Parallel processor programs in the Federal Government

Science.gov (United States)

Schneck, P. B.; Austin, D.; Squires, S. L.; Lehmann, J.; Mizell, D.; Wallgren, K.

1985-01-01

In 1982, a report dealing with the nation's research needs in high-speed computing called for increased access to supercomputing resources for the research community, research in computational mathematics, and increased research in the technology base needed for the next generation of supercomputers. Since that time a number of programs addressing future generations of computers, particularly parallel processors, have been started by U.S. government agencies. The present paper provides a description of the largest government programs in parallel processing. Established in fiscal year 1985 by the Institute for Defense Analyses for the National Security Agency, the Supercomputing Research Center will pursue research to advance the state of the art in supercomputing. Attention is also given to the DOE applied mathematical sciences research program, the NYU Ultracomputer project, the DARPA multiprocessor system architectures program, NSF research on multiprocessor systems, ONR activities in parallel computing, and NASA parallel processor projects.

The Glasgow Parallel Reduction Machine: Programming Shared-memory Many-core Systems using Parallel Task Composition

Directory of Open Access Journals (Sweden)

Ashkan Tousimojarad

2013-12-01

Full Text Available We present the Glasgow Parallel Reduction Machine (GPRM, a novel, flexible framework for parallel task-composition based many-core programming. We allow the programmer to structure programs into task code, written as C++ classes, and communication code, written in a restricted subset of C++ with functional semantics and parallel evaluation. In this paper we discuss the GPRM, the virtual machine framework that enables the parallel task composition approach. We focus the discussion on GPIR, the functional language used as the intermediate representation of the bytecode running on the GPRM. Using examples in this language we show the flexibility and power of our task composition framework. We demonstrate the potential using an implementation of a merge sort algorithm on a 64-core Tilera processor, as well as on a conventional Intel quad-core processor and an AMD 48-core processor system. We also compare our framework with OpenMP tasks in a parallel pointer chasing algorithm running on the Tilera processor. Our results show that the GPRM programs outperform the corresponding OpenMP codes on all test platforms, and can greatly facilitate writing of parallel programs, in particular non-data parallel algorithms such as reductions.

The kpx, a program analyzer for parallelization

International Nuclear Information System (INIS)

Matsuyama, Yuji; Orii, Shigeo; Ota, Toshiro; Kume, Etsuo; Aikawa, Hiroshi.

1997-03-01

The kpx is a program analyzer, developed as a common technological basis for promoting parallel processing. The kpx consists of three tools. The first is ktool, that shows how much execution time is spent in program segments. The second is ptool, that shows parallelization overhead on the Paragon system. The last is xtool, that shows parallelization overhead on the VPP system. The kpx, designed to work for any FORTRAN cord on any UNIX computer, is confirmed to work well after testing on Paragon, SP2, SR2201, VPP500, VPP300, Monte-4, SX-4 and T90. (author)

Speedup predictions on large scientific parallel programs

International Nuclear Information System (INIS)

Williams, E.; Bobrowicz, F.

1985-01-01

How much speedup can we expect for large scientific parallel programs running on supercomputers. For insight into this problem we extend the parallel processing environment currently existing on the Cray X-MP (a shared memory multiprocessor with at most four processors) to a simulated N-processor environment, where N greater than or equal to 1. Several large scientific parallel programs from Los Alamos National Laboratory were run in this simulated environment, and speedups were predicted. A speedup of 14.4 on 16 processors was measured for one of the three most used codes at the Laboratory

Declarative Parallel Programming in Spreadsheet End-User Development

DEFF Research Database (Denmark)

Biermann, Florian

2016-01-01

Spreadsheets are first-order functional languages and are widely used in research and industry as a tool to conveniently perform all kinds of computations. Because cells on a spreadsheet are immutable, there are possibilities for implicit parallelization of spreadsheet computations. In this liter...... can directly apply results from functional array programming to a spreadsheet model of computations.......Spreadsheets are first-order functional languages and are widely used in research and industry as a tool to conveniently perform all kinds of computations. Because cells on a spreadsheet are immutable, there are possibilities for implicit parallelization of spreadsheet computations....... In this literature study, we provide an overview of the publications on spreadsheet end-user programming and declarative array programming to inform further research on parallel programming in spreadsheets. Our results show that there is a clear overlap between spreadsheet programming and array programming and we...

Programming parallel architectures - The BLAZE family of languages

Science.gov (United States)

Mehrotra, Piyush

1989-01-01

This paper gives an overview of the various approaches to programming multiprocessor architectures that are currently being explored. It is argued that two of these approaches, interactive programming environments and functional parallel languages, are particularly attractive, since they remove much of the burden of exploiting parallel architectures from the user. This paper also describes recent work in the design of parallel languages. Research on languages for both shared and nonshared memory multiprocessors is described.

Programming parallel architectures: The BLAZE family of languages

Science.gov (United States)

Mehrotra, Piyush

1988-01-01

Programming multiprocessor architectures is a critical research issue. An overview is given of the various approaches to programming these architectures that are currently being explored. It is argued that two of these approaches, interactive programming environments and functional parallel languages, are particularly attractive since they remove much of the burden of exploiting parallel architectures from the user. Also described is recent work by the author in the design of parallel languages. Research on languages for both shared and nonshared memory multiprocessors is described, as well as the relations of this work to other current language research projects.

Parallel adaptation of a vectorised quantumchemical program system

International Nuclear Information System (INIS)

Van Corler, L.C.H.; Van Lenthe, J.H.

1987-01-01

Supercomputers, like the CRAY 1 or the Cyber 205, have had, and still have, a marked influence on Quantum Chemistry. Vectorization has led to a considerable increase in the performance of Quantum Chemistry programs. However, clockcycle times more than a factor 10 smaller than those of the present supercomputers are not to be expected. Therefore future supercomputers will have to depend on parallel structures. Recently, the first examples of such supercomputers have been installed. To be prepared for this new generation of (parallel) supercomputers one should consider the concepts one wants to use and the kind of problems one will encounter during implementation of existing vectorized programs on those parallel systems. The authors implemented four important parts of a large quantumchemical program system (ATMOL), i.e. integrals, SCF, 4-index and Direct-CI in the parallel environment at ECSEC (Rome, Italy). This system offers simulated parallellism on the host computer (IBM 4381) and real parallellism on at most 10 attached processors (FPS-164). Quantumchemical programs usually handle large amounts of data and very large, often sparse matrices. The transfer of that many data can cause problems concerning communication and overhead, in view of which shared memory and shared disks must be considered. The strategy and the tools that were used to parallellise the programs are shown. Also, some examples are presented to illustrate effectiveness and performance of the system in Rome for these type of calculations

The BLAZE language - A parallel language for scientific programming

Science.gov (United States)

Mehrotra, Piyush; Van Rosendale, John

1987-01-01

A Pascal-like scientific programming language, BLAZE, is described. BLAZE contains array arithmetic, forall loops, and APL-style accumulation operators, which allow natural expression of fine grained parallelism. It also employs an applicative or functional procedure invocation mechanism, which makes it easy for compilers to extract coarse grained parallelism using machine specific program restructuring. Thus BLAZE should allow one to achieve highly parallel execution on multiprocessor architectures, while still providing the user with conceptually sequential control flow. A central goal in the design of BLAZE is portability across a broad range of parallel architectures. The multiple levels of parallelism present in BLAZE code, in principle, allow a compiler to extract the types of parallelism appropriate for the given architecture while neglecting the remainder. The features of BLAZE are described and it is shown how this language would be used in typical scientific programming.

The BLAZE language: A parallel language for scientific programming

Science.gov (United States)

Mehrotra, P.; Vanrosendale, J.

1985-01-01

A Pascal-like scientific programming language, Blaze, is described. Blaze contains array arithmetic, forall loops, and APL-style accumulation operators, which allow natural expression of fine grained parallelism. It also employs an applicative or functional procedure invocation mechanism, which makes it easy for compilers to extract coarse grained parallelism using machine specific program restructuring. Thus Blaze should allow one to achieve highly parallel execution on multiprocessor architectures, while still providing the user with onceptually sequential control flow. A central goal in the design of Blaze is portability across a broad range of parallel architectures. The multiple levels of parallelism present in Blaze code, in principle, allow a compiler to extract the types of parallelism appropriate for the given architecture while neglecting the remainder. The features of Blaze are described and shows how this language would be used in typical scientific programming.

Parallel programming practical aspects, models and current limitations

CERN Document Server

Tarkov, Mikhail S

2014-01-01

Parallel programming is designed for the use of parallel computer systems for solving time-consuming problems that cannot be solved on a sequential computer in a reasonable time. These problems can be divided into two classes: 1. Processing large data arrays (including processing images and signals in real time)2. Simulation of complex physical processes and chemical reactions For each of these classes, prospective methods are designed for solving problems. For data processing, one of the most promising technologies is the use of artificial neural networks. Particles-in-cell method and cellular automata are very useful for simulation. Problems of scalability of parallel algorithms and the transfer of existing parallel programs to future parallel computers are very acute now. An important task is to optimize the use of the equipment (including the CPU cache) of parallel computers. Along with parallelizing information processing, it is essential to ensure the processing reliability by the relevant organization ...

On the Automatic Parallelization of Sparse and Irregular Fortran Programs

Directory of Open Access Journals (Sweden)

Yuan Lin

1999-01-01

Full Text Available Automatic parallelization is usually believed to be less effective at exploiting implicit parallelism in sparse/irregular programs than in their dense/regular counterparts. However, not much is really known because there have been few research reports on this topic. In this work, we have studied the possibility of using an automatic parallelizing compiler to detect the parallelism in sparse/irregular programs. The study with a collection of sparse/irregular programs led us to some common loop patterns. Based on these patterns new techniques were derived that produced good speedups when manually applied to our benchmark codes. More importantly, these parallelization methods can be implemented in a parallelizing compiler and can be applied automatically.

Survey on present status and trend of parallel programming environments

International Nuclear Information System (INIS)

Takemiya, Hiroshi; Higuchi, Kenji; Honma, Ichiro; Ohta, Hirofumi; Kawasaki, Takuji; Imamura, Toshiyuki; Koide, Hiroshi; Akimoto, Masayuki.

1997-03-01

This report intends to provide useful information on software tools for parallel programming through the survey on parallel programming environments of the following six parallel computers, Fujitsu VPP300/500, NEC SX-4, Hitachi SR2201, Cray T94, IBM SP, and Intel Paragon, all of which are installed at Japan Atomic Energy Research Institute (JAERI), moreover, the present status of R and D's on parallel softwares of parallel languages, compilers, debuggers, performance evaluation tools, and integrated tools is reported. This survey has been made as a part of our project of developing a basic software for parallel programming environment, which is designed on the concept of STA (Seamless Thinking Aid to programmers). (author)

Parallelization for first principles electronic state calculation program

International Nuclear Information System (INIS)

Watanabe, Hiroshi; Oguchi, Tamio.

1997-03-01

In this report we study the parallelization for First principles electronic state calculation program. The target machines are NEC SX-4 for shared memory type parallelization and FUJITSU VPP300 for distributed memory type parallelization. The features of each parallel machine are surveyed, and the parallelization methods suitable for each are proposed. It is shown that 1.60 times acceleration is achieved with 2 CPU parallelization by SX-4 and 4.97 times acceleration is achieved with 12 PE parallelization by VPP 300. (author)

An object-oriented programming paradigm for parallelization of computational fluid dynamics

International Nuclear Information System (INIS)

Ohta, Takashi.

1997-03-01

We propose an object-oriented programming paradigm for parallelization of scientific computing programs, and show that the approach can be a very useful strategy. Generally, parallelization of scientific programs tends to be complicated and unportable due to the specific requirements of each parallel computer or compiler. In this paper, we show that the object-oriented programming design, which separates the parallel processing parts from the solver of the applications, can achieve the large improvement in the maintenance of the codes, as well as the high portability. We design the program for the two-dimensional Euler equations according to the paradigm, and evaluate the parallel performance on IBM SP2. (author)

Testing New Programming Paradigms with NAS Parallel Benchmarks

Science.gov (United States)

Jin, H.; Frumkin, M.; Schultz, M.; Yan, J.

2000-01-01

Over the past decade, high performance computing has evolved rapidly, not only in hardware architectures but also with increasing complexity of real applications. Technologies have been developing to aim at scaling up to thousands of processors on both distributed and shared memory systems. Development of parallel programs on these computers is always a challenging task. Today, writing parallel programs with message passing (e.g. MPI) is the most popular way of achieving scalability and high performance. However, writing message passing programs is difficult and error prone. Recent years new effort has been made in defining new parallel programming paradigms. The best examples are: HPF (based on data parallelism) and OpenMP (based on shared memory parallelism). Both provide simple and clear extensions to sequential programs, thus greatly simplify the tedious tasks encountered in writing message passing programs. HPF is independent of memory hierarchy, however, due to the immaturity of compiler technology its performance is still questionable. Although use of parallel compiler directives is not new, OpenMP offers a portable solution in the shared-memory domain. Another important development involves the tremendous progress in the internet and its associated technology. Although still in its infancy, Java promisses portability in a heterogeneous environment and offers possibility to "compile once and run anywhere." In light of testing these new technologies, we implemented new parallel versions of the NAS Parallel Benchmarks (NPBs) with HPF and OpenMP directives, and extended the work with Java and Java-threads. The purpose of this study is to examine the effectiveness of alternative programming paradigms. NPBs consist of five kernels and three simulated applications that mimic the computation and data movement of large scale computational fluid dynamics (CFD) applications. We started with the serial version included in NPB2.3. Optimization of memory and cache usage

Automatic Parallelization Tool: Classification of Program Code for Parallel Computing

Directory of Open Access Journals (Sweden)

Mustafa Basthikodi

2016-04-01

Full Text Available Performance growth of single-core processors has come to a halt in the past decade, but was re-enabled by the introduction of parallelism in processors. Multicore frameworks along with Graphical Processing Units empowered to enhance parallelism broadly. Couples of compilers are updated to developing challenges forsynchronization and threading issues. Appropriate program and algorithm classifications will have advantage to a great extent to the group of software engineers to get opportunities for effective parallelization. In present work we investigated current species for classification of algorithms, in that related work on classification is discussed along with the comparison of issues that challenges the classification. The set of algorithms are chosen which matches the structure with different issues and perform given task. We have tested these algorithms utilizing existing automatic species extraction toolsalong with Bones compiler. We have added functionalities to existing tool, providing a more detailed characterization. The contributions of our work include support for pointer arithmetic, conditional and incremental statements, user defined types, constants and mathematical functions. With this, we can retain significant data which is not captured by original speciesof algorithms. We executed new theories into the device, empowering automatic characterization of program code.

Development of massively parallel quantum chemistry program SMASH

International Nuclear Information System (INIS)

Ishimura, Kazuya

2015-01-01

A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C 150 H 30 ) 2 with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer

Parallelization for X-ray crystal structural analysis program

Energy Technology Data Exchange (ETDEWEB)

Watanabe, Hiroshi [Japan Atomic Energy Research Inst., Tokyo (Japan); Minami, Masayuki; Yamamoto, Akiji

1997-10-01

In this report we study vectorization and parallelization for X-ray crystal structural analysis program. The target machine is NEC SX-4 which is a distributed/shared memory type vector parallel supercomputer. X-ray crystal structural analysis is surveyed, and a new multi-dimensional discrete Fourier transform method is proposed. The new method is designed to have a very long vector length, so that it enables to obtain the 12.0 times higher performance result that the original code. Besides the above-mentioned vectorization, the parallelization by micro-task functions on SX-4 reaches 13.7 times acceleration in the part of multi-dimensional discrete Fourier transform with 14 CPUs, and 3.0 times acceleration in the whole program. Totally 35.9 times acceleration to the original 1CPU scalar version is achieved with vectorization and parallelization on SX-4. (author)

The FORCE: A highly portable parallel programming language

Science.gov (United States)

Jordan, Harry F.; Benten, Muhammad S.; Alaghband, Gita; Jakob, Ruediger

1989-01-01

Here, it is explained why the FORCE parallel programming language is easily portable among six different shared-memory microprocessors, and how a two-level macro preprocessor makes it possible to hide low level machine dependencies and to build machine-independent high level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared memory multiprocessor executing them.

The FORCE - A highly portable parallel programming language

Science.gov (United States)

Jordan, Harry F.; Benten, Muhammad S.; Alaghband, Gita; Jakob, Ruediger

1989-01-01

This paper explains why the FORCE parallel programming language is easily portable among six different shared-memory multiprocessors, and how a two-level macro preprocessor makes it possible to hide low-level machine dependencies and to build machine-independent high-level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared-memory multiprocessor executing them.

MPI_XSTAR: MPI-based Parallelization of the XSTAR Photoionization Program

Science.gov (United States)

Danehkar, Ashkbiz; Nowak, Michael A.; Lee, Julia C.; Smith, Randall K.

2018-02-01

We describe a program for the parallel implementation of multiple runs of XSTAR, a photoionization code that is used to predict the physical properties of an ionized gas from its emission and/or absorption lines. The parallelization program, called MPI_XSTAR, has been developed and implemented in the C++ language by using the Message Passing Interface (MPI) protocol, a conventional standard of parallel computing. We have benchmarked parallel multiprocessing executions of XSTAR, using MPI_XSTAR, against a serial execution of XSTAR, in terms of the parallelization speedup and the computing resource efficiency. Our experience indicates that the parallel execution runs significantly faster than the serial execution, however, the efficiency in terms of the computing resource usage decreases with increasing the number of processors used in the parallel computing.

Development of massively parallel quantum chemistry program SMASH

Energy Technology Data Exchange (ETDEWEB)

Ishimura, Kazuya [Department of Theoretical and Computational Molecular Science, Institute for Molecular Science 38 Nishigo-Naka, Myodaiji, Okazaki, Aichi 444-8585 (Japan)

2015-12-31

A massively parallel program for quantum chemistry calculations SMASH was released under the Apache License 2.0 in September 2014. The SMASH program is written in the Fortran90/95 language with MPI and OpenMP standards for parallelization. Frequently used routines, such as one- and two-electron integral calculations, are modularized to make program developments simple. The speed-up of the B3LYP energy calculation for (C{sub 150}H{sub 30}){sub 2} with the cc-pVDZ basis set (4500 basis functions) was 50,499 on 98,304 cores of the K computer.

Three dimensional Burn-up program parallelization using socket programming

International Nuclear Information System (INIS)

Haliyati R, Evi; Su'ud, Zaki

2002-01-01

A computer parallelization process was built with a purpose to decrease execution time of a physics program. In this case, a multi computer system was built to be used to analyze burn-up process of a nuclear reactor. This multi computer system was design need using a protocol communication among sockets, i.e. TCP/IP. This system consists of computer as a server and the rest as clients. The server has a main control to all its clients. The server also divides the reactor core geometrically to in parts in accordance with the number of clients, each computer including the server has a task to conduct burn-up analysis of 1/n part of the total reactor core measure. This burn-up analysis was conducted simultaneously and in a parallel way by all computers, so a faster program execution time was achieved close to 1/n times that of one computer. Then an analysis was carried out and states that in order to calculate the density of atoms in a reactor of 91 cm x 91 cm x 116 cm, the usage of a parallel system of 2 computers has the highest efficiency

Integrated Task And Data Parallel Programming: Language Design

Science.gov (United States)

Grimshaw, Andrew S.; West, Emily A.

1998-01-01

his research investigates the combination of task and data parallel language constructs within a single programming language. There are an number of applications that exhibit properties which would be well served by such an integrated language. Examples include global climate models, aircraft design problems, and multidisciplinary design optimization problems. Our approach incorporates data parallel language constructs into an existing, object oriented, task parallel language. The language will support creation and manipulation of parallel classes and objects of both types (task parallel and data parallel). Ultimately, the language will allow data parallel and task parallel classes to be used either as building blocks or managers of parallel objects of either type, thus allowing the development of single and multi-paradigm parallel applications. 1995 Research Accomplishments In February I presented a paper at Frontiers '95 describing the design of the data parallel language subset. During the spring I wrote and defended my dissertation proposal. Since that time I have developed a runtime model for the language subset. I have begun implementing the model and hand-coding simple examples which demonstrate the language subset. I have identified an astrophysical fluid flow application which will validate the data parallel language subset. 1996 Research Agenda Milestones for the coming year include implementing a significant portion of the data parallel language subset over the Legion system. Using simple hand-coded methods, I plan to demonstrate (1) concurrent task and data parallel objects and (2) task parallel objects managing both task and data parallel objects. My next steps will focus on constructing a compiler and implementing the fluid flow application with the language. Concurrently, I will conduct a search for a real-world application exhibiting both task and data parallelism within the same program m. Additional 1995 Activities During the fall I collaborated

User's guide of parallel program development environment (PPDE). The 2nd edition

International Nuclear Information System (INIS)

Ueno, Hirokazu; Takemiya, Hiroshi; Imamura, Toshiyuki; Koide, Hiroshi; Matsuda, Katsuyuki; Higuchi, Kenji; Hirayama, Toshio; Ohta, Hirofumi

2000-03-01

The STA basic system has been enhanced to accelerate support for parallel programming on heterogeneous parallel computers, through a series of R and D on the technology of parallel processing. The enhancement has been made through extending the function of the PPDF, Parallel Program Development Environment in the STA basic system. The extended PPDE has the function to make: 1) the automatic creation of a 'makefile' and a shell script file for its execution, 2) the multi-tools execution which makes the tools on heterogeneous computers to execute with one operation a task on a computer, and 3) the mirror composition to reflect editing results of a file on a computer into all related files on other computers. These additional functions will enhance the work efficiency for program development on some computers. More functions have been added to the PPDE to provide help for parallel program development. New functions were also designed to complement a HPF translator and a parallelizing support tool when working together so that a sequential program is efficiently converted to a parallel program. This report describes the use of extended PPDE. (author)

A Programming Model for Massive Data Parallelism with Data Dependencies

International Nuclear Information System (INIS)

Cui, Xiaohui; Mueller, Frank; Potok, Thomas E.; Zhang, Yongpeng

2009-01-01

Accelerating processors can often be more cost and energy effective for a wide range of data-parallel computing problems than general-purpose processors. For graphics processor units (GPUs), this is particularly the case when program development is aided by environments such as NVIDIA s Compute Unified Device Architecture (CUDA), which dramatically reduces the gap between domain-specific architectures and general purpose programming. Nonetheless, general-purpose GPU (GPGPU) programming remains subject to several restrictions. Most significantly, the separation of host (CPU) and accelerator (GPU) address spaces requires explicit management of GPU memory resources, especially for massive data parallelism that well exceeds the memory capacity of GPUs. One solution to this problem is to transfer data between the GPU and host memories frequently. In this work, we investigate another approach. We run massively data-parallel applications on GPU clusters. We further propose a programming model for massive data parallelism with data dependencies for this scenario. Experience from micro benchmarks and real-world applications shows that our model provides not only ease of programming but also significant performance gains

An environment for parallel structuring of Fortran programs

International Nuclear Information System (INIS)

Sridharan, K.; McShea, M.; Denton, C.; Eventoff, B.; Browne, J.C.; Newton, P.; Ellis, M.; Grossbard, D.; Wise, T.; Clemmer, D.

1990-01-01

The paper describes and illustrates an environment for interactive support of the detection and implementation of macro-level parallelism in Fortran programs. The approach couples algorithms for dependence analysis with both innovative techniques for complexity management and capabilities for the measurement and analysis of the parallel computation structures generated through use of the environment. The resulting environment is complementary to the more common approach of seeking local parallelism by loop unrolling, either by an automatic compiler or manually. (orig.)

Adapting high-level language programs for parallel processing using data flow

Science.gov (United States)

Standley, Hilda M.

1988-01-01

EASY-FLOW, a very high-level data flow language, is introduced for the purpose of adapting programs written in a conventional high-level language to a parallel environment. The level of parallelism provided is of the large-grained variety in which parallel activities take place between subprograms or processes. A program written in EASY-FLOW is a set of subprogram calls as units, structured by iteration, branching, and distribution constructs. A data flow graph may be deduced from an EASY-FLOW program.

Compiling Scientific Programs for Scalable Parallel Systems

National Research Council Canada - National Science Library

Kennedy, Ken

2001-01-01

...). The research performed in this project included new techniques for recognizing implicit parallelism in sequential programs, a powerful and precise set-based framework for analysis and transformation...

User's guide of parallel program development environment (PPDE). The 2nd edition

Energy Technology Data Exchange (ETDEWEB)

Ueno, Hirokazu; Takemiya, Hiroshi; Imamura, Toshiyuki; Koide, Hiroshi; Matsuda, Katsuyuki; Higuchi, Kenji; Hirayama, Toshio [Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research Institute, Tokyo (Japan); Ohta, Hirofumi [Hitachi Ltd., Tokyo (Japan)

2000-03-01

The STA basic system has been enhanced to accelerate support for parallel programming on heterogeneous parallel computers, through a series of R and D on the technology of parallel processing. The enhancement has been made through extending the function of the PPDF, Parallel Program Development Environment in the STA basic system. The extended PPDE has the function to make: 1) the automatic creation of a 'makefile' and a shell script file for its execution, 2) the multi-tools execution which makes the tools on heterogeneous computers to execute with one operation a task on a computer, and 3) the mirror composition to reflect editing results of a file on a computer into all related files on other computers. These additional functions will enhance the work efficiency for program development on some computers. More functions have been added to the PPDE to provide help for parallel program development. New functions were also designed to complement a HPF translator and a paralleilizing support tool when working together so that a sequential program is efficiently converted to a parallel program. This report describes the use of extended PPDE. (author)

Program For Parallel Discrete-Event Simulation

Science.gov (United States)

Beckman, Brian C.; Blume, Leo R.; Geiselman, John S.; Presley, Matthew T.; Wedel, John J., Jr.; Bellenot, Steven F.; Diloreto, Michael; Hontalas, Philip J.; Reiher, Peter L.; Weiland, Frederick P.

1991-01-01

User does not have to add any special logic to aid in synchronization. Time Warp Operating System (TWOS) computer program is special-purpose operating system designed to support parallel discrete-event simulation. Complete implementation of Time Warp mechanism. Supports only simulations and other computations designed for virtual time. Time Warp Simulator (TWSIM) subdirectory contains sequential simulation engine interface-compatible with TWOS. TWOS and TWSIM written in, and support simulations in, C programming language.

Cell verification of parallel burnup calculation program MCBMPI based on MPI

International Nuclear Information System (INIS)

Yang Wankui; Liu Yaoguang; Ma Jimin; Wang Guanbo; Yang Xin; She Ding

2014-01-01

The parallel burnup calculation program MCBMPI was developed. The program was modularized. The parallel MCNP5 program MCNP5MPI was employed as neutron transport calculation module. And a composite of three solution methods was used to solve burnup equation, i.e. matrix exponential technique, TTA analytical solution, and Gauss Seidel iteration. MPI parallel zone decomposition strategy was concluded in the program. The program system only consists of MCNP5MPI and burnup subroutine. The latter achieves three main functions, i.e. zone decomposition, nuclide transferring and decaying, and data exchanging with MCNP5MPI. Also, the program was verified with the pressurized water reactor (PWR) cell burnup benchmark. The results show that it,s capable to apply the program to burnup calculation of multiple zones, and the computation efficiency could be significantly improved with the development of computer hardware. (authors)

Vdebug: debugging tool for parallel scientific programs. Design report on vdebug

International Nuclear Information System (INIS)

Matsuda, Katsuyuki; Takemiya, Hiroshi

2000-02-01

We report on a debugging tool called vdebug which supports debugging work for parallel scientific simulation programs. It is difficult to debug scientific programs with an existing debugger, because the volume of data generated by the programs is too large for users to check data in characters. Usually, the existing debugger shows data values in characters. To alleviate it, we have developed vdebug which enables to check the validity of large amounts of data by showing these data values visually. Although targets of vdebug have been restricted to sequential programs, we have made it applicable to parallel programs by realizing the function of merging and visualizing data distributed on programs on each computer node. Now, vdebug works on seven kinds of parallel computers. In this report, we describe the design of vdebug. (author)

From sequential to parallel programming with patterns

CERN Document Server

CERN. Geneva

2018-01-01

To increase in both performance and efficiency, our programming models need to adapt to better exploit modern processors. The classic idioms and patterns for programming such as loops, branches or recursion are the pillars of almost every code and are well known among all programmers. These patterns all have in common that they are sequential in nature. Embracing parallel programming patterns, which allow us to program for multi- and many-core hardware in a natural way, greatly simplifies the task of designing a program that scales and performs on modern hardware, independently of the used programming language, and in a generic way.

On program restructuring, scheduling, and communication for parallel processor systems

Energy Technology Data Exchange (ETDEWEB)

Polychronopoulos, Constantine D. [Univ. of Illinois, Urbana, IL (United States)

1986-08-01

This dissertation discusses several software and hardware aspects of program execution on large-scale, high-performance parallel processor systems. The issues covered are program restructuring, partitioning, scheduling and interprocessor communication, synchronization, and hardware design issues of specialized units. All this work was performed focusing on a single goal: to maximize program speedup, or equivalently, to minimize parallel execution time. Parafrase, a Fortran restructuring compiler was used to transform programs in a parallel form and conduct experiments. Two new program restructuring techniques are presented, loop coalescing and subscript blocking. Compile-time and run-time scheduling schemes are covered extensively. Depending on the program construct, these algorithms generate optimal or near-optimal schedules. For the case of arbitrarily nested hybrid loops, two optimal scheduling algorithms for dynamic and static scheduling are presented. Simulation results are given for a new dynamic scheduling algorithm. The performance of this algorithm is compared to that of self-scheduling. Techniques for program partitioning and minimization of interprocessor communication for idealized program models and for real Fortran programs are also discussed. The close relationship between scheduling, interprocessor communication, and synchronization becomes apparent at several points in this work. Finally, the impact of various types of overhead on program speedup and experimental results are presented.

Characterizing and Mitigating Work Time Inflation in Task Parallel Programs

Directory of Open Access Journals (Sweden)

Stephen L. Olivier

2013-01-01

Full Text Available Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, and work time inflation – additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential computation. We identify the contributions of each factor to lost efficiency in various task parallel OpenMP applications and diagnose the causes of work time inflation in those applications. Increased data access latency can cause significant work time inflation in NUMA systems. Our locality framework for task parallel OpenMP programs mitigates this cause of work time inflation. Our extensions to the Qthreads library demonstrate that locality-aware scheduling can improve performance up to 3X compared to the Intel OpenMP task scheduler.

Parallel implementation of the PHOENIX generalized stellar atmosphere program. II. Wavelength parallelization

International Nuclear Information System (INIS)

Baron, E.; Hauschildt, Peter H.

1998-01-01

We describe an important addition to the parallel implementation of our generalized nonlocal thermodynamic equilibrium (NLTE) stellar atmosphere and radiative transfer computer program PHOENIX. In a previous paper in this series we described data and task parallel algorithms we have developed for radiative transfer, spectral line opacity, and NLTE opacity and rate calculations. These algorithms divided the work spatially or by spectral lines, that is, distributing the radial zones, individual spectral lines, or characteristic rays among different processors and employ, in addition, task parallelism for logically independent functions (such as atomic and molecular line opacities). For finite, monotonic velocity fields, the radiative transfer equation is an initial value problem in wavelength, and hence each wavelength point depends upon the previous one. However, for sophisticated NLTE models of both static and moving atmospheres needed to accurately describe, e.g., novae and supernovae, the number of wavelength points is very large (200,000 - 300,000) and hence parallelization over wavelength can lead both to considerable speedup in calculation time and the ability to make use of the aggregate memory available on massively parallel supercomputers. Here, we describe an implementation of a pipelined design for the wavelength parallelization of PHOENIX, where the necessary data from the processor working on a previous wavelength point is sent to the processor working on the succeeding wavelength point as soon as it is known. Our implementation uses a MIMD design based on a relatively small number of standard message passing interface (MPI) library calls and is fully portable between serial and parallel computers. copyright 1998 The American Astronomical Society

Parallel Volunteer Learning during Youth Programs

Science.gov (United States)

Lesmeister, Marilyn K.; Green, Jeremy; Derby, Amy; Bothum, Candi

2012-01-01

Lack of time is a hindrance for volunteers to participate in educational opportunities, yet volunteer success in an organization is tied to the orientation and education they receive. Meeting diverse educational needs of volunteers can be a challenge for program managers. Scheduling a Volunteer Learning Track for chaperones that is parallel to a…

Communications oriented programming of parallel iterative solutions of sparse linear systems

Science.gov (United States)

Patrick, M. L.; Pratt, T. W.

1986-01-01

Parallel algorithms are developed for a class of scientific computational problems by partitioning the problems into smaller problems which may be solved concurrently. The effectiveness of the resulting parallel solutions is determined by the amount and frequency of communication and synchronization and the extent to which communication can be overlapped with computation. Three different parallel algorithms for solving the same class of problems are presented, and their effectiveness is analyzed from this point of view. The algorithms are programmed using a new programming environment. Run-time statistics and experience obtained from the execution of these programs assist in measuring the effectiveness of these algorithms.

Massive parallel electromagnetic field simulation program JEMS-FDTD design and implementation on jasmin

International Nuclear Information System (INIS)

Li Hanyu; Zhou Haijing; Dong Zhiwei; Liao Cheng; Chang Lei; Cao Xiaolin; Xiao Li

2010-01-01

A large-scale parallel electromagnetic field simulation program JEMS-FDTD(J Electromagnetic Solver-Finite Difference Time Domain) is designed and implemented on JASMIN (J parallel Adaptive Structured Mesh applications INfrastructure). This program can simulate propagation, radiation, couple of electromagnetic field by solving Maxwell equations on structured mesh explicitly with FDTD method. JEMS-FDTD is able to simulate billion-mesh-scale problems on thousands of processors. In this article, the program is verified by simulating the radiation of an electric dipole. A beam waveguide is simulated to demonstrate the capability of large scale parallel computation. A parallel performance test indicates that a high parallel efficiency is obtained. (authors)

Development and benchmark verification of a parallelized Monte Carlo burnup calculation program MCBMPI

International Nuclear Information System (INIS)

Yang Wankui; Liu Yaoguang; Ma Jimin; Yang Xin; Wang Guanbo

2014-01-01

MCBMPI, a parallelized burnup calculation program, was developed. The program is modularized. Neutron transport calculation module employs the parallelized MCNP5 program MCNP5MPI, and burnup calculation module employs ORIGEN2, with the MPI parallel zone decomposition strategy. The program system only consists of MCNP5MPI and an interface subroutine. The interface subroutine achieves three main functions, i.e. zone decomposition, nuclide transferring and decaying, data exchanging with MCNP5MPI. Also, the program was verified with the Pressurized Water Reactor (PWR) cell burnup benchmark, the results showed that it's capable to apply the program to burnup calculation of multiple zones, and the computation efficiency could be significantly improved with the development of computer hardware. (authors)

User's guide of parallel program development environment (PPDE). The 2nd edition

Energy Technology Data Exchange (ETDEWEB)

Ueno, Hirokazu; Takemiya, Hiroshi; Imamura, Toshiyuki; Koide, Hiroshi; Matsuda, Katsuyuki; Higuchi, Kenji; Hirayama, Toshio [Center for Promotion of Computational Science and Engineering, Japan Atomic Energy Research Institute, Tokyo (Japan); Ohta, Hirofumi [Hitachi Ltd., Tokyo (Japan)

2000-03-01

The STA basic system has been enhanced to accelerate support for parallel programming on heterogeneous parallel computers, through a series of R and D on the technology of parallel processing. The enhancement has been made through extending the function of the PPDF, Parallel Program Development Environment in the STA basic system. The extended PPDE has the function to make: 1) the automatic creation of a 'makefile' and a shell script file for its execution, 2) the multi-tools execution which makes the tools on heterogeneous computers to execute with one operation a task on a computer, and 3) the mirror composition to reflect editing results of a file on a computer into all related files on other computers. These additional functions will enhance the work efficiency for program development on some computers. More functions have been added to the PPDE to provide help for parallel program development. New functions were also designed to complement a HPF translator and a paralleilizing support tool when working together so that a sequential program is efficiently converted to a parallel program. This report describes the use of extended PPDE. (author)

Compiling the parallel programming language NestStep to the CELL processor

OpenAIRE

Holm, Magnus

2010-01-01

The goal of this project is to create a source-to-source compiler which will translate NestStep code to C code. The compiler's job is to replace NestStep constructs with a series of function calls to the NestStep runtime system. NestStep is a parallel programming language extension based on the BSP model. It adds constructs for parallel programming on top of an imperative programming language. For this project, only constructs extending the C language are relevant. The output code will compil...

A language for data-parallel and task parallel programming dedicated to multi-SIMD computers. Contributions to hydrodynamic simulation with lattice gases

International Nuclear Information System (INIS)

Pic, Marc Michel

1995-01-01

Parallel programming covers task-parallelism and data-parallelism. Many problems need both parallelisms. Multi-SIMD computers allow hierarchical approach of these parallelisms. The T++ language, based on C++, is dedicated to exploit Multi-SIMD computers using a programming paradigm which is an extension of array-programming to tasks managing. Our language introduced array of independent tasks to achieve separately (MIMD), on subsets of processors of identical behaviour (SIMD), in order to translate the hierarchical inclusion of data-parallelism in task-parallelism. To manipulate in a symmetrical way tasks and data we propose meta-operations which have the same behaviour on tasks arrays and on data arrays. We explain how to implement this language on our parallel computer SYMPHONIE in order to profit by the locally-shared memory, by the hardware virtualization, and by the multiplicity of communications networks. We analyse simultaneously a typical application of such architecture. Finite elements scheme for Fluid mechanic needs powerful parallel computers and requires large floating points abilities. Lattice gases is an alternative to such simulations. Boolean lattice bases are simple, stable, modular, need to floating point computation, but include numerical noise. Boltzmann lattice gases present large precision of computation, but needs floating points and are only locally stable. We propose a new scheme, called multi-bit, who keeps the advantages of each boolean model to which it is applied, with large numerical precision and reduced noise. Experiments on viscosity, physical behaviour, noise reduction and spurious invariants are shown and implementation techniques for parallel Multi-SIMD computers detailed. (author) [fr

Contributions to computational stereology and parallel programming

DEFF Research Database (Denmark)

Rasmusson, Allan

rotator, even without the need for isotropic sections. To meet the need for computational power to perform image restoration of virtual tissue sections, parallel programming on GPUs has also been part of the project. This has lead to a significant change in paradigm for a previously developed surgical...

Heterogeneous Multicore Parallel Programming for Graphics Processing Units

Directory of Open Access Journals (Sweden)

Francois Bodin

2009-01-01

Full Text Available Hybrid parallel multicore architectures based on graphics processing units (GPUs can provide tremendous computing power. Current NVIDIA and AMD Graphics Product Group hardware display a peak performance of hundreds of gigaflops. However, exploiting GPUs from existing applications is a difficult task that requires non-portable rewriting of the code. In this paper, we present HMPP, a Heterogeneous Multicore Parallel Programming workbench with compilers, developed by CAPS entreprise, that allows the integration of heterogeneous hardware accelerators in a unintrusive manner while preserving the legacy code.

Parallel programming of saccades during natural scene viewing: evidence from eye movement positions.

Science.gov (United States)

Wu, Esther X W; Gilani, Syed Omer; van Boxtel, Jeroen J A; Amihai, Ido; Chua, Fook Kee; Yen, Shih-Cheng

2013-10-24

Previous studies have shown that saccade plans during natural scene viewing can be programmed in parallel. This evidence comes mainly from temporal indicators, i.e., fixation durations and latencies. In the current study, we asked whether eye movement positions recorded during scene viewing also reflect parallel programming of saccades. As participants viewed scenes in preparation for a memory task, their inspection of the scene was suddenly disrupted by a transition to another scene. We examined whether saccades after the transition were invariably directed immediately toward the center or were contingent on saccade onset times relative to the transition. The results, which showed a dissociation in eye movement behavior between two groups of saccades after the scene transition, supported the parallel programming account. Saccades with relatively long onset times (>100 ms) after the transition were directed immediately toward the center of the scene, probably to restart scene exploration. Saccades with short onset times (programming of saccades during scene viewing. Additionally, results from the analyses of intersaccadic intervals were also consistent with the parallel programming hypothesis.

Basic design of parallel computational program for probabilistic structural analysis

International Nuclear Information System (INIS)

Kaji, Yoshiyuki; Arai, Taketoshi; Gu, Wenwei; Nakamura, Hitoshi

1999-06-01

In our laboratory, for 'development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory' (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)

Basic design of parallel computational program for probabilistic structural analysis

Energy Technology Data Exchange (ETDEWEB)

Kaji, Yoshiyuki; Arai, Taketoshi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment; Gu, Wenwei; Nakamura, Hitoshi

1999-06-01

In our laboratory, for `development of damage evaluation method of structural brittle materials by microscopic fracture mechanics and probabilistic theory` (nuclear computational science cross-over research) we examine computational method related to super parallel computation system which is coupled with material strength theory based on microscopic fracture mechanics for latent cracks and continuum structural model to develop new structural reliability evaluation methods for ceramic structures. This technical report is the review results regarding probabilistic structural mechanics theory, basic terms of formula and program methods of parallel computation which are related to principal terms in basic design of computational mechanics program. (author)

On the Performance of the Python Programming Language for Serial and Parallel Scientific Computations

Directory of Open Access Journals (Sweden)

Xing Cai

2005-01-01

Full Text Available This article addresses the performance of scientific applications that use the Python programming language. First, we investigate several techniques for improving the computational efficiency of serial Python codes. Then, we discuss the basic programming techniques in Python for parallelizing serial scientific applications. It is shown that an efficient implementation of the array-related operations is essential for achieving good parallel performance, as for the serial case. Once the array-related operations are efficiently implemented, probably using a mixed-language implementation, good serial and parallel performance become achievable. This is confirmed by a set of numerical experiments. Python is also shown to be well suited for writing high-level parallel programs.

MulticoreBSP for C : A high-performance library for shared-memory parallel programming

NARCIS (Netherlands)

Yzelman, A. N.; Bisseling, R. H.; Roose, D.; Meerbergen, K.

2014-01-01

The bulk synchronous parallel (BSP) model, as well as parallel programming interfaces based on BSP, classically target distributed-memory parallel architectures. In earlier work, Yzelman and Bisseling designed a MulticoreBSP for Java library specifically for shared-memory architectures. In the

A multithreaded parallel implementation of a dynamic programming algorithm for sequence comparison.

Science.gov (United States)

Martins, W S; Del Cuvillo, J B; Useche, F J; Theobald, K B; Gao, G R

2001-01-01

This paper discusses the issues involved in implementing a dynamic programming algorithm for biological sequence comparison on a general-purpose parallel computing platform based on a fine-grain event-driven multithreaded program execution model. Fine-grain multithreading permits efficient parallelism exploitation in this application both by taking advantage of asynchronous point-to-point synchronizations and communication with low overheads and by effectively tolerating latency through the overlapping of computation and communication. We have implemented our scheme on EARTH, a fine-grain event-driven multithreaded execution and architecture model which has been ported to a number of parallel machines with off-the-shelf processors. Our experimental results show that the dynamic programming algorithm can be efficiently implemented on EARTH systems with high performance (e.g., speedup of 90 on 120 nodes), good programmability and reasonable cost.

High performance parallelism pearls 2 multicore and many-core programming approaches

CERN Document Server

Jeffers, Jim

2015-01-01

High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to Volume 1, the techniques included here explain how to use processors and coprocessors with the same programming - illustrating the most effective ways to combine Xeon Phi coprocessors with Xeon and other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as biomed, genetics, finance, manufacturing, imaging, and more. Each chapter in this edited work includes detailed explanations of t

Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language

KAUST Repository

Klein, Tobias

2016-04-19

The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This facilitates understanding a program\\'s function and structure, finding the causes of possible slowdowns, locating program bugs, and interactively exploring and visually comparing different code variants in order to improve performance and correctness. Our approach enables very specific, user-centered analysis, both in terms of the recording of the run-time behavior and the visualization itself. Instead of having to manually write instrumented code to record data, simple code annotations tell the source-to-source compiler which code instrumentation to generate automatically. The visualization part of our framework then enables the interactive analysis of kernel run-time behavior in a way that can be very specific to a particular problem or optimization goal, such as analyzing the causes of memory bank conflicts or understanding an entire parallel algorithm.

Run-Time and Compiler Support for Programming in Adaptive Parallel Environments

Directory of Open Access Journals (Sweden)

Guy Edjlali

1997-01-01

Full Text Available For better utilization of computing resources, it is important to consider parallel programming environments in which the number of available processors varies at run-time. In this article, we discuss run-time support for data-parallel programming in such an adaptive environment. Executing programs in an adaptive environment requires redistributing data when the number of processors changes, and also requires determining new loop bounds and communication patterns for the new set of processors. We have developed a run-time library to provide this support. We discuss how the run-time library can be used by compilers of high-performance Fortran (HPF-like languages to generate code for an adaptive environment. We present performance results for a Navier-Stokes solver and a multigrid template run on a network of workstations and an IBM SP-2. Our experiments show that if the number of processors is not varied frequently, the cost of data redistribution is not significant compared to the time required for the actual computation. Overall, our work establishes the feasibility of compiling HPF for a network of nondedicated workstations, which are likely to be an important resource for parallel programming in the future.

Scientific programming on massively parallel processor CP-PACS

International Nuclear Information System (INIS)

Boku, Taisuke

1998-01-01

The massively parallel processor CP-PACS takes various problems of calculation physics as the object, and it has been designed so that its architecture has been devised to do various numerical processings. In this report, the outline of the CP-PACS and the example of programming in the Kernel CG benchmark in NAS Parallel Benchmarks, version 1, are shown, and the pseudo vector processing mechanism and the parallel processing tuning of scientific and technical computation utilizing the three-dimensional hyper crossbar net, which are two great features of the architecture of the CP-PACS are described. As for the CP-PACS, the PUs based on RISC processor and added with pseudo vector processor are used. Pseudo vector processing is realized as the loop processing by scalar command. The features of the connection net of PUs are explained. The algorithm of the NPB version 1 Kernel CG is shown. The part that takes the time for processing most in the main loop is the product of matrix and vector (matvec), and the parallel processing of the matvec is explained. The time for the computation by the CPU is determined. As the evaluation of the performance, the evaluation of the time for execution, the short vector processing of pseudo vector processor based on slide window, and the comparison with other parallel computers are reported. (K.I.)

F-Nets and Software Cabling: Deriving a Formal Model and Language for Portable Parallel Programming

Science.gov (United States)

DiNucci, David C.; Saini, Subhash (Technical Monitor)

1998-01-01

Parallel programming is still being based upon antiquated sequence-based definitions of the terms "algorithm" and "computation", resulting in programs which are architecture dependent and difficult to design and analyze. By focusing on obstacles inherent in existing practice, a more portable model is derived here, which is then formalized into a model called Soviets which utilizes a combination of imperative and functional styles. This formalization suggests more general notions of algorithm and computation, as well as insights into the meaning of structured programming in a parallel setting. To illustrate how these principles can be applied, a very-high-level graphical architecture-independent parallel language, called Software Cabling, is described, with many of the features normally expected from today's computer languages (e.g. data abstraction, data parallelism, and object-based programming constructs).

Evolution of a minimal parallel programming model

International Nuclear Information System (INIS)

Lusk, Ewing; Butler, Ralph; Pieper, Steven C.

2017-01-01

Here, we take a historical approach to our presentation of self-scheduled task parallelism, a programming model with its origins in early irregular and nondeterministic computations encountered in automated theorem proving and logic programming. We show how an extremely simple task model has evolved into a system, asynchronous dynamic load balancing (ADLB), and a scalable implementation capable of supporting sophisticated applications on today’s (and tomorrow’s) largest supercomputers; and we illustrate the use of ADLB with a Green’s function Monte Carlo application, a modern, mature nuclear physics code in production use. Our lesson is that by surrendering a certain amount of generality and thus applicability, a minimal programming model (in terms of its basic concepts and the size of its application programmer interface) can achieve extreme scalability without introducing complexity.

Towards Interactive Visual Exploration of Parallel Programs using a Domain-Specific Language

KAUST Repository

Klein, Tobias; Bruckner, Stefan; Grö ller, M. Eduard; Hadwiger, Markus; Rautek, Peter

2016-01-01

The use of GPUs and the massively parallel computing paradigm have become wide-spread. We describe a framework for the interactive visualization and visual analysis of the run-time behavior of massively parallel programs, especially OpenCL kernels. This facilitates understanding a program's function and structure, finding the causes of possible slowdowns, locating program bugs, and interactively exploring and visually comparing different code variants in order to improve performance and correctness. Our approach enables very specific, user-centered analysis, both in terms of the recording of the run-time behavior and the visualization itself. Instead of having to manually write instrumented code to record data, simple code annotations tell the source-to-source compiler which code instrumentation to generate automatically. The visualization part of our framework then enables the interactive analysis of kernel run-time behavior in a way that can be very specific to a particular problem or optimization goal, such as analyzing the causes of memory bank conflicts or understanding an entire parallel algorithm.

A backtracking algorithm for the stream AND-parallel execution of logic programs

Energy Technology Data Exchange (ETDEWEB)

Somogyi, Z.; Ramamohanarao, K.; Vaghani, J. (Univ. of Melbourne, Parkville (Australia))

1988-06-01

The authors present the first backtracking algorithm for stream AND-parallel logic programs. It relies on compile-time knowledge of the data flow graph of each clause to let it figure out efficiently which goals to kill or restart when a goal fails. This crucial information, which they derive from mode declarations, was not available at compile-time in any previous stream AND-parallel system. They show that modes can increase the precision of the backtracking algorithm, though their algorithm allows this precision to be traded off against overhead on a procedure-by-procedure and call-by-call basis. The modes also allow their algorithm to handle efficiently programs that manipulate partially instantiated data structures and an important class of programs with circular dependency graphs. On code that does not need backtracking, the efficiency of their algorithm approaches that of the committed-choice languages; on code that does need backtracking its overhead is comparable to that of the independent AND-parallel backtracking algorithms.

Feedback Driven Annotation and Refactoring of Parallel Programs

DEFF Research Database (Denmark)

Larsen, Per

and communication in embedded programs. Runtime checks are developed to ensure that annotations correctly describe observable program behavior. The performance impact of runtime checking is evaluated on several benchmark kernels and is negligible in all cases. The second aspect is compilation feedback. Annotations...... are not effective unless programmers are told how and when they are benecial. A prototype compilation feedback system was developed in collaboration with IBM Haifa Research Labs. It reports issues that prevent further analysis to the programmer. Performance evaluation shows that three programs performes signicantly......This thesis combines programmer knowledge and feedback to improve modeling and optimization of software. The research is motivated by two observations. First, there is a great need for automatic analysis of software for embedded systems - to expose and model parallelism inherent in programs. Second...

Process-Oriented Parallel Programming with an Application to Data-Intensive Computing

OpenAIRE

Givelberg, Edward

2014-01-01

We introduce process-oriented programming as a natural extension of object-oriented programming for parallel computing. It is based on the observation that every class of an object-oriented language can be instantiated as a process, accessible via a remote pointer. The introduction of process pointers requires no syntax extension, identifies processes with programming objects, and enables processes to exchange information simply by executing remote methods. Process-oriented programming is a h...

P3T+: A Performance Estimator for Distributed and Parallel Programs

Directory of Open Access Journals (Sweden)

T. Fahringer

2000-01-01

Full Text Available Developing distributed and parallel programs on today's multiprocessor architectures is still a challenging task. Particular distressing is the lack of effective performance tools that support the programmer in evaluating changes in code, problem and machine sizes, and target architectures. In this paper we introduce P3T+ which is a performance estimator for mostly regular HPF (High Performance Fortran programs but partially covers also message passing programs (MPI. P3T+ is unique by modeling programs, compiler code transformations, and parallel and distributed architectures. It computes at compile-time a variety of performance parameters including work distribution, number of transfers, amount of data transferred, transfer times, computation times, and number of cache misses. Several novel technologies are employed to compute these parameters: loop iteration spaces, array access patterns, and data distributions are modeled by employing highly effective symbolic analysis. Communication is estimated by simulating the behavior of a communication library used by the underlying compiler. Computation times are predicted through pre-measured kernels on every target architecture of interest. We carefully model most critical architecture specific factors such as cache lines sizes, number of cache lines available, startup times, message transfer time per byte, etc. P3T+ has been implemented and is closely integrated with the Vienna High Performance Compiler (VFC to support programmers develop parallel and distributed applications. Experimental results for realistic kernel codes taken from real-world applications are presented to demonstrate both accuracy and usefulness of P3T+.

Academic training: From Evolution Theory to Parallel and Distributed Genetic Programming

CERN Multimedia

2007-01-01

2006-2007 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 15, 16 March From 11:00 to 12:00 - Main Auditorium, bldg. 500 From Evolution Theory to Parallel and Distributed Genetic Programming F. FERNANDEZ DE VEGA / Univ. of Extremadura, SP Lecture No. 1: From Evolution Theory to Evolutionary Computation Evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) involving combinatorial optimization problems, which are based to some degree on the evolution of biological life in the natural world. In this tutorial we will review the source of inspiration for this metaheuristic and its capability for solving problems. We will show the main flavours within the field, and different problems that have been successfully solved employing this kind of techniques. Lecture No. 2: Parallel and Distributed Genetic Programming The successful application of Genetic Programming (GP, one of the available Evolutionary Algorithms) to optimization problems has encouraged an ...

Application Portable Parallel Library

Science.gov (United States)

Cole, Gary L.; Blech, Richard A.; Quealy, Angela; Townsend, Scott

1995-01-01

Application Portable Parallel Library (APPL) computer program is subroutine-based message-passing software library intended to provide consistent interface to variety of multiprocessor computers on market today. Minimizes effort needed to move application program from one computer to another. User develops application program once and then easily moves application program from parallel computer on which created to another parallel computer. ("Parallel computer" also include heterogeneous collection of networked computers). Written in C language with one FORTRAN 77 subroutine for UNIX-based computers and callable from application programs written in C language or FORTRAN 77.

Final Report: Center for Programming Models for Scalable Parallel Computing

Energy Technology Data Exchange (ETDEWEB)

Mellor-Crummey, John [William Marsh Rice University

2011-09-13

As part of the Center for Programming Models for Scalable Parallel Computing, Rice University collaborated with project partners in the design, development and deployment of language, compiler, and runtime support for parallel programming models to support application development for the “leadership-class” computer systems at DOE national laboratories. Work over the course of this project has focused on the design, implementation, and evaluation of a second-generation version of Coarray Fortran. Research and development efforts of the project have focused on the CAF 2.0 language, compiler, runtime system, and supporting infrastructure. This has involved working with the teams that provide infrastructure for CAF that we rely on, implementing new language and runtime features, producing an open source compiler that enabled us to evaluate our ideas, and evaluating our design and implementation through the use of benchmarks. The report details the research, development, findings, and conclusions from this work.

76 FR 62808 - Pilot Program for Parallel Review of Medical Products

Science.gov (United States)

2011-10-11

... voluntary participation in the pilot program, as well as the guiding principles the Agencies intend to... 57045), parallel review is intended to reduce the time between FDA marketing approval and CMS national...

Empirical valence bond models for reactive potential energy surfaces: a parallel multilevel genetic program approach.

Science.gov (United States)

Bellucci, Michael A; Coker, David F

2011-07-28

We describe a new method for constructing empirical valence bond potential energy surfaces using a parallel multilevel genetic program (PMLGP). Genetic programs can be used to perform an efficient search through function space and parameter space to find the best functions and sets of parameters that fit energies obtained by ab initio electronic structure calculations. Building on the traditional genetic program approach, the PMLGP utilizes a hierarchy of genetic programming on two different levels. The lower level genetic programs are used to optimize coevolving populations in parallel while the higher level genetic program (HLGP) is used to optimize the genetic operator probabilities of the lower level genetic programs. The HLGP allows the algorithm to dynamically learn the mutation or combination of mutations that most effectively increase the fitness of the populations, causing a significant increase in the algorithm's accuracy and efficiency. The algorithm's accuracy and efficiency is tested against a standard parallel genetic program with a variety of one-dimensional test cases. Subsequently, the PMLGP is utilized to obtain an accurate empirical valence bond model for proton transfer in 3-hydroxy-gamma-pyrone in gas phase and protic solvent. © 2011 American Institute of Physics

Implementing the PM Programming Language using MPI and OpenMP - a New Tool for Programming Geophysical Models on Parallel Systems

Science.gov (United States)

Bellerby, Tim

2015-04-01

PM (Parallel Models) is a new parallel programming language specifically designed for writing environmental and geophysical models. The language is intended to enable implementers to concentrate on the science behind the model rather than the details of running on parallel hardware. At the same time PM leaves the programmer in control - all parallelisation is explicit and the parallel structure of any given program may be deduced directly from the code. This paper describes a PM implementation based on the Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) standards, looking at issues involved with translating the PM parallelisation model to MPI/OpenMP protocols and considering performance in terms of the competing factors of finer-grained parallelisation and increased communication overhead. In order to maximise portability, the implementation stays within the MPI 1.3 standard as much as possible, with MPI-2 MPI-IO file handling the only significant exception. Moreover, it does not assume a thread-safe implementation of MPI. PM adopts a two-tier abstract representation of parallel hardware. A PM processor is a conceptual unit capable of efficiently executing a set of language tasks, with a complete parallel system consisting of an abstract N-dimensional array of such processors. PM processors may map to single cores executing tasks using cooperative multi-tasking, to multiple cores or even to separate processing nodes, efficiently sharing tasks using algorithms such as work stealing. While tasks may move between hardware elements within a PM processor, they may not move between processors without specific programmer intervention. Tasks are assigned to processors using a nested parallelism approach, building on ideas from Reyes et al. (2009). The main program owns all available processors. When the program enters a parallel statement then either processors are divided out among the newly generated tasks (number of new tasks number of processors

76 FR 66309 - Pilot Program for Parallel Review of Medical Products; Correction

Science.gov (United States)

2011-10-26

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Medicare and Medicaid Services [CMS-3180-N2] Food and Drug Administration [Docket No. FDA-2010-N-0308] Pilot Program for Parallel Review of Medical... 11, 2011 (76 FR 62808). The document announced a pilot program for sponsors of innovative device...

Teaching Scientific Computing: A Model-Centered Approach to Pipeline and Parallel Programming with C

Directory of Open Access Journals (Sweden)

Vladimiras Dolgopolovas

2015-01-01

Full Text Available The aim of this study is to present an approach to the introduction into pipeline and parallel computing, using a model of the multiphase queueing system. Pipeline computing, including software pipelines, is among the key concepts in modern computing and electronics engineering. The modern computer science and engineering education requires a comprehensive curriculum, so the introduction to pipeline and parallel computing is the essential topic to be included in the curriculum. At the same time, the topic is among the most motivating tasks due to the comprehensive multidisciplinary and technical requirements. To enhance the educational process, the paper proposes a novel model-centered framework and develops the relevant learning objects. It allows implementing an educational platform of constructivist learning process, thus enabling learners’ experimentation with the provided programming models, obtaining learners’ competences of the modern scientific research and computational thinking, and capturing the relevant technical knowledge. It also provides an integral platform that allows a simultaneous and comparative introduction to pipelining and parallel computing. The programming language C for developing programming models and message passing interface (MPI and OpenMP parallelization tools have been chosen for implementation.

Massively Parallel Finite Element Programming

KAUST Repository

Heister, Timo; Kronbichler, Martin; Bangerth, Wolfgang

2010-01-01

Today's large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal.II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability. © 2010 Springer-Verlag.

Massively Parallel Finite Element Programming

KAUST Repository

Heister, Timo

2010-01-01

Today\\'s large finite element simulations require parallel algorithms to scale on clusters with thousands or tens of thousands of processor cores. We present data structures and algorithms to take advantage of the power of high performance computers in generic finite element codes. Existing generic finite element libraries often restrict the parallelization to parallel linear algebra routines. This is a limiting factor when solving on more than a few hundreds of cores. We describe routines for distributed storage of all major components coupled with efficient, scalable algorithms. We give an overview of our effort to enable the modern and generic finite element library deal.II to take advantage of the power of large clusters. In particular, we describe the construction of a distributed mesh and develop algorithms to fully parallelize the finite element calculation. Numerical results demonstrate good scalability. © 2010 Springer-Verlag.

Feasibility studies for a high energy physics MC program on massive parallel platforms

International Nuclear Information System (INIS)

Bertolotto, L.M.; Peach, K.J.; Apostolakis, J.; Bruschini, C.E.; Calafiura, P.; Gagliardi, F.; Metcalf, M.; Norton, A.; Panzer-Steindel, B.

1994-01-01

The parallelization of a Monte Carlo program for the NA48 experiment is presented. As a first step, a task farming structure was realized. Based on this, a further step, making use of a distributed database for showers in the electro-magnetic calorimeter, was implemented. Further possibilities for using parallel processing for a quasi-real time calibration of the calorimeter are described

Parallel programming with Python

CERN Document Server

Palach, Jan

2014-01-01

A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.

Enabling Requirements-Based Programming for Highly-Dependable Complex Parallel and Distributed Systems

Science.gov (United States)

Hinchey, Michael G.; Rash, James L.; Rouff, Christopher A.

2005-01-01

The manual application of formal methods in system specification has produced successes, but in the end, despite any claims and assertions by practitioners, there is no provable relationship between a manually derived system specification or formal model and the customer's original requirements. Complex parallel and distributed system present the worst case implications for today s dearth of viable approaches for achieving system dependability. No avenue other than formal methods constitutes a serious contender for resolving the problem, and so recognition of requirements-based programming has come at a critical juncture. We describe a new, NASA-developed automated requirement-based programming method that can be applied to certain classes of systems, including complex parallel and distributed systems, to achieve a high degree of dependability.

Compiler Technology for Parallel Scientific Computation

Directory of Open Access Journals (Sweden)

Can Özturan

1994-01-01

Full Text Available There is a need for compiler technology that, given the source program, will generate efficient parallel codes for different architectures with minimal user involvement. Parallel computation is becoming indispensable in solving large-scale problems in science and engineering. Yet, the use of parallel computation is limited by the high costs of developing the needed software. To overcome this difficulty we advocate a comprehensive approach to the development of scalable architecture-independent software for scientific computation based on our experience with equational programming language (EPL. Our approach is based on a program decomposition, parallel code synthesis, and run-time support for parallel scientific computation. The program decomposition is guided by the source program annotations provided by the user. The synthesis of parallel code is based on configurations that describe the overall computation as a set of interacting components. Run-time support is provided by the compiler-generated code that redistributes computation and data during object program execution. The generated parallel code is optimized using techniques of data alignment, operator placement, wavefront determination, and memory optimization. In this article we discuss annotations, configurations, parallel code generation, and run-time support suitable for parallel programs written in the functional parallel programming language EPL and in Fortran.

Practical parallel programming

CERN Document Server

Bauer, Barr E

2014-01-01

This is the book that will teach programmers to write faster, more efficient code for parallel processors. The reader is introduced to a vast array of procedures and paradigms on which actual coding may be based. Examples and real-life simulations using these devices are presented in C and FORTRAN.

The FORCE: A portable parallel programming language supporting computational structural mechanics

Science.gov (United States)

Jordan, Harry F.; Benten, Muhammad S.; Brehm, Juergen; Ramanan, Aruna

1989-01-01

This project supports the conversion of codes in Computational Structural Mechanics (CSM) to a parallel form which will efficiently exploit the computational power available from multiprocessors. The work is a part of a comprehensive, FORTRAN-based system to form a basis for a parallel version of the NICE/SPAR combination which will form the CSM Testbed. The software is macro-based and rests on the force methodology developed by the principal investigator in connection with an early scientific multiprocessor. Machine independence is an important characteristic of the system so that retargeting it to the Flex/32, or any other multiprocessor on which NICE/SPAR might be imnplemented, is well supported. The principal investigator has experience in producing parallel software for both full and sparse systems of linear equations using the force macros. Other researchers have used the Force in finite element programs. It has been possible to rapidly develop software which performs at maximum efficiency on a multiprocessor. The inherent machine independence of the system also means that the parallelization will not be limited to a specific multiprocessor.

Parallelization and checkpointing of GPU applications through program transformation

Energy Technology Data Exchange (ETDEWEB)

Solano-Quinde, Lizandro Damian [Iowa State Univ., Ames, IA (United States)

2012-01-01

GPUs have emerged as a powerful tool for accelerating general-purpose applications. The availability of programming languages that makes writing general-purpose applications for running on GPUs tractable have consolidated GPUs as an alternative for accelerating general purpose applications. Among the areas that have benefited from GPU acceleration are: signal and image processing, computational fluid dynamics, quantum chemistry, and, in general, the High Performance Computing (HPC) Industry. In order to continue to exploit higher levels of parallelism with GPUs, multi-GPU systems are gaining popularity. In this context, single-GPU applications are parallelized for running in multi-GPU systems. Furthermore, multi-GPU systems help to solve the GPU memory limitation for applications with large application memory footprint. Parallelizing single-GPU applications has been approached by libraries that distribute the workload at runtime, however, they impose execution overhead and are not portable. On the other hand, on traditional CPU systems, parallelization has been approached through application transformation at pre-compile time, which enhances the application to distribute the workload at application level and does not have the issues of library-based approaches. Hence, a parallelization scheme for GPU systems based on application transformation is needed. Like any computing engine of today, reliability is also a concern in GPUs. GPUs are vulnerable to transient and permanent failures. Current checkpoint/restart techniques are not suitable for systems with GPUs. Checkpointing for GPU systems present new and interesting challenges, primarily due to the natural differences imposed by the hardware design, the memory subsystem architecture, the massive number of threads, and the limited amount of synchronization among threads. Therefore, a checkpoint/restart technique suitable for GPU systems is needed. The goal of this work is to exploit higher levels of parallelism and

Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation.

Science.gov (United States)

Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin

2013-12-01

Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

Pattern-Driven Automatic Parallelization

Directory of Open Access Journals (Sweden)

Christoph W. Kessler

1996-01-01

Full Text Available This article describes a knowledge-based system for automatic parallelization of a wide class of sequential numerical codes operating on vectors and dense matrices, and for execution on distributed memory message-passing multiprocessors. Its main feature is a fast and powerful pattern recognition tool that locally identifies frequently occurring computations and programming concepts in the source code. This tool also works for dusty deck codes that have been "encrypted" by former machine-specific code transformations. Successful pattern recognition guides sophisticated code transformations including local algorithm replacement such that the parallelized code need not emerge from the sequential program structure by just parallelizing the loops. It allows access to an expert's knowledge on useful parallel algorithms, available machine-specific library routines, and powerful program transformations. The partially restored program semantics also supports local array alignment, distribution, and redistribution, and allows for faster and more exact prediction of the performance of the parallelized target code than is usually possible.

MPI_XSTAR: MPI-based parallelization of XSTAR program

Science.gov (United States)

Danehkar, A.

2017-12-01

MPI_XSTAR parallelizes execution of multiple XSTAR runs using Message Passing Interface (MPI). XSTAR (ascl:9910.008), part of the HEASARC's HEAsoft (ascl:1408.004) package, calculates the physical conditions and emission spectra of ionized gases. MPI_XSTAR invokes XSTINITABLE from HEASoft to generate a job list of XSTAR commands for given physical parameters. The job list is used to make directories in ascending order, where each individual XSTAR is spawned on each processor and outputs are saved. HEASoft's XSTAR2TABLE program is invoked upon the contents of each directory in order to produce table model FITS files for spectroscopy analysis tools.

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.

Practical parallel computing

CERN Document Server

Morse, H Stephen

1994-01-01

Practical Parallel Computing provides information pertinent to the fundamental aspects of high-performance parallel processing. This book discusses the development of parallel applications on a variety of equipment.Organized into three parts encompassing 12 chapters, this book begins with an overview of the technology trends that converge to favor massively parallel hardware over traditional mainframes and vector machines. This text then gives a tutorial introduction to parallel hardware architectures. Other chapters provide worked-out examples of programs using several parallel languages. Thi

Overview of the Force Scientific Parallel Language

Directory of Open Access Journals (Sweden)

Gita Alaghband

1994-01-01

Full Text Available The Force parallel programming language designed for large-scale shared-memory multiprocessors is presented. The language provides a number of parallel constructs as extensions to the ordinary Fortran language and is implemented as a two-level macro preprocessor to support portability across shared memory multiprocessors. The global parallelism model on which the Force is based provides a powerful parallel language. The parallel constructs, generic synchronization, and freedom from process management supported by the Force has resulted in structured parallel programs that are ported to the many multiprocessors on which the Force is implemented. Two new parallel constructs for looping and functional decomposition are discussed. Several programming examples to illustrate some parallel programming approaches using the Force are also presented.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets.

Science.gov (United States)

Shrimankar, D D; Sathe, S R

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today's supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures.

Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets

Science.gov (United States)

Shrimankar, D. D.; Sathe, S. R.

2016-01-01

Sequence alignment is an important tool for describing the relationships between DNA sequences. Many sequence alignment algorithms exist, differing in efficiency, in their models of the sequences, and in the relationship between sequences. The focus of this study is to obtain an optimal alignment between two sequences of biological data, particularly DNA sequences. The algorithm is discussed with particular emphasis on time, speedup, and efficiency optimizations. Parallel programming presents a number of critical challenges to application developers. Today’s supercomputer often consists of clusters of SMP nodes. Programming paradigms such as OpenMP and MPI are used to write parallel codes for such architectures. However, the OpenMP programs cannot be scaled for more than a single SMP node. However, programs written in MPI can have more than single SMP nodes. But such a programming paradigm has an overhead of internode communication. In this work, we explore the tradeoffs between using OpenMP and MPI. We demonstrate that the communication overhead incurs significantly even in OpenMP loop execution and increases with the number of cores participating. We also demonstrate a communication model to approximate the overhead from communication in OpenMP loops. Our results are astonishing and interesting to a large variety of input data files. We have developed our own load balancing and cache optimization technique for message passing model. Our experimental results show that our own developed techniques give optimum performance of our parallel algorithm for various sizes of input parameter, such as sequence size and tile size, on a wide variety of multicore architectures. PMID:27932868

The numerical parallel computing of photon transport

International Nuclear Information System (INIS)

Huang Qingnan; Liang Xiaoguang; Zhang Lifa

1998-12-01

The parallel computing of photon transport is investigated, the parallel algorithm and the parallelization of programs on parallel computers both with shared memory and with distributed memory are discussed. By analyzing the inherent law of the mathematics and physics model of photon transport according to the structure feature of parallel computers, using the strategy of 'to divide and conquer', adjusting the algorithm structure of the program, dissolving the data relationship, finding parallel liable ingredients and creating large grain parallel subtasks, the sequential computing of photon transport into is efficiently transformed into parallel and vector computing. The program was run on various HP parallel computers such as the HY-1 (PVP), the Challenge (SMP) and the YH-3 (MPP) and very good parallel speedup has been gotten

Shared Variable Oriented Parallel Precompiler for SPMD Model

Institute of Scientific and Technical Information of China (English)

无

1995-01-01

For the moment,commercial parallel computer systems with distributed memory architecture are usually provided with parallel FORTRAN or parallel C compliers,which are just traditional sequential FORTRAN or C compilers expanded with communication statements.Programmers suffer from writing parallel programs with communication statements. The Shared Variable Oriented Parallel Precompiler (SVOPP) proposed in this paper can automatically generate appropriate communication statements based on shared variables for SPMD(Single Program Multiple Data) computation model and greatly ease the parallel programming with high communication efficiency.The core function of parallel C precompiler has been successfully verified on a transputer-based parallel computer.Its prominent performance shows that SVOPP is probably a break-through in parallel programming technique.

Resolutions of the Coulomb operator: VIII. Parallel implementation using the modern programming language X10.

Science.gov (United States)

Limpanuparb, Taweetham; Milthorpe, Josh; Rendell, Alistair P

2014-10-30

Use of the modern parallel programming language X10 for computing long-range Coulomb and exchange interactions is presented. By using X10, a partitioned global address space language with support for task parallelism and the explicit representation of data locality, the resolution of the Ewald operator can be parallelized in a straightforward manner including use of both intranode and internode parallelism. We evaluate four different schemes for dynamic load balancing of integral calculation using X10's work stealing runtime, and report performance results for long-range HF energy calculation of large molecule/high quality basis running on up to 1024 cores of a high performance cluster machine. Copyright © 2014 Wiley Periodicals, Inc.

A scalable parallel algorithm for multiple objective linear programs

Science.gov (United States)

Wiecek, Malgorzata M.; Zhang, Hong

1994-01-01

This paper presents an ADBASE-based parallel algorithm for solving multiple objective linear programs (MOLP's). Job balance, speedup and scalability are of primary interest in evaluating efficiency of the new algorithm. Implementation results on Intel iPSC/2 and Paragon multiprocessors show that the algorithm significantly speeds up the process of solving MOLP's, which is understood as generating all or some efficient extreme points and unbounded efficient edges. The algorithm gives specially good results for large and very large problems. Motivation and justification for solving such large MOLP's are also included.

Algorithmic differentiation of pragma-defined parallel regions differentiating computer programs containing OpenMP

CERN Document Server

Förster, Michael

2014-01-01

Numerical programs often use parallel programming techniques such as OpenMP to compute the program's output values as efficient as possible. In addition, derivative values of these output values with respect to certain input values play a crucial role. To achieve code that computes not only the output values simultaneously but also the derivative values, this work introduces several source-to-source transformation rules. These rules are based on a technique called algorithmic differentiation. The main focus of this work lies on the important reverse mode of algorithmic differentiation. The inh

Generalized Analytical Program of Thyristor Phase Control Circuit with Series and Parallel Resonance Load

OpenAIRE

Nakanishi, Sen-ichiro; Ishida, Hideaki; Himei, Toyoji

1981-01-01

The systematic analytical method is reqUired for the ac phase control circuit by means of an inverse parallel thyristor pair which has a series and parallel L-C resonant load, because the phase control action causes abnormal and interesting phenomena, such as an extreme increase of voltage and current, an unique increase and decrease of contained higher harmonics, and a wide variation of power factor, etc. In this paper, the program for the analysis of the thyristor phase control circuit with...

Parallelism in matrix computations

CERN Document Server

Gallopoulos, Efstratios; Sameh, Ahmed H

2016-01-01

This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations. It assumes general but not extensive knowledge of numerical linear algebra, parallel architectures, and parallel programming paradigms. The book consists of four parts: (I) Basics; (II) Dense and Special Matrix Computations; (III) Sparse Matrix Computations; and (IV) Matrix functions and characteristics. Part I deals with parallel programming paradigms and fundamental kernels, including reordering schemes for sparse matrices. Part II is devoted to dense matrix computations such as parallel algorithms for solving linear systems, linear least squares, the symmetric algebraic eigenvalue problem, and the singular-value decomposition. It also deals with the development of parallel algorithms for special linear systems such as banded ,Vandermonde ,Toeplitz ,and block Toeplitz systems. Part III addresses sparse matrix computations: (a) the development of pa...

High performance parallel computers for science: New developments at the Fermilab advanced computer program

International Nuclear Information System (INIS)

Nash, T.; Areti, H.; Atac, R.

1988-08-01

Fermilab's Advanced Computer Program (ACP) has been developing highly cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 MFlops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction. 10 refs., 7 figs

Development, Verification and Validation of Parallel, Scalable Volume of Fluid CFD Program for Propulsion Applications

Science.gov (United States)

West, Jeff; Yang, H. Q.

2014-01-01

There are many instances involving liquid/gas interfaces and their dynamics in the design of liquid engine powered rockets such as the Space Launch System (SLS). Some examples of these applications are: Propellant tank draining and slosh, subcritical condition injector analysis for gas generators, preburners and thrust chambers, water deluge mitigation for launch induced environments and even solid rocket motor liquid slag dynamics. Commercially available CFD programs simulating gas/liquid interfaces using the Volume of Fluid approach are currently limited in their parallel scalability. In 2010 for instance, an internal NASA/MSFC review of three commercial tools revealed that parallel scalability was seriously compromised at 8 cpus and no additional speedup was possible after 32 cpus. Other non-interface CFD applications at the time were demonstrating useful parallel scalability up to 4,096 processors or more. Based on this review, NASA/MSFC initiated an effort to implement a Volume of Fluid implementation within the unstructured mesh, pressure-based algorithm CFD program, Loci-STREAM. After verification was achieved by comparing results to the commercial CFD program CFD-Ace+, and validation by direct comparison with data, Loci-STREAM-VoF is now the production CFD tool for propellant slosh force and slosh damping rate simulations at NASA/MSFC. On these applications, good parallel scalability has been demonstrated for problems sizes of tens of millions of cells and thousands of cpu cores. Ongoing efforts are focused on the application of Loci-STREAM-VoF to predict the transient flow patterns of water on the SLS Mobile Launch Platform in order to support the phasing of water for launch environment mitigation so that vehicle determinantal effects are not realized.

The technical feasibility of uranium enrichment for nuclear bomb construction at the parallel nuclear program plant

International Nuclear Information System (INIS)

Rosa, L.P.

1990-01-01

It is discussed the hole of the Parallel Nuclear Program is Brazil and the feasibility of uranium enrichment for nuclear bomb construction. This program involves two research centers, one belonging to the brazilian navy and another to the aeronautics. Some other brazilian institutes like CTA, IPEN, COPESP and CETEX and also taking part in the program. (A.C.A.S.)

Implementations of BLAST for parallel computers.

Science.gov (United States)

Jülich, A

1995-02-01

The BLAST sequence comparison programs have been ported to a variety of parallel computers-the shared memory machine Cray Y-MP 8/864 and the distributed memory architectures Intel iPSC/860 and nCUBE. Additionally, the programs were ported to run on workstation clusters. We explain the parallelization techniques and consider the pros and cons of these methods. The BLAST programs are very well suited for parallelization for a moderate number of processors. We illustrate our results using the program blastp as an example. As input data for blastp, a 799 residue protein query sequence and the protein database PIR were used.

Exploiting Symmetry on Parallel Architectures.

Science.gov (United States)

Stiller, Lewis Benjamin

1995-01-01

This thesis describes techniques for the design of parallel programs that solve well-structured problems with inherent symmetry. Part I demonstrates the reduction of such problems to generalized matrix multiplication by a group-equivariant matrix. Fast techniques for this multiplication are described, including factorization, orbit decomposition, and Fourier transforms over finite groups. Our algorithms entail interaction between two symmetry groups: one arising at the software level from the problem's symmetry and the other arising at the hardware level from the processors' communication network. Part II illustrates the applicability of our symmetry -exploitation techniques by presenting a series of case studies of the design and implementation of parallel programs. First, a parallel program that solves chess endgames by factorization of an associated dihedral group-equivariant matrix is described. This code runs faster than previous serial programs, and discovered it a number of results. Second, parallel algorithms for Fourier transforms for finite groups are developed, and preliminary parallel implementations for group transforms of dihedral and of symmetric groups are described. Applications in learning, vision, pattern recognition, and statistics are proposed. Third, parallel implementations solving several computational science problems are described, including the direct n-body problem, convolutions arising from molecular biology, and some communication primitives such as broadcast and reduce. Some of our implementations ran orders of magnitude faster than previous techniques, and were used in the investigation of various physical phenomena.

The language parallel Pascal and other aspects of the massively parallel processor

Science.gov (United States)

Reeves, A. P.; Bruner, J. D.

1982-01-01

A high level language for the Massively Parallel Processor (MPP) was designed. This language, called Parallel Pascal, is described in detail. A description of the language design, a description of the intermediate language, Parallel P-Code, and details for the MPP implementation are included. Formal descriptions of Parallel Pascal and Parallel P-Code are given. A compiler was developed which converts programs in Parallel Pascal into the intermediate Parallel P-Code language. The code generator to complete the compiler for the MPP is being developed independently. A Parallel Pascal to Pascal translator was also developed. The architecture design for a VLSI version of the MPP was completed with a description of fault tolerant interconnection networks. The memory arrangement aspects of the MPP are discussed and a survey of other high level languages is given.

An approach to multicore parallelism using functional programming: A case study based on Presburger Arithmetic

DEFF Research Database (Denmark)

Dung, Phan Anh; Hansen, Michael Reichhardt

2015-01-01

In this paper we investigate multicore parallelism in the context of functional programming by means of two quantifier-elimination procedures for Presburger Arithmetic: one is based on Cooper’s algorithm and the other is based on the Omega Test. We first develop correct-by-construction prototype...... platform executing on an 8-core machine. A speedup of approximately 4 was obtained for Cooper’s algorithm and a speedup of approximately 6 was obtained for the exact-shadow part of the Omega Test. The considered procedures are complex, memory-intense algorithms on huge formula trees and the case study...... reveals more general applicable techniques and guideline for deriving parallel algorithms from sequential ones in the context of data-intensive tree algorithms. The obtained insights should apply for any strict and impure functional programming language. Furthermore, the results obtained for the exact...

Parallel computing: numerics, applications, and trends

National Research Council Canada - National Science Library

Trobec, Roman; Vajteršic, Marián; Zinterhof, Peter

2009-01-01

... and/or distributed systems. The contributions to this book are focused on topics most concerned in the trends of today's parallel computing. These range from parallel algorithmics, programming, tools, network computing to future parallel computing. Particular attention is paid to parallel numerics: linear algebra, differential equations, numerica...

Parallel Computing Strategies for Irregular Algorithms

Science.gov (United States)

Biswas, Rupak; Oliker, Leonid; Shan, Hongzhang; Biegel, Bryan (Technical Monitor)

2002-01-01

Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.

SOFTWARE FOR DESIGNING PARALLEL APPLICATIONS

Directory of Open Access Journals (Sweden)

M. K. Bouza

2017-01-01

Full Text Available The object of research is the tools to support the development of parallel programs in C/C ++. The methods and software which automates the process of designing parallel applications are proposed.

Development of whole core thermal-hydraulic analysis program ACT. 4. Simplified fuel assembly model and parallelization by MPI

International Nuclear Information System (INIS)

Ohshima, Hiroyuki

2001-10-01

A whole core thermal-hydraulic analysis program ACT is being developed for the purpose of evaluating detailed in-core thermal hydraulic phenomena of fast reactors including the effect of the flow between wrapper-tube walls (inter-wrapper flow) under various reactor operation conditions. As appropriate boundary conditions in addition to a detailed modeling of the core are essential for accurate simulations of in-core thermal hydraulics, ACT consists of not only fuel assembly and inter-wrapper flow analysis modules but also a heat transport system analysis module that gives response of the plant dynamics to the core model. This report describes incorporation of a simplified model to the fuel assembly analysis module and program parallelization by a message passing method toward large-scale simulations. ACT has a fuel assembly analysis module which can simulate a whole fuel pin bundle in each fuel assembly of the core and, however, it may take much CPU time for a large-scale core simulation. Therefore, a simplified fuel assembly model that is thermal-hydraulically equivalent to the detailed one has been incorporated in order to save the simulation time and resources. This simplified model is applied to several parts of fuel assemblies in a core where the detailed simulation results are not required. With regard to the program parallelization, the calculation load and the data flow of ACT were analyzed and the optimum parallelization has been done including the improvement of the numerical simulation algorithm of ACT. Message Passing Interface (MPI) is applied to data communication between processes and synchronization in parallel calculations. Parallelized ACT was verified through a comparison simulation with the original one. In addition to the above works, input manuals of the core analysis module and the heat transport system analysis module have been prepared. (author)

Mobile and replicated alignment of arrays in data-parallel programs

Science.gov (United States)

Chatterjee, Siddhartha; Gilbert, John R.; Schreiber, Robert

1993-01-01

When a data-parallel language like FORTRAN 90 is compiled for a distributed-memory machine, aggregate data objects (such as arrays) are distributed across the processor memories. The mapping determines the amount of residual communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: first, an alignment that maps all the objects to an abstract template, and then a distribution that maps the template to the processors. We solve two facets of the problem of finding alignments that reduce residual communication: we determine alignments that vary in loops, and objects that should have replicated alignments. We show that loop-dependent mobile alignment is sometimes necessary for optimum performance, and we provide algorithms with which a compiler can determine good mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself (via spread operations) or can be used to improve performance. We propose an algorithm based on network flow that determines which objects to replicate so as to minimize the total amount of broadcast communication in replication. This work on mobile and replicated alignment extends our earlier work on determining static alignment.

Parallelizing Gene Expression Programming Algorithm in Enabling Large-Scale Classification

Directory of Open Access Journals (Sweden)

Lixiong Xu

2017-01-01

Full Text Available As one of the most effective function mining algorithms, Gene Expression Programming (GEP algorithm has been widely used in classification, pattern recognition, prediction, and other research fields. Based on the self-evolution, GEP is able to mine an optimal function for dealing with further complicated tasks. However, in big data researches, GEP encounters low efficiency issue due to its long time mining processes. To improve the efficiency of GEP in big data researches especially for processing large-scale classification tasks, this paper presents a parallelized GEP algorithm using MapReduce computing model. The experimental results show that the presented algorithm is scalable and efficient for processing large-scale classification tasks.

HPC parallel programming model for gyrokinetic MHD simulation

International Nuclear Information System (INIS)

Naitou, Hiroshi; Yamada, Yusuke; Tokuda, Shinji; Ishii, Yasutomo; Yagi, Masatoshi

2011-01-01

The 3-dimensional gyrokinetic PIC (particle-in-cell) code for MHD simulation, Gpic-MHD, was installed on SR16000 (“Plasma Simulator”), which is a scalar cluster system consisting of 8,192 logical cores. The Gpic-MHD code advances particle and field quantities in time. In order to distribute calculations over large number of logical cores, the total simulation domain in cylindrical geometry was broken up into N DD-r × N DD-z (number of radial decomposition times number of axial decomposition) small domains including approximately the same number of particles. The axial direction was uniformly decomposed, while the radial direction was non-uniformly decomposed. N RP replicas (copies) of each decomposed domain were used (“particle decomposition”). The hybrid parallelization model of multi-threads and multi-processes was employed: threads were parallelized by the auto-parallelization and N DD-r × N DD-z × N RP processes were parallelized by MPI (message-passing interface). The parallelization performance of Gpic-MHD was investigated for the medium size system of N r × N θ × N z = 1025 × 128 × 128 mesh with 4.196 or 8.192 billion particles. The highest speed for the fixed number of logical cores was obtained for two threads, the maximum number of N DD-z , and optimum combination of N DD-r and N RP . The observed optimum speeds demonstrated good scaling up to 8,192 logical cores. (author)

An Introduction to Parallel Computation R

Indian Academy of Sciences (India)

How are they programmed? This article provides an introduction. A parallel computer is a network of processors built for ... and have been used to solve problems much faster than a single ... in parallel computer design is to select an organization which ..... The most ambitious approach to parallel computing is to develop.

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).

Parallel computing works

Energy Technology Data Exchange (ETDEWEB)

1991-10-23

An account of the Caltech Concurrent Computation Program (C{sup 3}P), a five year project that focused on answering the question: Can parallel computers be used to do large-scale scientific computations '' As the title indicates, the question is answered in the affirmative, by implementing numerous scientific applications on real parallel computers and doing computations that produced new scientific results. In the process of doing so, C{sup 3}P helped design and build several new computers, designed and implemented basic system software, developed algorithms for frequently used mathematical computations on massively parallel machines, devised performance models and measured the performance of many computers, and created a high performance computing facility based exclusively on parallel computers. While the initial focus of C{sup 3}P was the hypercube architecture developed by C. Seitz, many of the methods developed and lessons learned have been applied successfully on other massively parallel architectures.

Rubus: A compiler for seamless and extensible parallelism

Science.gov (United States)

Adnan, Muhammad; Aslam, Faisal; Sarwar, Syed Mansoor

2017-01-01

Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU), originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer’s expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84 times has been

Rubus: A compiler for seamless and extensible parallelism.

Directory of Open Access Journals (Sweden)

Muhammad Adnan

Full Text Available Nowadays, a typical processor may have multiple processing cores on a single chip. Furthermore, a special purpose processing unit called Graphic Processing Unit (GPU, originally designed for 2D/3D games, is now available for general purpose use in computers and mobile devices. However, the traditional programming languages which were designed to work with machines having single core CPUs, cannot utilize the parallelism available on multi-core processors efficiently. Therefore, to exploit the extraordinary processing power of multi-core processors, researchers are working on new tools and techniques to facilitate parallel programming. To this end, languages like CUDA and OpenCL have been introduced, which can be used to write code with parallelism. The main shortcoming of these languages is that programmer needs to specify all the complex details manually in order to parallelize the code across multiple cores. Therefore, the code written in these languages is difficult to understand, debug and maintain. Furthermore, to parallelize legacy code can require rewriting a significant portion of code in CUDA or OpenCL, which can consume significant time and resources. Thus, the amount of parallelism achieved is proportional to the skills of the programmer and the time spent in code optimizations. This paper proposes a new open source compiler, Rubus, to achieve seamless parallelism. The Rubus compiler relieves the programmer from manually specifying the low-level details. It analyses and transforms a sequential program into a parallel program automatically, without any user intervention. This achieves massive speedup and better utilization of the underlying hardware without a programmer's expertise in parallel programming. For five different benchmarks, on average a speedup of 34.54 times has been achieved by Rubus as compared to Java on a basic GPU having only 96 cores. Whereas, for a matrix multiplication benchmark the average execution speedup of 84

.NET 4.5 parallel extensions

CERN Document Server

Freeman, Bryan

2013-01-01

This book contains practical recipes on everything you will need to create task-based parallel programs using C#, .NET 4.5, and Visual Studio. The book is packed with illustrated code examples to create scalable programs.This book is intended to help experienced C# developers write applications that leverage the power of modern multicore processors. It provides the necessary knowledge for an experienced C# developer to work with .NET parallelism APIs. Previous experience of writing multithreaded applications is not necessary.

Patterns for Parallel Software Design

CERN Document Server

Ortega-Arjona, Jorge Luis

2010-01-01

Essential reading to understand patterns for parallel programming Software patterns have revolutionized the way we think about how software is designed, built, and documented, and the design of parallel software requires you to consider other particular design aspects and special skills. From clusters to supercomputers, success heavily depends on the design skills of software developers. Patterns for Parallel Software Design presents a pattern-oriented software architecture approach to parallel software design. This approach is not a design method in the classic sense, but a new way of managin

ParaHaplo 3.0: A program package for imputation and a haplotype-based whole-genome association study using hybrid parallel computing

Directory of Open Access Journals (Sweden)

Kamatani Naoyuki

2011-05-01

Full Text Available Abstract Background Use of missing genotype imputations and haplotype reconstructions are valuable in genome-wide association studies (GWASs. By modeling the patterns of linkage disequilibrium in a reference panel, genotypes not directly measured in the study samples can be imputed and used for GWASs. Since millions of single nucleotide polymorphisms need to be imputed in a GWAS, faster methods for genotype imputation and haplotype reconstruction are required. Results We developed a program package for parallel computation of genotype imputation and haplotype reconstruction. Our program package, ParaHaplo 3.0, is intended for use in workstation clusters using the Intel Message Passing Interface. We compared the performance of ParaHaplo 3.0 on the Japanese in Tokyo, Japan and Han Chinese in Beijing, and Chinese in the HapMap dataset. A parallel version of ParaHaplo 3.0 can conduct genotype imputation 20 times faster than a non-parallel version of ParaHaplo. Conclusions ParaHaplo 3.0 is an invaluable tool for conducting haplotype-based GWASs. The need for faster genotype imputation and haplotype reconstruction using parallel computing will become increasingly important as the data sizes of such projects continue to increase. ParaHaplo executable binaries and program sources are available at http://en.sourceforge.jp/projects/parallelgwas/releases/.

SPSS and SAS programs for determining the number of components using parallel analysis and velicer's MAP test.

Science.gov (United States)

O'Connor, B P

2000-08-01

Popular statistical software packages do not have the proper procedures for determining the number of components in factor and principal components analyses. Parallel analysis and Velicer's minimum average partial (MAP) test are validated procedures, recommended widely by statisticians. However, many researchers continue to use alternative, simpler, but flawed procedures, such as the eigenvalues-greater-than-one rule. Use of the proper procedures might be increased if these procedures could be conducted within familiar software environments. This paper describes brief and efficient programs for using SPSS and SAS to conduct parallel analyses and the MAP test.

Enhancing Application Performance Using Mini-Apps: Comparison of Hybrid Parallel Programming Paradigms

Science.gov (United States)

Lawson, Gary; Sosonkina, Masha; Baurle, Robert; Hammond, Dana

2017-01-01

In many fields, real-world applications for High Performance Computing have already been developed. For these applications to stay up-to-date, new parallel strategies must be explored to yield the best performance; however, restructuring or modifying a real-world application may be daunting depending on the size of the code. In this case, a mini-app may be employed to quickly explore such options without modifying the entire code. In this work, several mini-apps have been created to enhance a real-world application performance, namely the VULCAN code for complex flow analysis developed at the NASA Langley Research Center. These mini-apps explore hybrid parallel programming paradigms with Message Passing Interface (MPI) for distributed memory access and either Shared MPI (SMPI) or OpenMP for shared memory accesses. Performance testing shows that MPI+SMPI yields the best execution performance, while requiring the largest number of code changes. A maximum speedup of 23 was measured for MPI+SMPI, but only 11 was measured for MPI+OpenMP.

Adapting algorithms to massively parallel hardware

CERN Document Server

Sioulas, Panagiotis

2016-01-01

In the recent years, the trend in computing has shifted from delivering processors with faster clock speeds to increasing the number of cores per processor. This marks a paradigm shift towards parallel programming in which applications are programmed to exploit the power provided by multi-cores. Usually there is gain in terms of the time-to-solution and the memory footprint. Specifically, this trend has sparked an interest towards massively parallel systems that can provide a large number of processors, and possibly computing nodes, as in the GPUs and MPPAs (Massively Parallel Processor Arrays). In this project, the focus was on two distinct computing problems: k-d tree searches and track seeding cellular automata. The goal was to adapt the algorithms to parallel systems and evaluate their performance in different cases.

Design strategies for irregularly adapting parallel applications

International Nuclear Information System (INIS)

Oliker, Leonid; Biswas, Rupak; Shan, Hongzhang; Sing, Jaswinder Pal

2000-01-01

Achieving scalable performance for dynamic irregular applications is eminently challenging. Traditional message-passing approaches have been making steady progress towards this goal; however, they suffer from complex implementation requirements. The use of a global address space greatly simplifies the programming task, but can degrade the performance of dynamically adapting computations. In this work, we examine two major classes of adaptive applications, under five competing programming methodologies and four leading parallel architectures. Results indicate that it is possible to achieve message-passing performance using shared-memory programming techniques by carefully following the same high level strategies. Adaptive applications have computational work loads and communication patterns which change unpredictably at runtime, requiring dynamic load balancing to achieve scalable performance on parallel machines. Efficient parallel implementations of such adaptive applications are therefore a challenging task. This work examines the implementation of two typical adaptive applications, Dynamic Remeshing and N-Body, across various programming paradigms and architectural platforms. We compare several critical factors of the parallel code development, including performance, programmability, scalability, algorithmic development, and portability

Implementation and performance of parallelized elegant

International Nuclear Information System (INIS)

Wang, Y.; Borland, M.

2008-01-01

The program elegant is widely used for design and modeling of linacs for free-electron lasers and energy recovery linacs, as well as storage rings and other applications. As part of a multi-year effort, we have parallelized many aspects of the code, including single-particle dynamics, wakefields, and coherent synchrotron radiation. We report on the approach used for gradual parallelization, which proved very beneficial in getting parallel features into the hands of users quickly. We also report details of parallelization of collective effects. Finally, we discuss performance of the parallelized code in various applications.

The parallel adult education system

DEFF Research Database (Denmark)

Wahlgren, Bjarne

2015-01-01

for competence development. The Danish university educational system includes two parallel programs: a traditional academic track (candidatus) and an alternative practice-based track (master). The practice-based program was established in 2001 and organized as part time. The total program takes half the time...

Parallelization in Modern C++

CERN Multimedia

CERN. Geneva

2016-01-01

The traditionally used and well established parallel programming models OpenMP and MPI are both targeting lower level parallelism and are meant to be as language agnostic as possible. For a long time, those models were the only widely available portable options for developing parallel C++ applications beyond using plain threads. This has strongly limited the optimization capabilities of compilers, has inhibited extensibility and genericity, and has restricted the use of those models together with other, modern higher level abstractions introduced by the C++11 and C++14 standards. The recent revival of interest in the industry and wider community for the C++ language has also spurred a remarkable amount of standardization proposals and technical specifications being developed. Those efforts however have so far failed to build a vision on how to seamlessly integrate various types of parallelism, such as iterative parallel execution, task-based parallelism, asynchronous many-task execution flows, continuation s...

Investigation of the applicability of a functional programming model to fault-tolerant parallel processing for knowledge-based systems

Science.gov (United States)

Harper, Richard

1989-01-01

In a fault-tolerant parallel computer, a functional programming model can facilitate distributed checkpointing, error recovery, load balancing, and graceful degradation. Such a model has been implemented on the Draper Fault-Tolerant Parallel Processor (FTPP). When used in conjunction with the FTPP's fault detection and masking capabilities, this implementation results in a graceful degradation of system performance after faults. Three graceful degradation algorithms have been implemented and are presented. A user interface has been implemented which requires minimal cognitive overhead by the application programmer, masking such complexities as the system's redundancy, distributed nature, variable complement of processing resources, load balancing, fault occurrence and recovery. This user interface is described and its use demonstrated. The applicability of the functional programming style to the Activation Framework, a paradigm for intelligent systems, is then briefly described.

Parallelism in computations in quantum and statistical mechanics

International Nuclear Information System (INIS)

Clementi, E.; Corongiu, G.; Detrich, J.H.

1985-01-01

Often very fundamental biochemical and biophysical problems defy simulations because of limitations in today's computers. We present and discuss a distributed system composed of two IBM 4341 s and/or an IBM 4381 as front-end processors and ten FPS-164 attached array processors. This parallel system - called LCAP - has presently a peak performance of about 110 Mflops; extensions to higher performance are discussed. Presently, the system applications use a modified version of VM/SP as the operating system: description of the modifications is given. Three applications programs have been migrated from sequential to parallel: a molecular quantum mechanical, a Metropolis-Monte Carlo and a molecular dynamics program. Descriptions of the parallel codes are briefly outlined. Use of these parallel codes has already opened up new capabilities for our research. The very positive performance comparisons with today's supercomputers allow us to conclude that parallel computers and programming, of the type we have considered, represent a pragmatic answer to many computationally intensive problems. (orig.)

CUBESIM, Hypercube and Denelcor Hep Parallel Computer Simulation

International Nuclear Information System (INIS)

Dunigan, T.H.

1988-01-01

1 - Description of program or function: CUBESIM is a set of subroutine libraries and programs for the simulation of message-passing parallel computers and shared-memory parallel computers. Subroutines are supplied to simulate the Intel hypercube and the Denelcor HEP parallel computers. The system permits a user to develop and test parallel programs written in C or FORTRAN on a single processor. The user may alter such hypercube parameters as message startup times, packet size, and the computation-to-communication ratio. The simulation generates a trace file that can be used for debugging, performance analysis, or graphical display. 2 - Method of solution: The CUBESIM simulator is linked with the user's parallel application routines to run as a single UNIX process. The simulator library provides a small operating system to perform process and message management. 3 - Restrictions on the complexity of the problem: Up to 128 processors can be simulated with a virtual memory limit of 6 million bytes. Up to 1000 processes can be simulated

Portable programming on parallel/networked computers using the Application Portable Parallel Library (APPL)

Science.gov (United States)

Quealy, Angela; Cole, Gary L.; Blech, Richard A.

1993-01-01

The Application Portable Parallel Library (APPL) is a subroutine-based library of communication primitives that is callable from applications written in FORTRAN or C. APPL provides a consistent programmer interface to a variety of distributed and shared-memory multiprocessor MIMD machines. The objective of APPL is to minimize the effort required to move parallel applications from one machine to another, or to a network of homogeneous machines. APPL encompasses many of the message-passing primitives that are currently available on commercial multiprocessor systems. This paper describes APPL (version 2.3.1) and its usage, reports the status of the APPL project, and indicates possible directions for the future. Several applications using APPL are discussed, as well as performance and overhead results.

Exploiting variability for energy optimization of parallel programs

Energy Technology Data Exchange (ETDEWEB)

Lavrijsen, Wim [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Iancu, Costin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); de Jong, Wibe [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chen, Xin [Georgia Inst. of Technology, Atlanta, GA (United States); Schwan, Karsten [Georgia Inst. of Technology, Atlanta, GA (United States)

2016-04-18

Here in this paper we present optimizations that use DVFS mechanisms to reduce the total energy usage in scientific applications. Our main insight is that noise is intrinsic to large scale parallel executions and it appears whenever shared resources are contended. The presence of noise allows us to identify and manipulate any program regions amenable to DVFS. When compared to previous energy optimizations that make per core decisions using predictions of the running time, our scheme uses a qualitative approach to recognize the signature of executions amenable to DVFS. By recognizing the "shape of variability" we can optimize codes with highly dynamic behavior, which pose challenges to all existing DVFS techniques. We validate our approach using offline and online analyses for one-sided and two-sided communication paradigms. We have applied our methods to NWChem, and we show best case improvements in energy use of 12% at no loss in performance when using online optimizations running on 720 Haswell cores with one-sided communication. With NWChem on MPI two-sided and offline analysis, capturing the initialization, we find energy savings of up to 20%, with less than 1% performance cost.

Automatic Management of Parallel and Distributed System Resources

Science.gov (United States)

Yan, Jerry; Ngai, Tin Fook; Lundstrom, Stephen F.

1990-01-01

Viewgraphs on automatic management of parallel and distributed system resources are presented. Topics covered include: parallel applications; intelligent management of multiprocessing systems; performance evaluation of parallel architecture; dynamic concurrent programs; compiler-directed system approach; lattice gaseous cellular automata; and sparse matrix Cholesky factorization.

Streaming for Functional Data-Parallel Languages

DEFF Research Database (Denmark)

Madsen, Frederik Meisner

In this thesis, we investigate streaming as a general solution to the space inefficiency commonly found in functional data-parallel programming languages. The data-parallel paradigm maps well to parallel SIMD-style hardware. However, the traditional fully materializing execution strategy...... by extending two existing data-parallel languages: NESL and Accelerate. In the extensions we map bulk operations to data-parallel streams that can evaluate fully sequential, fully parallel or anything in between. By a dataflow, piecewise parallel execution strategy, the runtime system can adjust to any target...... flattening necessitates all sub-computations to materialize at the same time. For example, naive n by n matrix multiplication requires n^3 space in NESL because the algorithm contains n^3 independent scalar multiplications. For large values of n, this is completely unacceptable. We address the problem...

Automatic Parallelization An Overview of Fundamental Compiler Techniques

CERN Document Server

Midkiff, Samuel P

2012-01-01

Compiling for parallelism is a longstanding topic of compiler research. This book describes the fundamental principles of compiling "regular" numerical programs for parallelism. We begin with an explanation of analyses that allow a compiler to understand the interaction of data reads and writes in different statements and loop iterations during program execution. These analyses include dependence analysis, use-def analysis and pointer analysis. Next, we describe how the results of these analyses are used to enable transformations that make loops more amenable to parallelization, and

A solution for automatic parallelization of sequential assembly code

Directory of Open Access Journals (Sweden)

Kovačević Đorđe

2013-01-01

Full Text Available Since modern multicore processors can execute existing sequential programs only on a single core, there is a strong need for automatic parallelization of program code. Relying on existing algorithms, this paper describes one new software solution tool for parallelization of sequential assembly code. The main goal of this paper is to develop the parallelizator which reads sequential assembler code and at the output provides parallelized code for MIPS processor with multiple cores. The idea is the following: the parser translates assembler input file to program objects suitable for further processing. After that the static single assignment is done. Based on the data flow graph, the parallelization algorithm separates instructions on different cores. Once sequential code is parallelized by the parallelization algorithm, registers are allocated with the algorithm for linear allocation, and the result at the end of the program is distributed assembler code on each of the cores. In the paper we evaluate the speedup of the matrix multiplication example, which was processed by the parallelizator of assembly code. The result is almost linear speedup of code execution, which increases with the number of cores. The speed up on the two cores is 1.99, while on 16 cores the speed up is 13.88.

Concurrent Collections (CnC): A new approach to parallel programming

CERN Multimedia

CERN. Geneva

2010-01-01

A common approach in designing parallel languages is to provide some high level handles to manipulate the use of the parallel platform. This exposes some aspects of the target platform, for example, shared vs. distributed memory. It may expose some but not all types of parallelism, for example, data parallelism but not task parallelism. This approach must find a balance between the desire to provide a simple view for the domain expert and provide sufficient power for tuning. This is hard for any given architecture and harder if the language is to apply to a range of architectures. Either simplicity or power is lost. Instead of viewing the language design problem as one of providing the programmer with high level handles, we view the problem as one of designing an interface. On one side of this interface is the programmer (domain expert) who knows the application but needs no knowledge of any aspects of the platform. On the other side of the interface is the performance expert (programmer o...

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

Science.gov (United States)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

Parallel Object-Oriented Computation Applied to a Finite Element Problem

Directory of Open Access Journals (Sweden)

Jon B. Weissman

1993-01-01

Full Text Available The conventional wisdom in the scientific computing community is that the best way to solve large-scale numerically intensive scientific problems on today's parallel MIMD computers is to use Fortran or C programmed in a data-parallel style using low-level message-passing primitives. This approach inevitably leads to nonportable codes and extensive development time, and restricts parallel programming to the domain of the expert programmer. We believe that these problems are not inherent to parallel computing but are the result of the programming tools used. We will show that comparable performance can be achieved with little effort if better tools that present higher level abstractions are used. The vehicle for our demonstration is a 2D electromagnetic finite element scattering code we have implemented in Mentat, an object-oriented parallel processing system. We briefly describe the application. Mentat, the implementation, and present performance results for both a Mentat and a hand-coded parallel Fortran version.

Parallelism and Scalability in an Image Processing Application

DEFF Research Database (Denmark)

Rasmussen, Morten Sleth; Stuart, Matthias Bo; Karlsson, Sven

2008-01-01

parallel programs. This paper investigates parallelism and scalability of an embedded image processing application. The major challenges faced when parallelizing the application were to extract enough parallelism from the application and to reduce load imbalance. The application has limited immediately......The recent trends in processor architecture show that parallel processing is moving into new areas of computing in the form of many-core desktop processors and multi-processor system-on-chip. This means that parallel processing is required in application areas that traditionally have not used...

Parallelism and Scalability in an Image Processing Application

DEFF Research Database (Denmark)

Rasmussen, Morten Sleth; Stuart, Matthias Bo; Karlsson, Sven

2009-01-01

parallel programs. This paper investigates parallelism and scalability of an embedded image processing application. The major challenges faced when parallelizing the application were to extract enough parallelism from the application and to reduce load imbalance. The application has limited immediately......The recent trends in processor architecture show that parallel processing is moving into new areas of computing in the form of many-core desktop processors and multi-processor system-on-chips. This means that parallel processing is required in application areas that traditionally have not used...

Computer-Aided Parallelizer and Optimizer

Science.gov (United States)

Jin, Haoqiang

2011-01-01

The Computer-Aided Parallelizer and Optimizer (CAPO) automates the insertion of compiler directives (see figure) to facilitate parallel processing on Shared Memory Parallel (SMP) machines. While CAPO currently is integrated seamlessly into CAPTools (developed at the University of Greenwich, now marketed as ParaWise), CAPO was independently developed at Ames Research Center as one of the components for the Legacy Code Modernization (LCM) project. The current version takes serial FORTRAN programs, performs interprocedural data dependence analysis, and generates OpenMP directives. Due to the widely supported OpenMP standard, the generated OpenMP codes have the potential to run on a wide range of SMP machines. CAPO relies on accurate interprocedural data dependence information currently provided by CAPTools. Compiler directives are generated through identification of parallel loops in the outermost level, construction of parallel regions around parallel loops and optimization of parallel regions, and insertion of directives with automatic identification of private, reduction, induction, and shared variables. Attempts also have been made to identify potential pipeline parallelism (implemented with point-to-point synchronization). Although directives are generated automatically, user interaction with the tool is still important for producing good parallel codes. A comprehensive graphical user interface is included for users to interact with the parallelization process.

The ongoing investigation of high performance parallel computing in HEP

CERN Document Server

Peach, Kenneth J; Böck, R K; Dobinson, Robert W; Hansroul, M; Norton, Alan Robert; Willers, Ian Malcolm; Baud, J P; Carminati, F; Gagliardi, F; McIntosh, E; Metcalf, M; Robertson, L; CERN. Geneva. Detector Research and Development Committee

1993-01-01

Past and current exploitation of parallel computing in High Energy Physics is summarized and a list of R & D projects in this area is presented. The applicability of new parallel hardware and software to physics problems is investigated, in the light of the requirements for computing power of LHC experiments and the current trends in the computer industry. Four main themes are discussed (possibilities for a finer grain of parallelism; fine-grain communication mechanism; usable parallel programming environment; different programming models and architectures, using standard commercial products). Parallel computing technology is potentially of interest for offline and vital for real time applications in LHC. A substantial investment in applications development and evaluation of state of the art hardware and software products is needed. A solid development environment is required at an early stage, before mainline LHC program development begins.

Eighth SIAM conference on parallel processing for scientific computing: Final program and abstracts

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-12-31

This SIAM conference is the premier forum for developments in parallel numerical algorithms, a field that has seen very lively and fruitful developments over the past decade, and whose health is still robust. Themes for this conference were: combinatorial optimization; data-parallel languages; large-scale parallel applications; message-passing; molecular modeling; parallel I/O; parallel libraries; parallel software tools; parallel compilers; particle simulations; problem-solving environments; and sparse matrix computations.

A Model for Speedup of Parallel Programs

Science.gov (United States)

1997-01-01

Sanjeev. K Setia . The interaction between mem- ory allocation and adaptive partitioning in message- passing multicomputers. In IPPS 󈨣 Workshop on Job...Scheduling Strategies for Parallel Processing, pages 89{99, 1995. [15] Sanjeev K. Setia and Satish K. Tripathi. A compar- ative analysis of static

Fast implementations of 3D PET reconstruction using vector and parallel programming techniques

International Nuclear Information System (INIS)

Guerrero, T.M.; Cherry, S.R.; Dahlbom, M.; Ricci, A.R.; Hoffman, E.J.

1993-01-01

Computationally intensive techniques that offer potential clinical use have arisen in nuclear medicine. Examples include iterative reconstruction, 3D PET data acquisition and reconstruction, and 3D image volume manipulation including image registration. One obstacle in achieving clinical acceptance of these techniques is the computational time required. This study focuses on methods to reduce the computation time for 3D PET reconstruction through the use of fast computer hardware, vector and parallel programming techniques, and algorithm optimization. The strengths and weaknesses of i860 microprocessor based workstation accelerator boards are investigated in implementations of 3D PET reconstruction

Micro-mechanical Simulations of Soils using Massively Parallel Supercomputers

Directory of Open Access Journals (Sweden)

David W. Washington

2004-06-01

Full Text Available In this research a computer program, Trubal version 1.51, based on the Discrete Element Method was converted to run on a Connection Machine (CM-5,a massively parallel supercomputer with 512 nodes, to expedite the computational times of simulating Geotechnical boundary value problems. The dynamic memory algorithm in Trubal program did not perform efficiently in CM-2 machine with the Single Instruction Multiple Data (SIMD architecture. This was due to the communication overhead involving global array reductions, global array broadcast and random data movement. Therefore, a dynamic memory algorithm in Trubal program was converted to a static memory arrangement and Trubal program was successfully converted to run on CM-5 machines. The converted program was called "TRUBAL for Parallel Machines (TPM." Simulating two physical triaxial experiments and comparing simulation results with Trubal simulations validated the TPM program. With a 512 nodes CM-5 machine TPM produced a nine-fold speedup demonstrating the inherent parallelism within algorithms based on the Discrete Element Method.

Power stability methods for parallel systems

International Nuclear Information System (INIS)

Wallach, Y.

1988-01-01

Parallel-Processing Systems are already commercially available. This paper shows that if one of them - the Alternating Sequential Parallel, or ASP system - is applied to network stability calculations it will lead to a higher speed of solution. The ASP system is first described and is then shown to be cheaper, more reliable and available than other parallel systems. Also, no deadlock need be feared and the speedup is normally very high. A number of ASP systems were already assembled (the SMS systems, Topps, DIRMU etc.). At present, an IBM Local Area Network is being modified so that it too can work in the ASP mode. Existing ASP systems were programmed in Fortran or assembly language. Since newer systems (e.g. DIRMU) are programmed in Modula-2, this language can be used. Stability analysis is based on solving nonlinear differential and algebraic equations. The algorithm for solving the nonlinear differential equations on ASP, is described and programmed in Modula-2. The speedup is computed and is shown to be almost optimal

Advanced parallel processing with supercomputer architectures

International Nuclear Information System (INIS)

Hwang, K.

1987-01-01

This paper investigates advanced parallel processing techniques and innovative hardware/software architectures that can be applied to boost the performance of supercomputers. Critical issues on architectural choices, parallel languages, compiling techniques, resource management, concurrency control, programming environment, parallel algorithms, and performance enhancement methods are examined and the best answers are presented. The authors cover advanced processing techniques suitable for supercomputers, high-end mainframes, minisupers, and array processors. The coverage emphasizes vectorization, multitasking, multiprocessing, and distributed computing. In order to achieve these operation modes, parallel languages, smart compilers, synchronization mechanisms, load balancing methods, mapping parallel algorithms, operating system functions, application library, and multidiscipline interactions are investigated to ensure high performance. At the end, they assess the potentials of optical and neural technologies for developing future supercomputers

A parallel solver for huge dense linear systems

Science.gov (United States)

Badia, J. M.; Movilla, J. L.; Climente, J. I.; Castillo, M.; Marqués, M.; Mayo, R.; Quintana-Ortí, E. S.; Planelles, J.

2011-11-01

HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facilitate the parallel solution of very large dense systems to scientists and engineers. The API makes use of parallelism to yield an efficient solution of the systems on a wide range of parallel platforms, from clusters of processors to massively parallel multiprocessors. It exploits out-of-core strategies to leverage the secondary memory in order to solve huge linear systems O(100.000). The API is based on the parallel linear algebra library PLAPACK, and on its Out-Of-Core (OOC) extension POOCLAPACK. Both PLAPACK and POOCLAPACK use the Message Passing Interface (MPI) as the communication layer and BLAS to perform the local matrix operations. The API provides a friendly interface to the users, hiding almost all the technical aspects related to the parallel execution of the code and the use of the secondary memory to solve the systems. In particular, the API can automatically select the best way to store and solve the systems, depending of the dimension of the system, the number of processes and the main memory of the platform. Experimental results on several parallel platforms report high performance, reaching more than 1 TFLOP with 64 cores to solve a system with more than 200 000 equations and more than 10 000 right-hand side vectors. New version program summaryProgram title: Huge Dense System Solver (HDSS) Catalogue identifier: AEHU_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHU_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 87 062 No. of bytes in distributed program, including test data, etc.: 1 069 110 Distribution format: tar.gz Programming language: Fortran90, C Computer: Parallel architectures: multiprocessors, computer clusters Operating system

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

Science.gov (United States)

Rostrup, Scott; De Sterck, Hans

2010-12-01

Increasingly, high-performance computing is looking towards data-parallel computational devices to enhance computational performance. Two technologies that have received significant attention are IBM's Cell Processor and NVIDIA's CUDA programming model for graphics processing unit (GPU) computing. In this paper we investigate the acceleration of parallel hyperbolic partial differential equation simulation on structured grids with explicit time integration on clusters with Cell and GPU backends. The message passing interface (MPI) is used for communication between nodes at the coarsest level of parallelism. Optimizations of the simulation code at the several finer levels of parallelism that the data-parallel devices provide are described in terms of data layout, data flow and data-parallel instructions. Optimized Cell and GPU performance are compared with reference code performance on a single x86 central processing unit (CPU) core in single and double precision. We further compare the CPU, Cell and GPU platforms on a chip-to-chip basis, and compare performance on single cluster nodes with two CPUs, two Cell processors or two GPUs in a shared memory configuration (without MPI). We finally compare performance on clusters with 32 CPUs, 32 Cell processors, and 32 GPUs using MPI. Our GPU cluster results use NVIDIA Tesla GPUs with GT200 architecture, but some preliminary results on recently introduced NVIDIA GPUs with the next-generation Fermi architecture are also included. This paper provides computational scientists and engineers who are considering porting their codes to accelerator environments with insight into how structured grid based explicit algorithms can be optimized for clusters with Cell and GPU accelerators. It also provides insight into the speed-up that may be gained on current and future accelerator architectures for this class of applications. Program summaryProgram title: SWsolver Catalogue identifier: AEGY_v1_0 Program summary URL

Algorithms for computational fluid dynamics n parallel processors

International Nuclear Information System (INIS)

Van de Velde, E.F.

1986-01-01

A study of parallel algorithms for the numerical solution of partial differential equations arising in computational fluid dynamics is presented. The actual implementation on parallel processors of shared and nonshared memory design is discussed. The performance of these algorithms is analyzed in terms of machine efficiency, communication time, bottlenecks and software development costs. For elliptic equations, a parallel preconditioned conjugate gradient method is described, which has been used to solve pressure equations discretized with high order finite elements on irregular grids. A parallel full multigrid method and a parallel fast Poisson solver are also presented. Hyperbolic conservation laws were discretized with parallel versions of finite difference methods like the Lax-Wendroff scheme and with the Random Choice method. Techniques are developed for comparing the behavior of an algorithm on different architectures as a function of problem size and local computational effort. Effective use of these advanced architecture machines requires the use of machine dependent programming. It is shown that the portability problems can be minimized by introducing high level operations on vectors and matrices structured into program libraries

Applications of the parallel computing system using network

International Nuclear Information System (INIS)

Ido, Shunji; Hasebe, Hiroki

1994-01-01

Parallel programming is applied to multiple processors connected in Ethernet. Data exchanges between tasks located in each processing element are realized by two ways. One is socket which is standard library on recent UNIX operating systems. Another is a network connecting software, named as Parallel Virtual Machine (PVM) which is a free software developed by ORNL, to use many workstations connected to network as a parallel computer. This paper discusses the availability of parallel computing using network and UNIX workstations and comparison between specialized parallel systems (Transputer and iPSC/860) in a Monte Carlo simulation which generally shows high parallelization ratio. (author)

Parallel community climate model: Description and user`s guide

Energy Technology Data Exchange (ETDEWEB)

Drake, J.B.; Flanery, R.E.; Semeraro, B.D.; Worley, P.H. [and others

1996-07-15

This report gives an overview of a parallel version of the NCAR Community Climate Model, CCM2, implemented for MIMD massively parallel computers using a message-passing programming paradigm. The parallel implementation was developed on an Intel iPSC/860 with 128 processors and on the Intel Delta with 512 processors, and the initial target platform for the production version of the code is the Intel Paragon with 2048 processors. Because the implementation uses a standard, portable message-passing libraries, the code has been easily ported to other multiprocessors supporting a message-passing programming paradigm. The parallelization strategy used is to decompose the problem domain into geographical patches and assign each processor the computation associated with a distinct subset of the patches. With this decomposition, the physics calculations involve only grid points and data local to a processor and are performed in parallel. Using parallel algorithms developed for the semi-Lagrangian transport, the fast Fourier transform and the Legendre transform, both physics and dynamics are computed in parallel with minimal data movement and modest change to the original CCM2 source code. Sequential or parallel history tapes are written and input files (in history tape format) are read sequentially by the parallel code to promote compatibility with production use of the model on other computer systems. A validation exercise has been performed with the parallel code and is detailed along with some performance numbers on the Intel Paragon and the IBM SP2. A discussion of reproducibility of results is included. A user`s guide for the PCCM2 version 2.1 on the various parallel machines completes the report. Procedures for compilation, setup and execution are given. A discussion of code internals is included for those who may wish to modify and use the program in their own research.

Parallel Libraries to support High-Level Programming

DEFF Research Database (Denmark)

Larsen, Morten Nørgaard

and the Microsoft .NET iv framework. Normally, one would not directly think of the .NET framework when talking scientific applications, but Microsoft has in the last couple of versions of .NET introduce a number of tools for writing parallel and high performance code. The first section examines how programmers can...

An Expert System for the Development of Efficient Parallel Code

Science.gov (United States)

Jost, Gabriele; Chun, Robert; Jin, Hao-Qiang; Labarta, Jesus; Gimenez, Judit

2004-01-01

We have built the prototype of an expert system to assist the user in the development of efficient parallel code. The system was integrated into the parallel programming environment that is currently being developed at NASA Ames. The expert system interfaces to tools for automatic parallelization and performance analysis. It uses static program structure information and performance data in order to automatically determine causes of poor performance and to make suggestions for improvements. In this paper we give an overview of our programming environment, describe the prototype implementation of our expert system, and demonstrate its usefulness with several case studies.

Directions in parallel processor architecture, and GPUs too

CERN Multimedia

CERN. Geneva

2014-01-01

Modern computing is power-limited in every domain of computing. Performance increments extracted from instruction-level parallelism (ILP) are no longer power-efficient; they haven't been for some time. Thread-level parallelism (TLP) is a more easily exploited form of parallelism, at the expense of programmer effort to expose it in the program. In this talk, I will introduce you to disparate topics in parallel processor architecture that will impact programming models (and you) in both the near and far future. About the speaker Olivier is a senior GPU (SM) architect at NVIDIA and an active participant in the concurrency working group of the ISO C++ committee. He has also worked on very large diesel engines as a mechanical engineer, and taught at McGill University (Canada) as a faculty instructor.

Abstract Level Parallelization of Finite Difference Methods

Directory of Open Access Journals (Sweden)

Edwin Vollebregt

1997-01-01

Full Text Available A formalism is proposed for describing finite difference calculations in an abstract way. The formalism consists of index sets and stencils, for characterizing the structure of sets of data items and interactions between data items (“neighbouring relations”. The formalism provides a means for lifting programming to a more abstract level. This simplifies the tasks of performance analysis and verification of correctness, and opens the way for automaticcode generation. The notation is particularly useful in parallelization, for the systematic construction of parallel programs in a process/channel programming paradigm (e.g., message passing. This is important because message passing, unfortunately, still is the only approach that leads to acceptable performance for many more unstructured or irregular problems on parallel computers that have non-uniform memory access times. It will be shown that the use of index sets and stencils greatly simplifies the determination of which data must be exchanged between different computing processes.

Block-Parallel Data Analysis with DIY2

Energy Technology Data Exchange (ETDEWEB)

Morozov, Dmitriy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Peterka, Tom [Argonne National Lab. (ANL), Argonne, IL (United States)

2017-08-30

DIY2 is a programming model and runtime for block-parallel analytics on distributed-memory machines. Its main abstraction is block-structured data parallelism: data are decomposed into blocks; blocks are assigned to processing elements (processes or threads); computation is described as iterations over these blocks, and communication between blocks is defined by reusable patterns. By expressing computation in this general form, the DIY2 runtime is free to optimize the movement of blocks between slow and fast memories (disk and flash vs. DRAM) and to concurrently execute blocks residing in memory with multiple threads. This enables the same program to execute in-core, out-of-core, serial, parallel, single-threaded, multithreaded, or combinations thereof. This paper describes the implementation of the main features of the DIY2 programming model and optimizations to improve performance. DIY2 is evaluated on benchmark test cases to establish baseline performance for several common patterns and on larger complete analysis codes running on large-scale HPC machines.

Parallel algorithms for continuum dynamics

International Nuclear Information System (INIS)

Hicks, D.L.; Liebrock, L.M.

1987-01-01

Simply porting existing parallel programs to a new parallel processor may not achieve the full speedup possible; to achieve the maximum efficiency may require redesigning the parallel algorithms for the specific architecture. The authors discuss here parallel algorithms that were developed first for the HEP processor and then ported to the CRAY X-MP/4, the ELXSI/10, and the Intel iPSC/32. Focus is mainly on the most recent parallel processing results produced, i.e., those on the Intel Hypercube. The applications are simulations of continuum dynamics in which the momentum and stress gradients are important. Examples of these are inertial confinement fusion experiments, severe breaks in the coolant system of a reactor, weapons physics, shock-wave physics. Speedup efficiencies on the Intel iPSC Hypercube are very sensitive to the ratio of communication to computation. Great care must be taken in designing algorithms for this machine to avoid global communication. This is much more critical on the iPSC than it was on the three previous parallel processors

Parallelization of the model-based iterative reconstruction algorithm DIRA

International Nuclear Information System (INIS)

Oertenberg, A.; Sandborg, M.; Alm Carlsson, G.; Malusek, A.; Magnusson, M.

2016-01-01

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelization of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelization of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelized using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelization of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelization with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained. (authors)

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

Science.gov (United States)

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Searching for globally optimal functional forms for interatomic potentials using genetic programming with parallel tempering.

Science.gov (United States)

Slepoy, A; Peters, M D; Thompson, A P

2007-11-30

Molecular dynamics and other molecular simulation methods rely on a potential energy function, based only on the relative coordinates of the atomic nuclei. Such a function, called a force field, approximately represents the electronic structure interactions of a condensed matter system. Developing such approximate functions and fitting their parameters remains an arduous, time-consuming process, relying on expert physical intuition. To address this problem, a functional programming methodology was developed that may enable automated discovery of entirely new force-field functional forms, while simultaneously fitting parameter values. The method uses a combination of genetic programming, Metropolis Monte Carlo importance sampling and parallel tempering, to efficiently search a large space of candidate functional forms and parameters. The methodology was tested using a nontrivial problem with a well-defined globally optimal solution: a small set of atomic configurations was generated and the energy of each configuration was calculated using the Lennard-Jones pair potential. Starting with a population of random functions, our fully automated, massively parallel implementation of the method reproducibly discovered the original Lennard-Jones pair potential by searching for several hours on 100 processors, sampling only a minuscule portion of the total search space. This result indicates that, with further improvement, the method may be suitable for unsupervised development of more accurate force fields with completely new functional forms. Copyright (c) 2007 Wiley Periodicals, Inc.

Experience with a clustered parallel reduction machine

NARCIS (Netherlands)

Beemster, M.; Hartel, Pieter H.; Hertzberger, L.O.; Hofman, R.F.H.; Langendoen, K.G.; Li, L.L.; Milikowski, R.; Vree, W.G.; Barendregt, H.P.; Mulder, J.C.

A clustered architecture has been designed to exploit divide and conquer parallelism in functional programs. The programming methodology developed for the machine is based on explicit annotations and program transformations. It has been successfully applied to a number of algorithms resulting in a

A high-speed linear algebra library with automatic parallelism

Science.gov (United States)

Boucher, Michael L.

1994-01-01

Parallel or distributed processing is key to getting highest performance workstations. However, designing and implementing efficient parallel algorithms is difficult and error-prone. It is even more difficult to write code that is both portable to and efficient on many different computers. Finally, it is harder still to satisfy the above requirements and include the reliability and ease of use required of commercial software intended for use in a production environment. As a result, the application of parallel processing technology to commercial software has been extremely small even though there are numerous computationally demanding programs that would significantly benefit from application of parallel processing. This paper describes DSSLIB, which is a library of subroutines that perform many of the time-consuming computations in engineering and scientific software. DSSLIB combines the high efficiency and speed of parallel computation with a serial programming model that eliminates many undesirable side-effects of typical parallel code. The result is a simple way to incorporate the power of parallel processing into commercial software without compromising maintainability, reliability, or ease of use. This gives significant advantages over less powerful non-parallel entries in the market.

Drainage network extraction from a high-resolution DEM using parallel programming in the .NET Framework

Science.gov (United States)

Du, Chao; Ye, Aizhong; Gan, Yanjun; You, Jinjun; Duan, Qinyun; Ma, Feng; Hou, Jingwen

2017-12-01

High-resolution Digital Elevation Models (DEMs) can be used to extract high-accuracy prerequisite drainage networks. A higher resolution represents a larger number of grids. With an increase in the number of grids, the flow direction determination will require substantial computer resources and computing time. Parallel computing is a feasible method with which to resolve this problem. In this paper, we proposed a parallel programming method within the .NET Framework with a C# Compiler in a Windows environment. The basin is divided into sub-basins, and subsequently the different sub-basins operate on multiple threads concurrently to calculate flow directions. The method was applied to calculate the flow direction of the Yellow River basin from 3 arc-second resolution SRTM DEM. Drainage networks were extracted and compared with HydroSHEDS river network to assess their accuracy. The results demonstrate that this method can calculate the flow direction from high-resolution DEMs efficiently and extract high-precision continuous drainage networks.

The Fortran-P Translator: Towards Automatic Translation of Fortran 77 Programs for Massively Parallel Processors

Directory of Open Access Journals (Sweden)

Matthew O'keefe

1995-01-01

Full Text Available Massively parallel processors (MPPs hold the promise of extremely high performance that, if realized, could be used to study problems of unprecedented size and complexity. One of the primary stumbling blocks to this promise has been the lack of tools to translate application codes to MPP form. In this article we show how applications codes written in a subset of Fortran 77, called Fortran-P, can be translated to achieve good performance on several massively parallel machines. This subset can express codes that are self-similar, where the algorithm applied to the global data domain is also applied to each subdomain. We have found many codes that match the Fortran-P programming style and have converted them using our tools. We believe a self-similar coding style will accomplish what a vectorizable style has accomplished for vector machines by allowing the construction of robust, user-friendly, automatic translation systems that increase programmer productivity and generate fast, efficient code for MPPs.

Combining Compile-Time and Run-Time Parallelization

Directory of Open Access Journals (Sweden)

Sungdo Moon

1999-01-01

Full Text Available This paper demonstrates that significant improvements to automatic parallelization technology require that existing systems be extended in two ways: (1 they must combine high‐quality compile‐time analysis with low‐cost run‐time testing; and (2 they must take control flow into account during analysis. We support this claim with the results of an experiment that measures the safety of parallelization at run time for loops left unparallelized by the Stanford SUIF compiler’s automatic parallelization system. We present results of measurements on programs from two benchmark suites – SPECFP95 and NAS sample benchmarks – which identify inherently parallel loops in these programs that are missed by the compiler. We characterize remaining parallelization opportunities, and find that most of the loops require run‐time testing, analysis of control flow, or some combination of the two. We present a new compile‐time analysis technique that can be used to parallelize most of these remaining loops. This technique is designed to not only improve the results of compile‐time parallelization, but also to produce low‐cost, directed run‐time tests that allow the system to defer binding of parallelization until run‐time when safety cannot be proven statically. We call this approach predicated array data‐flow analysis. We augment array data‐flow analysis, which the compiler uses to identify independent and privatizable arrays, by associating predicates with array data‐flow values. Predicated array data‐flow analysis allows the compiler to derive “optimistic” data‐flow values guarded by predicates; these predicates can be used to derive a run‐time test guaranteeing the safety of parallelization.

A CS1 pedagogical approach to parallel thinking

Science.gov (United States)

Rague, Brian William

Almost all collegiate programs in Computer Science offer an introductory course in programming primarily devoted to communicating the foundational principles of software design and development. The ACM designates this introduction to computer programming course for first-year students as CS1, during which methodologies for solving problems within a discrete computational context are presented. Logical thinking is highlighted, guided primarily by a sequential approach to algorithm development and made manifest by typically using the latest, commercially successful programming language. In response to the most recent developments in accessible multicore computers, instructors of these introductory classes may wish to include training on how to design workable parallel code. Novel issues arise when programming concurrent applications which can make teaching these concepts to beginning programmers a seemingly formidable task. Student comprehension of design strategies related to parallel systems should be monitored to ensure an effective classroom experience. This research investigated the feasibility of integrating parallel computing concepts into the first-year CS classroom. To quantitatively assess student comprehension of parallel computing, an experimental educational study using a two-factor mixed group design was conducted to evaluate two instructional interventions in addition to a control group: (1) topic lecture only, and (2) topic lecture with laboratory work using a software visualization Parallel Analysis Tool (PAT) specifically designed for this project. A new evaluation instrument developed for this study, the Perceptions of Parallelism Survey (PoPS), was used to measure student learning regarding parallel systems. The results from this educational study show a statistically significant main effect among the repeated measures, implying that student comprehension levels of parallel concepts as measured by the PoPS improve immediately after the delivery of

Finite element electromagnetic field computation on the Sequent Symmetry 81 parallel computer

International Nuclear Information System (INIS)

Ratnajeevan, S.; Hoole, H.

1990-01-01

Finite element field analysis algorithms lend themselves to parallelization and this fact is exploited in this paper to implement a finite element analysis program for electromagnetic field computation on the Sequent Symmetry 81 parallel computer with three processors. In terms of waiting time, the maximum gains are to be made in matrix solution and therefore this paper concentrates on the gains in parallelizing the solution part of finite element analysis. An outline of how parallelization could be exploited in most finite element operations is given in this paper although the actual implemention of parallelism on the Sequent Symmetry 81 parallel computer was in sparsity computation, matrix assembly and the matrix solution areas. In all cases, the algorithms were modified suit the parallel programming application rather than allowing the compiler to parallelize on existing algorithms

Discrete Hadamard transformation algorithm's parallelism analysis and achievement

Science.gov (United States)

Hu, Hui

2009-07-01

With respect to Discrete Hadamard Transformation (DHT) wide application in real-time signal processing while limitation in operation speed of DSP. The article makes DHT parallel research and its parallel performance analysis. Based on multiprocessor platform-TMS320C80 programming structure, the research is carried out to achieve two kinds of parallel DHT algorithms. Several experiments demonstrated the effectiveness of the proposed algorithms.

Is Monte Carlo embarrassingly parallel?

Energy Technology Data Exchange (ETDEWEB)

Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands); Delft Nuclear Consultancy, IJsselzoom 2, 2902 LB Capelle aan den IJssel (Netherlands)

2012-07-01

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

Is Monte Carlo embarrassingly parallel?

International Nuclear Information System (INIS)

Hoogenboom, J. E.

2012-01-01

Monte Carlo is often stated as being embarrassingly parallel. However, running a Monte Carlo calculation, especially a reactor criticality calculation, in parallel using tens of processors shows a serious limitation in speedup and the execution time may even increase beyond a certain number of processors. In this paper the main causes of the loss of efficiency when using many processors are analyzed using a simple Monte Carlo program for criticality. The basic mechanism for parallel execution is MPI. One of the bottlenecks turn out to be the rendez-vous points in the parallel calculation used for synchronization and exchange of data between processors. This happens at least at the end of each cycle for fission source generation in order to collect the full fission source distribution for the next cycle and to estimate the effective multiplication factor, which is not only part of the requested results, but also input to the next cycle for population control. Basic improvements to overcome this limitation are suggested and tested. Also other time losses in the parallel calculation are identified. Moreover, the threading mechanism, which allows the parallel execution of tasks based on shared memory using OpenMP, is analyzed in detail. Recommendations are given to get the maximum efficiency out of a parallel Monte Carlo calculation. (authors)

A program system for ab initio MO calculations on vector and parallel processing machines. Pt. 3

International Nuclear Information System (INIS)

Wiest, R.; Demuynck, J.; Benard, M.; Rohmer, M.M.; Ernenwein, R.

1991-01-01

This series of three papers presents a program system for ab initio molecular orbital calculations on vector and parallel computers. Part III is devoted to the four-index transformation on a molecular orbital basis of size NMO of the file of two-electorn integrals (pqparallelrs) generated by a contracted Gaussian set of size NATO (number of atomic orbitals). A fast Yoshimine algorithm first sorts the (pqparallelrs) integrals with respect to index pq only. This file of half-sorted integrals labelled by their rs-index can be processed without further modification to generate either the transformed integrals or the supermatrix elements. The large memory available on the CRAY-2 hase made possible to implement the transformation algorithm proposed by Bender in 1972, which requires a core-storage allocation varying as (NATO) 3 . Two versions of Bender's algorithm are included in the present program. The first version is an in-core version, where the complete file of accumulated contributions to transformed integrals in stored and updated in central memory. This version has been parallelized by distributing over a limited number of logical tasks the NATO steps corresponding to the scanning of the most external loop. The second version is an out-of-core version, in which twin files are alternatively used as input and output for the accumulated contributions to transformed integrals. This version is not parallel. The choice of one or another version and (for version 1) the determination of the number of tasks depends upon the balance between the available and the requested amounts of storage. The storage management and the choice of the proper version are carried out automatically using dynamic storage allocation. Both versions are vectorized and take advantage of the molecular symmetry. (orig.)

Parallelization of elliptic solver for solving 1D Boussinesq model

Science.gov (United States)

Tarwidi, D.; Adytia, D.

2018-03-01

In this paper, a parallel implementation of an elliptic solver in solving 1D Boussinesq model is presented. Numerical solution of Boussinesq model is obtained by implementing a staggered grid scheme to continuity, momentum, and elliptic equation of Boussinesq model. Tridiagonal system emerging from numerical scheme of elliptic equation is solved by cyclic reduction algorithm. The parallel implementation of cyclic reduction is executed on multicore processors with shared memory architectures using OpenMP. To measure the performance of parallel program, large number of grids is varied from 28 to 214. Two test cases of numerical experiment, i.e. propagation of solitary and standing wave, are proposed to evaluate the parallel program. The numerical results are verified with analytical solution of solitary and standing wave. The best speedup of solitary and standing wave test cases is about 2.07 with 214 of grids and 1.86 with 213 of grids, respectively, which are executed by using 8 threads. Moreover, the best efficiency of parallel program is 76.2% and 73.5% for solitary and standing wave test cases, respectively.

Vectorization, parallelization and porting of nuclear codes (vectorization and parallelization). Progress report fiscal 1998

International Nuclear Information System (INIS)

Ishizuki, Shigeru; Kawai, Wataru; Nemoto, Toshiyuki; Ogasawara, Shinobu; Kume, Etsuo; Adachi, Masaaki; Kawasaki, Nobuo; Yatake, Yo-ichi

2000-03-01

Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system, the AP3000 system and the Paragon system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 12 codes in fiscal 1998. These results are reported in 3 parts, i.e., the vectorization and parallelization on vector processors part, the parallelization on scalar processors part and the porting part. In this report, we describe the vectorization and parallelization on vector processors. In this vectorization and parallelization on vector processors part, the vectorization of General Tokamak Circuit Simulation Program code GTCSP, the vectorization and parallelization of Molecular Dynamics NTV (n-particle, Temperature and Velocity) Simulation code MSP2, Eddy Current Analysis code EDDYCAL, Thermal Analysis Code for Test of Passive Cooling System by HENDEL T2 code THANPACST2 and MHD Equilibrium code SELENEJ on the VPP500 are described. In the parallelization on scalar processors part, the parallelization of Monte Carlo N-Particle Transport code MCNP4B2, Plasma Hydrodynamics code using Cubic Interpolated Propagation Method PHCIP and Vectorized Monte Carlo code (continuous energy model / multi-group model) MVP/GMVP on the Paragon are described. In the porting part, the porting of Monte Carlo N-Particle Transport code MCNP4B2 and Reactor Safety Analysis code RELAP5 on the AP3000 are described. (author)

Massively parallel sparse matrix function calculations with NTPoly

Science.gov (United States)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

An efficient implementation of parallel molecular dynamics method on SMP cluster architecture

International Nuclear Information System (INIS)

Suzuki, Masaaki; Okuda, Hiroshi; Yagawa, Genki

2003-01-01

The authors have applied MPI/OpenMP hybrid parallel programming model to parallelize a molecular dynamics (MD) method on a symmetric multiprocessor (SMP) cluster architecture. In that architecture, it can be expected that the hybrid parallel programming model, which uses the message passing library such as MPI for inter-SMP node communication and the loop directive such as OpenMP for intra-SNP node parallelization, is the most effective one. In this study, the parallel performance of the hybrid style has been compared with that of conventional flat parallel programming style, which uses only MPI, both in cases the fast multipole method (FMM) is employed for computing long-distance interactions and that is not employed. The computer environments used here are Hitachi SR8000/MPP placed at the University of Tokyo. The results of calculation are as follows. Without FMM, the parallel efficiency using 16 SMP nodes (128 PEs) is: 90% with the hybrid style, 75% with the flat-MPI style for MD simulation with 33,402 atoms. With FMM, the parallel efficiency using 16 SMP nodes (128 PEs) is: 60% with the hybrid style, 48% with the flat-MPI style for MD simulation with 117,649 atoms. (author)

6th International Parallel Tools Workshop

CERN Document Server

Brinkmann, Steffen; Gracia, José; Resch, Michael; Nagel, Wolfgang

2013-01-01

The latest advances in the High Performance Computing hardware have significantly raised the level of available compute performance. At the same time, the growing hardware capabilities of modern supercomputing architectures have caused an increasing complexity of the parallel application development. Despite numerous efforts to improve and simplify parallel programming, there is still a lot of manual debugging and  tuning work required. This process  is supported by special software tools, facilitating debugging, performance analysis, and optimization and thus  making a major contribution to the development of  robust and efficient parallel software. This book introduces a selection of the tools, which were presented and discussed at the 6th International Parallel Tools Workshop, held in Stuttgart, Germany, 25-26 September 2012.

Expressing Parallelism with ROOT

Energy Technology Data Exchange (ETDEWEB)

Piparo, D. [CERN; Tejedor, E. [CERN; Guiraud, E. [CERN; Ganis, G. [CERN; Mato, P. [CERN; Moneta, L. [CERN; Valls Pla, X. [CERN; Canal, P. [Fermilab

2017-11-22

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.

Expressing Parallelism with ROOT

Science.gov (United States)

Piparo, D.; Tejedor, E.; Guiraud, E.; Ganis, G.; Mato, P.; Moneta, L.; Valls Pla, X.; Canal, P.

2017-10-01

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.

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.

Comparative Evaluation and Case Studies of Shared-Memory and Data-Parallel Execution Patterns

Directory of Open Access Journals (Sweden)

Xiaodong Zhang

1999-01-01

Full Text Available Shared‐memory and data‐parallel programming models are two important paradigms for scientific applications. Both models provide high‐level program abstractions, and simple and uniform views of network structures. The common features of the two models significantly simplify program coding and debugging for scientific applications. However, the underlining execution and overhead patterns are significantly different between the two models due to their programming constraints, and due to different and complex structures of interconnection networks and systems which support the two models. We performed this experimental study to present implications and comparisons of execution patterns on two commercial architectures. We implemented a standard electromagnetic simulation program (EM and a linear system solver using the shared‐memory model on the KSR‐1 and the data‐parallel model on the CM‐5. Our objectives are to examine the execution pattern changes required for an implementation transformation between the two models; to study memory access patterns; to address scalability issues; and to investigate relative costs and advantages/disadvantages of using the two models for scientific computations. Our results indicate that the EM program tends to become computation‐intensive in the KSR‐1 shared‐memory system, and memory‐demanding in the CM‐5 data‐parallel system when the systems and the problems are scaled. The EM program, a highly data‐parallel program performed extremely well, and the linear system solver, a highly control‐structured program suffered significantly in the data‐parallel model on the CM‐5. Our study provides further evidence that matching execution patterns of algorithms to parallel architectures would achieve better performance.

An Educational Tool for Interactive Parallel and Distributed Processing

DEFF Research Database (Denmark)

Pagliarini, Luigi; Lund, Henrik Hautop

2011-01-01

In this paper we try to describe how the Modular Interactive Tiles System (MITS) can be a valuable tool for introducing students to interactive parallel and distributed processing programming. This is done by providing an educational hands-on tool that allows a change of representation of the abs......In this paper we try to describe how the Modular Interactive Tiles System (MITS) can be a valuable tool for introducing students to interactive parallel and distributed processing programming. This is done by providing an educational hands-on tool that allows a change of representation...... of the abstract problems related to designing interactive parallel and distributed systems. Indeed, MITS seems to bring a series of goals into the education, such as parallel programming, distributedness, communication protocols, master dependency, software behavioral models, adaptive interactivity, feedback......, connectivity, topology, island modeling, user and multiuser interaction, which can hardly be found in other tools. Finally, we introduce the system of modular interactive tiles as a tool for easy, fast, and flexible hands-on exploration of these issues, and through examples show how to implement interactive...

Parallel treatment of simulation particles in particle-in-cell codes on SUPRENUM

International Nuclear Information System (INIS)

Seldner, D.

1990-02-01

This report contains the program documentation and description of the program package 2D-PLAS, which has been developed at the Nuclear Research Center Karlsruhe in the Institute for Data Processing in Technology (IDT) under the auspices of the BMFT. 2D-PLAS is a parallel program version of the treatment of the simulation particles of the two-dimensional stationary particle-in-cell code BFCPIC which has been developed at the Nuclear Research Center Karlsruhe. This parallel version has been designed for the parallel computer SUPRENUM. (orig.) [de

Collectively loading programs in a multiple program multiple data environment

Science.gov (United States)

Aho, Michael E.; Attinella, John E.; Gooding, Thomas M.; Gooding, Thomas M.; Miller, Samuel J.

2016-11-08

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

Introducing PROFESS 2.0: A parallelized, fully linear scaling program for orbital-free density functional theory calculations

Science.gov (United States)

Hung, Linda; Huang, Chen; Shin, Ilgyou; Ho, Gregory S.; Lignères, Vincent L.; Carter, Emily A.

2010-12-01

Orbital-free density functional theory (OFDFT) is a first principles quantum mechanics method to find the ground-state energy of a system by variationally minimizing with respect to the electron density. No orbitals are used in the evaluation of the kinetic energy (unlike Kohn-Sham DFT), and the method scales nearly linearly with the size of the system. The PRinceton Orbital-Free Electronic Structure Software (PROFESS) uses OFDFT to model materials from the atomic scale to the mesoscale. This new version of PROFESS allows the study of larger systems with two significant changes: PROFESS is now parallelized, and the ion-electron and ion-ion terms scale quasilinearly, instead of quadratically as in PROFESS v1 (L. Hung and E.A. Carter, Chem. Phys. Lett. 475 (2009) 163). At the start of a run, PROFESS reads the various input files that describe the geometry of the system (ion positions and cell dimensions), the type of elements (defined by electron-ion pseudopotentials), the actions you want it to perform (minimize with respect to electron density and/or ion positions and/or cell lattice vectors), and the various options for the computation (such as which functionals you want it to use). Based on these inputs, PROFESS sets up a computation and performs the appropriate optimizations. Energies, forces, stresses, material geometries, and electron density configurations are some of the values that can be output throughout the optimization. New version program summaryProgram Title: PROFESS Catalogue identifier: AEBN_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEBN_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 68 721 No. of bytes in distributed program, including test data, etc.: 1 708 547 Distribution format: tar.gz Programming language: Fortran 90 Computer

SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws

Science.gov (United States)

Cooke, Daniel; Rushton, Nelson

2013-01-01

With the introduction of new parallel architectures like the cell and multicore chips from IBM, Intel, AMD, and ARM, as well as the petascale processing available for highend computing, a larger number of programmers will need to write parallel codes. Adding the parallel control structure to the sequence, selection, and iterative control constructs increases the complexity of code development, which often results in increased development costs and decreased reliability. SequenceL is a high-level programming language that is, a programming language that is closer to a human s way of thinking than to a machine s. Historically, high-level languages have resulted in decreased development costs and increased reliability, at the expense of performance. In recent applications at JSC and in industry, SequenceL has demonstrated the usual advantages of high-level programming in terms of low cost and high reliability. SequenceL programs, however, have run at speeds typically comparable with, and in many cases faster than, their counterparts written in C and C++ when run on single-core processors. Moreover, SequenceL is able to generate parallel executables automatically for multicore hardware, gaining parallel speedups without any extra effort from the programmer beyond what is required to write the sequen tial/singlecore code. A SequenceL-to-C++ translator has been developed that automatically renders readable multithreaded C++ from a combination of a SequenceL program and sample data input. The SequenceL language is based on two fundamental computational laws, Consume-Simplify- Produce (CSP) and Normalize-Trans - pose (NT), which enable it to automate the creation of parallel algorithms from high-level code that has no annotations of parallelism whatsoever. In our anecdotal experience, SequenceL development has been in every case less costly than development of the same algorithm in sequential (that is, single-core, single process) C or C++, and an order of magnitude less

Parallel-Architecture Simulator Development Using Hardware Transactional Memory

OpenAIRE

Armejach Sanosa, Adrià

2009-01-01

To address the need for a simpler parallel programming model, Transactional Memory (TM) has been developed and promises good parallel performance with easy-to-write parallel code. Unlike lock-based approaches, with TM, programmers do not need to explicitly specify and manage the synchronization among threads. However, programmers simply mark code segments as transactions, and the TM system manages the concurrency control for them. TM can be implemented either in software (STM) or hardware (HT...

Using Coarrays to Parallelize Legacy Fortran Applications: Strategy and Case Study

Directory of Open Access Journals (Sweden)

Hari Radhakrishnan

2015-01-01

Full Text Available This paper summarizes a strategy for parallelizing a legacy Fortran 77 program using the object-oriented (OO and coarray features that entered Fortran in the 2003 and 2008 standards, respectively. OO programming (OOP facilitates the construction of an extensible suite of model-verification and performance tests that drive the development. Coarray parallel programming facilitates a rapid evolution from a serial application to a parallel application capable of running on multicore processors and many-core accelerators in shared and distributed memory. We delineate 17 code modernization steps used to refactor and parallelize the program and study the resulting performance. Our initial studies were done using the Intel Fortran compiler on a 32-core shared memory server. Scaling behavior was very poor, and profile analysis using TAU showed that the bottleneck in the performance was due to our implementation of a collective, sequential summation procedure. We were able to improve the scalability and achieve nearly linear speedup by replacing the sequential summation with a parallel, binary tree algorithm. We also tested the Cray compiler, which provides its own collective summation procedure. Intel provides no collective reductions. With Cray, the program shows linear speedup even in distributed-memory execution. We anticipate similar results with other compilers once they support the new collective procedures proposed for Fortran 2015.

Parallel Programming Application to Matrix Algebra in the Spectral Method for Control Systems Analysis, Synthesis and Identification

Directory of Open Access Journals (Sweden)

V. Yu. Kleshnin

2016-01-01

Full Text Available The article describes the matrix algebra libraries based on the modern technologies of parallel programming for the Spectrum software, which can use a spectral method (in the spectral form of mathematical description to analyse, synthesise and identify deterministic and stochastic dynamical systems. The developed matrix algebra libraries use the following technologies for the GPUs: OmniThreadLibrary, OpenMP, Intel Threading Building Blocks, Intel Cilk Plus for CPUs nVidia CUDA, OpenCL, and Microsoft Accelerated Massive Parallelism.The developed libraries support matrices with real elements (single and double precision. The matrix dimensions are limited by 32-bit or 64-bit memory model and computer configuration. These libraries are general-purpose and can be used not only for the Spectrum software. They can also find application in the other projects where there is a need to perform operations with large matrices.The article provides a comparative analysis of the libraries developed for various matrix operations (addition, subtraction, scalar multiplication, multiplication, powers of matrices, tensor multiplication, transpose, inverse matrix, finding a solution of the system of linear equations through the numerical experiments using different CPU and GPU. The article contains sample programs and performance test results for matrix multiplication, which requires most of all computational resources in regard to the other operations.

Explorations of the implementation of a parallel IDW interpolation algorithm in a Linux cluster-based parallel GIS

Science.gov (United States)

Huang, Fang; Liu, Dingsheng; Tan, Xicheng; Wang, Jian; Chen, Yunping; He, Binbin

2011-04-01

To design and implement an open-source parallel GIS (OP-GIS) based on a Linux cluster, the parallel inverse distance weighting (IDW) interpolation algorithm has been chosen as an example to explore the working model and the principle of algorithm parallel pattern (APP), one of the parallelization patterns for OP-GIS. Based on an analysis of the serial IDW interpolation algorithm of GRASS GIS, this paper has proposed and designed a specific parallel IDW interpolation algorithm, incorporating both single process, multiple data (SPMD) and master/slave (M/S) programming modes. The main steps of the parallel IDW interpolation algorithm are: (1) the master node packages the related information, and then broadcasts it to the slave nodes; (2) each node calculates its assigned data extent along one row using the serial algorithm; (3) the master node gathers the data from all nodes; and (4) iterations continue until all rows have been processed, after which the results are outputted. According to the experiments performed in the course of this work, the parallel IDW interpolation algorithm can attain an efficiency greater than 0.93 compared with similar algorithms, which indicates that the parallel algorithm can greatly reduce processing time and maximize speed and performance.

Parallel Conjugate Gradient: Effects of Ordering Strategies, Programming Paradigms, and Architectural Platforms

Science.gov (United States)

Oliker, Leonid; Heber, Gerd; Biswas, Rupak

2000-01-01

The Conjugate Gradient (CG) algorithm is perhaps the best-known iterative technique to solve sparse linear systems that are symmetric and positive definite. A sparse matrix-vector multiply (SPMV) usually accounts for most of the floating-point operations within a CG iteration. In this paper, we investigate the effects of various ordering and partitioning strategies on the performance of parallel CG and SPMV using different programming paradigms and architectures. Results show that for this class of applications, ordering significantly improves overall performance, that cache reuse may be more important than reducing communication, and that it is possible to achieve message passing performance using shared memory constructs through careful data ordering and distribution. However, a multi-threaded implementation of CG on the Tera MTA does not require special ordering or partitioning to obtain high efficiency and scalability.

Study on MPI/OpenMP hybrid parallelism for Monte Carlo neutron transport code

International Nuclear Information System (INIS)

Liang Jingang; Xu Qi; Wang Kan; Liu Shiwen

2013-01-01

Parallel programming with mixed mode of messages-passing and shared-memory has several advantages when used in Monte Carlo neutron transport code, such as fitting hardware of distributed-shared clusters, economizing memory demand of Monte Carlo transport, improving parallel performance, and so on. MPI/OpenMP hybrid parallelism was implemented based on a one dimension Monte Carlo neutron transport code. Some critical factors affecting the parallel performance were analyzed and solutions were proposed for several problems such as contention access, lock contention and false sharing. After optimization the code was tested finally. It is shown that the hybrid parallel code can reach good performance just as pure MPI parallel program, while it saves a lot of memory usage at the same time. Therefore hybrid parallel is efficient for achieving large-scale parallel of Monte Carlo neutron transport. (authors)

Truly nested data-parallelism: compiling SaC for the Microgrid architecture

NARCIS (Netherlands)

Herhut, S.; Joslin, C.; Scholz, S.-B.; Grelck, C.; Morazan, M.

2009-01-01

Data-parallel programming facilitates elegant specification of concurrency. However, the composability of data-parallel operations so far has been constrained by the requirement to have only at data- parallel operation at runtime. In this paper, we present early results on our work to exploit

Final Report, Center for Programming Models for Scalable Parallel Computing: Co-Array Fortran, Grant Number DE-FC02-01ER25505

Energy Technology Data Exchange (ETDEWEB)

Robert W. Numrich

2008-04-22

The major accomplishment of this project is the production of CafLib, an 'object-oriented' parallel numerical library written in Co-Array Fortran. CafLib contains distributed objects such as block vectors and block matrices along with procedures, attached to each object, that perform basic linear algebra operations such as matrix multiplication, matrix transpose and LU decomposition. It also contains constructors and destructors for each object that hide the details of data decomposition from the programmer, and it contains collective operations that allow the programmer to calculate global reductions, such as global sums, global minima and global maxima, as well as vector and matrix norms of several kinds. CafLib is designed to be extensible in such a way that programmers can define distributed grid and field objects, based on vector and matrix objects from the library, for finite difference algorithms to solve partial differential equations. A very important extra benefit that resulted from the project is the inclusion of the co-array programming model in the next Fortran standard called Fortran 2008. It is the first parallel programming model ever included as a standard part of the language. Co-arrays will be a supported feature in all Fortran compilers, and the portability provided by standardization will encourage a large number of programmers to adopt it for new parallel application development. The combination of object-oriented programming in Fortran 2003 with co-arrays in Fortran 2008 provides a very powerful programming model for high-performance scientific computing. Additional benefits from the project, beyond the original goal, include a programto provide access to the co-array model through access to the Cray compiler as a resource for teaching and research. Several academics, for the first time, included the co-array model as a topic in their courses on parallel computing. A separate collaborative project with LANL and PNNL showed how to

Pthreads vs MPI Parallel Performance of Angular-Domain Decomposed S

International Nuclear Information System (INIS)

Azmy, Y.Y.; Barnett, D.A.

2000-01-01

Two programming models for parallelizing the Angular Domain Decomposition (ADD) of the discrete ordinates (S n ) approximation of the neutron transport equation are examined. These are the shared memory model based on the POSIX threads (Pthreads) standard, and the message passing model based on the Message Passing Interface (MPI) standard. These standard libraries are available on most multiprocessor platforms thus making the resulting parallel codes widely portable. The question is: on a fixed platform, and for a particular code solving a given test problem, which of the two programming models delivers better parallel performance? Such comparison is possible on Symmetric Multi-Processors (SMP) architectures in which several CPUs physically share a common memory, and in addition are capable of emulating message passing functionality. Implementation of the two-dimensional,(S n ), Arbitrarily High Order Transport (AHOT) code for solving neutron transport problems using these two parallelization models is described. Measured parallel performance of each model on the COMPAQ AlphaServer 8400 and the SGI Origin 2000 platforms is described, and comparison of the observed speedup for the two programming models is reported. For the case presented in this paper it appears that the MPI implementation scales better than the Pthreads implementation on both platforms

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.

2017-03-13

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it\\'s time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Exploration Of Deep Learning Algorithms Using Openacc Parallel Programming Model

KAUST Repository

Hamam, Alwaleed A.; Khan, Ayaz H.

2017-01-01

Deep learning is based on a set of algorithms that attempt to model high level abstractions in data. Specifically, RBM is a deep learning algorithm that used in the project to increase it's time performance using some efficient parallel implementation by OpenACC tool with best possible optimizations on RBM to harness the massively parallel power of NVIDIA GPUs. GPUs development in the last few years has contributed to growing the concept of deep learning. OpenACC is a directive based ap-proach for computing where directives provide compiler hints to accelerate code. The traditional Restricted Boltzmann Ma-chine is a stochastic neural network that essentially perform a binary version of factor analysis. RBM is a useful neural net-work basis for larger modern deep learning model, such as Deep Belief Network. RBM parameters are estimated using an efficient training method that called Contrastive Divergence. Parallel implementation of RBM is available using different models such as OpenMP, and CUDA. But this project has been the first attempt to apply OpenACC model on RBM.

Development of parallel benchmark code by sheet metal forming simulator 'ITAS'

International Nuclear Information System (INIS)

Watanabe, Hiroshi; Suzuki, Shintaro; Minami, Kazuo

1999-03-01

This report describes the development of parallel benchmark code by sheet metal forming simulator 'ITAS'. ITAS is a nonlinear elasto-plastic analysis program by the finite element method for the purpose of the simulation of sheet metal forming. ITAS adopts the dynamic analysis method that computes displacement of sheet metal at every time unit and utilizes the implicit method with the direct linear equation solver. Therefore the simulator is very robust. However, it requires a lot of computational time and memory capacity. In the development of the parallel benchmark code, we designed the code by MPI programming to reduce the computational time. In numerical experiments on the five kinds of parallel super computers at CCSE JAERI, i.e., SP2, SR2201, SX-4, T94 and VPP300, good performances are observed. The result will be shown to the public through WWW so that the benchmark results may become a guideline of research and development of the parallel program. (author)

On а Recursive-Parallel Algorithm for Solving the Knapsack Problem

Directory of Open Access Journals (Sweden)

Vladimir V. Vasilchikov

2018-01-01

Full Text Available In this paper, we offer an efficient parallel algorithm for solving the NP-complete Knapsack Problem in its basic, so-called 0-1 variant. To find its exact solution, algorithms belonging to the category ”branch and bound methods” have long been used. To speed up the solving with varying degrees of efficiency, various options for parallelizing computations are also used. We propose here an algorithm for solving the problem, based on the paradigm of recursive-parallel computations. We consider it suited well for problems of this kind, when it is difficult to immediately break up the computations into a sufficient number of subtasks that are comparable in complexity, since they appear dynamically at run time. We used the RPM ParLib library, developed by the author, as the main tool to program the algorithm. This library allows us to develop effective applications for parallel computing on a local network in the .NET Framework. Such applications have the ability to generate parallel branches of computation directly during program execution and dynamically redistribute work between computing modules. Any language with support for the .NET Framework can be used as a programming language in conjunction with this library. For our experiments, we developed some C# applications using this library. The main purpose of these experiments was to study the acceleration achieved by recursive-parallel computing. A detailed description of the algorithm and its testing, as well as the results obtained, are also given in the paper.

Parallel computation

International Nuclear Information System (INIS)

Jejcic, A.; Maillard, J.; Maurel, G.; Silva, J.; Wolff-Bacha, F.

1997-01-01

The work in the field of parallel processing has developed as research activities using several numerical Monte Carlo simulations related to basic or applied current problems of nuclear and particle physics. For the applications utilizing the GEANT code development or improvement works were done on parts simulating low energy physical phenomena like radiation, transport and interaction. The problem of actinide burning by means of accelerators was approached using a simulation with the GEANT code. A program of neutron tracking in the range of low energies up to the thermal region has been developed. It is coupled to the GEANT code and permits in a single pass the simulation of a hybrid reactor core receiving a proton burst. Other works in this field refers to simulations for nuclear medicine applications like, for instance, development of biological probes, evaluation and characterization of the gamma cameras (collimators, crystal thickness) as well as the method for dosimetric calculations. Particularly, these calculations are suited for a geometrical parallelization approach especially adapted to parallel machines of the TN310 type. Other works mentioned in the same field refer to simulation of the electron channelling in crystals and simulation of the beam-beam interaction effect in colliders. The GEANT code was also used to simulate the operation of germanium detectors designed for natural and artificial radioactivity monitoring of environment

Parallel evolutionary computation in bioinformatics applications.

Science.gov (United States)

Pinho, Jorge; Sobral, João Luis; Rocha, Miguel

2013-05-01

A large number of optimization problems within the field of Bioinformatics require methods able to handle its inherent complexity (e.g. NP-hard problems) and also demand increased computational efforts. In this context, the use of parallel architectures is a necessity. In this work, we propose ParJECoLi, a Java based library that offers a large set of metaheuristic methods (such as Evolutionary Algorithms) and also addresses the issue of its efficient execution on a wide range of parallel architectures. The proposed approach focuses on the easiness of use, making the adaptation to distinct parallel environments (multicore, cluster, grid) transparent to the user. Indeed, this work shows how the development of the optimization library can proceed independently of its adaptation for several architectures, making use of Aspect-Oriented Programming. The pluggable nature of parallelism related modules allows the user to easily configure its environment, adding parallelism modules to the base source code when needed. The performance of the platform is validated with two case studies within biological model optimization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Domain decomposition methods and parallel computing

International Nuclear Information System (INIS)

Meurant, G.

1991-01-01

In this paper, we show how to efficiently solve large linear systems on parallel computers. These linear systems arise from discretization of scientific computing problems described by systems of partial differential equations. We show how to get a discrete finite dimensional system from the continuous problem and the chosen conjugate gradient iterative algorithm is briefly described. Then, the different kinds of parallel architectures are reviewed and their advantages and deficiencies are emphasized. We sketch the problems found in programming the conjugate gradient method on parallel computers. For this algorithm to be efficient on parallel machines, domain decomposition techniques are introduced. We give results of numerical experiments showing that these techniques allow a good rate of convergence for the conjugate gradient algorithm as well as computational speeds in excess of a billion of floating point operations per second. (author). 5 refs., 11 figs., 2 tabs., 1 inset

Execution Model of Three Parallel Languages: OpenMP, UPC and CAF

Directory of Open Access Journals (Sweden)

Ami Marowka

2005-01-01

Full Text Available The aim of this paper is to present a qualitative evaluation of three state-of-the-art parallel languages: OpenMP, Unified Parallel C (UPC and Co-Array Fortran (CAF. OpenMP and UPC are explicit parallel programming languages based on the ANSI standard. CAF is an implicit programming language. On the one hand, OpenMP designs for shared-memory architectures and extends the base-language by using compiler directives that annotate the original source-code. On the other hand, UPC and CAF designs for distribute-shared memory architectures and extends the base-language by new parallel constructs. We deconstruct each language into its basic components, show examples, make a detailed analysis, compare them, and finally draw some conclusions.

A parallel implementation of a maximum entropy reconstruction algorithm for PET images in a visual language

International Nuclear Information System (INIS)

Bastiens, K.; Lemahieu, I.

1994-01-01

The application of a maximum entropy reconstruction algorithm to PET images requires a lot of computing resources. A parallel implementation could seriously reduce the execution time. However, programming a parallel application is still a non trivial task, needing specialized people. In this paper a programming environment based on a visual programming language is used for a parallel implementation of the reconstruction algorithm. This programming environment allows less experienced programmers to use the performance of multiprocessor systems. (authors)

Programs Lucky and LuckyC - 3D parallel transport codes for the multi-group transport equation solution for XYZ geometry by Pm Sn method

International Nuclear Information System (INIS)

Moriakov, A.; Vasyukhno, V.; Netecha, M.; Khacheresov, G.

2003-01-01

Powerful supercomputers are available today. MBC-1000M is one of Russian supercomputers that may be used by distant way access. Programs LUCKY and LUCKY C were created to work for multi-processors systems. These programs have algorithms created especially for these computers and used MPI (message passing interface) service for exchanges between processors. LUCKY may resolved shielding tasks by multigroup discreet ordinate method. LUCKY C may resolve critical tasks by same method. Only XYZ orthogonal geometry is available. Under little space steps to approximate discreet operator this geometry may be used as universal one to describe complex geometrical structures. Cross section libraries are used up to P8 approximation by Legendre polynomials for nuclear data in GIT format. Programming language is Fortran-90. 'Vector' processors may be used that lets get a time profit up to 30 times. But unfortunately MBC-1000M has not these processors. Nevertheless sufficient value for efficiency of parallel calculations was obtained under 'space' (LUCKY) and 'space and energy' (LUCKY C ) paralleling. AUTOCAD program is used to control geometry after a treatment of input data. Programs have powerful geometry module, it is a beautiful tool to achieve any geometry. Output results may be processed by graphic programs on personal computer. (authors)

Parallel processing of neutron transport in fuel assembly calculation

International Nuclear Information System (INIS)

Song, Jae Seung

1992-02-01

Group constants, which are used for reactor analyses by nodal method, are generated by fuel assembly calculations based on the neutron transport theory, since one or a quarter of the fuel assembly corresponds to a unit mesh in the current nodal calculation. The group constant calculation for a fuel assembly is performed through spectrum calculations, a two-dimensional fuel assembly calculation, and depletion calculations. The purpose of this study is to develop a parallel algorithm to be used in a parallel processor for the fuel assembly calculation and the depletion calculations of the group constant generation. A serial program, which solves the neutron integral transport equation using the transmission probability method and the linear depletion equation, was prepared and verified by a benchmark calculation. Small changes from the serial program was enough to parallelize the depletion calculation which has inherent parallel characteristics. In the fuel assembly calculation, however, efficient parallelization is not simple and easy because of the many coupling parameters in the calculation and data communications among CPU's. In this study, the group distribution method is introduced for the parallel processing of the fuel assembly calculation to minimize the data communications. The parallel processing was performed on Quadputer with 4 CPU's operating in NURAD Lab. at KAIST. Efficiencies of 54.3 % and 78.0 % were obtained in the fuel assembly calculation and depletion calculation, respectively, which lead to the overall speedup of about 2.5. As a result, it is concluded that the computing time consumed for the group constant generation can be easily reduced by parallel processing on the parallel computer with small size CPU's

A program system for ab initio MO calculations on vector and parallel processing machines. Pt. 1

International Nuclear Information System (INIS)

Ernenwein, R.; Rohmer, M.M.; Benard, M.

1990-01-01

We present a program system for ab initio molecular orbital calculations on vector and parallel computers. The present article is devoted to the computation of one- and two-electron integrals over contracted Gaussian basis sets involving s-, p-, d- and f-type functions. The McMurchie and Davidson (MMD) algorithm has been implemented and parallelized by distributing over a limited number of logical tasks the calculation of the 55 relevant classes of integrals. All sections of the MMD algorithm have been efficiently vectorized, leading to a scalar/vector ratio of 5.8. Different algorithms are proposed and compared for an optimal vectorization of the contraction of the 'intermediate integrals' generated by the MMD formalism. Advantage is taken of the dynamic storage allocation for tuning the length of the vector loops (i.e. the size of the vectorization buffer) as a function of (i) the total memory available for the job, (ii) the number of logical tasks defined by the user (≤13), and (iii) the storage requested by each specific class of integrals. Test calculations carried out on a CRAY-2 computer show that the average number of finite integrals computed over a (s, p, d, f) CGTO basis set is about 1180000 per second and per processor. The combination of vectorization and parallelism on this 4-processor machine reduces the CPU time by a factor larger than 20 with respect to the scalar and sequential performance. (orig.)

High-energy physics software parallelization using database techniques

International Nuclear Information System (INIS)

Argante, E.; Van der Stok, P.D.V.; Willers, I.

1997-01-01

A programming model for software parallelization, called CoCa, is introduced that copes with problems caused by typical features of high-energy physics software. By basing CoCa on the database transaction paradigm, the complexity induced by the parallelization is for a large part transparent to the programmer, resulting in a higher level of abstraction than the native message passing software. CoCa is implemented on a Meiko CS-2 and on a SUN SPARCcenter 2000 parallel computer. On the CS-2, the performance is comparable with the performance of native PVM and MPI. (orig.)

A parallel implementation of a maximum entropy reconstruction algorithm for PET images in a visual language

Energy Technology Data Exchange (ETDEWEB)

Bastiens, K; Lemahieu, I [University of Ghent - ELIS Department, St. Pietersnieuwstraat 41, B-9000 Ghent (Belgium)

1994-12-31

The application of a maximum entropy reconstruction algorithm to PET images requires a lot of computing resources. A parallel implementation could seriously reduce the execution time. However, programming a parallel application is still a non trivial task, needing specialized people. In this paper a programming environment based on a visual programming language is used for a parallel implementation of the reconstruction algorithm. This programming environment allows less experienced programmers to use the performance of multiprocessor systems. (authors). 8 refs, 3 figs, 1 tab.

Test generation for digital circuits using parallel processing

Science.gov (United States)

Hartmann, Carlos R.; Ali, Akhtar-Uz-Zaman M.

1990-12-01

The problem of test generation for digital logic circuits is an NP-Hard problem. Recently, the availability of low cost, high performance parallel machines has spurred interest in developing fast parallel algorithms for computer-aided design and test. This report describes a method of applying a 15-valued logic system for digital logic circuit test vector generation in a parallel programming environment. A concept called fault site testing allows for test generation, in parallel, that targets more than one fault at a given location. The multi-valued logic system allows results obtained by distinct processors and/or processes to be merged by means of simple set intersections. A machine-independent description is given for the proposed algorithm.

An educational tool for interactive parallel and distributed processing

DEFF Research Database (Denmark)

Pagliarini, Luigi; Lund, Henrik Hautop

2012-01-01

In this article we try to describe how the modular interactive tiles system (MITS) can be a valuable tool for introducing students to interactive parallel and distributed processing programming. This is done by providing a handson educational tool that allows a change in the representation...... of abstract problems related to designing interactive parallel and distributed systems. Indeed, the MITS seems to bring a series of goals into education, such as parallel programming, distributedness, communication protocols, master dependency, software behavioral models, adaptive interactivity, feedback......, connectivity, topology, island modeling, and user and multi-user interaction which can rarely be found in other tools. Finally, we introduce the system of modular interactive tiles as a tool for easy, fast, and flexible hands-on exploration of these issues, and through examples we show how to implement...

High performance parallel computers for science

International Nuclear Information System (INIS)

Nash, T.; Areti, H.; Atac, R.; Biel, J.; Cook, A.; Deppe, J.; Edel, M.; Fischler, M.; Gaines, I.; Hance, R.

1989-01-01

This paper reports that Fermilab's Advanced Computer Program (ACP) has been developing cost effective, yet practical, parallel computers for high energy physics since 1984. The ACP's latest developments are proceeding in two directions. A Second Generation ACP Multiprocessor System for experiments will include $3500 RISC processors each with performance over 15 VAX MIPS. To support such high performance, the new system allows parallel I/O, parallel interprocess communication, and parallel host processes. The ACP Multi-Array Processor, has been developed for theoretical physics. Each $4000 node is a FORTRAN or C programmable pipelined 20 Mflops (peak), 10 MByte single board computer. These are plugged into a 16 port crossbar switch crate which handles both inter and intra crate communication. The crates are connected in a hypercube. Site oriented applications like lattice gauge theory are supported by system software called CANOPY, which makes the hardware virtually transparent to users. A 256 node, 5 GFlop, system is under construction

On the effective parallel programming of multi-core processors

NARCIS (Netherlands)

Varbanescu, A.L.

2010-01-01

Multi-core processors are considered now the only feasible alternative to the large single-core processors which have become limited by technological aspects such as power consumption and heat dissipation. However, due to their inherent parallel structure and their diversity, multi-cores are

Parallel processing of Monte Carlo code MCNP for particle transport problem

Energy Technology Data Exchange (ETDEWEB)

Higuchi, Kenji; Kawasaki, Takuji

1996-06-01

It is possible to vectorize or parallelize Monte Carlo codes (MC code) for photon and neutron transport problem, making use of independency of the calculation for each particle. Applicability of existing MC code to parallel processing is mentioned. As for parallel computer, we have used both vector-parallel processor and scalar-parallel processor in performance evaluation. We have made (i) vector-parallel processing of MCNP code on Monte Carlo machine Monte-4 with four vector processors, (ii) parallel processing on Paragon XP/S with 256 processors. In this report we describe the methodology and results for parallel processing on two types of parallel or distributed memory computers. In addition, we mention the evaluation of parallel programming environments for parallel computers used in the present work as a part of the work developing STA (Seamless Thinking Aid) Basic Software. (author)

User-friendly parallelization of GAUDI applications with Python

International Nuclear Information System (INIS)

Mato, Pere; Smith, Eoin

2010-01-01

GAUDI is a software framework in C++ used to build event data processing applications using a set of standard components with well-defined interfaces. Simulation, high-level trigger, reconstruction, and analysis programs used by several experiments are developed using GAUDI. These applications can be configured and driven by simple Python scripts. Given the fact that a considerable amount of existing software has been developed using serial methodology, and has existed in some cases for many years, implementation of parallelisation techniques at the framework level may offer a way of exploiting current multi-core technologies to maximize performance and reduce latencies without re-writing thousands/millions of lines of code. In the solution we have developed, the parallelization techniques are introduced to the high level Python scripts which configure and drive the applications, such that the core C++ application code requires no modification, and that end users need make only minimal changes to their scripts. The developed solution leverages from existing generic Python modules that support parallel processing. Naturally, the parallel version of a given program should produce results consistent with its serial execution. The evaluation of several prototypes incorporating various parallelization techniques are presented and discussed.

User-friendly parallelization of GAUDI applications with Python

Energy Technology Data Exchange (ETDEWEB)

Mato, Pere; Smith, Eoin, E-mail: pere.mato@cern.c [PH Department, CERN, 1211 Geneva 23 (Switzerland)

2010-04-01

GAUDI is a software framework in C++ used to build event data processing applications using a set of standard components with well-defined interfaces. Simulation, high-level trigger, reconstruction, and analysis programs used by several experiments are developed using GAUDI. These applications can be configured and driven by simple Python scripts. Given the fact that a considerable amount of existing software has been developed using serial methodology, and has existed in some cases for many years, implementation of parallelisation techniques at the framework level may offer a way of exploiting current multi-core technologies to maximize performance and reduce latencies without re-writing thousands/millions of lines of code. In the solution we have developed, the parallelization techniques are introduced to the high level Python scripts which configure and drive the applications, such that the core C++ application code requires no modification, and that end users need make only minimal changes to their scripts. The developed solution leverages from existing generic Python modules that support parallel processing. Naturally, the parallel version of a given program should produce results consistent with its serial execution. The evaluation of several prototypes incorporating various parallelization techniques are presented and discussed.

The 2nd Symposium on the Frontiers of Massively Parallel Computations

Science.gov (United States)

Mills, Ronnie (Editor)

1988-01-01

Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.

A Novel Parallel Algorithm for Edit Distance Computation

Directory of Open Access Journals (Sweden)

Muhammad Murtaza Yousaf

2018-01-01

Full Text Available The edit distance between two sequences is the minimum number of weighted transformation-operations that are required to transform one string into the other. The weighted transformation-operations are insert, remove, and substitute. Dynamic programming solution to find edit distance exists but it becomes computationally intensive when the lengths of strings become very large. This work presents a novel parallel algorithm to solve edit distance problem of string matching. The algorithm is based on resolving dependencies in the dynamic programming solution of the problem and it is able to compute each row of edit distance table in parallel. In this way, it becomes possible to compute the complete table in min(m,n iterations for strings of size m and n whereas state-of-the-art parallel algorithm solves the problem in max(m,n iterations. The proposed algorithm also increases the amount of parallelism in each of its iteration. The algorithm is also capable of exploiting spatial locality while its implementation. Additionally, the algorithm works in a load balanced way that further improves its performance. The algorithm is implemented for multicore systems having shared memory. Implementation of the algorithm in OpenMP shows linear speedup and better execution time as compared to state-of-the-art parallel approach. Efficiency of the algorithm is also proven better in comparison to its competitor.

Automatic parallelization of while-Loops using speculative execution

International Nuclear Information System (INIS)

Collard, J.F.

1995-01-01

Automatic parallelization of imperative sequential programs has focused on nests of for-loops. The most recent of them consist in finding an affine mapping with respect to the loop indices to simultaneously capture the temporal and spatial properties of the parallelized program. Such a mapping is usually called a open-quotes space-time transformation.close quotes This work describes an extension of these techniques to while-loops using speculative execution. We show that space-time transformations are a good framework for summing up previous restructuration techniques of while-loop, such as pipelining. Moreover, we show that these transformations can be derived and applied automatically

Logical inference techniques for loop parallelization

DEFF Research Database (Denmark)

Oancea, Cosmin Eugen; Rauchwerger, Lawrence

2012-01-01

the parallelization transformation by verifying the independence of the loop's memory references. To this end it represents array references using the USR (uniform set representation) language and expresses the independence condition as an equation, S={}, where S is a set expression representing array indexes. Using...... of their estimated complexities. We evaluate our automated solution on 26 benchmarks from PERFECT-CLUB and SPEC suites and show that our approach is effective in parallelizing large, complex loops and obtains much better full program speedups than the Intel and IBM Fortran compilers....

Simplifying the parallelization of scientific codes by a function-centric approach in Python

International Nuclear Information System (INIS)

Nilsen, Jon K; Cai Xing; Langtangen, Hans Petter; Hoeyland, Bjoern

2010-01-01

The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallelization-specific tasks are implemented. We provide specific examples of such a Python code layer, which can act as templates for parallelizing a wide set of serial scientific codes. The use of Python for parallelization is motivated by the fact that the language is well suited for reusing existing serial codes programmed in other languages. The extreme flexibility of Python with regard to handling functions makes it very easy to wrap up decomposed computational tasks of a serial scientific application as Python functions. Many parallelization-specific components can be implemented as generic Python functions, which may take as input those wrapped functions that perform concrete computational tasks. The overall programming effort needed by this parallelization approach is limited, and the resulting parallel Python scripts have a compact and clean structure. The usefulness of the parallelization approach is exemplified by three different classes of application in natural and social sciences.

Development of parallel 3D discrete ordinates transport program on JASMIN framework

International Nuclear Information System (INIS)

Cheng, T.; Wei, J.; Shen, H.; Zhong, B.; Deng, L.

2015-01-01

A parallel 3D discrete ordinates radiation transport code JSNT-S is developed, aiming at simulating real-world radiation shielding and reactor physics applications in a reasonable time. Through the patch-based domain partition algorithm, the memory requirement is shared among processors and a space-angle parallel sweeping algorithm is developed based on data-driven algorithm. Acceleration methods such as partial current rebalance are implemented. The correctness is proved through the VENUS-3 and other benchmark models. In the radiation shielding calculation of the Qinshan-II reactor pressure vessel model with 24.3 billion DoF, only 88 seconds is required and the overall parallel efficiency of 44% is achieved on 1536 CPU cores. (author)

Leveraging Parallel Data Processing Frameworks with Verified Lifting

Directory of Open Access Journals (Sweden)

Maaz Bin Safeer Ahmad

2016-11-01

Full Text Available Many parallel data frameworks have been proposed in recent years that let sequential programs access parallel processing. To capitalize on the benefits of such frameworks, existing code must often be rewritten to the domain-specific languages that each framework supports. This rewriting–tedious and error-prone–also requires developers to choose the framework that best optimizes performance given a specific workload. This paper describes Casper, a novel compiler that automatically retargets sequential Java code for execution on Hadoop, a parallel data processing framework that implements the MapReduce paradigm. Given a sequential code fragment, Casper uses verified lifting to infer a high-level summary expressed in our program specification language that is then compiled for execution on Hadoop. We demonstrate that Casper automatically translates Java benchmarks into Hadoop. The translated results execute on average 3.3x faster than the sequential implementations and scale better, as well, to larger datasets.

Bayer image parallel decoding based on GPU

Science.gov (United States)

Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua

2012-11-01

In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.

A method of paralleling computer calculation for two-dimensional kinetic plasma model

International Nuclear Information System (INIS)

Brazhnik, V.A.; Demchenko, V.V.; Dem'yanov, V.G.; D'yakov, V.E.; Ol'shanskij, V.V.; Panchenko, V.I.

1987-01-01

A method for parallel computer calculation and OSIRIS program complex realizing it and designed for numerical plasma simulation by the macroparticle method are described. The calculation can be carried out either with one or simultaneously with two computers BESM-6, that is provided by some package of interacting programs functioning in every computer. Program interaction in every computer is based on event techniques realized in OS DISPAK. Parallel computer calculation with two BESM-6 computers allows to accelerate the computation 1.5 times

Vectorization, parallelization and porting of nuclear codes on the VPP500 system (parallelization). Progress report fiscal 1996

Energy Technology Data Exchange (ETDEWEB)

Watanabe, Hideo; Kawai, Wataru; Nemoto, Toshiyuki [Fujitsu Ltd., Tokyo (Japan); and others

1997-12-01

Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. These results are reported in 3 parts, i.e., the vectorization part, the parallelization part and the porting part. In this report, we describe the parallelization. In this parallelization part, the parallelization of 2-Dimensional relativistic electromagnetic particle code EM2D, Cylindrical Direct Numerical Simulation code CYLDNS and molecular dynamics code for simulating radiation damages in diamond crystals DGR are described. In the vectorization part, the vectorization of two and three dimensional discrete ordinates simulation code DORT-TORT, gas dynamics analysis code FLOWGR and relativistic Boltzmann-Uehling-Uhlenbeck simulation code RBUU are described. And then, in the porting part, the porting of reactor safety analysis code RELAP5/MOD3.2 and RELAP5/MOD3.2.1.2, nuclear data processing system NJOY and 2-D multigroup discrete ordinate transport code TWOTRAN-II are described. And also, a survey for the porting of command-driven interactive data analysis plotting program IPLOT are described. (author)

Parallel computational in nuclear group constant calculation

International Nuclear Information System (INIS)

Su'ud, Zaki; Rustandi, Yaddi K.; Kurniadi, Rizal

2002-01-01

In this paper parallel computational method in nuclear group constant calculation using collision probability method will be discuss. The main focus is on the calculation of collision matrix which need large amount of computational time. The geometry treated here is concentric cylinder. The calculation of collision probability matrix is carried out using semi analytic method using Beckley Naylor Function. To accelerate computation speed some computer parallel used to solve the problem. We used LINUX based parallelization using PVM software with C or fortran language. While in windows based we used socket programming using DELPHI or C builder. The calculation results shows the important of optimal weight for each processor in case there area many type of processor speed

GRADSPMHD: A parallel MHD code based on the SPH formalism

Science.gov (United States)

Vanaverbeke, S.; Keppens, R.; Poedts, S.

2014-03-01

We present GRADSPMHD, a completely Lagrangian parallel magnetohydrodynamics code based on the SPH formalism. The implementation of the equations of SPMHD in the “GRAD-h” formalism assembles known results, including the derivation of the discretized MHD equations from a variational principle, the inclusion of time-dependent artificial viscosity, resistivity and conductivity terms, as well as the inclusion of a mixed hyperbolic/parabolic correction scheme for satisfying the ∇ṡB→ constraint on the magnetic field. The code uses a tree-based formalism for neighbor finding and can optionally use the tree code for computing the self-gravity of the plasma. The structure of the code closely follows the framework of our parallel GRADSPH FORTRAN 90 code which we added previously to the CPC program library. We demonstrate the capabilities of GRADSPMHD by running 1, 2, and 3 dimensional standard benchmark tests and we find good agreement with previous work done by other researchers. The code is also applied to the problem of simulating the magnetorotational instability in 2.5D shearing box tests as well as in global simulations of magnetized accretion disks. We find good agreement with available results on this subject in the literature. Finally, we discuss the performance of the code on a parallel supercomputer with distributed memory architecture. Catalogue identifier: AERP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERP_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 620503 No. of bytes in distributed program, including test data, etc.: 19837671 Distribution format: tar.gz Programming language: FORTRAN 90/MPI. Computer: HPC cluster. Operating system: Unix. Has the code been vectorized or parallelized?: Yes, parallelized using MPI. RAM: ˜30 MB for a

Parallel Ada benchmarks for the SVMS

Science.gov (United States)

Collard, Philippe E.

1990-01-01

The use of parallel processing paradigm to design and develop faster and more reliable computers appear to clearly mark the future of information processing. NASA started the development of such an architecture: the Spaceborne VHSIC Multi-processor System (SVMS). Ada will be one of the languages used to program the SVMS. One of the unique characteristics of Ada is that it supports parallel processing at the language level through the tasking constructs. It is important for the SVMS project team to assess how efficiently the SVMS architecture will be implemented, as well as how efficiently Ada environment will be ported to the SVMS. AUTOCLASS II, a Bayesian classifier written in Common Lisp, was selected as one of the benchmarks for SVMS configurations. The purpose of the R and D effort was to provide the SVMS project team with the version of AUTOCLASS II, written in Ada, that would make use of Ada tasking constructs as much as possible so as to constitute a suitable benchmark. Additionally, a set of programs was developed that would measure Ada tasking efficiency on parallel architectures as well as determine the critical parameters influencing tasking efficiency. All this was designed to provide the SVMS project team with a set of suitable tools in the development of the SVMS architecture.

From functional programming to multicore parallelism: A case study based on Presburger Arithmetic

DEFF Research Database (Denmark)

Dung, Phan Anh; Hansen, Michael Reichhardt

2011-01-01

, we are interested in using PA in connection with the Duration Calculus Model Checker (DCMC) [5]. There are effective decision procedures for PA including Cooper’s algorithm and the Omega Test; however, their complexity is extremely high with doubly exponential lower bound and triply exponential upper...... bound [7]. We investigate these decision procedures in the context of multicore parallelism with the hope of exploiting multicore powers. Unfortunately, we are not aware of any prior parallelism research related to decision procedures for PA. The closest work is the preliminary results on parallelism...

Introduction to massively-parallel computing in high-energy physics

CERN Document Server

AUTHOR|(CDS)2083520

1993-01-01

Ever since computers were first used for scientific and numerical work, there has existed an "arms race" between the technical development of faster computing hardware, and the desires of scientists to solve larger problems in shorter time-scales. However, the vast leaps in processor performance achieved through advances in semi-conductor science have reached a hiatus as the technology comes up against the physical limits of the speed of light and quantum effects. This has lead all high performance computer manufacturers to turn towards a parallel architecture for their new machines. In these lectures we will introduce the history and concepts behind parallel computing, and review the various parallel architectures and software environments currently available. We will then introduce programming methodologies that allow efficient exploitation of parallel machines, and present case studies of the parallelization of typical High Energy Physics codes for the two main classes of parallel computing architecture (S...

A layered semantics for a parallel object-oriented language

NARCIS (Netherlands)

P.H.M. America (Pierre); J.J.M.M. Rutten (Jan)

1990-01-01

textabstractWe develop a denotational semantics for POOL, a parallel object-oriented programming language. The main contribution of this semantics is an accurate mathematical model of the most important concept in object-oriented programming: the object. This is achieved by structuring the semantics

PAREMD: A parallel program for the evaluation of momentum space properties of atoms and molecules

Science.gov (United States)

Meena, Deep Raj; Gadre, Shridhar R.; Balanarayan, P.

2018-03-01

The present work describes a code for evaluating the electron momentum density (EMD), its moments and the associated Shannon information entropy for a multi-electron molecular system. The code works specifically for electronic wave functions obtained from traditional electronic structure packages such as GAMESS and GAUSSIAN. For the momentum space orbitals, the general expression for Gaussian basis sets in position space is analytically Fourier transformed to momentum space Gaussian basis functions. The molecular orbital coefficients of the wave function are taken as an input from the output file of the electronic structure calculation. The analytic expressions of EMD are evaluated over a fine grid and the accuracy of the code is verified by a normalization check and a numerical kinetic energy evaluation which is compared with the analytic kinetic energy given by the electronic structure package. Apart from electron momentum density, electron density in position space has also been integrated into this package. The program is written in C++ and is executed through a Shell script. It is also tuned for multicore machines with shared memory through OpenMP. The program has been tested for a variety of molecules and correlated methods such as CISD, Møller-Plesset second order (MP2) theory and density functional methods. For correlated methods, the PAREMD program uses natural spin orbitals as an input. The program has been benchmarked for a variety of Gaussian basis sets for different molecules showing a linear speedup on a parallel architecture.

Parallelization of a numerical simulation code for isotropic turbulence

International Nuclear Information System (INIS)

Sato, Shigeru; Yokokawa, Mitsuo; Watanabe, Tadashi; Kaburaki, Hideo.

1996-03-01

A parallel pseudospectral code which solves the three-dimensional Navier-Stokes equation by direct numerical simulation is developed and execution time, parallelization efficiency, load balance and scalability are evaluated. A vector parallel supercomputer, Fujitsu VPP500 with up to 16 processors is used for this calculation for Fourier modes up to 256x256x256 using 16 processors. Good scalability for number of processors is achieved when number of Fourier mode is fixed. For small Fourier modes, calculation time of the program is proportional to NlogN which is ideal complexity of calculation for 3D-FFT on vector parallel processors. It is found that the calculation performance decreases as the increase of the Fourier modes. (author)

Visual analysis of inter-process communication for large-scale parallel computing.

Science.gov (United States)

Muelder, Chris; Gygi, Francois; Ma, Kwan-Liu

2009-01-01

In serial computation, program profiling is often helpful for optimization of key sections of code. When moving to parallel computation, not only does the code execution need to be considered but also communication between the different processes which can induce delays that are detrimental to performance. As the number of processes increases, so does the impact of the communication delays on performance. For large-scale parallel applications, it is critical to understand how the communication impacts performance in order to make the code more efficient. There are several tools available for visualizing program execution and communications on parallel systems. These tools generally provide either views which statistically summarize the entire program execution or process-centric views. However, process-centric visualizations do not scale well as the number of processes gets very large. In particular, the most common representation of parallel processes is a Gantt char t with a row for each process. As the number of processes increases, these charts can become difficult to work with and can even exceed screen resolution. We propose a new visualization approach that affords more scalability and then demonstrate it on systems running with up to 16,384 processes.

A scalable implementation of RI-SCF on parallel computers

International Nuclear Information System (INIS)

Fruechtl, H.A.; Kendall, R.A.; Harrison, R.J.

1996-01-01

In order to avoid the integral bottleneck of conventional SCF calculations, the Resolution of the Identity (RI) method is used to obtain an approximate solution to the Hartree-Fock equations. In this approximation only three-center integrals are needed to build the Fock matrix. It has been implemented as part of the NWChem package of portable and scalable ab initio programs for parallel computers. Utilizing the V-approximation, both the Coulomb and exchange contribution to the Fock matrix can be calculated from a transformed set of three-center integrals which have to be precalculated and stored. A distributed in-core method as well as a disk based implementation have been programmed. Details of the implementation as well as the parallel programming tools used are described. We also give results and timings from benchmark calculations

Parallel Nonlinear Optimization for Astrodynamic Navigation, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — CU Aerospace proposes the development of a new parallel nonlinear program (NLP) solver software package. NLPs allow the solution of complex optimization problems,...

The new landscape of parallel computer architecture

International Nuclear Information System (INIS)

Shalf, John

2007-01-01

The past few years has seen a sea change in computer architecture that will impact every facet of our society as every electronic device from cell phone to supercomputer will need to confront parallelism of unprecedented scale. Whereas the conventional multicore approach (2, 4, and even 8 cores) adopted by the computing industry will eventually hit a performance plateau, the highest performance per watt and per chip area is achieved using manycore technology (hundreds or even thousands of cores). However, fully unleashing the potential of the manycore approach to ensure future advances in sustained computational performance will require fundamental advances in computer architecture and programming models that are nothing short of reinventing computing. In this paper we examine the reasons behind the movement to exponentially increasing parallelism, and its ramifications for system design, applications and programming models

The new landscape of parallel computer architecture

Energy Technology Data Exchange (ETDEWEB)

Shalf, John [NERSC Division, Lawrence Berkeley National Laboratory 1 Cyclotron Road, Berkeley California, 94720 (United States)

2007-07-15

The past few years has seen a sea change in computer architecture that will impact every facet of our society as every electronic device from cell phone to supercomputer will need to confront parallelism of unprecedented scale. Whereas the conventional multicore approach (2, 4, and even 8 cores) adopted by the computing industry will eventually hit a performance plateau, the highest performance per watt and per chip area is achieved using manycore technology (hundreds or even thousands of cores). However, fully unleashing the potential of the manycore approach to ensure future advances in sustained computational performance will require fundamental advances in computer architecture and programming models that are nothing short of reinventing computing. In this paper we examine the reasons behind the movement to exponentially increasing parallelism, and its ramifications for system design, applications and programming models.

GASPRNG: GPU accelerated scalable parallel random number generator library

Science.gov (United States)

Gao, Shuang; Peterson, Gregory D.

2013-04-01

Graphics processors represent a promising technology for accelerating computational science applications. Many computational science applications require fast and scalable random number generation with good statistical properties, so they use the Scalable Parallel Random Number Generators library (SPRNG). We present the GPU Accelerated SPRNG library (GASPRNG) to accelerate SPRNG in GPU-based high performance computing systems. GASPRNG includes code for a host CPU and CUDA code for execution on NVIDIA graphics processing units (GPUs) along with a programming interface to support various usage models for pseudorandom numbers and computational science applications executing on the CPU, GPU, or both. This paper describes the implementation approach used to produce high performance and also describes how to use the programming interface. The programming interface allows a user to be able to use GASPRNG the same way as SPRNG on traditional serial or parallel computers as well as to develop tightly coupled programs executing primarily on the GPU. We also describe how to install GASPRNG and use it. To help illustrate linking with GASPRNG, various demonstration codes are included for the different usage models. GASPRNG on a single GPU shows up to 280x speedup over SPRNG on a single CPU core and is able to scale for larger systems in the same manner as SPRNG. Because GASPRNG generates identical streams of pseudorandom numbers as SPRNG, users can be confident about the quality of GASPRNG for scalable computational science applications. Catalogue identifier: AEOI_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOI_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: UTK license. No. of lines in distributed program, including test data, etc.: 167900 No. of bytes in distributed program, including test data, etc.: 1422058 Distribution format: tar.gz Programming language: C and CUDA. Computer: Any PC or

An Automatic Instruction-Level Parallelization of Machine Code

Directory of Open Access Journals (Sweden)

MARINKOVIC, V.

2018-02-01

Full Text Available Prevailing multicores and novel manycores have made a great challenge of modern day - parallelization of embedded software that is still written as sequential. In this paper, automatic code parallelization is considered, focusing on developing a parallelization tool at the binary level as well as on the validation of this approach. The novel instruction-level parallelization algorithm for assembly code which uses the register names after SSA to find independent blocks of code and then to schedule independent blocks using METIS to achieve good load balance is developed. The sequential consistency is verified and the validation is done by measuring the program execution time on the target architecture. Great speedup, taken as the performance measure in the validation process, and optimal load balancing are achieved for multicore RISC processors with 2 to 16 cores (e.g. MIPS, MicroBlaze, etc.. In particular, for 16 cores, the average speedup is 7.92x, while in some cases it reaches 14x. An approach to automatic parallelization provided by this paper is useful to researchers and developers in the area of parallelization as the basis for further optimizations, as the back-end of a compiler, or as the code parallelization tool for an embedded system.

Parallel R-matrix computation

International Nuclear Information System (INIS)

Heggarty, J.W.

1999-06-01

For almost thirty years, sequential R-matrix computation has been used by atomic physics research groups, from around the world, to model collision phenomena involving the scattering of electrons or positrons with atomic or molecular targets. As considerable progress has been made in the understanding of fundamental scattering processes, new data, obtained from more complex calculations, is of current interest to experimentalists. Performing such calculations, however, places considerable demands on the computational resources to be provided by the target machine, in terms of both processor speed and memory requirement. Indeed, in some instances the computational requirements are so great that the proposed R-matrix calculations are intractable, even when utilising contemporary classic supercomputers. Historically, increases in the computational requirements of R-matrix computation were accommodated by porting the problem codes to a more powerful classic supercomputer. Although this approach has been successful in the past, it is no longer considered to be a satisfactory solution due to the limitations of current (and future) Von Neumann machines. As a consequence, there has been considerable interest in the high performance multicomputers, that have emerged over the last decade which appear to offer the computational resources required by contemporary R-matrix research. Unfortunately, developing codes for these machines is not as simple a task as it was to develop codes for successive classic supercomputers. The difficulty arises from the considerable differences in the computing models that exist between the two types of machine and results in the programming of multicomputers to be widely acknowledged as a difficult, time consuming and error-prone task. Nevertheless, unless parallel R-matrix computation is realised, important theoretical and experimental atomic physics research will continue to be hindered. This thesis describes work that was undertaken in

A massively-parallel electronic-structure calculations based on real-space density functional theory

International Nuclear Information System (INIS)

Iwata, Jun-Ichi; Takahashi, Daisuke; Oshiyama, Atsushi; Boku, Taisuke; Shiraishi, Kenji; Okada, Susumu; Yabana, Kazuhiro

2010-01-01

Based on the real-space finite-difference method, we have developed a first-principles density functional program that efficiently performs large-scale calculations on massively-parallel computers. In addition to efficient parallel implementation, we also implemented several computational improvements, substantially reducing the computational costs of O(N 3 ) operations such as the Gram-Schmidt procedure and subspace diagonalization. Using the program on a massively-parallel computer cluster with a theoretical peak performance of several TFLOPS, we perform electronic-structure calculations for a system consisting of over 10,000 Si atoms, and obtain a self-consistent electronic-structure in a few hundred hours. We analyze in detail the costs of the program in terms of computation and of inter-node communications to clarify the efficiency, the applicability, and the possibility for further improvements.

Mathematical Methods and Algorithms of Mobile Parallel Computing on the Base of Multi-core Processors

Directory of Open Access Journals (Sweden)

Alexander B. Bakulev

2012-11-01

Full Text Available This article deals with mathematical models and algorithms, providing mobility of sequential programs parallel representation on the high-level language, presents formal model of operation environment processes management, based on the proposed model of programs parallel representation, presenting computation process on the base of multi-core processors.

An object-oriented bulk synchronous parallel library for multicore programming

NARCIS (Netherlands)

Yzelman, A.N.; Bisseling, R.H.

2012-01-01

We show that the bulk synchronous parallel (BSP) model, originally designed for distributed-memory systems, is also applicable for shared-memory multicore systems and, furthermore, that BSP libraries are useful in scientific computing on these systems. A proof-of-concept MulticoreBSP library has

Neurite, a finite difference large scale parallel program for the simulation of electrical signal propagation in neurites under mechanical loading.

Directory of Open Access Journals (Sweden)

Julián A García-Grajales

Full Text Available With the growing body of research on traumatic brain injury and spinal cord injury, computational neuroscience has recently focused its modeling efforts on neuronal functional deficits following mechanical loading. However, in most of these efforts, cell damage is generally only characterized by purely mechanistic criteria, functions of quantities such as stress, strain or their corresponding rates. The modeling of functional deficits in neurites as a consequence of macroscopic mechanical insults has been rarely explored. In particular, a quantitative mechanically based model of electrophysiological impairment in neuronal cells, Neurite, has only very recently been proposed. In this paper, we present the implementation details of this model: a finite difference parallel program for simulating electrical signal propagation along neurites under mechanical loading. Following the application of a macroscopic strain at a given strain rate produced by a mechanical insult, Neurite is able to simulate the resulting neuronal electrical signal propagation, and thus the corresponding functional deficits. The simulation of the coupled mechanical and electrophysiological behaviors requires computational expensive calculations that increase in complexity as the network of the simulated cells grows. The solvers implemented in Neurite--explicit and implicit--were therefore parallelized using graphics processing units in order to reduce the burden of the simulation costs of large scale scenarios. Cable Theory and Hodgkin-Huxley models were implemented to account for the electrophysiological passive and active regions of a neurite, respectively, whereas a coupled mechanical model accounting for the neurite mechanical behavior within its surrounding medium was adopted as a link between electrophysiology and mechanics. This paper provides the details of the parallel implementation of Neurite, along with three different application examples: a long myelinated axon

Diderot: a Domain-Specific Language for Portable Parallel Scientific Visualization and Image Analysis.

Science.gov (United States)

Kindlmann, Gordon; Chiw, Charisee; Seltzer, Nicholas; Samuels, Lamont; Reppy, John

2016-01-01

Many algorithms for scientific visualization and image analysis are rooted in the world of continuous scalar, vector, and tensor fields, but are programmed in low-level languages and libraries that obscure their mathematical foundations. Diderot is a parallel domain-specific language that is designed to bridge this semantic gap by providing the programmer with a high-level, mathematical programming notation that allows direct expression of mathematical concepts in code. Furthermore, Diderot provides parallel performance that takes advantage of modern multicore processors and GPUs. The high-level notation allows a concise and natural expression of the algorithms and the parallelism allows efficient execution on real-world datasets.

Parallelization and automatic data distribution for nuclear reactor simulations

Energy Technology Data Exchange (ETDEWEB)

Liebrock, L.M. [Liebrock-Hicks Research, Calumet, MI (United States)

1997-07-01

Detailed attempts at realistic nuclear reactor simulations currently take many times real time to execute on high performance workstations. Even the fastest sequential machine can not run these simulations fast enough to ensure that the best corrective measure is used during a nuclear accident to prevent a minor malfunction from becoming a major catastrophe. Since sequential computers have nearly reached the speed of light barrier, these simulations will have to be run in parallel to make significant improvements in speed. In physical reactor plants, parallelism abounds. Fluids flow, controls change, and reactions occur in parallel with only adjacent components directly affecting each other. These do not occur in the sequentialized manner, with global instantaneous effects, that is often used in simulators. Development of parallel algorithms that more closely approximate the real-world operation of a reactor may, in addition to speeding up the simulations, actually improve the accuracy and reliability of the predictions generated. Three types of parallel architecture (shared memory machines, distributed memory multicomputers, and distributed networks) are briefly reviewed as targets for parallelization of nuclear reactor simulation. Various parallelization models (loop-based model, shared memory model, functional model, data parallel model, and a combined functional and data parallel model) are discussed along with their advantages and disadvantages for nuclear reactor simulation. A variety of tools are introduced for each of the models. Emphasis is placed on the data parallel model as the primary focus for two-phase flow simulation. Tools to support data parallel programming for multiple component applications and special parallelization considerations are also discussed.

Parallelization and automatic data distribution for nuclear reactor simulations

International Nuclear Information System (INIS)

Liebrock, L.M.

1997-01-01

Detailed attempts at realistic nuclear reactor simulations currently take many times real time to execute on high performance workstations. Even the fastest sequential machine can not run these simulations fast enough to ensure that the best corrective measure is used during a nuclear accident to prevent a minor malfunction from becoming a major catastrophe. Since sequential computers have nearly reached the speed of light barrier, these simulations will have to be run in parallel to make significant improvements in speed. In physical reactor plants, parallelism abounds. Fluids flow, controls change, and reactions occur in parallel with only adjacent components directly affecting each other. These do not occur in the sequentialized manner, with global instantaneous effects, that is often used in simulators. Development of parallel algorithms that more closely approximate the real-world operation of a reactor may, in addition to speeding up the simulations, actually improve the accuracy and reliability of the predictions generated. Three types of parallel architecture (shared memory machines, distributed memory multicomputers, and distributed networks) are briefly reviewed as targets for parallelization of nuclear reactor simulation. Various parallelization models (loop-based model, shared memory model, functional model, data parallel model, and a combined functional and data parallel model) are discussed along with their advantages and disadvantages for nuclear reactor simulation. A variety of tools are introduced for each of the models. Emphasis is placed on the data parallel model as the primary focus for two-phase flow simulation. Tools to support data parallel programming for multiple component applications and special parallelization considerations are also discussed

A Topological Model for Parallel Algorithm Design

Science.gov (United States)

1991-09-01

effort should be directed to planning, requirements analysis, specification and design, with 20% invested into the actual coding, and then the final 40...be olle more language to learn. And by investing the effort into improving the utility of ai, existing language instead of creating a new one, this...193) it abandons the notion of a process as a fundemental concept of parallel program design and that it facilitates program derivation by rigorously

Application of Pfortran and Co-Array Fortran in the Parallelization of the GROMOS96 Molecular Dynamics Module

Directory of Open Access Journals (Sweden)

Piotr Bała

2001-01-01

Full Text Available After at least a decade of parallel tool development, parallelization of scientific applications remains a significant undertaking. Typically parallelization is a specialized activity supported only partially by the programming tool set, with the programmer involved with parallel issues in addition to sequential ones. The details of concern range from algorithm design down to low-level data movement details. The aim of parallel programming tools is to automate the latter without sacrificing performance and portability, allowing the programmer to focus on algorithm specification and development. We present our use of two similar parallelization tools, Pfortran and Cray's Co-Array Fortran, in the parallelization of the GROMOS96 molecular dynamics module. Our parallelization started from the GROMOS96 distribution's shared-memory implementation of the replicated algorithm, but used little of that existing parallel structure. Consequently, our parallelization was close to starting with the sequential version. We found the intuitive extensions to Pfortran and Co-Array Fortran helpful in the rapid parallelization of the project. We present performance figures for both the Pfortran and Co-Array Fortran parallelizations showing linear speedup within the range expected by these parallelization methods.

Parallel computing for data science with examples in R, C++ and CUDA

CERN Document Server

Matloff, Norman

2015-01-01

Parallel Computing for Data Science: With Examples in R, C++ and CUDA is one of the first parallel computing books to concentrate exclusively on parallel data structures, algorithms, software tools, and applications in data science. It includes examples not only from the classic ""n observations, p variables"" matrix format but also from time series, network graph models, and numerous other structures common in data science. The examples illustrate the range of issues encountered in parallel programming.With the main focus on computation, the book shows how to compute on three types of platfor

Design Patterns: establishing a discipline of parallel software engineering

CERN Multimedia

CERN. Geneva

2010-01-01

Many core processors present us with a software challenge. We must turn our serial code into parallel code. To accomplish this wholesale transformation of our software ecosystem, we must define established practice is in parallel programming and then develop tools to support that practice. This leads to design patterns supported by frameworks optimized at runtime with advanced autotuning compilers. In this talk I provide an update of my ongoing research with the ParLab at UC Berkeley to realize this vision. In particular, I will describe our draft parallel pattern language, our early experiments with software frameworks, and the associated runtime optimization tools.About the speakerTim Mattson is a parallel programmer (Ph.D. Chemistry, UCSC, 1985). He does linear algebra, finds oil, shakes molecules, solves differential equations, and models electrons in simple atomic systems. He has spent his career working with computer scientists to make sure the needs of parallel applications programmers are met.Tim has ...

Parallel computing for event reconstruction in high-energy physics

International Nuclear Information System (INIS)

Wolbers, S.

1993-01-01

Parallel computing has been recognized as a solution to large computing problems. In High Energy Physics offline event reconstruction of detector data is a very large computing problem that has been solved with parallel computing techniques. A review of the parallel programming package CPS (Cooperative Processes Software) developed and used at Fermilab for offline reconstruction of Terabytes of data requiring the delivery of hundreds of Vax-Years per experiment is given. The Fermilab UNIX farms, consisting of 180 Silicon Graphics workstations and 144 IBM RS6000 workstations, are used to provide the computing power for the experiments. Fermilab has had a long history of providing production parallel computing starting with the ACP (Advanced Computer Project) Farms in 1986. The Fermilab UNIX Farms have been in production for over 2 years with 24 hour/day service to experimental user groups. Additional tools for management, control and monitoring these large systems will be described. Possible future directions for parallel computing in High Energy Physics will be given

On-line event reconstruction using a parallel in-memory data base

OpenAIRE

Argante, E; Van der Stok, P D V; Willers, Ian Malcolm

1995-01-01

PORS is a system designed for on-line event reconstruction in high energy physics (HEP) experiments. It uses the CPREAD reconstruction program. Central to the system is a parallel in-memory database which is used as communication medium between parallel workers. A farming control structure is implemented with PORS in a natural way. The database provides structured storage of data with a short life time. PORS serves as a case study for the construction of a methodology on how to apply parallel...

Distributed Memory Programming on Many-Cores

DEFF Research Database (Denmark)

Berthold, Jost; Dieterle, Mischa; Lobachev, Oleg

2009-01-01

Eden is a parallel extension of the lazy functional language Haskell providing dynamic process creation and automatic data exchange. As a Haskell extension, Eden takes a high-level approach to parallel programming and thereby simplifies parallel program development. The current implementation is ...

Vectorization, parallelization and porting of nuclear codes. 2001

International Nuclear Information System (INIS)

Akiyama, Mitsunaga; Katakura, Fumishige; Kume, Etsuo; Nemoto, Toshiyuki; Tsuruoka, Takuya; Adachi, Masaaki

2003-07-01

Several computer codes in the nuclear field have been vectorized, parallelized and transported on the super computer system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 10 codes in fiscal 2001. In this report, the parallelization of Neutron Radiography for 3 Dimensional CT code NR3DCT, the vectorization of unsteady-state heat conduction code THERMO3D, the porting of initial program of MHD simulation, the tuning of Heat And Mass Balance Analysis Code HAMBAC, the porting and parallelization of Monte Carlo N-Particle transport code MCNP4C3, the porting and parallelization of Monte Carlo N-Particle transport code system MCNPX2.1.5, the porting of induced activity calculation code CINAC-V4, the use of VisLink library in multidimensional two-fluid model code ACD3D and the porting of experiment data processing code from GS8500 to SR8000 are described. (author)

7th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Gracia, José; Nagel, Wolfgang; Resch, Michael

2014-01-01

Current advances in High Performance Computing (HPC) increasingly impact efficient software development workflows. Programmers for HPC applications need to consider trends such as increased core counts, multiple levels of parallelism, reduced memory per core, and I/O system challenges in order to derive well performing and highly scalable codes. At the same time, the increasing complexity adds further sources of program defects. While novel programming paradigms and advanced system libraries provide solutions for some of these challenges, appropriate supporting tools are indispensable. Such tools aid application developers in debugging, performance analysis, or code optimization and therefore make a major contribution to the development of robust and efficient parallel software. This book introduces a selection of the tools presented and discussed at the 7th International Parallel Tools Workshop, held in Dresden, Germany, September 3-4, 2013.  

Parallel Evolutionary Optimization for Neuromorphic Network Training

Energy Technology Data Exchange (ETDEWEB)

Schuman, Catherine D [ORNL; Disney, Adam [University of Tennessee (UT); Singh, Susheela [North Carolina State University (NCSU), Raleigh; Bruer, Grant [University of Tennessee (UT); Mitchell, John Parker [University of Tennessee (UT); Klibisz, Aleksander [University of Tennessee (UT); Plank, James [University of Tennessee (UT)

2016-01-01

One of the key impediments to the success of current neuromorphic computing architectures is the issue of how best to program them. Evolutionary optimization (EO) is one promising programming technique; in particular, its wide applicability makes it especially attractive for neuromorphic architectures, which can have many different characteristics. In this paper, we explore different facets of EO on a spiking neuromorphic computing model called DANNA. We focus on the performance of EO in the design of our DANNA simulator, and on how to structure EO on both multicore and massively parallel computing systems. We evaluate how our parallel methods impact the performance of EO on Titan, the U.S.'s largest open science supercomputer, and BOB, a Beowulf-style cluster of Raspberry Pi's. We also focus on how to improve the EO by evaluating commonality in higher performing neural networks, and present the result of a study that evaluates the EO performed by Titan.

Northeast Artificial Intelligence Consortium Annual Report - 1988 Parallel Vision. Volume 9

Science.gov (United States)

1989-10-01

supports the Northeast Aritificial Intelligence Consortium (NAIC). Volume 9 Parallel Vision Report submitted by Christopher M. Brown Randal C. Nelson...NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT - 1988 Parallel Vision Syracuse University Christopher M. Brown and Randal C. Nelson...Technical Director Directorate of Intelligence & Reconnaissance FOR THE COMMANDER: IGOR G. PLONISCH Directorate of Plans & Programs If your address has

PERFORMANCE EVALUATION OF OR1200 PROCESSOR WITH EVOLUTIONARY PARALLEL HPRC USING GEP

Directory of Open Access Journals (Sweden)

R. Maheswari

2012-04-01

Full Text Available In this fast computing era, most of the embedded system requires more computing power to complete the complex function/ task at the lesser amount of time. One way to achieve this is by boosting up the processor performance which allows processor core to run faster. This paper presents a novel technique of increasing the performance by parallel HPRC (High Performance Reconfigurable Computing in the CPU/DSP (Digital Signal Processor unit of OR1200 (Open Reduced Instruction Set Computer (RISC 1200 using Gene Expression Programming (GEP an evolutionary programming model. OR1200 is a soft-core RISC processor of the Intellectual Property cores that can efficiently run any modern operating system. In the manufacturing process of OR1200 a parallel HPRC is placed internally in the Integer Execution Pipeline unit of the CPU/DSP core to increase the performance. The GEP Parallel HPRC is activated /deactivated by triggering the signals i HPRC_Gene_Start ii HPRC_Gene_End. A Verilog HDL(Hardware Description language functional code for Gene Expression Programming parallel HPRC is developed and synthesised using XILINX ISE in the former part of the work and a CoreMark processor core benchmark is used to test the performance of the OR1200 soft core in the later part of the work. The result of the implementation ensures the overall speed-up increased to 20.59% by GEP based parallel HPRC in the execution unit of OR1200.

Parallel Algorithms for Graph Optimization using Tree Decompositions

Energy Technology Data Exchange (ETDEWEB)

Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL; Groer, Christopher S [ORNL

2012-06-01

Although many $\\cal{NP}$-hard graph optimization problems can be solved in polynomial time on graphs of bounded tree-width, the adoption of these techniques into mainstream scientific computation has been limited due to the high memory requirements of the necessary dynamic programming tables and excessive runtimes of sequential implementations. This work addresses both challenges by proposing a set of new parallel algorithms for all steps of a tree decomposition-based approach to solve the maximum weighted independent set problem. A hybrid OpenMP/MPI implementation includes a highly scalable parallel dynamic programming algorithm leveraging the MADNESS task-based runtime, and computational results demonstrate scaling. This work enables a significant expansion of the scale of graphs on which exact solutions to maximum weighted independent set can be obtained, and forms a framework for solving additional graph optimization problems with similar techniques.

Parallelizing an electron transport Monte Carlo simulator (MOCASIN 2.0)

International Nuclear Information System (INIS)

Schwetman, H.; Burdick, S.

1988-01-01

Electron transport simulators are tools for studying electrical properties of semiconducting materials and devices. As demands for modeling more complex devices and new materials have emerged, so have demands for more processing power. This paper documents a project to convert an electron transport simulator (MOCASIN 2.0) to a parallel processing environment. In addition to describing the conversion, the paper presents PPL, a parallel programming version of C running on a Sequent multiprocessor system. In timing tests, models that simulated the movement of 2,000 particles for 100 time steps were executed on ten processors, with a parallel efficiency of over 97%

A Programming Environment for Parallel Vision Algorithms

Science.gov (United States)

1990-04-11

industrial arm on the market , while the unique head was designed by Rochester’s Computer Science and Mechanical Engineering Departments. 9a 4.1 Introduction...R. Constraining-Unification and the Programming Language Unicorn . In Logic Programming, Functions, Relations, and Equations, Degroot and Lind- strom

Parallel algorithms for network routing problems and recurrences

International Nuclear Information System (INIS)

Wisniewski, J.A.; Sameh, A.H.

1982-01-01

In this paper, we consider the parallel solution of recurrences, and linear systems in the regular algebra of Carre. These problems are equivalent to solving the shortest path problem in graph theory, and they also arise in the analysis of Fortran programs. Our methods for solving linear systems in the regular algebra are analogues of well-known methods for solving systems of linear algebraic equations. A parallel version of Dijkstra's method, which has no linear algebraic analogue, is presented. Considerations for choosing an algorithm when the problem is large and sparse are also discussed

Just-in-Time Compilation-Inspired Methodology for Parallelization of Compute Intensive Java Code

Directory of Open Access Journals (Sweden)

GHULAM MUSTAFA

2017-01-01

Full Text Available Compute intensive programs generally consume significant fraction of execution time in a small amount of repetitive code. Such repetitive code is commonly known as hotspot code. We observed that compute intensive hotspots often possess exploitable loop level parallelism. A JIT (Just-in-Time compiler profiles a running program to identify its hotspots. Hotspots are then translated into native code, for efficient execution. Using similar approach, we propose a methodology to identify hotspots and exploit their parallelization potential on multicore systems. Proposed methodology selects and parallelizes each DOALL loop that is either contained in a hotspot method or calls a hotspot method. The methodology could be integrated in front-end of a JIT compiler to parallelize sequential code, just before native translation. However, compilation to native code is out of scope of this work. As a case study, we analyze eighteen JGF (Java Grande Forum benchmarks to determine parallelization potential of hotspots. Eight benchmarks demonstrate a speedup of up to 7.6x on an 8-core system

Just-in-time compilation-inspired methodology for parallelization of compute intensive java code

International Nuclear Information System (INIS)

Mustafa, G.; Ghani, M.U.

2017-01-01

Compute intensive programs generally consume significant fraction of execution time in a small amount of repetitive code. Such repetitive code is commonly known as hotspot code. We observed that compute intensive hotspots often possess exploitable loop level parallelism. A JIT (Just-in-Time) compiler profiles a running program to identify its hotspots. Hotspots are then translated into native code, for efficient execution. Using similar approach, we propose a methodology to identify hotspots and exploit their parallelization potential on multicore systems. Proposed methodology selects and parallelizes each DOALL loop that is either contained in a hotspot method or calls a hotspot method. The methodology could be integrated in front-end of a JIT compiler to parallelize sequential code, just before native translation. However, compilation to native code is out of scope of this work. As a case study, we analyze eighteen JGF (Java Grande Forum) benchmarks to determine parallelization potential of hotspots. Eight benchmarks demonstrate a speedup of up to 7.6x on an 8-core system. (author)

Parallel Education and Defining the Fourth Sector.

Science.gov (United States)

Chessell, Diana

1996-01-01

Parallel to the primary, secondary, postsecondary, and adult/community education sectors is education not associated with formal programs--learning in arts and cultural sites. The emergence of cultural and educational tourism is an opportunity for adult/community education to define itself by extending lifelong learning opportunities into parallel…

Real-time trajectory optimization on parallel processors

Science.gov (United States)

Psiaki, Mark L.

1993-01-01

A parallel algorithm has been developed for rapidly solving trajectory optimization problems. The goal of the work has been to develop an algorithm that is suitable to do real-time, on-line optimal guidance through repeated solution of a trajectory optimization problem. The algorithm has been developed on an INTEL iPSC/860 message passing parallel processor. It uses a zero-order-hold discretization of a continuous-time problem and solves the resulting nonlinear programming problem using a custom-designed augmented Lagrangian nonlinear programming algorithm. The algorithm achieves parallelism of function, derivative, and search direction calculations through the principle of domain decomposition applied along the time axis. It has been encoded and tested on 3 example problems, the Goddard problem, the acceleration-limited, planar minimum-time to the origin problem, and a National Aerospace Plane minimum-fuel ascent guidance problem. Execution times as fast as 118 sec of wall clock time have been achieved for a 128-stage Goddard problem solved on 32 processors. A 32-stage minimum-time problem has been solved in 151 sec on 32 processors. A 32-stage National Aerospace Plane problem required 2 hours when solved on 32 processors. A speed-up factor of 7.2 has been achieved by using 32-nodes instead of 1-node to solve a 64-stage Goddard problem.

Connectionist Models and Parallelism in High Level Vision.

Science.gov (United States)

1985-01-01

GRANT NUMBER(s) Jerome A. Feldman N00014-82-K-0193 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENt. PROJECT, TASK Computer Science...Connectionist Models 2.1 Background and Overviev % Computer science is just beginning to look seriously at parallel computation : it may turn out that...the chair. The program includes intermediate level networks that compute more complex joints and ones that compute parallelograms in the image. These

Parallel grid generation algorithm for distributed memory computers

Science.gov (United States)

Moitra, Stuti; Moitra, Anutosh

1994-01-01

A parallel grid-generation algorithm and its implementation on the Intel iPSC/860 computer are described. The grid-generation scheme is based on an algebraic formulation of homotopic relations. Methods for utilizing the inherent parallelism of the grid-generation scheme are described, and implementation of multiple levELs of parallelism on multiple instruction multiple data machines are indicated. The algorithm is capable of providing near orthogonality and spacing control at solid boundaries while requiring minimal interprocessor communications. Results obtained on the Intel hypercube for a blended wing-body configuration are used to demonstrate the effectiveness of the algorithm. Fortran implementations bAsed on the native programming model of the iPSC/860 computer and the Express system of software tools are reported. Computational gains in execution time speed-up ratios are given.

Highly parallel machines and future of scientific computing

International Nuclear Information System (INIS)

Singh, G.S.

1992-01-01

Computing requirement of large scale scientific computing has always been ahead of what state of the art hardware could supply in the form of supercomputers of the day. And for any single processor system the limit to increase in the computing power was realized a few years back itself. Now with the advent of parallel computing systems the availability of machines with the required computing power seems a reality. In this paper the author tries to visualize the future large scale scientific computing in the penultimate decade of the present century. The author summarized trends in parallel computers and emphasize the need for a better programming environment and software tools for optimal performance. The author concludes this paper with critique on parallel architectures, software tools and algorithms. (author). 10 refs., 2 tabs

Temporal fringe pattern analysis with parallel computing

International Nuclear Information System (INIS)

Tuck Wah Ng; Kar Tien Ang; Argentini, Gianluca

2005-01-01

Temporal fringe pattern analysis is invaluable in transient phenomena studies but necessitates long processing times. Here we describe a parallel computing strategy based on the single-program multiple-data model and hyperthreading processor technology to reduce the execution time. In a two-node cluster workstation configuration we found that execution periods were reduced by 1.6 times when four virtual processors were used. To allow even lower execution times with an increasing number of processors, the time allocated for data transfer, data read, and waiting should be minimized. Parallel computing is found here to present a feasible approach to reduce execution times in temporal fringe pattern analysis

What is "the patient perspective" in patient engagement programs? Implicit logics and parallels to feminist theories.

Science.gov (United States)

Rowland, Paula; McMillan, Sarah; McGillicuddy, Patti; Richards, Joy

2017-01-01

Public and patient involvement (PPI) in health care may refer to many different processes, ranging from participating in decision-making about one's own care to participating in health services research, health policy development, or organizational reforms. Across these many forms of public and patient involvement, the conceptual and theoretical underpinnings remain poorly articulated. Instead, most public and patient involvement programs rely on policy initiatives as their conceptual frameworks. This lack of conceptual clarity participates in dilemmas of program design, implementation, and evaluation. This study contributes to the development of theoretical understandings of public and patient involvement. In particular, we focus on the deployment of patient engagement programs within health service organizations. To develop a deeper understanding of the conceptual underpinnings of these programs, we examined the concept of "the patient perspective" as used by patient engagement practitioners and participants. Specifically, we focused on the way this phrase was used in the singular: "the" patient perspective or "the" patient voice. From qualitative analysis of interviews with 20 patient advisers and 6 staff members within a large urban health network in Canada, we argue that "the patient perspective" is referred to as a particular kind of situated knowledge, specifically an embodied knowledge of vulnerability. We draw parallels between this logic of patient perspective and the logic of early feminist theory, including the concepts of standpoint theory and strong objectivity. We suggest that champions of patient engagement may learn much from the way feminist theorists have constructed their arguments and addressed critique.

Massively parallel computation of PARASOL code on the Origin 3800 system

International Nuclear Information System (INIS)

Hosokawa, Masanari; Takizuka, Tomonori

2001-10-01

The divertor particle simulation code named PARASOL simulates open-field plasmas between divertor walls self-consistently by using an electrostatic PIC method and a binary collision Monte Carlo model. The PARASOL parallelized with MPI-1.1 for scalar parallel computer worked on Intel Paragon XP/S system. A system SGI Origin 3800 was newly installed (May, 2001). The parallel programming was improved at this switchover. As a result of the high-performance new hardware and this improvement, the PARASOL is speeded up by about 60 times with the same number of processors. (author)

Data-parallel tomographic reconstruction : A comparison of filtered backprojection and direct Fourier reconstruction

NARCIS (Netherlands)

Roerdink, J.B.T.M.; Westenberg, M.A

1998-01-01

We consider the parallelization of two standard 2D reconstruction algorithms, filtered backprojection and direct Fourier reconstruction, using the data-parallel programming style. The algorithms are implemented on a Connection Machine CM-5 with 16 processors and a peak performance of 2 Gflop/s.

Massively Parallel QCD

International Nuclear Information System (INIS)

Soltz, R; Vranas, P; Blumrich, M; Chen, D; Gara, A; Giampap, M; Heidelberger, P; Salapura, V; Sexton, J; Bhanot, G

2007-01-01

The theory of the strong nuclear force, Quantum Chromodynamics (QCD), can be numerically simulated from first principles on massively-parallel supercomputers using the method of Lattice Gauge Theory. We describe the special programming requirements of lattice QCD (LQCD) as well as the optimal supercomputer hardware architectures that it suggests. We demonstrate these methods on the BlueGene massively-parallel supercomputer and argue that LQCD and the BlueGene architecture are a natural match. This can be traced to the simple fact that LQCD is a regular lattice discretization of space into lattice sites while the BlueGene supercomputer is a discretization of space into compute nodes, and that both are constrained by requirements of locality. This simple relation is both technologically important and theoretically intriguing. The main result of this paper is the speedup of LQCD using up to 131,072 CPUs on the largest BlueGene/L supercomputer. The speedup is perfect with sustained performance of about 20% of peak. This corresponds to a maximum of 70.5 sustained TFlop/s. At these speeds LQCD and BlueGene are poised to produce the next generation of strong interaction physics theoretical results

The Research of the Parallel Computing Development from the Angle of Cloud Computing

Science.gov (United States)

Peng, Zhensheng; Gong, Qingge; Duan, Yanyu; Wang, Yun

2017-10-01

Cloud computing is the development of parallel computing, distributed computing and grid computing. The development of cloud computing makes parallel computing come into people’s lives. Firstly, this paper expounds the concept of cloud computing and introduces two several traditional parallel programming model. Secondly, it analyzes and studies the principles, advantages and disadvantages of OpenMP, MPI and Map Reduce respectively. Finally, it takes MPI, OpenMP models compared to Map Reduce from the angle of cloud computing. The results of this paper are intended to provide a reference for the development of parallel computing.

Performance evaluation of the HEP, ELXSI and CRAY X-MP parallel processors on hydrocode test problems

International Nuclear Information System (INIS)

Liebrock, L.M.; McGrath, J.F.; Hicks, D.L.

1986-01-01

Parallel programming promises improved processing speeds for hydrocodes, magnetohydrocodes, multiphase flow codes, thermal-hydraulics codes, wavecodes and other continuum dynamics codes. This paper presents the results of some investigations of parallel algorithms on three parallel processors: the CRAY X-MP, ELXSI and the HEP computers. Introduction and Background: We report the results of investigations of parallel algorithms for computational continuum dynamics. These programs (hydrocodes, wavecodes, etc.) produce simulations of the solutions to problems arising in the motion of continua: solid dynamics, liquid dynamics, gas dynamics, plasma dynamics, multiphase flow dynamics, thermal-hydraulic dynamics and multimaterial flow dynamics. This report restricts its scope to one-dimensional algorithms such as the von Neumann-Richtmyer (1950) scheme

Protocol-Based Verification of Message-Passing Parallel Programs

DEFF Research Database (Denmark)

López-Acosta, Hugo-Andrés; Eduardo R. B. Marques, Eduardo R. B.; Martins, Francisco

2015-01-01

We present ParTypes, a type-based methodology for the verification of Message Passing Interface (MPI) programs written in the C programming language. The aim is to statically verify programs against protocol specifications, enforcing properties such as fidelity and absence of deadlocks. We develo...

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

Science.gov (United States)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and

TME (Task Mapping Editor): tool for executing distributed parallel computing. TME user's manual

International Nuclear Information System (INIS)

Takemiya, Hiroshi; Yamagishi, Nobuhiro; Imamura, Toshiyuki

2000-03-01

At the Center for Promotion of Computational Science and Engineering, a software environment PPExe has been developed to support scientific computing on a parallel computer cluster (distributed parallel scientific computing). TME (Task Mapping Editor) is one of components of the PPExe and provides a visual programming environment for distributed parallel scientific computing. Users can specify data dependence among tasks (programs) visually as a data flow diagram and map these tasks onto computers interactively through GUI of TME. The specified tasks are processed by other components of PPExe such as Meta-scheduler, RIM (Resource Information Monitor), and EMS (Execution Management System) according to the execution order of these tasks determined by TME. In this report, we describe the usage of TME. (author)

Fiscal 2000 report on advanced parallelized compiler technology. Outlines; 2000 nendo advanced heiretsuka compiler gijutsu hokokusho (Gaiyo hen)

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

Research and development was carried out concerning the automatic parallelized compiler technology which improves on the practical performance, cost/performance ratio, and ease of operation of the multiprocessor system now used for constructing supercomputers and expected to provide a fundamental architecture for microprocessors for the 21st century. Efforts were made to develop an automatic multigrain parallelization technology for extracting multigrain as parallelized from a program and for making full use of the same and a parallelizing tuning technology for accelerating parallelization by feeding back to the compiler the dynamic information and user knowledge to be acquired during execution. Moreover, a benchmark program was selected and studies were made to set execution rules and evaluation indexes for the establishment of technologies for subjectively evaluating the performance of parallelizing compilers for the existing commercial parallel processing computers, which was achieved through the implementation and evaluation of the 'Advanced parallelizing compiler technology research and development project.' (NEDO)

Center for Programming Models for Scalable Parallel Computing - Towards Enhancing OpenMP for Manycore and Heterogeneous Nodes

Energy Technology Data Exchange (ETDEWEB)

Barbara Chapman

2012-02-01

OpenMP was not well recognized at the beginning of the project, around year 2003, because of its limited use in DoE production applications and the inmature hardware support for an efficient implementation. Yet in the recent years, it has been graduately adopted both in HPC applications, mostly in the form of MPI+OpenMP hybrid code, and in mid-scale desktop applications for scientific and experimental studies. We have observed this trend and worked deligiently to improve our OpenMP compiler and runtimes, as well as to work with the OpenMP standard organization to make sure OpenMP are evolved in the direction close to DoE missions. In the Center for Programming Models for Scalable Parallel Computing project, the HPCTools team at the University of Houston (UH), directed by Dr. Barbara Chapman, has been working with project partners, external collaborators and hardware vendors to increase the scalability and applicability of OpenMP for multi-core (and future manycore) platforms and for distributed memory systems by exploring different programming models, language extensions, compiler optimizations, as well as runtime library support.

Parallel rendering

Science.gov (United States)

Crockett, Thomas W.

1995-01-01

This article provides a broad introduction to the subject of parallel rendering, encompassing both hardware and software systems. The focus is on the underlying concepts and the issues which arise in the design of parallel rendering algorithms and systems. We examine the different types of parallelism and how they can be applied in rendering applications. Concepts from parallel computing, such as data decomposition, task granularity, scalability, and load balancing, are considered in relation to the rendering problem. We also explore concepts from computer graphics, such as coherence and projection, which have a significant impact on the structure of parallel rendering algorithms. Our survey covers a number of practical considerations as well, including the choice of architectural platform, communication and memory requirements, and the problem of image assembly and display. We illustrate the discussion with numerous examples from the parallel rendering literature, representing most of the principal rendering methods currently used in computer graphics.

The CRAFT Fortran Programming Model

Directory of Open Access Journals (Sweden)

Douglas M. Pase

1994-01-01

Full Text Available Many programming models for massively parallel machines exist, and each has its advantages and disadvantages. In this article we present a programming model that combines features from other programming models that (1 can be efficiently implemented on present and future Cray Research massively parallel processor (MPP systems and (2 are useful in constructing highly parallel programs. The model supports several styles of programming: message-passing, data parallel, global address (shared data, and work-sharing. These styles may be combined within the same program. The model includes features that allow a user to define a program in terms of the behavior of the system as a whole, where the behavior of individual tasks is implicit from this systemic definition. (In general, features marked as shared are designed to support this perspective. It also supports an opposite perspective, where a program may be defined in terms of the behaviors of individual tasks, and a program is implicitly the sum of the behaviors of all tasks. (Features marked as private are designed to support this perspective. Users can exploit any combination of either set of features without ambiguity and thus are free to define a program from whatever perspective is most appropriate to the problem at hand.

Static and dynamic load-balancing strategies for parallel reservoir simulation

International Nuclear Information System (INIS)

Anguille, L.; Killough, J.E.; Li, T.M.C.; Toepfer, J.L.

1995-01-01

Accurate simulation of the complex phenomena that occur in flow in porous media can tax even the most powerful serial computers. Emergence of new parallel computer architectures as a future efficient tool in reservoir simulation may overcome this difficulty. Unfortunately, major problems remain to be solved before using parallel computers commercially: production serial programs must be rewritten to be efficient in parallel environments and load balancing methods must be explored to evenly distribute the workload on each processor during the simulation. This study implements both a static load-balancing algorithm and a receiver-initiated dynamic load-sharing algorithm to achieve high parallel efficiencies on both the IBM SP2 and Intel IPSC/860 parallel computers. Significant speedup improvement was recorded for both methods. Further optimization of these algorithms yielded a technique with efficiencies as high as 90% and 70% on 8 and 32 nodes, respectively. The increased performance was the result of the minimization of message-passing overhead

Parallel computation for solving the tridiagonal linear system of equations

International Nuclear Information System (INIS)

Ishiguro, Misako; Harada, Hiroo; Fujii, Minoru; Fujimura, Toichiro; Nakamura, Yasuhiro; Nanba, Katsumi.

1981-09-01

Recently, applications of parallel computation for scientific calculations have increased from the need of the high speed calculation of large scale programs. At the JAERI computing center, an array processor FACOM 230-75 APU has installed to study the applicability of parallel computation for nuclear codes. We made some numerical experiments by using the APU on the methods of solution of tridiagonal linear equation which is an important problem in scientific calculations. Referring to the recent papers with parallel methods, we investigate eight ones. These are Gauss elimination method, Parallel Gauss method, Accelerated parallel Gauss method, Jacobi method, Recursive doubling method, Cyclic reduction method, Chebyshev iteration method, and Conjugate gradient method. The computing time and accuracy were compared among the methods on the basis of the numerical experiments. As the result, it is found that the Cyclic reduction method is best both in computing time and accuracy and the Gauss elimination method is the second one. (author)

Parallel computations

CERN Document Server

1982-01-01

Parallel Computations focuses on parallel computation, with emphasis on algorithms used in a variety of numerical and physical applications and for many different types of parallel computers. Topics covered range from vectorization of fast Fourier transforms (FFTs) and of the incomplete Cholesky conjugate gradient (ICCG) algorithm on the Cray-1 to calculation of table lookups and piecewise functions. Single tridiagonal linear systems and vectorized computation of reactive flow are also discussed.Comprised of 13 chapters, this volume begins by classifying parallel computers and describing techn

Parallel sorting algorithms

CERN Document Server

Akl, Selim G

1985-01-01

Parallel Sorting Algorithms explains how to use parallel algorithms to sort a sequence of items on a variety of parallel computers. The book reviews the sorting problem, the parallel models of computation, parallel algorithms, and the lower bounds on the parallel sorting problems. The text also presents twenty different algorithms, such as linear arrays, mesh-connected computers, cube-connected computers. Another example where algorithm can be applied is on the shared-memory SIMD (single instruction stream multiple data stream) computers in which the whole sequence to be sorted can fit in the

Scalable Parallel Distributed Coprocessor System for Graph Searching Problems with Massive Data

Directory of Open Access Journals (Sweden)

Wanrong Huang

2017-01-01

Full Text Available The Internet applications, such as network searching, electronic commerce, and modern medical applications, produce and process massive data. Considerable data parallelism exists in computation processes of data-intensive applications. A traversal algorithm, breadth-first search (BFS, is fundamental in many graph processing applications and metrics when a graph grows in scale. A variety of scientific programming methods have been proposed for accelerating and parallelizing BFS because of the poor temporal and spatial locality caused by inherent irregular memory access patterns. However, new parallel hardware could provide better improvement for scientific methods. To address small-world graph problems, we propose a scalable and novel field-programmable gate array-based heterogeneous multicore system for scientific programming. The core is multithread for streaming processing. And the communication network InfiniBand is adopted for scalability. We design a binary search algorithm to address mapping to unify all processor addresses. Within the limits permitted by the Graph500 test bench after 1D parallel hybrid BFS algorithm testing, our 8-core and 8-thread-per-core system achieved superior performance and efficiency compared with the prior work under the same degree of parallelism. Our system is efficient not as a special acceleration unit but as a processor platform that deals with graph searching applications.

Logical inference techniques for loop parallelization

KAUST Repository

Oancea, Cosmin E.; Rauchwerger, Lawrence

2012-01-01

This paper presents a fully automatic approach to loop parallelization that integrates the use of static and run-time analysis and thus overcomes many known difficulties such as nonlinear and indirect array indexing and complex control flow. Our hybrid analysis framework validates the parallelization transformation by verifying the independence of the loop's memory references. To this end it represents array references using the USR (uniform set representation) language and expresses the independence condition as an equation, S = Ø, where S is a set expression representing array indexes. Using a language instead of an array-abstraction representation for S results in a smaller number of conservative approximations but exhibits a potentially-high runtime cost. To alleviate this cost we introduce a language translation F from the USR set-expression language to an equally rich language of predicates (F(S) ⇒ S = Ø). Loop parallelization is then validated using a novel logic inference algorithm that factorizes the obtained complex predicates (F(S)) into a sequence of sufficient-independence conditions that are evaluated first statically and, when needed, dynamically, in increasing order of their estimated complexities. We evaluate our automated solution on 26 benchmarks from PERFECTCLUB and SPEC suites and show that our approach is effective in parallelizing large, complex loops and obtains much better full program speedups than the Intel and IBM Fortran compilers. Copyright © 2012 ACM.

Logical inference techniques for loop parallelization

KAUST Repository

Oancea, Cosmin E.

2012-01-01

This paper presents a fully automatic approach to loop parallelization that integrates the use of static and run-time analysis and thus overcomes many known difficulties such as nonlinear and indirect array indexing and complex control flow. Our hybrid analysis framework validates the parallelization transformation by verifying the independence of the loop\\'s memory references. To this end it represents array references using the USR (uniform set representation) language and expresses the independence condition as an equation, S = Ø, where S is a set expression representing array indexes. Using a language instead of an array-abstraction representation for S results in a smaller number of conservative approximations but exhibits a potentially-high runtime cost. To alleviate this cost we introduce a language translation F from the USR set-expression language to an equally rich language of predicates (F(S) ⇒ S = Ø). Loop parallelization is then validated using a novel logic inference algorithm that factorizes the obtained complex predicates (F(S)) into a sequence of sufficient-independence conditions that are evaluated first statically and, when needed, dynamically, in increasing order of their estimated complexities. We evaluate our automated solution on 26 benchmarks from PERFECTCLUB and SPEC suites and show that our approach is effective in parallelizing large, complex loops and obtains much better full program speedups than the Intel and IBM Fortran compilers. Copyright © 2012 ACM.

Compiler and Runtime Support for Programming in Adaptive Parallel Environments

Science.gov (United States)

1998-10-15

noother job is waiting for resources, and use a smaller number of processors when other jobs needresources. Setia et al. [15, 20] have shown that such...15] Vijay K. Naik, Sanjeev Setia , and Mark Squillante. Performance analysis of job scheduling policiesin parallel supercomputing environments. In...on networks ofheterogeneous workstations. Technical Report CSE-94-012, Oregon Graduate Institute of Scienceand Technology, 1994.[20] Sanjeev Setia

A package of Linux scripts for the parallelization of Monte Carlo simulations

Science.gov (United States)

Badal, Andreu; Sempau, Josep

2006-09-01

Despite the fact that fast computers are nowadays available at low cost, there are many situations where obtaining a reasonably low statistical uncertainty in a Monte Carlo (MC) simulation involves a prohibitively large amount of time. This limitation can be overcome by having recourse to parallel computing. Most tools designed to facilitate this approach require modification of the source code and the installation of additional software, which may be inconvenient for some users. We present a set of tools, named clonEasy, that implement a parallelization scheme of a MC simulation that is free from these drawbacks. In clonEasy, which is designed to run under Linux, a set of "clone" CPUs is governed by a "master" computer by taking advantage of the capabilities of the Secure Shell (ssh) protocol. Any Linux computer on the Internet that can be ssh-accessed by the user can be used as a clone. A key ingredient for the parallel calculation to be reliable is the availability of an independent string of random numbers for each CPU. Many generators—such as RANLUX, RANECU or the Mersenne Twister—can readily produce these strings by initializing them appropriately and, hence, they are suitable to be used with clonEasy. This work was primarily motivated by the need to find a straightforward way to parallelize PENELOPE, a code for MC simulation of radiation transport that (in its current 2005 version) employs the generator RANECU, which uses a combination of two multiplicative linear congruential generators (MLCGs). Thus, this paper is focused on this class of generators and, in particular, we briefly present an extension of RANECU that increases its period up to ˜5×10 and we introduce seedsMLCG, a tool that provides the information necessary to initialize disjoint sequences of an MLCG to feed different CPUs. This program, in combination with clonEasy, allows to run PENELOPE in parallel easily, without requiring specific libraries or significant alterations of the

Vector and parallel processors in computational science

International Nuclear Information System (INIS)

Duff, I.S.; Reid, J.K.

1985-01-01

This book presents the papers given at a conference which reviewed the new developments in parallel and vector processing. Topics considered at the conference included hardware (array processors, supercomputers), programming languages, software aids, numerical methods (e.g., Monte Carlo algorithms, iterative methods, finite elements, optimization), and applications (e.g., neutron transport theory, meteorology, image processing)

Electromagnetic Physics Models for Parallel Computing Architectures

Science.gov (United States)

Amadio, G.; Ananya, A.; Apostolakis, J.; Aurora, A.; Bandieramonte, M.; Bhattacharyya, A.; Bianchini, C.; Brun, R.; Canal, P.; Carminati, F.; Duhem, L.; Elvira, D.; Gheata, A.; Gheata, M.; Goulas, I.; Iope, R.; Jun, S. Y.; Lima, G.; Mohanty, A.; Nikitina, T.; Novak, M.; Pokorski, W.; Ribon, A.; Seghal, R.; Shadura, O.; Vallecorsa, S.; Wenzel, S.; Zhang, Y.

2016-10-01

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Results of preliminary performance evaluation and physics validation are presented as well.

Efficient Parallel Kernel Solvers for Computational Fluid Dynamics Applications

Science.gov (United States)

Sun, Xian-He

1997-01-01

Distributed-memory parallel computers dominate today's parallel computing arena. These machines, such as Intel Paragon, IBM SP2, and Cray Origin2OO, have successfully delivered high performance computing power for solving some of the so-called "grand-challenge" problems. Despite initial success, parallel machines have not been widely accepted in production engineering environments due to the complexity of parallel programming. On a parallel computing system, a task has to be partitioned and distributed appropriately among processors to reduce communication cost and to attain load balance. More importantly, even with careful partitioning and mapping, the performance of an algorithm may still be unsatisfactory, since conventional sequential algorithms may be serial in nature and may not be implemented efficiently on parallel machines. In many cases, new algorithms have to be introduced to increase parallel performance. In order to achieve optimal performance, in addition to partitioning and mapping, a careful performance study should be conducted for a given application to find a good algorithm-machine combination. This process, however, is usually painful and elusive. The goal of this project is to design and develop efficient parallel algorithms for highly accurate Computational Fluid Dynamics (CFD) simulations and other engineering applications. The work plan is 1) developing highly accurate parallel numerical algorithms, 2) conduct preliminary testing to verify the effectiveness and potential of these algorithms, 3) incorporate newly developed algorithms into actual simulation packages. The work plan has well achieved. Two highly accurate, efficient Poisson solvers have been developed and tested based on two different approaches: (1) Adopting a mathematical geometry which has a better capacity to describe the fluid, (2) Using compact scheme to gain high order accuracy in numerical discretization. The previously developed Parallel Diagonal Dominant (PDD) algorithm

Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

Science.gov (United States)

Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

2010-01-01

This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

SPINET: A Parallel Computing Approach to Spine Simulations

Directory of Open Access Journals (Sweden)

Peter G. Kropf

1996-01-01

Full Text Available Research in scientitic programming enables us to realize more and more complex applications, and on the other hand, application-driven demands on computing methods and power are continuously growing. Therefore, interdisciplinary approaches become more widely used. The interdisciplinary SPINET project presented in this article applies modern scientific computing tools to biomechanical simulations: parallel computing and symbolic and modern functional programming. The target application is the human spine. Simulations of the spine help us to investigate and better understand the mechanisms of back pain and spinal injury. Two approaches have been used: the first uses the finite element method for high-performance simulations of static biomechanical models, and the second generates a simulation developmenttool for experimenting with different dynamic models. A finite element program for static analysis has been parallelized for the MUSIC machine. To solve the sparse system of linear equations, a conjugate gradient solver (iterative method and a frontal solver (direct method have been implemented. The preprocessor required for the frontal solver is written in the modern functional programming language SML, the solver itself in C, thus exploiting the characteristic advantages of both functional and imperative programming. The speedup analysis of both solvers show very satisfactory results for this irregular problem. A mixed symbolic-numeric environment for rigid body system simulations is presented. It automatically generates C code from a problem specification expressed by the Lagrange formalism using Maple.

Parallel Computation of the Jacobian Matrix for Nonlinear Equation Solvers Using MATLAB

Science.gov (United States)

Rose, Geoffrey K.; Nguyen, Duc T.; Newman, Brett A.

2017-01-01

Demonstrating speedup for parallel code on a multicore shared memory PC can be challenging in MATLAB due to underlying parallel operations that are often opaque to the user. This can limit potential for improvement of serial code even for the so-called embarrassingly parallel applications. One such application is the computation of the Jacobian matrix inherent to most nonlinear equation solvers. Computation of this matrix represents the primary bottleneck in nonlinear solver speed such that commercial finite element (FE) and multi-body-dynamic (MBD) codes attempt to minimize computations. A timing study using MATLAB's Parallel Computing Toolbox was performed for numerical computation of the Jacobian. Several approaches for implementing parallel code were investigated while only the single program multiple data (spmd) method using composite objects provided positive results. Parallel code speedup is demonstrated but the goal of linear speedup through the addition of processors was not achieved due to PC architecture.

MEDUSA - An overset grid flow solver for network-based parallel computer systems

Science.gov (United States)

Smith, Merritt H.; Pallis, Jani M.

1993-01-01

Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.

Parallelization of pressure equation solver for incompressible N-S equations

International Nuclear Information System (INIS)

Ichihara, Kiyoshi; Yokokawa, Mitsuo; Kaburaki, Hideo.

1996-03-01

A pressure equation solver in a code for 3-dimensional incompressible flow analysis has been parallelized by using red-black SOR method and PCG method on Fujitsu VPP500, a vector parallel computer with distributed memory. For the comparison of scalability, the solver using the red-black SOR method has been also parallelized on the Intel Paragon, a scalar parallel computer with a distributed memory. The scalability of the red-black SOR method on both VPP500 and Paragon was lost, when number of processor elements was increased. The reason of non-scalability on both systems is increasing communication time between processor elements. In addition, the parallelization by DO-loop division makes the vectorizing efficiency lower on VPP500. For an effective implementation on VPP500, a large scale problem which holds very long vectorized DO-loops in the parallel program should be solved. PCG method with red-black SOR method applied to incomplete LU factorization (red-black PCG) has more iteration steps than normal PCG method with forward and backward substitution, in spite of same number of the floating point operations in a DO-loop of incomplete LU factorization. The parallelized red-black PCG method has less merits than the parallelized red-black SOR method when the computational region has fewer grids, because the low vectorization efficiency is obtained in red-black PCG method. (author)

Parallel MR imaging.

Science.gov (United States)

Deshmane, Anagha; Gulani, Vikas; Griswold, Mark A; Seiberlich, Nicole

2012-07-01

Parallel imaging is a robust method for accelerating the acquisition of magnetic resonance imaging (MRI) data, and has made possible many new applications of MR imaging. Parallel imaging works by acquiring a reduced amount of k-space data with an array of receiver coils. These undersampled data can be acquired more quickly, but the undersampling leads to aliased images. One of several parallel imaging algorithms can then be used to reconstruct artifact-free images from either the aliased images (SENSE-type reconstruction) or from the undersampled data (GRAPPA-type reconstruction). The advantages of parallel imaging in a clinical setting include faster image acquisition, which can be used, for instance, to shorten breath-hold times resulting in fewer motion-corrupted examinations. In this article the basic concepts behind parallel imaging are introduced. The relationship between undersampling and aliasing is discussed and two commonly used parallel imaging methods, SENSE and GRAPPA, are explained in detail. Examples of artifacts arising from parallel imaging are shown and ways to detect and mitigate these artifacts are described. Finally, several current applications of parallel imaging are presented and recent advancements and promising research in parallel imaging are briefly reviewed. Copyright © 2012 Wiley Periodicals, Inc.

Multilevel Parallelization of AutoDock 4.2

Directory of Open Access Journals (Sweden)

Norgan Andrew P

2011-04-01

Full Text Available Abstract Background Virtual (computational screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4. Results Using MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers. Conclusions Using MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDock's Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI and node-level (OpenMP parallelization to best fit both workloads and computational resources.

Multilevel Parallelization of AutoDock 4.2.

Science.gov (United States)

Norgan, Andrew P; Coffman, Paul K; Kocher, Jean-Pierre A; Katzmann, David J; Sosa, Carlos P

2011-04-28

Virtual (computational) screening is an increasingly important tool for drug discovery. AutoDock is a popular open-source application for performing molecular docking, the prediction of ligand-receptor interactions. AutoDock is a serial application, though several previous efforts have parallelized various aspects of the program. In this paper, we report on a multi-level parallelization of AutoDock 4.2 (mpAD4). Using MPI and OpenMP, AutoDock 4.2 was parallelized for use on MPI-enabled systems and to multithread the execution of individual docking jobs. In addition, code was implemented to reduce input/output (I/O) traffic by reusing grid maps at each node from docking to docking. Performance of mpAD4 was examined on two multiprocessor computers. Using MPI with OpenMP multithreading, mpAD4 scales with near linearity on the multiprocessor systems tested. In situations where I/O is limiting, reuse of grid maps reduces both system I/O and overall screening time. Multithreading of AutoDock's Lamarkian Genetic Algorithm with OpenMP increases the speed of execution of individual docking jobs, and when combined with MPI parallelization can significantly reduce the execution time of virtual screens. This work is significant in that mpAD4 speeds the execution of certain molecular docking workloads and allows the user to optimize the degree of system-level (MPI) and node-level (OpenMP) parallelization to best fit both workloads and computational resources.

High-Performance Psychometrics: The Parallel-E Parallel-M Algorithm for Generalized Latent Variable Models. Research Report. ETS RR-16-34

Science.gov (United States)

von Davier, Matthias

2016-01-01

This report presents results on a parallel implementation of the expectation-maximization (EM) algorithm for multidimensional latent variable models. The developments presented here are based on code that parallelizes both the E step and the M step of the parallel-E parallel-M algorithm. Examples presented in this report include item response…

PLAST: parallel local alignment search tool for database comparison

Directory of Open Access Journals (Sweden)

Lavenier Dominique

2009-10-01

Full Text Available Abstract Background Sequence similarity searching is an important and challenging task in molecular biology and next-generation sequencing should further strengthen the need for faster algorithms to process such vast amounts of data. At the same time, the internal architecture of current microprocessors is tending towards more parallelism, leading to the use of chips with two, four and more cores integrated on the same die. The main purpose of this work was to design an effective algorithm to fit with the parallel capabilities of modern microprocessors. Results A parallel algorithm for comparing large genomic banks and targeting middle-range computers has been developed and implemented in PLAST software. The algorithm exploits two key parallel features of existing and future microprocessors: the SIMD programming model (SSE instruction set and the multithreading concept (multicore. Compared to multithreaded BLAST software, tests performed on an 8-processor server have shown speedup ranging from 3 to 6 with a similar level of accuracy. Conclusion A parallel algorithmic approach driven by the knowledge of the internal microprocessor architecture allows significant speedup to be obtained while preserving standard sensitivity for similarity search problems.

Programming with Intervals

Science.gov (United States)

Matsakis, Nicholas D.; Gross, Thomas R.

Intervals are a new, higher-level primitive for parallel programming with which programmers directly construct the program schedule. Programs using intervals can be statically analyzed to ensure that they do not deadlock or contain data races. In this paper, we demonstrate the flexibility of intervals by showing how to use them to emulate common parallel control-flow constructs like barriers and signals, as well as higher-level patterns such as bounded-buffer producer-consumer. We have implemented intervals as a publicly available library for Java and Scala.

PERFORMANCE ANALYSIS BETWEEN EXPLICIT SCHEDULING AND IMPLICIT SCHEDULING OF PARALLEL ARRAY-BASED DOMAIN DECOMPOSITION USING OPENMP

Directory of Open Access Journals (Sweden)

MOHAMMED FAIZ ABOALMAALY

2014-10-01

Full Text Available With the continuous revolution of multicore architecture, several parallel programming platforms have been introduced in order to pave the way for fast and efficient development of parallel algorithms. Back into its categories, parallel computing can be done through two forms: Data-Level Parallelism (DLP or Task-Level Parallelism (TLP. The former can be done by the distribution of data among the available processing elements while the latter is based on executing independent tasks concurrently. Most of the parallel programming platforms have built-in techniques to distribute the data among processors, these techniques are technically known as automatic distribution (scheduling. However, due to their wide range of purposes, variation of data types, amount of distributed data, possibility of extra computational overhead and other hardware-dependent factors, manual distribution could achieve better outcomes in terms of performance when compared to the automatic distribution. In this paper, this assumption is investigated by conducting a comparison between automatic and our newly proposed manual distribution of data among threads in parallel. Empirical results of matrix addition and matrix multiplication show a considerable performance gain when manual distribution is applied against automatic distribution.

Comparative efficiencies of three parallel algorithms for nonlinear ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

This algorithm is better suited for large size problems on coarse ... and reliable time integration algorithms for solving the second-order dynamic equilibrium equations that arise due ... Programming models required to take advantage of the parallel and distributed ..... In addition, MPI added the concept of a 'virtual topology'.

Scaling up machine learning: parallel and distributed approaches

National Research Council Canada - National Science Library

Bekkerman, Ron; Bilenko, Mikhail; Langford, John

2012-01-01

... presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters; concurrent programming frameworks that include CUDA, MPI, MapReduce, and DryadLINQ; and various learning settings: supervised, unsupervised, semi-supervised, and online learning. Extensive coverage of parallelizat...

Performance studies of the parallel VIM code

International Nuclear Information System (INIS)

Shi, B.; Blomquist, R.N.

1996-01-01

In this paper, the authors evaluate the performance of the parallel version of the VIM Monte Carlo code on the IBM SPx at the High Performance Computing Research Facility at ANL. Three test problems with contrasting computational characteristics were used to assess effects in performance. A statistical method for estimating the inefficiencies due to load imbalance and communication is also introduced. VIM is a large scale continuous energy Monte Carlo radiation transport program and was parallelized using history partitioning, the master/worker approach, and p4 message passing library. Dynamic load balancing is accomplished when the master processor assigns chunks of histories to workers that have completed a previously assigned task, accommodating variations in the lengths of histories, processor speeds, and worker loads. At the end of each batch (generation), the fission sites and tallies are sent from each worker to the master process, contributing to the parallel inefficiency. All communications are between master and workers, and are serial. The SPx is a scalable 128-node parallel supercomputer with high-performance Omega switches of 63 microsec latency and 35 MBytes/sec bandwidth. For uniform and reproducible performance, they used only the 120 identical regular processors (IBM RS/6000) and excluded the remaining eight planet nodes, which may be loaded by other's jobs

CUDA/GPU Technology : Parallel Programming For High Performance Scientific Computing

OpenAIRE

YUHENDRA; KUZE, Hiroaki; JOSAPHAT, Tetuko Sri Sumantyo

2009-01-01

[ABSTRACT]Graphics processing units (GP Us) originally designed for computer video cards have emerged as the most powerful chip in a high-performance workstation. In the high performance computation capabilities, graphic processing units (GPU) lead to much more powerful performance than conventional CPUs by means of parallel processing. In 2007, the birth of Compute Unified Device Architecture (CUDA) and CUDA-enabled GPUs by NVIDIA Corporation brought a revolution in the general purpose GPU a...

Badlands: A parallel basin and landscape dynamics model

Directory of Open Access Journals (Sweden)

T. Salles

2016-01-01

Full Text Available Over more than three decades, a number of numerical landscape evolution models (LEMs have been developed to study the combined effects of climate, sea-level, tectonics and sediments on Earth surface dynamics. Most of them are written in efficient programming languages, but often cannot be used on parallel architectures. Here, I present a LEM which ports a common core of accepted physical principles governing landscape evolution into a distributed memory parallel environment. Badlands (acronym for BAsin anD LANdscape DynamicS is an open-source, flexible, TIN-based landscape evolution model, built to simulate topography development at various space and time scales.

A CFD Heterogeneous Parallel Solver Based on Collaborating CPU and GPU

Science.gov (United States)

Lai, Jianqi; Tian, Zhengyu; Li, Hua; Pan, Sha

2018-03-01

Since Graphic Processing Unit (GPU) has a strong ability of floating-point computation and memory bandwidth for data parallelism, it has been widely used in the areas of common computing such as molecular dynamics (MD), computational fluid dynamics (CFD) and so on. The emergence of compute unified device architecture (CUDA), which reduces the complexity of compiling program, brings the great opportunities to CFD. There are three different modes for parallel solution of NS equations: parallel solver based on CPU, parallel solver based on GPU and heterogeneous parallel solver based on collaborating CPU and GPU. As we can see, GPUs are relatively rich in compute capacity but poor in memory capacity and the CPUs do the opposite. We need to make full use of the GPUs and CPUs, so a CFD heterogeneous parallel solver based on collaborating CPU and GPU has been established. Three cases are presented to analyse the solver’s computational accuracy and heterogeneous parallel efficiency. The numerical results agree well with experiment results, which demonstrate that the heterogeneous parallel solver has high computational precision. The speedup on a single GPU is more than 40 for laminar flow, it decreases for turbulent flow, but it still can reach more than 20. What’s more, the speedup increases as the grid size becomes larger.

Discussion about the design for mesh data structure within the parallel framework

International Nuclear Information System (INIS)

Shi Guangmei; Wu Ruian; Wang Keying; Ji Xiaoyu; Hao Zhiming; Mo Jun; He Yingbo

2010-01-01

The mesh data structure, one of the fundamental data structure within the parallel framework, its design and realization level have an effect upon parallel capability of the parallel framework. Through the architecture and the fundamental data structure within some typical parallel framework relatively analyzed, such as JASMIN, SIERRA, and ITAPS, the design thought of parallel framework is discussed. Through borrowing ideas from layered set of services design about the SIERRA Framework, and combining with the objective of PANDA Framework in the near future, this paper present the rudimentary system about PANDA framework layered set of services. On this foundation, detailed introduction is placed in the definition and the management of the mesh data structure that it is located in the underlayer of the PANDA framework. The design and realization about parallel distributed mesh data structure of PANDA are emphatically discussed. The PANDA framework extension and application program development based on PANDA framework are grounded on our efforts.

Examination of Speed Contribution of Parallelization for Several Fingerprint Pre-Processing Algorithms

Directory of Open Access Journals (Sweden)

GORGUNOGLU, S.

2014-05-01

Full Text Available In analysis of minutiae based fingerprint systems, fingerprints needs to be pre-processed. The pre-processing is carried out to enhance the quality of the fingerprint and to obtain more accurate minutiae points. Reducing the pre-processing time is important for identification and verification in real time systems and especially for databases holding large fingerprints information. Parallel processing and parallel CPU computing can be considered as distribution of processes over multi core processor. This is done by using parallel programming techniques. Reducing the execution time is the main objective in parallel processing. In this study, pre-processing of minutiae based fingerprint system is implemented by parallel processing on multi core computers using OpenMP and on graphics processor using CUDA to improve execution time. The execution times and speedup ratios are compared with the one that of single core processor. The results show that by using parallel processing, execution time is substantially improved. The improvement ratios obtained for different pre-processing algorithms allowed us to make suggestions on the more suitable approaches for parallelization.

Performance study of a cluster calculation; parallelization and application under geant4

International Nuclear Information System (INIS)

Trabelsi, Abir

2007-01-01

This work concretizes the final studies project for engineering computer sciences, it is archived within the national center of nuclear sciences and technology. The project consists in studying the performance of a set of machines in order to determine the best architecture to assemble them in a cluster. As well as the parallelism and the parallel implementation of GEANT4, as a tool of simulation. The realisation of this project consists on : 1) programming with C++ and executing the two benchmarks P MV and PMM on each station; 2) Interpreting this result in order to show the best architecture of the cluster; 3) parallelism with TOP-C the two benchmarks; 4) Executing the two Top-C versions on the cluster; 5) Generalizing this results; 6)parallelism et executing the parallel version of GEANT4. (Author). 14 refs

A SPECT reconstruction method for extending parallel to non-parallel geometries

International Nuclear Information System (INIS)

Wen Junhai; Liang Zhengrong

2010-01-01

Due to its simplicity, parallel-beam geometry is usually assumed for the development of image reconstruction algorithms. The established reconstruction methodologies are then extended to fan-beam, cone-beam and other non-parallel geometries for practical application. This situation occurs for quantitative SPECT (single photon emission computed tomography) imaging in inverting the attenuated Radon transform. Novikov reported an explicit parallel-beam formula for the inversion of the attenuated Radon transform in 2000. Thereafter, a formula for fan-beam geometry was reported by Bukhgeim and Kazantsev (2002 Preprint N. 99 Sobolev Institute of Mathematics). At the same time, we presented a formula for varying focal-length fan-beam geometry. Sometimes, the reconstruction formula is so implicit that we cannot obtain the explicit reconstruction formula in the non-parallel geometries. In this work, we propose a unified reconstruction framework for extending parallel-beam geometry to any non-parallel geometry using ray-driven techniques. Studies by computer simulations demonstrated the accuracy of the presented unified reconstruction framework for extending parallel-beam to non-parallel geometries in inverting the attenuated Radon transform.

Electromagnetic Physics Models for Parallel Computing Architectures

International Nuclear Information System (INIS)

Amadio, G; Bianchini, C; Iope, R; Ananya, A; Apostolakis, J; Aurora, A; Bandieramonte, M; Brun, R; Carminati, F; Gheata, A; Gheata, M; Goulas, I; Nikitina, T; Bhattacharyya, A; Mohanty, A; Canal, P; Elvira, D; Jun, S Y; Lima, G; Duhem, L

2016-01-01

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. GeantV, a next generation detector simulation, has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth and type of parallelization needed to achieve optimal performance. In this paper we describe implementation of electromagnetic physics models developed for parallel computing architectures as a part of the GeantV project. Results of preliminary performance evaluation and physics validation are presented as well. (paper)

Parallel Atomistic Simulations

Energy Technology Data Exchange (ETDEWEB)

HEFFELFINGER,GRANT S.

2000-01-18

Algorithms developed to enable the use of atomistic molecular simulation methods with parallel computers are reviewed. Methods appropriate for bonded as well as non-bonded (and charged) interactions are included. While strategies for obtaining parallel molecular simulations have been developed for the full variety of atomistic simulation methods, molecular dynamics and Monte Carlo have received the most attention. Three main types of parallel molecular dynamics simulations have been developed, the replicated data decomposition, the spatial decomposition, and the force decomposition. For Monte Carlo simulations, parallel algorithms have been developed which can be divided into two categories, those which require a modified Markov chain and those which do not. Parallel algorithms developed for other simulation methods such as Gibbs ensemble Monte Carlo, grand canonical molecular dynamics, and Monte Carlo methods for protein structure determination are also reviewed and issues such as how to measure parallel efficiency, especially in the case of parallel Monte Carlo algorithms with modified Markov chains are discussed.

Parallel Robot for Lower Limb Rehabilitation Exercises

Directory of Open Access Journals (Sweden)

Alireza Rastegarpanah

2016-01-01

Full Text Available The aim of this study is to investigate the capability of a 6-DoF parallel robot to perform various rehabilitation exercises. The foot trajectories of twenty healthy participants have been measured by a Vicon system during the performing of four different exercises. Based on the kinematics and dynamics of a parallel robot, a MATLAB program was developed in order to calculate the length of the actuators, the actuators’ forces, workspace, and singularity locus of the robot during the performing of the exercises. The calculated length of the actuators and the actuators’ forces were used by motion analysis in SolidWorks in order to simulate different foot trajectories by the CAD model of the robot. A physical parallel robot prototype was built in order to simulate and execute the foot trajectories of the participants. Kinect camera was used to track the motion of the leg’s model placed on the robot. The results demonstrate the robot’s capability to perform a full range of various rehabilitation exercises.

Acceleration of Radiance for Lighting Simulation by Using Parallel Computing with OpenCL

Energy Technology Data Exchange (ETDEWEB)

Zuo, Wangda; McNeil, Andrew; Wetter, Michael; Lee, Eleanor

2011-09-06

We report on the acceleration of annual daylighting simulations for fenestration systems in the Radiance ray-tracing program. The algorithm was optimized to reduce both the redundant data input/output operations and the floating-point operations. To further accelerate the simulation speed, the calculation for matrix multiplications was implemented using parallel computing on a graphics processing unit. We used OpenCL, which is a cross-platform parallel programming language. Numerical experiments show that the combination of the above measures can speed up the annual daylighting simulations 101.7 times or 28.6 times when the sky vector has 146 or 2306 elements, respectively.

Hardware and software and machine-tool simulation with parallel structures mechanisms

Directory of Open Access Journals (Sweden)

Keba P.V.

2016-12-01

Full Text Available The usage spectrum of mechanisms with parallel structure is spreading all the time. The mechanisms of machine-tools and manipulators become more complicated and it is necessary to improve the program-controlled modules. Closed circuit mechanisms are mostly spread in robotic complexes, where manipulator performs complicated spatial movements by the given trajectory. The usage spectrum is very wide and the most popular are sorting, welding, assembling and others. However, the problem of designing the operating programs is still present even today. It is just because the developed post-processors are created for the equipment that we have for now. But new machine tool constructions appear every day and there is a necessity to control them. The problems associated with using of hardware and software of mechanisms with parallel structure in computer-aided simulation are considered. The program for inverse problem kinematics solving is designed. New method of designing the control programs is found. The kinematic analysis methods options and calculated data obtained by computer mathematics systems are shown with «Tools Glide» software taken as an example.

Speeding Up the String Comparison of the IDS Snort using Parallel Programming: A Systematic Literature Review on the Parallelized Aho-Corasick Algorithm

Directory of Open Access Journals (Sweden)

SILVA JUNIOR,J. B.

2016-12-01

Full Text Available The Intrusion Detection System (IDS needs to compare the contents of all packets arriving at the network interface with a set of signatures for indicating possible attacks, a task that consumes much CPU processing time. In order to alleviate this problem, some researchers have tried to parallelize the IDS's comparison engine, transferring execution from the CPU to GPU. This paper identifies and maps the parallelization features of the Aho-Corasick algorithm, which is used in Snort to compare patterns, in order to show this algorithm's implementation and execution issues, as well as optimization techniques for the Aho-Corasick machine. We have found 147 papers from important computer science publications databases, and have mapped them. We selected 22 and analyzed them in order to find our results. Our analysis of the papers showed, among other results, that parallelization of the AC algorithm is a new task and the authors have focused on the State Transition Table as the most common way to implement the algorithm on the GPU. Furthermore, we found that some techniques speed up the algorithm and reduce the required machine storage space are highly used, such as the algorithm running on the fastest memories and mechanisms for reducing the number of nodes and bit maping.

digital control of external devices through the parallel port

African Journals Online (AJOL)

2012-11-03

Nov 3, 2012 ... PARALLEL PORT OF A COMPUTER USING VISUAL BASIC. P.E. Orukpea, A. Adesemowob a. Department of Electrical/Electronic Engineering, University of Benin, Nigeria. .... These are software (written program) used for con- trolling the ..... Computer Aided Design and Manufacturing. Prentice. Hall, First ...

Parallel integer sorting with medium and fine-scale parallelism

Science.gov (United States)

Dagum, Leonardo

1993-01-01

Two new parallel integer sorting algorithms, queue-sort and barrel-sort, are presented and analyzed in detail. These algorithms do not have optimal parallel complexity, yet they show very good performance in practice. Queue-sort designed for fine-scale parallel architectures which allow the queueing of multiple messages to the same destination. Barrel-sort is designed for medium-scale parallel architectures with a high message passing overhead. The performance results from the implementation of queue-sort on a Connection Machine CM-2 and barrel-sort on a 128 processor iPSC/860 are given. The two implementations are found to be comparable in performance but not as good as a fully vectorized bucket sort on the Cray YMP.

10th International Workshop on Parallel Tools for High Performance Computing

CERN Document Server

Gracia, José; Hilbrich, Tobias; Knüpfer, Andreas; Resch, Michael; Nagel, Wolfgang

2017-01-01

This book presents the proceedings of the 10th International Parallel Tools Workshop, held October 4-5, 2016 in Stuttgart, Germany – a forum to discuss the latest advances in parallel tools. High-performance computing plays an increasingly important role for numerical simulation and modelling in academic and industrial research. At the same time, using large-scale parallel systems efficiently is becoming more difficult. A number of tools addressing parallel program development and analysis have emerged from the high-performance computing community over the last decade, and what may have started as collection of small helper script has now matured to production-grade frameworks. Powerful user interfaces and an extensive body of documentation allow easy usage by non-specialists.

Parallel computing works!

CERN Document Server

Fox, Geoffrey C; Messina, Guiseppe C

2014-01-01

A clear illustration of how parallel computers can be successfully appliedto large-scale scientific computations. This book demonstrates how avariety of applications in physics, biology, mathematics and other scienceswere implemented on real parallel computers to produce new scientificresults. It investigates issues of fine-grained parallelism relevant forfuture supercomputers with particular emphasis on hypercube architecture. The authors describe how they used an experimental approach to configuredifferent massively parallel machines, design and implement basic systemsoftware, and develop

System-Enforced Deterministic Streaming for Efficient Pipeline Parallelism

Institute of Scientific and Technical Information of China (English)

张昱; 李兆鹏; 曹慧芳

2015-01-01

Pipeline parallelism is a popular parallel programming pattern for emerging applications. However, program-ming pipelines directly on conventional multithreaded shared memory is difficult and error-prone. We present DStream, a C library that provides high-level abstractions of deterministic threads and streams for simply representing pipeline stage work-ers and their communications. The deterministic stream is established atop our proposed single-producer/multi-consumer (SPMC) virtual memory, which integrates synchronization with the virtual memory model to enforce determinism on shared memory accesses. We investigate various strategies on how to efficiently implement DStream atop the SPMC memory, so that an infinite sequence of data items can be asynchronously published (fixed) and asynchronously consumed in order among adjacent stage workers. We have successfully transformed two representative pipeline applications – ferret and dedup using DStream, and conclude conversion rules. An empirical evaluation shows that the converted ferret performed on par with its Pthreads and TBB counterparts in term of running time, while the converted dedup is close to 2.56X, 7.05X faster than the Pthreads counterpart and 1.06X, 3.9X faster than the TBB counterpart on 16 and 32 CPUs, respectively.

Stochastic Optimal Control of Parallel Hybrid Electric Vehicles

Directory of Open Access Journals (Sweden)

Feiyan Qin

2017-02-01

Full Text Available Energy management strategies (EMSs in hybrid electric vehicles (HEVs are highly related to the fuel economy and emission performances. However, EMS constitutes a challenging problem due to the complex structure of a HEV and the unknown or partially known driving cycles. To meet this problem, this paper adopts a stochastic dynamic programming (SDP method for the EMS of a specially designed vehicle, a pre-transmission single-shaft torque-coupling parallel HEV. In this parallel HEV, the auto clutch output is connected to the transmission input through an electric motor, which benefits an efficient motor assist operation. In this EMS, demanded torque of driver is modeled as a one-state Markov process to represent the uncertainty of future driving situations. The obtained EMS has been evaluated with ADVISOR2002 over two standard government drive cycles and a self-defined one, and compared with a dynamic programming (DP one and a rule-based one. Simulation results have shown the real-time performance of the proposed approach, and potential vehicle performance improvement relative to the rule-based one.

A PC parallel port button box provides millisecond response time accuracy under Linux.

Science.gov (United States)

Stewart, Neil

2006-02-01

For psychologists, it is sometimes necessary to measure people's reaction times to the nearest millisecond. This article describes how to use the PC parallel port to receive signals from a button box to achieve millisecond response time accuracy. The workings of the parallel port, the corresponding port addresses, and a simple Linux program for controlling the port are described. A test of the speed and reliability of button box signal detection is reported. If the reader is moderately familiar with Linux, this article should provide sufficient instruction for him or her to build and test his or her own parallel port button box. This article also describes how the parallel port could be used to control an external apparatus.

Array abstractions for GPU programming

DEFF Research Database (Denmark)

Dybdal, Martin

The shift towards massively parallel hardware platforms for highperformance computing tasks has introduced a need for improved programming models that facilitate ease of reasoning for both users and compiler optimization. A promising direction is the field of functional data-parallel programming......, for which functional invariants can be utilized by optimizing compilers to perform large program transformations automatically. However, the previous work in this area allow users only limited ability to reason about the performance of algorithms. For this reason, such languages have yet to see wide...... industrial adoption. We present two programming languages that attempt at both supporting industrial applications and providing reasoning tools for hierarchical data-parallel architectures, such as GPUs. First, we present TAIL, an array based intermediate language and compiler framework for compiling a large...

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

Energy Technology Data Exchange (ETDEWEB)

Amadio, G.; et al.

2017-11-22

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physics models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.

Parallelization of applications for networks with homogeneous and heterogeneous processors

International Nuclear Information System (INIS)

Colombet, L.

1994-01-01

The aim of this thesis is to study and develop efficient methods for parallelization of scientific applications on parallel computers with distributed memory. The first part presents two libraries of PVM (Parallel Virtual Machine) and MPI (Message Passing Interface) communication tools. They allow implementation of programs on most parallel machines, but also on heterogeneous computer networks. This chapter illustrates the problems faced when trying to evaluate performances of networks with heterogeneous processors. To evaluate such performances, the concepts of speed-up and efficiency have been modified and adapted to account for heterogeneity. The second part deals with a study of parallel application libraries such as ScaLAPACK and with the development of communication masking techniques. The general concept is based on communication anticipation, in particular by pipelining message sending operations. Experimental results on Cray T3D and IBM SP1 machines validates the theoretical studies performed on basic algorithms of the libraries discussed above. Two examples of scientific applications are given: the first is a model of young stars for astrophysics and the other is a model of photon trajectories in the Compton effect. (J.S.). 83 refs., 65 figs., 24 tabs

Parallelization of a Monte Carlo particle transport simulation code

Science.gov (United States)

Hadjidoukas, P.; Bousis, C.; Emfietzoglou, D.

2010-05-01

We have developed a high performance version of the Monte Carlo particle transport simulation code MC4. The original application code, developed in Visual Basic for Applications (VBA) for Microsoft Excel, was first rewritten in the C programming language for improving code portability. Several pseudo-random number generators have been also integrated and studied. The new MC4 version was then parallelized for shared and distributed-memory multiprocessor systems using the Message Passing Interface. Two parallel pseudo-random number generator libraries (SPRNG and DCMT) have been seamlessly integrated. The performance speedup of parallel MC4 has been studied on a variety of parallel computing architectures including an Intel Xeon server with 4 dual-core processors, a Sun cluster consisting of 16 nodes of 2 dual-core AMD Opteron processors and a 200 dual-processor HP cluster. For large problem size, which is limited only by the physical memory of the multiprocessor server, the speedup results are almost linear on all systems. We have validated the parallel implementation against the serial VBA and C implementations using the same random number generator. Our experimental results on the transport and energy loss of electrons in a water medium show that the serial and parallel codes are equivalent in accuracy. The present improvements allow for studying of higher particle energies with the use of more accurate physical models, and improve statistics as more particles tracks can be simulated in low response time.

Compiling the functional data-parallel language SaC for Microgrids of Self-Adaptive Virtual Processors

NARCIS (Netherlands)

Grelck, C.; Herhut, S.; Jesshope, C.; Joslin, C.; Lankamp, M.; Scholz, S.-B.; Shafarenko, A.

2009-01-01

We present preliminary results from compiling the high-level, functional and data-parallel programming language SaC into a novel multi-core design: Microgrids of Self-Adaptive Virtual Processors (SVPs). The side-effect free nature of SaC in conjunction with its data-parallel foundation make it an

A parallel row-based algorithm with error control for standard-cell replacement on a hypercube multiprocessor

Science.gov (United States)

Sargent, Jeff Scott

1988-01-01

A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.

Endpoint-based parallel data processing in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.

2014-08-12

Endpoint-based parallel data processing in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI composed of data communications endpoints, each endpoint including a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI, including establishing a data communications geometry, the geometry specifying, for tasks representing processes of execution of the parallel application, a set of endpoints that are used in collective operations of the PAMI including a plurality of endpoints for one of the tasks; receiving in endpoints of the geometry an instruction for a collective operation; and executing the instruction for a collective operation through the endpoints in dependence upon the geometry, including dividing data communications operations among the plurality of endpoints for one of the tasks.

Parallel computing in cluster of GPU applied to a problem of nuclear engineering

International Nuclear Information System (INIS)

Moraes, Sergio Ricardo S.; Heimlich, Adino; Resende, Pedro

2013-01-01

Cluster computing has been widely used as a low cost alternative for parallel processing in scientific applications. With the use of Message-Passing Interface (MPI) protocol development became even more accessible and widespread in the scientific community. A more recent trend is the use of Graphic Processing Unit (GPU), which is a powerful co-processor able to perform hundreds of instructions in parallel, reaching a capacity of hundreds of times the processing of a CPU. However, a standard PC does not allow, in general, more than two GPUs. Hence, it is proposed in this work development and evaluation of a hybrid low cost parallel approach to the solution to a nuclear engineering typical problem. The idea is to use clusters parallelism technology (MPI) together with GPU programming techniques (CUDA - Compute Unified Device Architecture) to simulate neutron transport through a slab using Monte Carlo method. By using a cluster comprised by four quad-core computers with 2 GPU each, it has been developed programs using MPI and CUDA technologies. Experiments, applying different configurations, from 1 to 8 GPUs has been performed and results were compared with the sequential (non-parallel) version. A speed up of about 2.000 times has been observed when comparing the 8-GPU with the sequential version. Results here presented are discussed and analyzed with the objective of outlining gains and possible limitations of the proposed approach. (author)

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

Science.gov (United States)

Sylwestrzak, Marcin; Szlag, Daniel; Marchand, Paul J.; Kumar, Ashwin S.; Lasser, Theo

2017-08-01

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for many applications based on SOCM. In view of this difficulty, we implemented and adapted quantitative total flow estimation algorithms on graphics processing units (GPU) and achieved a 150 fold reduction in processing time when compared to a former CPU implementation. As SOCM constitutes the microscopy counterpart to spectral optical coherence tomography (SOCT), the developed processing procedure can be applied to both imaging modalities. We present the developed DLL library integrated in MATLAB (with an example) and have included the source code for adaptations and future improvements. Catalogue identifier: AFBT_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBT_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPLv3 No. of lines in distributed program, including test data, etc.: 913552 No. of bytes in distributed program, including test data, etc.: 270876249 Distribution format: tar.gz Programming language: CUDA/C, MATLAB. Computer: Intel x64 CPU, GPU supporting CUDA technology. Operating system: 64-bit Windows 7 Professional. Has the code been vectorized or parallelized?: Yes, CPU code has been vectorized in MATLAB, CUDA code has been parallelized. RAM: Dependent on users parameters, typically between several gigabytes and several tens of gigabytes Classification: 6.5, 18. Nature of problem: Speed up of data processing in optical coherence microscopy Solution method: Utilization of GPU for massively parallel data processing Additional comments: Compiled DLL library with source code and documentation, example of utilization (MATLAB script with raw data) Running time: 1,8 s for one B-scan (150 × faster in comparison to the CPU

Getting To Exascale: Applying Novel Parallel Programming Models To Lab Applications For The Next Generation Of Supercomputers

Energy Technology Data Exchange (ETDEWEB)

Dube, Evi [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Shereda, Charles [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Nau, Lee [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Harris, Lance [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2010-09-27

As supercomputing moves toward exascale, node architectures will change significantly. CPU core counts on nodes will increase by an order of magnitude or more. Heterogeneous architectures will become more commonplace, with GPUs or FPGAs providing additional computational power. Novel programming models may make better use of on-node parallelism in these new architectures than do current models. In this paper we examine several of these novel models – UPC, CUDA, and OpenCL –to determine their suitability to LLNL scientific application codes. Our study consisted of several phases: We conducted interviews with code teams and selected two codes to port; We learned how to program in the new models and ported the codes; We debugged and tuned the ported applications; We measured results, and documented our findings. We conclude that UPC is a challenge for porting code, Berkeley UPC is not very robust, and UPC is not suitable as a general alternative to OpenMP for a number of reasons. CUDA is well supported and robust but is a proprietary NVIDIA standard, while OpenCL is an open standard. Both are well suited to a specific set of application problems that can be run on GPUs, but some problems are not suited to GPUs. Further study of the landscape of novel models is recommended.

New Parallel Algorithms for Landscape Evolution Model

Science.gov (United States)

Jin, Y.; Zhang, H.; Shi, Y.

2017-12-01

Most landscape evolution models (LEM) developed in the last two decades solve the diffusion equation to simulate the transportation of surface sediments. This numerical approach is difficult to parallelize due to the computation of drainage area for each node, which needs huge amount of communication if run in parallel. In order to overcome this difficulty, we developed two parallel algorithms for LEM with a stream net. One algorithm handles the partition of grid with traditional methods and applies an efficient global reduction algorithm to do the computation of drainage areas and transport rates for the stream net; the other algorithm is based on a new partition algorithm, which partitions the nodes in catchments between processes first, and then partitions the cells according to the partition of nodes. Both methods focus on decreasing communication between processes and take the advantage of massive computing techniques, and numerical experiments show that they are both adequate to handle large scale problems with millions of cells. We implemented the two algorithms in our program based on the widely used finite element library deal.II, so that it can be easily coupled with ASPECT.

Shared memory parallelism for 3D cartesian discrete ordinates solver

International Nuclear Information System (INIS)

Moustafa, S.; Dutka-Malen, I.; Plagne, L.; Poncot, A.; Ramet, P.

2013-01-01

This paper describes the design and the performance of DOMINO, a 3D Cartesian SN solver that implements two nested levels of parallelism (multi-core + SIMD - Single Instruction on Multiple Data) on shared memory computation nodes. DOMINO is written in C++, a multi-paradigm programming language that enables the use of powerful and generic parallel programming tools such as Intel TBB and Eigen. These two libraries allow us to combine multi-thread parallelism with vector operations in an efficient and yet portable way. As a result, DOMINO can exploit the full power of modern multi-core processors and is able to tackle very large simulations, that usually require large HPC clusters, using a single computing node. For example, DOMINO solves a 3D full core PWR eigenvalue problem involving 26 energy groups, 288 angular directions (S16), 46*10 6 spatial cells and 1*10 12 DoFs within 11 hours on a single 32-core SMP node. This represents a sustained performance of 235 GFlops and 40.74% of the SMP node peak performance for the DOMINO sweep implementation. The very high Flops/Watt ratio of DOMINO makes it a very interesting building block for a future many-nodes nuclear simulation tool. (authors)

Mesh Partitioning Algorithm Based on Parallel Finite Element Analysis and Its Actualization

Directory of Open Access Journals (Sweden)

Lei Zhang

2013-01-01

Full Text Available In parallel computing based on finite element analysis, domain decomposition is a key technique for its preprocessing. Generally, a domain decomposition of a mesh can be realized through partitioning of a graph which is converted from a finite element mesh. This paper discusses the method for graph partitioning and the way to actualize mesh partitioning. Relevant softwares are introduced, and the data structure and key functions of Metis and ParMetis are introduced. The writing, compiling, and testing of the mesh partitioning interface program based on these key functions are performed. The results indicate some objective law and characteristics to guide the users who use the graph partitioning algorithm and software to write PFEM program, and ideal partitioning effects can be achieved by actualizing mesh partitioning through the program. The interface program can also be used directly by the engineering researchers as a module of the PFEM software. So that it can reduce the application of the threshold of graph partitioning algorithm, improve the calculation efficiency, and promote the application of graph theory and parallel computing.

Systematic approach for deriving feasible mappings of parallel algorithms to parallel computing platforms

NARCIS (Netherlands)

Arkin, Ethem; Tekinerdogan, Bedir; Imre, Kayhan M.

2017-01-01

The need for high-performance computing together with the increasing trend from single processor to parallel computer architectures has leveraged the adoption of parallel computing. To benefit from parallel computing power, usually parallel algorithms are defined that can be mapped and executed

Parallelization of MRCI based on hole-particle symmetry.

Science.gov (United States)

Suo, Bing; Zhai, Gaohong; Wang, Yubin; Wen, Zhenyi; Hu, Xiangqian; Li, Lemin

2005-01-15

The parallel implementation of multireference configuration interaction program based on the hole-particle symmetry is described. The platform to implement the parallelization is an Intel-Architectural cluster consisting of 12 nodes, each of which is equipped with two 2.4-G XEON processors, 3-GB memory, and 36-GB disk, and are connected by a Gigabit Ethernet Switch. The dependence of speedup on molecular symmetries and task granularities is discussed. Test calculations show that the scaling with the number of nodes is about 1.9 (for C1 and Cs), 1.65 (for C2v), and 1.55 (for D2h) when the number of nodes is doubled. The largest calculation performed on this cluster involves 5.6 x 10(8) CSFs.

Tensor contraction engine: Abstraction and automated parallel implementation of configuration-interaction, coupled-cluster, and many-body perturbation theories

International Nuclear Information System (INIS)

Hirata, So

2003-01-01

We develop a symbolic manipulation program and program generator (Tensor Contraction Engine or TCE) that automatically derives the working equations of a well-defined model of second-quantized many-electron theories and synthesizes efficient parallel computer programs on the basis of these equations. Provided an ansatz of a many-electron theory model, TCE performs valid contractions of creation and annihilation operators according to Wick's theorem, consolidates identical terms, and reduces the expressions into the form of multiple tensor contractions acted by permutation operators. Subsequently, it determines the binary contraction order for each multiple tensor contraction with the minimal operation and memory cost, factorizes common binary contractions (defines intermediate tensors), and identifies reusable intermediates. The resulting ordered list of binary tensor contractions, additions, and index permutations is translated into an optimized program that is combined with the NWChem and UTChem computational chemistry software packages. The programs synthesized by TCE take advantage of spin symmetry, Abelian point-group symmetry, and index permutation symmetry at every stage of calculations to minimize the number of arithmetic operations and storage requirement, adjust the peak local memory usage by index range tiling, and support parallel I/O interfaces and dynamic load balancing for parallel executions. We demonstrate the utility of TCE through automatic derivation and implementation of parallel programs for various models of configuration-interaction theory (CISD, CISDT, CISDTQ), many-body perturbation theory[MBPT(2), MBPT(3), MBPT(4)], and coupled-cluster theory (LCCD, CCD, LCCSD, CCSD, QCISD, CCSDT, and CCSDTQ)

Parallel algorithms

CERN Document Server

Casanova, Henri; Robert, Yves

2008-01-01

""…The authors of the present book, who have extensive credentials in both research and instruction in the area of parallelism, present a sound, principled treatment of parallel algorithms. … This book is very well written and extremely well designed from an instructional point of view. … The authors have created an instructive and fascinating text. The book will serve researchers as well as instructors who need a solid, readable text for a course on parallelism in computing. Indeed, for anyone who wants an understandable text from which to acquire a current, rigorous, and broad vi

Methods and models for the construction of weakly parallel tests

NARCIS (Netherlands)

Adema, J.J.; Adema, Jos J.

1992-01-01

Several methods are proposed for the construction of weakly parallel tests [i.e., tests with the same test information function (TIF)]. A mathematical programming model that constructs tests containing a prespecified TIF and a heuristic that assigns items to tests with information functions that are

Methods and models for the construction of weakly parallel tests

NARCIS (Netherlands)

Adema, J.J.; Adema, Jos J.

1990-01-01

Methods are proposed for the construction of weakly parallel tests, that is, tests with the same test information function. A mathematical programing model for constructing tests with a prespecified test information function and a heuristic for assigning items to tests such that their information

Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation

OpenAIRE

Vanderbauwhede, Wim; Davidson, Gavin

2017-01-01

Massively parallel accelerators such as GPGPUs, manycores and FPGAs represent a powerful and affordable tool for scientists who look to speed up simulations of complex systems. However, porting code to such devices requires a detailed understanding of heterogeneous programming tools and effective strategies for parallelization. In this paper we present a source to source compilation approach with whole-program analysis to automatically transform single-threaded FORTRAN 77 legacy code into Ope...

Flexbar 3.0 - SIMD and multicore parallelization.

Science.gov (United States)

Roehr, Johannes T; Dieterich, Christoph; Reinert, Knut

2017-09-15

High-throughput sequencing machines can process many samples in a single run. For Illumina systems, sequencing reads are barcoded with an additional DNA tag that is contained in the respective sequencing adapters. The recognition of barcode and adapter sequences is hence commonly needed for the analysis of next-generation sequencing data. Flexbar performs demultiplexing based on barcodes and adapter trimming for such data. The massive amounts of data generated on modern sequencing machines demand that this preprocessing is done as efficiently as possible. We present Flexbar 3.0, the successor of the popular program Flexbar. It employs now twofold parallelism: multi-threading and additionally SIMD vectorization. Both types of parallelism are used to speed-up the computation of pair-wise sequence alignments, which are used for the detection of barcodes and adapters. Furthermore, new features were included to cover a wide range of applications. We evaluated the performance of Flexbar based on a simulated sequencing dataset. Our program outcompetes other tools in terms of speed and is among the best tools in the presented quality benchmark. https://github.com/seqan/flexbar. johannes.roehr@fu-berlin.de or knut.reinert@fu-berlin.de. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Programming Models in HPC

Energy Technology Data Exchange (ETDEWEB)

Shipman, Galen M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-13

These are the slides for a presentation on programming models in HPC, at the Los Alamos National Laboratory's Parallel Computing Summer School. The following topics are covered: Flynn's Taxonomy of computer architectures; single instruction single data; single instruction multiple data; multiple instruction multiple data; address space organization; definition of Trinity (Intel Xeon-Phi is a MIMD architecture); single program multiple data; multiple program multiple data; ExMatEx workflow overview; definition of a programming model, programming languages, runtime systems; programming model and environments; MPI (Message Passing Interface); OpenMP; Kokkos (Performance Portable Thread-Parallel Programming Model); Kokkos abstractions, patterns, policies, and spaces; RAJA, a systematic approach to node-level portability and tuning; overview of the Legion Programming Model; mapping tasks and data to hardware resources; interoperability: supporting task-level models; Legion S3D execution and performance details; workflow, integration of external resources into the programming model.

Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis

Science.gov (United States)

Brouwer, Randall Jay

1991-01-01

The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.

Proceedings of the workshop on Compilation of (Symbolic) Languages for Parallel Computers

Energy Technology Data Exchange (ETDEWEB)

Foster, I.; Tick, E. (comp.)

1991-11-01

This report comprises the abstracts and papers for the talks presented at the Workshop on Compilation of (Symbolic) Languages for Parallel Computers, held October 31--November 1, 1991, in San Diego. These unreferred contributions were provided by the participants for the purpose of this workshop; many of them will be published elsewhere in peer-reviewed conferences and publications. Our goal is planning this workshop was to bring together researchers from different disciplines with common problems in compilation. In particular, we wished to encourage interaction between researchers working in compilation of symbolic languages and those working on compilation of conventional, imperative languages. The fundamental problems facing researchers interested in compilation of logic, functional, and procedural programming languages for parallel computers are essentially the same. However, differences in the basic programming paradigms have led to different communities emphasizing different species of the parallel compilation problem. For example, parallel logic and functional languages provide dataflow-like formalisms in which control dependencies are unimportant. Hence, a major focus of research in compilation has been on techniques that try to infer when sequential control flow can safely be imposed. Granularity analysis for scheduling is a related problem. The single- assignment property leads to a need for analysis of memory use in order to detect opportunities for reuse. Much of the work in each of these areas relies on the use of abstract interpretation techniques.

A multitransputer parallel processing system (MTPPS)

International Nuclear Information System (INIS)

Jethra, A.K.; Pande, S.S.; Borkar, S.P.; Khare, A.N.; Ghodgaonkar, M.D.; Bairi, B.R.

1993-01-01

This report describes the design and implementation of a 16 node Multi Transputer Parallel Processing System(MTPPS) which is a platform for parallel program development. It is a MIMD machine based on message passing paradigm. The basic compute engine is an Inmos Transputer Ims T800-20. Transputer with local memory constitutes the processing element (NODE) of this MIMD architecture. Multiple NODES can be connected to each other in an identifiable network topology through the high speed serial links of the transputer. A Network Configuration Unit (NCU) incorporates the necessary hardware to provide software controlled network configuration. System is modularly expandable and more NODES can be added to the system to achieve the required processing power. The system is backend to the IBM-PC which has been integrated into the system to provide user I/O interface. PC resources are available to the programmer. Interface hardware between the PC and the network of transputers is INMOS compatible. Therefore, all the commercially available development software compatible to INMOS products can run on this system. While giving the details of design and implementation, this report briefly summarises MIMD Architectures, Transputer Architecture and Parallel Processing Software Development issues. LINPACK performance evaluation of the system and solutions of neutron physics and plasma physics problem have been discussed along with results. (author). 12 refs., 22 figs., 3 tabs., 3 appendixes

Parallelization of a Quantum-Classic Hybrid Model For Nanoscale Semiconductor Devices

Directory of Open Access Journals (Sweden)

Oscar Salas

2011-07-01

Full Text Available The expensive reengineering of the sequential software and the difficult parallel programming are two of the many technical and economic obstacles to the wide use of HPC. We investigate the chance to improve in a rapid way the performance of a numerical serial code for the simulation of the transport of a charged carriers in a Double-Gate MOSFET. We introduce the Drift-Diffusion-Schrödinger-Poisson (DDSP model and we study a rapid parallelization strategy of the numerical procedure on shared memory architectures.

On the Parallel Elliptic Single/Multigrid Solutions about Aligned and Nonaligned Bodies Using the Virtual Machine for Multiprocessors

Directory of Open Access Journals (Sweden)

A. Averbuch

1994-01-01

Full Text Available Parallel elliptic single/multigrid solutions around an aligned and nonaligned body are presented and implemented on two multi-user and single-user shared memory multiprocessors (Sequent Symmetry and MOS and on a distributed memory multiprocessor (a Transputer network. Our parallel implementation uses the Virtual Machine for Muli-Processors (VMMP, a software package that provides a coherent set of services for explicitly parallel application programs running on diverse multiple instruction multiple data (MIMD multiprocessors, both shared memory and message passing. VMMP is intended to simplify parallel program writing and to promote portable and efficient programming. Furthermore, it ensures high portability of application programs by implementing the same services on all target multiprocessors. The performance of our algorithm is investigated in detail. It is seen to fit well the above architectures when the number of processors is less than the maximal number of grid points along the axes. In general, the efficiency in the nonaligned case is higher than in the aligned case. Alignment overhead is observed to be up to 200% in the shared-memory case and up to 65% in the message-passing case. We have demonstrated that when using VMMP, the portability of the algorithms is straightforward and efficient.

Parallel algorithms for mapping pipelined and parallel computations

Science.gov (United States)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

On the Optimization and Parallelizing Little Algorithm for Solving the Traveling Salesman Problem

Directory of Open Access Journals (Sweden)

V. V. Vasilchikov

2016-01-01

Full Text Available The paper describes some ways to accelerate solving the NP-complete Traveling Salesman Problem. The classic Little algorithm belonging to the category of ”branch and bound methods” can solve it both for directed and undirected graphs. However, for undirected graphs its operation can be accelerated by eliminating the consideration of branches examined earlier. The paper proposes changes to be made in the key operations of the algorithm to speed up its execution. It also describes the results of an experiment that demonstrated a significant acceleration of solving the problem by using an advanced algorithm. Another way to speed up the work is to parallelize the algorithm. For problems of this kind it is difficult to break the task into a sufficient number of subtasks having comparable complexity. Their parallelism arises dynamically during the execution. For such problems, it seems reasonable to use parallel-recursive algorithms. In our case the use of the library RPM ParLib developed by the author was a good choice. It allows us to develop effective applications for parallel computing on a local network using any .NET-compatible programming language. We used C# to develop the programs. Parallel applications were developed as for basic and modified algorithms, the comparing of their speed was made. Experiments were performed for the graphs with the number of vertexes up to 45 and with the number of network computers up to 16. We also investigated the acceleration that can be achieved by parallelizing the basic Little algorithm for directed graphs. The results of these experiments are also presented in the paper. 

Designing a parallel evolutionary algorithm for inferring gene networks on the cloud computing environment.

Science.gov (United States)

Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che

2014-01-16

To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high

OpenCL programming by example

CERN Document Server

Banger, Ravishekhar

2013-01-01

This book follows an example-driven, simplified, and practical approach to using OpenCL for general purpose GPU programming.If you are a beginner in parallel programming and would like to quickly accelerate your algorithms using OpenCL, this book is perfect for you! You will find the diverse topics and case studies in this book interesting and informative. You will only require a good knowledge of C programming for this book, and an understanding of parallel implementations will be useful, but not necessary.

Parallel-aware, dedicated job co-scheduling within/across symmetric multiprocessing nodes

Science.gov (United States)

Jones, Terry R.; Watson, Pythagoras C.; Tuel, William; Brenner, Larry; ,Caffrey, Patrick; Fier, Jeffrey

2010-10-05

In a parallel computing environment comprising a network of SMP nodes each having at least one processor, a parallel-aware co-scheduling method and system for improving the performance and scalability of a dedicated parallel job having synchronizing collective operations. The method and system uses a global co-scheduler and an operating system kernel dispatcher adapted to coordinate interfering system and daemon activities on a node and across nodes to promote intra-node and inter-node overlap of said interfering system and daemon activities as well as intra-node and inter-node overlap of said synchronizing collective operations. In this manner, the impact of random short-lived interruptions, such as timer-decrement processing and periodic daemon activity, on synchronizing collective operations is minimized on large processor-count SPMD bulk-synchronous programming styles.

Parallel channel effects under BWR LOCA conditions

International Nuclear Information System (INIS)

Suzuki, H.; Hatamiya, S.; Murase, M.

1988-01-01

Due to parallel channel effects, different flow patterns such as liquid down-flow and gas up-flow appear simultaneously in fuel bundles of a BWR core during postulated LOCAs. Applying the parallel channel effects to the fuel bundle, water drain tubes with a restricted bottom end have been developed in order to mitigate counter-current flow limiting and to increase the falling water flow rate at the upper tie plate. The upper tie plate with water drain tubes is an especially effective means of increasing the safety margin of a reactor with narrow gaps between fuel rods and high steam velocity at the upper tie plate. The characteristics of the water drain tubes have been experimentally investigated using a small-scaled steam-water system simulating a BWR core. Then, their effect on the fuel cladding temperature was evaluated using the LOCA analysis program SAFER. (orig.)

Program Correctness, Verification and Testing for Exascale (Corvette)

Energy Technology Data Exchange (ETDEWEB)

Sen, Koushik [Univ. of California, Berkeley, CA (United States); Iancu, Costin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Demmel, James W [UC Berkeley

2018-01-26

The goal of this project is to provide tools to assess the correctness of parallel programs written using hybrid parallelism. There is a dire lack of both theoretical and engineering know-how in the area of finding bugs in hybrid or large scale parallel programs, which our research aims to change. In the project we have demonstrated novel approaches in several areas: 1. Low overhead automated and precise detection of concurrency bugs at scale. 2. Using low overhead bug detection tools to guide speculative program transformations for performance. 3. Techniques to reduce the concurrency required to reproduce a bug using partial program restart/replay. 4. Techniques to provide reproducible execution of floating point programs. 5. Techniques for tuning the floating point precision used in codes.

Template based parallel checkpointing in a massively parallel computer system

Science.gov (United States)

Archer, Charles Jens [Rochester, MN; Inglett, Todd Alan [Rochester, MN

2009-01-13

A method and apparatus for a template based parallel checkpoint save for a massively parallel super computer system using a parallel variation of the rsync protocol, and network broadcast. In preferred embodiments, the checkpoint data for each node is compared to a template checkpoint file that resides in the storage and that was previously produced. Embodiments herein greatly decrease the amount of data that must be transmitted and stored for faster checkpointing and increased efficiency of the computer system. Embodiments are directed to a parallel computer system with nodes arranged in a cluster with a high speed interconnect that can perform broadcast communication. The checkpoint contains a set of actual small data blocks with their corresponding checksums from all nodes in the system. The data blocks may be compressed using conventional non-lossy data compression algorithms to further reduce the overall checkpoint size.

GTfold: Enabling parallel RNA secondary structure prediction on multi-core desktops

DEFF Research Database (Denmark)

Swenson, M Shel; Anderson, Joshua; Ash, Andrew

2012-01-01

achieved significant improvements in runtime, but their implementations were not portable from niche high-performance computers or easily accessible to most RNA researchers. With the increasing prevalence of multi-core desktop machines, a new parallel prediction program is needed to take full advantage...

DIALIGN P: Fast pair-wise and multiple sequence alignment using parallel processors

Directory of Open Access Journals (Sweden)

Kaufmann Michael

2004-09-01

Full Text Available Abstract Background Parallel computing is frequently used to speed up computationally expensive tasks in Bioinformatics. Results Herein, a parallel version of the multi-alignment program DIALIGN is introduced. We propose two ways of dividing the program into independent sub-routines that can be run on different processors: (a pair-wise sequence alignments that are used as a first step to multiple alignment account for most of the CPU time in DIALIGN. Since alignments of different sequence pairs are completely independent of each other, they can be distributed to multiple processors without any effect on the resulting output alignments. (b For alignments of large genomic sequences, we use a heuristics by splitting up sequences into sub-sequences based on a previously introduced anchored alignment procedure. For our test sequences, this combined approach reduces the program running time of DIALIGN by up to 97%. Conclusions By distributing sub-routines to multiple processors, the running time of DIALIGN can be crucially improved. With these improvements, it is possible to apply the program in large-scale genomics and proteomics projects that were previously beyond its scope.

Concurrent particle-in-cell plasma simulation on a multi-transputer parallel computer

International Nuclear Information System (INIS)

Khare, A.N.; Jethra, A.; Patel, Kartik

1992-01-01

This report describes the parallelization of a Particle-in-Cell (PIC) plasma simulation code on a multi-transputer parallel computer. The algorithm used in the parallelization of the PIC method is described. The decomposition schemes related to the distribution of the particles among the processors are discussed. The implementation of the algorithm on a transputer network connected as a torus is presented. The solutions of the problems related to global communication of data are presented in the form of a set of generalized communication functions. The performance of the program as a function of data size and the number of transputers show that the implementation is scalable and represents an effective way of achieving high performance at acceptable cost. (author). 11 refs., 4 figs., 2 tabs., appendices

Vectorization, parallelization and porting of nuclear codes (porting). Progress report fiscal 1998

International Nuclear Information System (INIS)

Nemoto, Toshiyuki; Kawai, Wataru; Ishizuki, Shigeru; Kawasaki, Nobuo; Kume, Etsuo; Adachi, Masaaki; Ogasawara, Shinobu

2000-03-01

Several computer codes in the nuclear field have been vectorized, parallelized and transported on the FUJITSU VPP500 system, the AP3000 system and the Paragon system at Center for Promotion of Computational Science and Engineering in Japan Atomic Energy Research Institute. We dealt with 12 codes in fiscal 1998. These results are reported in 3 parts, i.e., the vectorization and parallelization on vector processors part, the parallelization on scalar processors part and the porting part. In this report, we describe the porting. In this porting part, the porting of Monte Carlo N-Particle Transport code MCNP4B2 and Reactor Safety Analysis code RELAP5 on the AP3000 are described. In the vectorization and parallelization on vector processors part, the vectorization of General Tokamak Circuit Simulation Program code GTCSP, the vectorization and parallelization of Molecular Dynamics Ntv Simulation code MSP2, Eddy Current Analysis code EDDYCAL, Thermal Analysis Code for Test of Passive Cooling System by HENDEL T2 code THANPACST2 and MHD Equilibrium code SELENEJ on the VPP500 are described. In the parallelization on scalar processors part, the parallelization of Monte Carlo N-Particle Transport code MCNP4B2, Plasma Hydrodynamics code using Cubic Interpolated propagation Method PHCIP and Vectorized Monte Carlo code (continuous energy model/multi-group model) MVP/GMVP on the Paragon are described. (author)

Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

Directory of Open Access Journals (Sweden)

Huei Peng

2013-04-01

Full Text Available This paper compares two optimal energy management methods for parallel hybrid electric vehicles using an Automatic Manual Transmission (AMT. A control-oriented model of the powertrain and vehicle dynamics is built first. The energy management is formulated as a typical optimal control problem to trade off the fuel consumption and gear shifting frequency under admissible constraints. The Dynamic Programming (DP and Pontryagin’s Minimum Principle (PMP are applied to obtain the optimal solutions. Tuning with the appropriate co-states, the PMP solution is found to be very close to that from DP. The solution for the gear shifting in PMP has an algebraic expression associated with the vehicular velocity and can be implemented more efficiently in the control algorithm. The computation time of PMP is significantly less than DP.

Parallel Simulation of Loosely Timed SystemC/TLM Programs: Challenges Raised by an Industrial Case Study

Directory of Open Access Journals (Sweden)

Denis Becker

2016-05-01

Full Text Available Transaction level models of systems-on-chip in SystemC are commonly used in the industry to provide an early simulation environment. The SystemC standard imposes coroutine semantics for the scheduling of simulated processes, to ensure determinism and reproducibility of simulations. However, because of this, sequential implementations have, for a long time, been the only option available, and still now the reference implementation is sequential. With the increasing size and complexity of models, and the multiplication of computation cores on recent machines, the parallelization of SystemC simulations is a major research concern. There have been several proposals for SystemC parallelization, but most of them are limited to cycle-accurate models. In this paper we focus on loosely timed models, which are commonly used in the industry. We present an industrial context and show that, unfortunately, most of the existing approaches for SystemC parallelization can fundamentally not apply in this context. We support this claim with a set of measurements performed on a platform used in production at STMicroelectronics. This paper surveys existing techniques, presents a visualization and profiling tool and identifies unsolved challenges in the parallelization of SystemC models at transaction level.

Optimal energy management for a series-parallel hybrid electric bus

International Nuclear Information System (INIS)

Xiong Weiwei; Zhang Yong; Yin Chengliang

2009-01-01

This paper aims to present a new type of series-parallel hybrid electric bus and its energy management strategy. This hybrid bus is a post-transmission coupled system employing a novel transmission as the series-parallel configuration switcher. In this paper, the vehicle architecture, transmission scheme and numerical models are presented. The energy management system governs the mode switching between the series mode and the parallel mode as well as the instantaneous power distribution. In this work, two separated controllers using fuzzy logic called Mode Decision and Parallel-driving Energy Management are employed to fulfill these two tasks. The energy management strategy and the applications of fuzzy logic are described. The strategy is validated by a forward-facing simulation program based on the software Matlab/Simulink. The results show that the energy management strategy is effective to control the engine operating in a high-efficiency region as well as to sustain the battery charge state while satisfy the drive ability. The energy consumption is theoretically reduced by 30.3% to that of the conventional bus under transit bus driving cycle. In addition, works need future study are also presented.

Computational fluid dynamics on a massively parallel computer

Science.gov (United States)

Jespersen, Dennis C.; Levit, Creon

1989-01-01

A finite difference code was implemented for the compressible Navier-Stokes equations on the Connection Machine, a massively parallel computer. The code is based on the ARC2D/ARC3D program and uses the implicit factored algorithm of Beam and Warming. The codes uses odd-even elimination to solve linear systems. Timings and computation rates are given for the code, and a comparison is made with a Cray XMP.

Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications

Science.gov (United States)

OKeefe, Matthew (Editor); Kerr, Christopher L. (Editor)

1998-01-01

This report contains the abstracts and technical papers from the Second International Workshop on Software Engineering and Code Design in Parallel Meteorological and Oceanographic Applications, held June 15-18, 1998, in Scottsdale, Arizona. The purpose of the workshop is to bring together software developers in meteorology and oceanography to discuss software engineering and code design issues for parallel architectures, including Massively Parallel Processors (MPP's), Parallel Vector Processors (PVP's), Symmetric Multi-Processors (SMP's), Distributed Shared Memory (DSM) multi-processors, and clusters. Issues to be discussed include: (1) code architectures for current parallel models, including basic data structures, storage allocation, variable naming conventions, coding rules and styles, i/o and pre/post-processing of data; (2) designing modular code; (3) load balancing and domain decomposition; (4) techniques that exploit parallelism efficiently yet hide the machine-related details from the programmer; (5) tools for making the programmer more productive; and (6) the proliferation of programming models (F--, OpenMP, MPI, and HPF).

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

Science.gov (United States)

Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)

2000-01-01

We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.

Application of parallel computing to seismic damage process simulation of an arch dam

International Nuclear Information System (INIS)

Zhong Hong; Lin Gao; Li Jianbo

2010-01-01

The simulation of damage process of high arch dam subjected to strong earthquake shocks is significant to the evaluation of its performance and seismic safety, considering the catastrophic effect of dam failure. However, such numerical simulation requires rigorous computational capacity. Conventional serial computing falls short of that and parallel computing is a fairly promising solution to this problem. The parallel finite element code PDPAD was developed for the damage prediction of arch dams utilizing the damage model with inheterogeneity of concrete considered. Developed with programming language Fortran, the code uses a master/slave mode for programming, domain decomposition method for allocation of tasks, MPI (Message Passing Interface) for communication and solvers from AZTEC library for solution of large-scale equations. Speedup test showed that the performance of PDPAD was quite satisfactory. The code was employed to study the damage process of a being-built arch dam on a 4-node PC Cluster, with more than one million degrees of freedom considered. The obtained damage mode was quite similar to that of shaking table test, indicating that the proposed procedure and parallel code PDPAD has a good potential in simulating seismic damage mode of arch dams. With the rapidly growing need for massive computation emerged from engineering problems, parallel computing will find more and more applications in pertinent areas.

Distributed parallel computing in stochastic modeling of groundwater systems.

Science.gov (United States)

Dong, Yanhui; Li, Guomin; Xu, Haizhen

2013-03-01

Stochastic modeling is a rapidly evolving, popular approach to the study of the uncertainty and heterogeneity of groundwater systems. However, the use of Monte Carlo-type simulations to solve practical groundwater problems often encounters computational bottlenecks that hinder the acquisition of meaningful results. To improve the computational efficiency, a system that combines stochastic model generation with MODFLOW-related programs and distributed parallel processing is investigated. The distributed computing framework, called the Java Parallel Processing Framework, is integrated into the system to allow the batch processing of stochastic models in distributed and parallel systems. As an example, the system is applied to the stochastic delineation of well capture zones in the Pinggu Basin in Beijing. Through the use of 50 processing threads on a cluster with 10 multicore nodes, the execution times of 500 realizations are reduced to 3% compared with those of a serial execution. Through this application, the system demonstrates its potential in solving difficult computational problems in practical stochastic modeling. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

Model-driven product line engineering for mapping parallel algorithms to parallel computing platforms

NARCIS (Netherlands)

Arkin, Ethem; Tekinerdogan, Bedir

2016-01-01

Mapping parallel algorithms to parallel computing platforms requires several activities such as the analysis of the parallel algorithm, the definition of the logical configuration of the platform, the mapping of the algorithm to the logical configuration platform and the implementation of the

Ab initio quantum chemistry in parallel-portable tools and applications

International Nuclear Information System (INIS)

Harrison, R.J.; Shepard, R.; Kendall, R.A.

1991-01-01

In common with many of the computational sciences, ab initio chemistry faces computational constraints to which a partial solution is offered by the prospect of highly parallel computers. Ab initio codes are large and complex (O(10 5 ) lines of FORTRAN), representing a significant investment of communal effort. The often conflicting requirements of portability and efficiency have been successfully resolved on vector computers by reliance on matrix oriented kernels. This proves inadequate even upon closely-coupled shared-memory parallel machines. We examine the algorithms employed during a typical sequence of calculations. Then we investigate how efficient portable parallel implementations may be derived, including the complex multi-reference singles and doubles configuration interaction algorithm. A portable toolkit, modeled after the Intel iPSC and the ANL-ACRF PARMACS, is developed, using shared memory and TCP/IP sockets. The toolkit is used as an initial platform for programs portable between LANS, Crays and true distributed-memory MIMD machines. Timings are presented. 53 refs., 4 tabs

Flexibility and Performance of Parallel File Systems

Science.gov (United States)

Kotz, David; Nieuwejaar, Nils

1996-01-01

As we gain experience with parallel file systems, it becomes increasingly clear that a single solution does not suit all applications. For example, it appears to be impossible to find a single appropriate interface, caching policy, file structure, or disk-management strategy. Furthermore, the proliferation of file-system interfaces and abstractions make applications difficult to port. We propose that the traditional functionality of parallel file systems be separated into two components: a fixed core that is standard on all platforms, encapsulating only primitive abstractions and interfaces, and a set of high-level libraries to provide a variety of abstractions and application-programmer interfaces (API's). We present our current and next-generation file systems as examples of this structure. Their features, such as a three-dimensional file structure, strided read and write interfaces, and I/O-node programs, are specifically designed with the flexibility and performance necessary to support a wide range of applications.

Implementing Parallel Google Map-Reduce in Eden

DEFF Research Database (Denmark)

Berthold, Jost; Dieterle, Mischa; Loogen, Rita

2009-01-01

Recent publications have emphasised map-reduce as a general programming model (labelled Google map-reduce), and described existing high-performance implementations for large data sets. We present two parallel implementations for this Google map-reduce skeleton, one following earlier work, and one...... of the Google map-reduce skeleton in usage and performance, and deliver runtime analyses for example applications. Although very flexible, the Google map-reduce skeleton is often too general, and typical examples reveal a better runtime behaviour using alternative skeletons....

A Parallel Adaboost-Backpropagation Neural Network for Massive Image Dataset Classification

Science.gov (United States)

Cao, Jianfang; Chen, Lichao; Wang, Min; Shi, Hao; Tian, Yun

2016-01-01

Image classification uses computers to simulate human understanding and cognition of images by automatically categorizing images. This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually regarded as weak classifiers) based on the Adaboost algorithm. Second, we design Map and Reduce tasks for both the parallel Adaboost-BP neural network and the feature extraction algorithm. Finally, we establish an automated classification model by building a Hadoop cluster. We use the Pascal VOC2007 and Caltech256 datasets to train and test the classification model. The results are superior to those obtained using traditional Adaboost-BP neural network or parallel BP neural network approaches. Our approach increased the average classification accuracy rate by approximately 14.5% and 26.0% compared to the traditional Adaboost-BP neural network and parallel BP neural network, respectively. Furthermore, the proposed approach requires less computation time and scales very well as evaluated by speedup, sizeup and scaleup. The proposed approach may provide a foundation for automated large-scale image classification and demonstrates practical value. PMID:27905520

Massively parallel mathematical sieves

Energy Technology Data Exchange (ETDEWEB)

Montry, G.R.

1989-01-01

The Sieve of Eratosthenes is a well-known algorithm for finding all prime numbers in a given subset of integers. A parallel version of the Sieve is described that produces computational speedups over 800 on a hypercube with 1,024 processing elements for problems of fixed size. Computational speedups as high as 980 are achieved when the problem size per processor is fixed. The method of parallelization generalizes to other sieves and will be efficient on any ensemble architecture. We investigate two highly parallel sieves using scattered decomposition and compare their performance on a hypercube multiprocessor. A comparison of different parallelization techniques for the sieve illustrates the trade-offs necessary in the design and implementation of massively parallel algorithms for large ensemble computers.

cellGPU: Massively parallel simulations of dynamic vertex models

Science.gov (United States)

Sussman, Daniel M.

2017-10-01

Vertex models represent confluent tissue by polygonal or polyhedral tilings of space, with the individual cells interacting via force laws that depend on both the geometry of the cells and the topology of the tessellation. This dependence on the connectivity of the cellular network introduces several complications to performing molecular-dynamics-like simulations of vertex models, and in particular makes parallelizing the simulations difficult. cellGPU addresses this difficulty and lays the foundation for massively parallelized, GPU-based simulations of these models. This article discusses its implementation for a pair of two-dimensional models, and compares the typical performance that can be expected between running cellGPU entirely on the CPU versus its performance when running on a range of commercial and server-grade graphics cards. By implementing the calculation of topological changes and forces on cells in a highly parallelizable fashion, cellGPU enables researchers to simulate time- and length-scales previously inaccessible via existing single-threaded CPU implementations. Program Files doi:http://dx.doi.org/10.17632/6j2cj29t3r.1 Licensing provisions: MIT Programming language: CUDA/C++ Nature of problem: Simulations of off-lattice "vertex models" of cells, in which the interaction forces depend on both the geometry and the topology of the cellular aggregate. Solution method: Highly parallelized GPU-accelerated dynamical simulations in which the force calculations and the topological features can be handled on either the CPU or GPU. Additional comments: The code is hosted at https://gitlab.com/dmsussman/cellGPU, with documentation additionally maintained at http://dmsussman.gitlab.io/cellGPUdocumentation

NDL-v2.0: A new version of the numerical differentiation library for parallel architectures

Science.gov (United States)

Hadjidoukas, P. E.; Angelikopoulos, P.; Voglis, C.; Papageorgiou, D. G.; Lagaris, I. E.

2014-07-01

We present a new version of the numerical differentiation library (NDL) used for the numerical estimation of first and second order partial derivatives of a function by finite differencing. In this version we have restructured the serial implementation of the code so as to achieve optimal task-based parallelization. The pure shared-memory parallelization of the library has been based on the lightweight OpenMP tasking model allowing for the full extraction of the available parallelism and efficient scheduling of multiple concurrent library calls. On multicore clusters, parallelism is exploited by means of TORC, an MPI-based multi-threaded tasking library. The new MPI implementation of NDL provides optimal performance in terms of function calls and, furthermore, supports asynchronous execution of multiple library calls within legacy MPI programs. In addition, a Python interface has been implemented for all cases, exporting the functionality of our library to sequential Python codes. Catalog identifier: AEDG_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDG_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 63036 No. of bytes in distributed program, including test data, etc.: 801872 Distribution format: tar.gz Programming language: ANSI Fortran-77, ANSI C, Python. Computer: Distributed systems (clusters), shared memory systems. Operating system: Linux, Unix. Has the code been vectorized or parallelized?: Yes. RAM: The library uses O(N) internal storage, N being the dimension of the problem. It can use up to O(N2) internal storage for Hessian calculations, if a task throttling factor has not been set by the user. Classification: 4.9, 4.14, 6.5. Catalog identifier of previous version: AEDG_v1_0 Journal reference of previous version: Comput. Phys. Comm. 180

An intelligent allocation algorithm for parallel processing

Science.gov (United States)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

Data communications in a parallel active messaging interface of a parallel computer

Science.gov (United States)

Archer, Charles J; Blocksome, Michael A; Ratterman, Joseph D; Smith, Brian E

2013-11-12

Data communications in a parallel active messaging interface (`PAMI`) of a parallel computer composed of compute nodes that execute a parallel application, each compute node including application processors that execute the parallel application and at least one management processor dedicated to gathering information regarding data communications. The PAMI is composed of data communications endpoints, each endpoint composed of a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes and the endpoints coupled for data communications through the PAMI and through data communications resources. Embodiments function by gathering call site statistics describing data communications resulting from execution of data communications instructions and identifying in dependence upon the call cite statistics a data communications algorithm for use in executing a data communications instruction at a call site in the parallel application.

Parallelized Genetic Identification of the Thermal-Electrochemical Model for Lithium-Ion Battery

Directory of Open Access Journals (Sweden)

Liqiang Zhang

2013-01-01

Full Text Available The parameters of a well predicted model can be used as health characteristics for Lithium-ion battery. This article reports a parallelized parameter identification of the thermal-electrochemical model, which significantly reduces the time consumption of parameter identification. Since the P2D model has the most predictability, it is chosen for further research and expanded to the thermal-electrochemical model by coupling thermal effect and temperature-dependent parameters. Then Genetic Algorithm is used for parameter identification, but it takes too much time because of the long time simulation of model. For this reason, a computer cluster is built by surplus computing resource in our laboratory based on Parallel Computing Toolbox and Distributed Computing Server in MATLAB. The performance of two parallelized methods, namely Single Program Multiple Data (SPMD and parallel FOR loop (PARFOR, is investigated and then the parallelized GA identification is proposed. With this method, model simulations running parallelly and the parameter identification could be speeded up more than a dozen times, and the identification result is batter than that from serial GA. This conclusion is validated by model parameter identification of a real LiFePO4 battery.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

Science.gov (United States)

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

A parallel buffer tree

DEFF Research Database (Denmark)

Sitchinava, Nodar; Zeh, Norbert

2012-01-01

We present the parallel buffer tree, a parallel external memory (PEM) data structure for batched search problems. This data structure is a non-trivial extension of Arge's sequential buffer tree to a private-cache multiprocessor environment and reduces the number of I/O operations by the number of...... in the optimal OhOf(psortN + K/PB) parallel I/O complexity, where K is the size of the output reported in the process and psortN is the parallel I/O complexity of sorting N elements using P processors....

Parallel Algorithms and Patterns

Energy Technology Data Exchange (ETDEWEB)

Robey, Robert W. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-06-16

This is a powerpoint presentation on parallel algorithms and patterns. A parallel algorithm is a well-defined, step-by-step computational procedure that emphasizes concurrency to solve a problem. Examples of problems include: Sorting, searching, optimization, matrix operations. A parallel pattern is a computational step in a sequence of independent, potentially concurrent operations that occurs in diverse scenarios with some frequency. Examples are: Reductions, prefix scans, ghost cell updates. We only touch on parallel patterns in this presentation. It really deserves its own detailed discussion which Gabe Rockefeller would like to develop.

ICASE Computer Science Program

Science.gov (United States)

1985-01-01

The Institute for Computer Applications in Science and Engineering computer science program is discussed in outline form. Information is given on such topics as problem decomposition, algorithm development, programming languages, and parallel architectures.

Refining SCJ Mission Specifications into Parallel Handler Designs

Directory of Open Access Journals (Sweden)

Frank Zeyda

2013-05-01

Full Text Available Safety-Critical Java (SCJ is a recent technology that restricts the execution and memory model of Java in such a way that applications can be statically analysed and certified for their real-time properties and safe use of memory. Our interest is in the development of comprehensive and sound techniques for the formal specification, refinement, design, and implementation of SCJ programs, using a correct-by-construction approach. As part of this work, we present here an account of laws and patterns that are of general use for the refinement of SCJ mission specifications into designs of parallel handlers used in the SCJ programming paradigm. Our notation is a combination of languages from the Circus family, supporting state-rich reactive models with the addition of class objects and real-time properties. Our work is a first step to elicit laws of programming for SCJ and fits into a refinement strategy that we have developed previously to derive SCJ programs.

Dynamic stability calculations for power grids employing a parallel computer

Energy Technology Data Exchange (ETDEWEB)

Schmidt, K

1982-06-01

The aim of dynamic contingency calculations in power systems is to estimate the effects of assumed disturbances, such as loss of generation. Due to the large dimensions of the problem these simulations require considerable computing time and costs, to the effect that they are at present only used in a planning state but not for routine checks in power control stations. In view of the homogeneity of the problem, where a multitude of equal generator models, having different parameters, are to be integrated simultaneously, the use of a parallel computer looks very attractive. The results of this study employing a prototype parallel computer (SMS 201) are presented. It consists of up to 128 equal microcomputers bus-connected to a control computer. Each of the modules is programmed to simulate a node of the power grid. Generators with their associated control are represented by models of 13 states each. Passive nodes are complemented by 'phantom'-generators, so that the whole power grid is homogenous, thus removing the need for load-flow-iterations. Programming of microcomputers is essentially performed in FORTRAN.

Totally parallel multilevel algorithms

Science.gov (United States)

Frederickson, Paul O.

1988-01-01

Four totally parallel algorithms for the solution of a sparse linear system have common characteristics which become quite apparent when they are implemented on a highly parallel hypercube such as the CM2. These four algorithms are Parallel Superconvergent Multigrid (PSMG) of Frederickson and McBryan, Robust Multigrid (RMG) of Hackbusch, the FFT based Spectral Algorithm, and Parallel Cyclic Reduction. In fact, all four can be formulated as particular cases of the same totally parallel multilevel algorithm, which are referred to as TPMA. In certain cases the spectral radius of TPMA is zero, and it is recognized to be a direct algorithm. In many other cases the spectral radius, although not zero, is small enough that a single iteration per timestep keeps the local error within the required tolerance.

Parallel Wavefront Analysis for a 4D Interferometer

Science.gov (United States)

Rao, Shanti R.

2011-01-01

This software provides a programming interface for automating data collection with a PhaseCam interferometer from 4D Technology, and distributing the image-processing algorithm across a cluster of general-purpose computers. Multiple instances of 4Sight (4D Technology s proprietary software) run on a networked cluster of computers. Each connects to a single server (the controller) and waits for instructions. The controller directs the interferometer to several images, then assigns each image to a different computer for processing. When the image processing is finished, the server directs one of the computers to collate and combine the processed images, saving the resulting measurement in a file on a disk. The available software captures approximately 100 images and analyzes them immediately. This software separates the capture and analysis processes, so that analysis can be done at a different time and faster by running the algorithm in parallel across several processors. The PhaseCam family of interferometers can measure an optical system in milliseconds, but it takes many seconds to process the data so that it is usable. In characterizing an adaptive optics system, like the next generation of astronomical observatories, thousands of measurements are required, and the processing time quickly becomes excessive. A programming interface distributes data processing for a PhaseCam interferometer across a Windows computing cluster. A scriptable controller program coordinates data acquisition from the interferometer, storage on networked hard disks, and parallel processing. Idle time of the interferometer is minimized. This architecture is implemented in Python and JavaScript, and may be altered to fit a customer s needs.

Study and simulation of a parallel numerical processing machine

International Nuclear Information System (INIS)

Bel Hadj, Slaheddine

1981-12-01

This study has been carried out in the perspective of the implementation on a minicomputer of the NEPTUNIX package (software for the resolution of very large algebra-differential equation systems). Aiming at increasing the system performance, a previous research work has shown the necessity of reducing the execution time of certain numerical computation tasks, which are of frequent use. It has also demonstrated the feasibility of handling these tasks with efficient algorithms of parallel type. The present work deals with the study and simulation of a parallel architecture processor adapted to the fast execution of these algorithms. A minicomputer fitted with a connection to such a parallel processor, has a greatly extended computing power. Then the architecture of a parallel numerical processor, based on the use of VLSI microprocessors and co-processors, is described. Its design aims at the best cost / performance ratio. The last part deals with the simulation processor with the 'CHAMBOR' program. Results show an increasing factor of 30 in speed, in comparison with the execution on a MITRA 15 minicomputer. Moreover the conflicts importance, mainly at the level of access to a shared resource is evaluated. Although this implementation has been designed having in mind a dedicated application, other uses could be envisaged, particularly for the simulation of nuclear reactors: operator guiding system, the behavioural study under accidental circumstances, etc. (author) [fr

A possibility of parallel and anti-parallel diffraction measurements on ...

Indian Academy of Sciences (India)

However, a bent perfect crystal (BPC) monochromator at monochromatic focusing condition can provide a quite flat and equal resolution property at both parallel and anti-parallel positions and thus one can have a chance to use both sides for the diffraction experiment. From the data of the FWHM and the / measured ...

Method of parallel processing in SANPO real time system

International Nuclear Information System (INIS)

Ostrovnoj, A.I.; Salamatin, I.M.

1981-01-01

A method of parellel processing in SANPO real time system is described. Algorithms of data accumulation and preliminary processing in this system as a parallel processes using a specialized high level programming language are described. Hierarchy of elementary processes are also described. It provides the synchronization of concurrent processes without semaphors. The developed means are applied to the systems of experiment automation using SM-3 minicomputers [ru

Large-scale parallel configuration interaction. I. Nonrelativisticand scalar-relativistic general active space implementationwith application to (Rb-Ba)+

DEFF Research Database (Denmark)

Knecht, Stefan; Jensen, Hans Jørgen Aagaard; Fleig, Timo

2008-01-01

We present a parallel implementation of a string-driven general active space configuration interaction program for nonrelativistic and scalar-relativistic electronic-structure calculations. The code has been modularly incorporated in the DIRAC quantum chemistry program package. The implementation...

Optimal task mapping in safety-critical real-time parallel systems; Placement optimal de taches pour les systemes paralleles temps-reel critiques

Energy Technology Data Exchange (ETDEWEB)

Aussagues, Ch

1998-12-11

This PhD thesis is dealing with the correct design of safety-critical real-time parallel systems. Such systems constitutes a fundamental part of high-performance systems for command and control that can be found in the nuclear domain or more generally in parallel embedded systems. The verification of their temporal correctness is the core of this thesis. our contribution is mainly in the following three points: the analysis and extension of a programming model for such real-time parallel systems; the proposal of an original method based on a new operator of synchronized product of state machines task-graphs; the validation of the approach by its implementation and evaluation. The work addresses particularly the main problem of optimal task mapping on a parallel architecture, such that the temporal constraints are globally guaranteed, i.e. the timeliness property is valid. The results incorporate also optimally criteria for the sizing and correct dimensioning of a parallel system, for instance in the number of processing elements. These criteria are connected with operational constraints of the application domain. Our approach is based on the off-line analysis of the feasibility of the deadline-driven dynamic scheduling that is used to schedule tasks inside one processor. This leads us to define the synchronized-product, a system of linear, constraints is automatically generated and then allows to calculate a maximum load of a group of tasks and then to verify their timeliness constraints. The communications, their timeliness verification and incorporation to the mapping problem is the second main contribution of this thesis. FInally, the global solving technique dealing with both task and communication aspects has been implemented and evaluated in the framework of the OASIS project in the LETI research center at the CEA/Saclay. (author) 96 refs.

Parallel Computing in SCALE

International Nuclear Information System (INIS)

DeHart, Mark D.; Williams, Mark L.; Bowman, Stephen M.

2010-01-01

The SCALE computational architecture has remained basically the same since its inception 30 years ago, although constituent modules and capabilities have changed significantly. This SCALE concept was intended to provide a framework whereby independent codes can be linked to provide a more comprehensive capability than possible with the individual programs - allowing flexibility to address a wide variety of applications. However, the current system was designed originally for mainframe computers with a single CPU and with significantly less memory than today's personal computers. It has been recognized that the present SCALE computation system could be restructured to take advantage of modern hardware and software capabilities, while retaining many of the modular features of the present system. Preliminary work is being done to define specifications and capabilities for a more advanced computational architecture. This paper describes the state of current SCALE development activities and plans for future development. With the release of SCALE 6.1 in 2010, a new phase of evolutionary development will be available to SCALE users within the TRITON and NEWT modules. The SCALE (Standardized Computer Analyses for Licensing Evaluation) code system developed by Oak Ridge National Laboratory (ORNL) provides a comprehensive and integrated package of codes and nuclear data for a wide range of applications in criticality safety, reactor physics, shielding, isotopic depletion and decay, and sensitivity/uncertainty (S/U) analysis. Over the last three years, since the release of version 5.1 in 2006, several important new codes have been introduced within SCALE, and significant advances applied to existing codes. Many of these new features became available with the release of SCALE 6.0 in early 2009. However, beginning with SCALE 6.1, a first generation of parallel computing is being introduced. In addition to near-term improvements, a plan for longer term SCALE enhancement

Starpc: a library for communication among tools on a parallel computer cluster. User's and developer's guide to Starpc

International Nuclear Information System (INIS)

Takemiya, Hiroshi; Yamagishi, Nobuhiro

2000-02-01

We report on a RPC(Remote Procedure Call)-based communication library, Starpc, for a parallel computer cluster. Starpc supports communication between Java Applets and C programs as well as between C programs. Starpc has the following three features. (1) It enables communication between Java Applets and C programs on an arbitrary computer without security violation, although Java Applets are supposed to communicate only with programs on the specific computer (Web server) in subject to a restriction on security. (2) Diverse network communication protocols are available on Starpc, because of using Nexus communication library developed at Argonne National Laboratory. (3) It works on many kinds of computers including eight parallel computers and four WS servers. In this report, the usage of Starpc and the development of applications using Starpc are described. (author)

Parallel k-means++

Energy Technology Data Exchange (ETDEWEB)

2017-04-04

A parallelization of the k-means++ seed selection algorithm on three distinct hardware platforms: GPU, multicore CPU, and multithreaded architecture. K-means++ was developed by David Arthur and Sergei Vassilvitskii in 2007 as an extension of the k-means data clustering technique. These algorithms allow people to cluster multidimensional data, by attempting to minimize the mean distance of data points within a cluster. K-means++ improved upon traditional k-means by using a more intelligent approach to selecting the initial seeds for the clustering process. While k-means++ has become a popular alternative to traditional k-means clustering, little work has been done to parallelize this technique. We have developed original C++ code for parallelizing the algorithm on three unique hardware architectures: GPU using NVidia's CUDA/Thrust framework, multicore CPU using OpenMP, and the Cray XMT multithreaded architecture. By parallelizing the process for these platforms, we are able to perform k-means++ clustering much more quickly than it could be done before.

High-speed detection of emergent market clustering via an unsupervised parallel genetic algorithm

Directory of Open Access Journals (Sweden)

Dieter Hendricks

2016-02-01

Full Text Available We implement a master-slave parallel genetic algorithm with a bespoke log-likelihood fitness function to identify emergent clusters within price evolutions. We use graphics processing units (GPUs to implement a parallel genetic algorithm and visualise the results using disjoint minimal spanning trees. We demonstrate that our GPU parallel genetic algorithm, implemented on a commercially available general purpose GPU, is able to recover stock clusters in sub-second speed, based on a subset of stocks in the South African market. This approach represents a pragmatic choice for low-cost, scalable parallel computing and is significantly faster than a prototype serial implementation in an optimised C-based fourth-generation programming language, although the results are not directly comparable because of compiler differences. Combined with fast online intraday correlation matrix estimation from high frequency data for cluster identification, the proposed implementation offers cost-effective, near-real-time risk assessment for financial practitioners.

Parallel magnetic resonance imaging

International Nuclear Information System (INIS)