Engineering and other elds require high performance parallel computing. When the problem at hand presents a structure regular enough to be dealt with automatically, it is sufficient to leave the parallelization and optimization to compiling tools. However, most of the important applications possess structures that lack regularity, and consequently, performance enhancement by exploitation of high performance computing requires new design techniques and tools. In these cases, issues such as data layout, data dependencies,locality, workload, load balance and minimization of communication which impact performance need to be carefully assessed for the client parallel implementation. Memory and synchronization latencies are serious bottlenecks in parallel computing. In the SPMD (Single Instruction Multiple Data Model), von Neumann style of programming is used and hence irregular computations are hard to program. On the other hand, in negrained multithreading models, the program is divided into many small threads and the threads interleaved to achieve maximum parallelism.
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Engineering and other elds require high performance parallel computing. When the problem at hand presents a structure regular enough to be dealt with automatically, it is sufficient to leave the parallelization and optimization to compiling tools. However, most of the important applications possess structures that lack regularity, and consequently, performance enhancement by exploitation of high performance computing requires new design techniques and tools. In these cases, issues such as data layout, data dependencies,locality, workload, load balance and minimization of communication which impact performance need to be carefully assessed for the client parallel implementation. Memory and synchronization latencies are serious bottlenecks in parallel computing. In the SPMD (Single Instruction Multiple Data Model), von Neumann style of programming is used and hence irregular computations are hard to program. On the other hand, in negrained multithreading models, the program is divided into many small threads and the threads interleaved to achieve maximum parallelism.
Parimala Thulasiraman received B.Eng.(Honors)and M.A.Sc.degrees in Computer Engineering from Concordia University, Montreal, Canada and obtained her Ph.D. from University of Delaware, Newark,DE, USA after finishing most of her formalities in McGill University, Montreal, Canada. She is now an Associate Professor at Manitoba University.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Engineering and other elds require high performance parallel computing. When the problem at hand presents a structure regular enough to be dealt with automatically, it is sufficient to leave the parallelization and optimization to compiling tools. However, most of the important applications possess structures that lack regularity, and consequently, performance enhancement by exploitation of high performance computing requires new design techniques and tools. In these cases, issues such as data layout, data dependencies,locality, workload, load balance and minimization of communication which impact performance need to be carefully assessed for the client parallel implementation. Memory and synchronization latencies are serious bottlenecks in parallel computing. In the SPMD (Single Instruction Multiple Data Model), von Neumann style of programming is used and hence irregular computations are hard to program. On the other hand, in negrained multithreading models, the program is divided into many small threads and the threads interleaved to achieve maximum parallelism. 228 pp. Englisch. N° de réf. du vendeur 9783838322148
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Engineering and other elds require high performance parallel computing. When the problem at hand presents a structure regular enough to be dealt with automatically, it is sufficient to leave the parallelization and optimization to compiling tools. However, . N° de réf. du vendeur 5412877
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Taschenbuch. Etat : Neu. Irregular computations on fine-grain multithreaded architecture | Parallel algorithms and architectures | Parimala Thulasiraman | Taschenbuch | 228 S. | Englisch | 2009 | LAP LAMBERT Academic Publishing | EAN 9783838322148 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 101429891
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Taschenbuch. Etat : Neu. Neuware -Engineering and other elds require high performance parallel computing. When the problem at hand presents a structure regular enough to be dealt with automatically, it is sufficient to leave the parallelization and optimization to compiling tools. However, most of the important applications possess structures that lack regularity, and consequently, performance enhancement by exploitation of high performance computing requires new design techniques and tools. In these cases, issues such as data layout, data dependencies,locality, workload, load balance and minimization of communication which impact performance need to be carefully assessed for the client parallel implementation. Memory and synchronization latencies are serious bottlenecks in parallel computing. In the SPMD (Single Instruction Multiple Data Model), von Neumann style of programming is used and hence irregular computations are hard to program. On the other hand, in negrained multithreading models, the program is divided into many small threads and the threads interleaved to achieve maximum parallelism.Books on Demand GmbH, Überseering 33, 22297 Hamburg 228 pp. Englisch. N° de réf. du vendeur 9783838322148
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Engineering and other elds require high performance parallel computing. When the problem at hand presents a structure regular enough to be dealt with automatically, it is sufficient to leave the parallelization and optimization to compiling tools. However, most of the important applications possess structures that lack regularity, and consequently, performance enhancement by exploitation of high performance computing requires new design techniques and tools. In these cases, issues such as data layout, data dependencies,locality, workload, load balance and minimization of communication which impact performance need to be carefully assessed for the client parallel implementation. Memory and synchronization latencies are serious bottlenecks in parallel computing. In the SPMD (Single Instruction Multiple Data Model), von Neumann style of programming is used and hence irregular computations are hard to program. On the other hand, in negrained multithreading models, the program is divided into many small threads and the threads interleaved to achieve maximum parallelism. N° de réf. du vendeur 9783838322148
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