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Partitioning of Parallel Programs for Execution of Multiprocessors

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Release : 1990
Genre : Multiprocessors
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Book Synopsis Partitioning of Parallel Programs for Execution of Multiprocessors by : Gururaj Pangal

Download or read book Partitioning of Parallel Programs for Execution of Multiprocessors written by Gururaj Pangal. This book was released on 1990. Available in PDF, EPUB and Kindle. Book excerpt:

Partitioning and Scheduling Parallel Programs for Multiprocessors

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Author :
Release : 1989
Genre : Computers
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Book Synopsis Partitioning and Scheduling Parallel Programs for Multiprocessors by : Vivek Sarkar

Download or read book Partitioning and Scheduling Parallel Programs for Multiprocessors written by Vivek Sarkar. This book was released on 1989. Available in PDF, EPUB and Kindle. Book excerpt: This book is one of the first to address the problem of forming useful parallelism from potential parallelism and to provide a general solution. The book presents two approaches to automatic partitioning and scheduling so that the same parallel program can be made to execute efficiently on widely different multiprocessors. The first approach is based on a macro dataflow model in which the program is partitioned into tasks at compile time and the tasks are scheduled on processors at run time. The second approach is based on a compile time scheduling model, where both the partitioning and scheduling are performed at compile time. Both approaches have been implemented in partition programs written in the single assignment language SISAL. The inputs to the partitioning and scheduling algorithms are a graphical representation of the parallel program and a list of parameters describing the target multiprocessor. Execution profile information is used to derive compile-time estimates of execution times and data sizes in the program. Both the macro dataflow and compile-time scheduling problems are expressed as optimization problems and are shown to be NP complete in the strong sense. Efficient approximation algorithms for these problems are presented. Finally, the effectiveness of the partitioning and scheduling algorithms is studied by multiprocessor simulations of various SISAL benchmark programs for different target multiprocessor parameters. Vivek Sarkar is a Member of Research Staff at the IBM T. J. Watson Research Center. Partitioning and Scheduling Parallel Programs for Multiprocessing is included in the series Research Monographs in Parallel and Distributed Computing. Copublished with Pitman Publishing.

Partitioning and Scheduling Parallel Programs for Execution on Multiprocessors

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Author :
Release : 1987
Genre :
Kind : eBook
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Book Synopsis Partitioning and Scheduling Parallel Programs for Execution on Multiprocessors by : Vivek Sarkar

Download or read book Partitioning and Scheduling Parallel Programs for Execution on Multiprocessors written by Vivek Sarkar. This book was released on 1987. Available in PDF, EPUB and Kindle. Book excerpt:

Compile-Time Partitioning and Scheduling of Parallel Programs. Extended Summary

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Release : 1986
Genre :
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Book Synopsis Compile-Time Partitioning and Scheduling of Parallel Programs. Extended Summary by : Vivek Sarkar

Download or read book Compile-Time Partitioning and Scheduling of Parallel Programs. Extended Summary written by Vivek Sarkar. This book was released on 1986. Available in PDF, EPUB and Kindle. Book excerpt: One of the biggest challenges facing language designers and implementors is to develop languages that will be suitable for use on multiprocessors. A wide variety of multiprocessor architectures are currently being built and that variety is expected to increase. Very little software is available to exploit parallelism and speed-up the execution of individual programs. What little work has been done, has focused largely on special-purpose parallelism (e.g. vectorization) or very limited classes of architectures. To understand the issues involved in taking advantage of parallelism and to evaluate architectures, we need to find compilation techniques for fairly general-purpose languages; these techniques need to be adapted to a wide variety of architectures. Only then will it be possible to compare various languages, alternative architectures, and their interaction with different applications. To compile and execute a program in a parallel fashion on a multiprocessor, there are three fundamental problems to be solved: 1) Identification of potential parallelism - discovering parallel computations in the program. 2) Partitioning the program into tasks - each task represents a serially-executed component that can execute in parallel with other tasks. 3) Scheduling the execution of tasks - the tasks must be scheduled for execution on multiple processors.

Compile-Time Partitioning and Scheduling of Parallel Programs

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Author :
Release : 1987
Genre :
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Book Synopsis Compile-Time Partitioning and Scheduling of Parallel Programs by : Vivek Sarkar

Download or read book Compile-Time Partitioning and Scheduling of Parallel Programs written by Vivek Sarkar. This book was released on 1987. Available in PDF, EPUB and Kindle. Book excerpt: Partitioning and scheduling techniques are necessary to implement parallel languages on multiprocessors. Multiprocessor performance is maximized when parallelism between tasks is optimally traded off with communication and synchronization overhead. The authors present compile-time partitioning and scheduling techniques to achieve this tradeoff. One of the biggest challenges facing compiler writers is to efficiently implement programming languages on multiprocessors. We need to find compilation techniques for general-purpose parallel languages; these techniques should be adaptable to a wide range of multiprocessor architectures. There are three fundamental problems to be solved when compiling a program for parallel execution on a multiprocessor: 1) Identifying potential parallelism; 2) Partitioning the program into sequential tasks; and 3) Scheduling the concurrent execution of these tasks. This document addresses the latter two problems and suggest that these be solved at compile- time instead of run-time for applications with fairly predictable execution times.

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