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Analytical modelling in parallel and distributed computing /
Examines complex performance evaluation of various typical parallel algorithms (shared memory, distributed memory) and their practical implementations. Includes real application examples we demonstrate the various influences during the process of modelling and performanceevaluation and the consequen...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Oxford [England] :
Chartridge Books Oxford,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 100 | 1 | |a Hanuliak, Peter, |e author. | |
| 245 | 1 | 0 | |a Analytical modelling in parallel and distributed computing / |c Peter Hanuliak and Michal Hanuliak. |
| 264 | 1 | |a Oxford [England] : |b Chartridge Books Oxford, |c 2014. | |
| 264 | 4 | |c ©2014 | |
| 300 | |a 1 online resource (308 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 504 | |a Includes bibliographical references. | ||
| 588 | 0 | |a Online resource; title from PDF title page (ebrary, viewed October 02, 2014). | |
| 505 | 0 | |a Cover -- Halftitle -- Title -- Copyright -- Contents -- Preview -- Acknowledgements -- Part I. Parallel Computing -- Introduction -- Developing periods in parallel computing -- 1 Modelling of Parallel Computers and Algorithms -- Model construction -- 2 Parallel Computers -- Classification -- Architectures of parallel computers -- Symmetrical multiprocessor system -- Network of workstations -- Grid systems -- Conventional HPC environment versus Grid environments -- Integration of parallel computers -- Metacomputing | |
| 505 | 8 | |a Modelling of parallel computers including communication networks3 Parallel Algorithms -- Introduction -- Parallel processes -- Classification of PAs -- Parallel algorithms with shared memory -- Parallel algorithms with distributed memory -- Developing parallel algorithms -- Decomposition strategies -- Natural parallel decomposition -- Domain decomposition -- Functional decomposition -- Mapping -- Inter process communication -- Inter process communication in shared memory -- Inter process communication in distributed memory -- Performance tuning | |
| 505 | 8 | |a 4 Parallel Program Developing StandardsParallel programming languages -- Open MP standard -- Open MP threads -- Problem decomposition -- MPI API standard -- MPI parallel algorithms -- Task Groups -- Communicators -- The order of tasks -- Collective MPI commands -- Synchronisation mechanisms -- Conditional synchronisation -- Rendezvous -- Synchronisation command barriers -- MPI collective communication mechanisms -- Data scattering collective communication commands -- Java -- 5 Parallel Computing Models -- SPMD model of parallel computation | |
| 505 | 8 | |a Fixed (atomic) networkPRAM model -- Fixed communication model GRAM -- Flexible models -- Flexible GRAM model -- The BSP model -- Computational model MPMD functionality of all system resources -- Load of communication network -- 6 The Role of Performance -- Performance evaluation methods -- Analytic techniques -- Asymptotic (order) analysis -- Application of queuing theory systems -- Kendall classification -- The simulation method -- Experimental measurement -- Part II. Theoretical aspects of PA -- 7 Performance Modelling of Parallel Algorithms | |
| 505 | 8 | |a Speed upEfficiency -- Isoefficiency -- Complex performance evaluation -- Conclusion and perspectives -- 8 Modelling in Parallel Algorithms -- Latencies of PA -- Part III. Applied Parallel Algorithms -- 9 Numerical Integration -- Decomposition model -- Mapping of parallel processes -- Performance optimisation -- Chosen illustration results -- 10 Synchronous Matrix Multiplication -- The systolic matrix multiplier -- Instruction systolic array matrix multiplier -- ISA matrix multiplier -- Dataflow matrix multiplication -- Wave front matrix multiplier | |
| 520 | |a Examines complex performance evaluation of various typical parallel algorithms (shared memory, distributed memory) and their practical implementations. Includes real application examples we demonstrate the various influences during the process of modelling and performanceevaluation and the consequences of their distributed parallel implementations. The current trends in High Performance Computing (HPC) are to use networks of workstations (NOW, SMP) or a network of NOW networks (Grid) as a cheaper alternative to the traditionally-used, massive parallel multiprocessors or supercomputers. Individual workstations could be single PCs (personal computers) used as parallelcomputers based on modern symmetric multicore or multiprocessor systems (SMPs) implemented inside the workstation. With the availability of powerful personal computers, workstations and networking devices, the latest trend in parallel computing is toconnect a number of individual workstations (PCs, PC SMPs) to solve computation-intensive tasks in a parallel way to typical clusters such as NOW, SMP and Grid. In this sense it is not yet correct to consider traditionally evolved parallel computing and distributed computing as two separate research disciplines. To exploit the parallel processing capability of this kind of cluster, the application program must be made parallel. An effective way ofdoing this for (parallelisation strategy) belongs to the most important step in developing an effective parallel algorithm (optimisation). Forbehaviour analysis we have to take into account all the overheads that have an influence on the performance of parallel algorithms (architecture, computation, communication etc.). | ||
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| 650 | 0 | |a Parallel processing (Electronic computers) | |
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| 700 | 1 | |a Hanuliak, Michal, |e author. | |
| 776 | 0 | 8 | |i Print version: |a Hanuliak, Peter. |t Analytical modelling in parallel and distributed computing. |d Oxford, [England] : Chandos Books Oxford, ©2014 |h xiv, 290 pages |z 9781909287907 |
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