposed to solve the problem through simulation resembling the flocking behavior of birds in nature. This method is superior to other clustering algorithms, including k-means, in the sense that the outcome is not sensitive to the initial state. One limitation of this approach is that the algorithmic complexity is inherently quadratic in the number of documents. As a result, execution time becomes a bottleneck with large number of documents. In this paper, we assess the benefits of exploiting the computational power of Beowulf-like clusters equipped with contemporary Graphics Processing Units (GPUs) as a means to significantly reduce the runtime of flocking-based document clustering. Our framework scales up to over one million documents processed simultaneously in a sixteennode GPU cluster. Results are also compared to a four-node cluster with higher-end GPUs. On these clusters, we observe 30X-50X speedups, which demonstrates the potential of GPU clusters to efficiently solve massive data mining problems. Such speedups combined with the scalability potential and accelerator-based parallelization are unique in the domain of document-based data mining, to the best of our knowledge.

  14. Membership determination of open clusters based on a spectral clustering method

    Science.gov (United States)

    Gao, Xin-Hua

    2018-06-01

    We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

  15. Cluster headache

    Science.gov (United States)

    Histamine headache; Headache - histamine; Migrainous neuralgia; Headache - cluster; Horton's headache; Vascular headache - cluster ... Doctors do not know exactly what causes cluster headaches. They ... (chemical in the body released during an allergic response) or ...

  16. Group analyses of connectivity-based cortical parcellation using repeated k-means clustering

    NARCIS (Netherlands)

    Nanetti, Luca; Cerliani, Leonardo; Gazzola, Valeria; Renken, Remco; Keysers, Christian

    2009-01-01

    K-means clustering has become a popular tool for connectivity-based cortical segmentation using Diffusion Weighted Imaging (DWI) data. A sometimes ignored issue is, however, that the output of the algorithm depends on the initial placement of starting points, and that different sets of starting

  17. Optimal Selection of Clustering Algorithm via Multi-Criteria Decision Analysis (MCDA for Load Profiling Applications

    Directory of Open Access Journals (Sweden)

    Ioannis P. Panapakidis

    2018-02-01

    Full Text Available Due to high implementation rates of smart meter systems, considerable amount of research is placed in machine learning tools for data handling and information retrieval. A key tool in load data processing is clustering. In recent years, a number of researches have proposed different clustering algorithms in the load profiling field. The present paper provides a methodology for addressing the aforementioned problem through Multi-Criteria Decision Analysis (MCDA and namely, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS. A comparison of the algorithms is employed. Next, a single test case on the selection of an algorithm is examined. User specific weights are applied and based on these weight values, the optimal algorithm is drawn.

  18. Single-cluster dynamics for the random-cluster model

    NARCIS (Netherlands)

    Deng, Y.; Qian, X.; Blöte, H.W.J.

    2009-01-01

    We formulate a single-cluster Monte Carlo algorithm for the simulation of the random-cluster model. This algorithm is a generalization of the Wolff single-cluster method for the q-state Potts model to noninteger values q>1. Its results for static quantities are in a satisfactory agreement with those

  19. Vertebra identification using template matching modelmp and K-means clustering.

    Science.gov (United States)

    Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

    2014-03-01

    Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

  20. MADIBA: A web server toolkit for biological interpretation of Plasmodium and plant gene clusters

    Directory of Open Access Journals (Sweden)

    Louw Abraham I

    2008-02-01

    Full Text Available Abstract Background Microarray technology makes it possible to identify changes in gene expression of an organism, under various conditions. Data mining is thus essential for deducing significant biological information such as the identification of new biological mechanisms or putative drug targets. While many algorithms and software have been developed for analysing gene expression, the extraction of relevant information from experimental data is still a substantial challenge, requiring significant time and skill. Description MADIBA (MicroArray Data Interface for Biological Annotation facilitates the assignment of biological meaning to gene expression clusters by automating the post-processing stage. A relational database has been designed to store the data from gene to pathway for Plasmodium, rice and Arabidopsis. Tools within the web interface allow rapid analyses for the identification of the Gene Ontology terms relevant to each cluster; visualising the metabolic pathways where the genes are implicated, their genomic localisations, putative common transcriptional regulatory elements in the upstream sequences, and an analysis specific to the organism being studied. Conclusion MADIBA is an integrated, online tool that will assist researchers in interpreting their results and understand the meaning of the co-expression of a cluster of genes. Functionality of MADIBA was validated by analysing a number of gene clusters from several published experiments – expression profiling of the Plasmodium life cycle, and salt stress treatments of Arabidopsis and rice. In most of the cases, the same conclusions found by the authors were quickly and easily obtained after analysing the gene clusters with MADIBA.