A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm

A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm

Bibliographic Details
Main Author: Chantamas, Wittaya
Language:English
Published: Kent State University / OhioLINK 2009
Subjects:
Computer Science
associative computing
joint data and control parallelism
computational model
multi-SIMD
model simulation
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=kent1259610266
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-kent12596102662021-08-03T05:37:07Z A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm Chantamas, Wittaya Computer Science associative computing joint data and control parallelism computational model multi-SIMD model simulation The multiple associative computing (MASC) model is an enhanced strictly synchronous multi-SIMD model that is a generalization of an associative computing model (ASC) designed to support multiple ASC threads by using control parallelism to substantially improve the low processor utilization often criticized in SIMDs. The MASC model combines the advantages of both SIMD and MIMD models such as simple description, inherent synchronous operations, and ease of programming and debugging of SIMDs while providing flexible control flow support of MIMDs with small thread synchronization overheads. In this research, a cycle of simulations is used to show that a MASC model with constant associative operation word length and a MASC model with log n associative operation word length are equivalent in power. Moreover, the MASC model is powerful as the B-RMBM, S-RMBM, COMMON CRCW PRAM, and BRM models. This research presents a model description of a MASC model that uses the manager and worker instruction stream paradigm. A cycle precision software simulator, which is able to provide the exact number of overhead and execution cycles the model requires to execute a program, is used to demonstrate the performance of this implementation of MASC on various algorithms. The simulator is actually a software prototype for the manager-worker version with sufficient software details to allow a computer engineer to convert this software prototype into a hardware prototype of the manager-worker version of MASC. On the example multithreaded algorithms used, when processing large-scale instances using multiple workers, the MASC Floyd-Warshall algorithm shows strong scaling with constant time overhead and, for an average case, the MASC Quickhull algorithm shows good scaling with low overhead. 2009-12-01 English text Kent State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=kent1259610266 http://rave.ohiolink.edu/etdc/view?acc_num=kent1259610266 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Computer Science
associative computing
joint data and control parallelism
computational model
multi-SIMD
model simulation
spellingShingle Computer Science
associative computing
joint data and control parallelism
computational model
multi-SIMD
model simulation
Chantamas, Wittaya
A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm
author Chantamas, Wittaya
author_facet Chantamas, Wittaya
author_sort Chantamas, Wittaya
title A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm
title_short A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm
title_full A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm
title_fullStr A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm
title_full_unstemmed A Multiple Associative Computing Model to Support the Execution of Data Parallel Branches Using the Manager-worker Paradigm
title_sort multiple associative computing model to support the execution of data parallel branches using the manager-worker paradigm
publisher Kent State University / OhioLINK
publishDate 2009
url http://rave.ohiolink.edu/etdc/view?acc_num=kent1259610266
work_keys_str_mv AT chantamaswittaya amultipleassociativecomputingmodeltosupporttheexecutionofdataparallelbranchesusingthemanagerworkerparadigm
AT chantamaswittaya multipleassociativecomputingmodeltosupporttheexecutionofdataparallelbranchesusingthemanagerworkerparadigm
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