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

Averbuch, Amir; Gabber, Eran; Itzikowitz, S.; Shoham, Barack

doi:10.1155/1994/895737

Cited by 3 publications

(3 citation statements)

References 6 publications

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“…VMMP was used in the implementation of many other problems, such as parallel solution of underwater acoustic IFD (implicit finite difference) schemes [25], using multigrid to solve Poisson equations on all the above target machines [26], solving Topelitz matrices [27] and parallel debugger [28], parallel implementation of BLAS 3 [29]. All the above implementations were also tested on shared memory and message passing multiprocessors.…”

Section: Vmmp Has Been Implemented On the Following Multiprocessorsmentioning

confidence: 99%

Portable parallel FFT for MIMD multiprocessors

Averbuch

Gabber

1998

Concurrency: Pract. Exper.

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Section: Vmmp Has Been Implemented On the Following Multiprocessorsmentioning

confidence: 99%

Portable parallel FFT for MIMD multiprocessors

Averbuch

Gabber

1998

Concurrency: Pract. Exper.

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“…VMMP was used in the implementation of many other problems, such as the parallel generalized in frequency FFT (GFFT) [33], comparsion of the implementation on all the above machines [34], parallel solution of underwater acoustic IFD (implicit finite difference) schemes [35], using multigrid to solve Poission equations on all the above target machines [36], solving Topelitz matrices [37], parallelizing BLAS 3[38], and in a parallel debugger. All the above implementations were tested also on shared memory and messagepassing multiprocessors.…”

Section: Vmmp Implementationmentioning

confidence: 99%

Portable parallelizing Fortran compiler

Averbuch

Dekel

Gabber

1996

Concurrency: Pract. Exper.

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The Portable Parallelizing Fortran Compiler (PPFC) is an additional component for the portable programming environment developed in Tel‐Aviv University for scientific code. This environment supports portable and efficient programming of diverse MIMD multiprocessors, both distributed‐ and shared‐memory. Till now this environment has consisted of two tools: the Virtual Machine for MultiProcessors (VMMP) and the Portable Parallelizing Pascal compiler (P3C). We have added the PPFC which is an automatic parallelizer compiler for the Fortran language. The compiler is fully automatic (does not require additional declarations to assist parallelization), which is characterized by loops operating on regular data structures, and produces efficient and portable code for a variety of multiprocessors from the same serial code. The parallel implementation uses the VMMP, which is a software package that provides a coherent set of services for explicitly parallel application programs running on diverse MIMD multiprocessors. VMMP is intended to simplify parallel program writing and to promote portable and efficient programming. The PPFC parallelized 12 out of the 24 Livermore Loops. It was also applied to parallelize all the 14 Fortran application programs that where parallelized by the P3C and achieved the same speed‐ups and efficiencies. In most examples the PPFC achieved high speed‐ups and efficiencies on all target multiprocessors. The PPFC emphasizes efficiency and code portability. Although PPFC employs a relatively simple data flow analysis, it produces efficient code for various widely used application programs.

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“…VMMP was used in the implementation of many other problems, such as parallel generalized in frequency FFT (GFFT) [35], comparison of the implementation on all the above machines [36], parallel solution of underwater acoustic IFD (implicit finite difference) schemes [37], using multigrid to solve Poission equations on all the above target machines [38], solving Topelitz matrices [39], in a parallel debugger [40]. All the above implementations were tested also on shared-memory and message-passing multiprocessors.…”

Section: Vmmp Implementationmentioning

confidence: 99%

Portable Parallel implementation of BLAS 3

Averbuch¹,

Amitai²,

Friedman³

et al. 1994

Concurrency: Pract. Exper.

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SUMMARYThe use of a massively parallel machine is aimed at the development of applications programs to solve most significant scientific, engineering, industrial and commercial problems.High-performance computing technology has emerged as a powerful and indispensable aid to scientific and engineering research, product and process development, and all aspects of manufacturing. Such computational power can be achieved only by massively parallel computws. It also requires a new and more effective mode of interaction between the computational sciences and applications and those parts of computer science concerned with the development of algorithms and software. We are interested in using parallel processing to handle large numerical tasks such as linear algebra problems. Yet, programming such systems has proven itself to be very complicated, error-prone and architecture-specific.One successful method for alleviating this problem, a method that worked well in the case of the massively pipelined supercomputers, is to use subprogram libraries. These libraries are built to efficiently perform some basic operations, while hiding low-level system specifics from the programmer. Efficiently porting a library to a new hardware, be it a vector machine or a shared memory or message passing based multiprocessor, is a major undertaking. It is a slow process that requires an intimate knowledge of the hardware features and optimization issues.We propose a scheme for the creation of portable implementations of such libraries. We present an implementation of BLAS (basic linear algebra subprograms), which is used as a standard linear algebra library. Our parallel implementation uses the virtual machine for multiprocessors (VMMP) (1990), which is a software package that provides a coherent set of services for explicitly parallel application programs running on diverse MIMD multiprocessors, both shared memory and message passing. VMMP is intended to simplify parallell program writing and to promote portable and efficient programming. Furthermore, it ensures high portability of application programs by implementating the same services on all target multiprocessors. Software created using this scheme is automatically efecient on both categories of MIMD machines, and on any hardware V M M P has been ported to.An additional level of abstraction is achieved using the programming language C*, an object-oriented language. Eckel, Stroustrup, 1989Stroustrup, ,1986. For the programmer who is using BLAS-.3, it is hiding both the data structures used to define linear algebra objects, and the parallel nature of the operations performed on these objects.We icoded BLAS on top of VMMP. This code was run without any modifications on two shared memory machines-the commercial Sequent Symmetry and the experimental Taunop. (The code should run on any machine the VMMP was ported onto, given the availability of a C* compiler). Performance results for thii implementation are given. The speed-up of the BLAS-3 routines, tested on 22 processors of the Sequent, was...

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

Cited by 3 publications

References 6 publications

Portable parallel FFT for MIMD multiprocessors

Portable parallel FFT for MIMD multiprocessors

Portable parallelizing Fortran compiler

Portable Parallel implementation of BLAS 3

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