Limited resource scheduling in sparse matrix algorithms
We present analytic models and simulation techniques that describe the performance of the multifrontal method on distributed memory architectures. We focus on particular strategies for partitioning, clustering, and mapping of task nodes to processors in order to minimize the overall parallel executi...
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| Veröffentlicht in: | Hawaii International Conference on System Sciences, 27th. Vol. 5: Biotechnology Jg. 2; S. 473 - 482 |
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| Hauptverfasser: | , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE Comput. Soc. Press
1994
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| ISBN: | 0818650907, 9780818650901 |
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| Abstract | We present analytic models and simulation techniques that describe the performance of the multifrontal method on distributed memory architectures. We focus on particular strategies for partitioning, clustering, and mapping of task nodes to processors in order to minimize the overall parallel execution time and minimize communication costs. The performance model has bees used to obtain estimates for the speedups of various engineering and scientific problems, on several distributed architectures. The result is that the available parallelism of these problems is strongly dependent on the sparsity structure of the input matrices.< > |
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| AbstractList | We present analytic models and simulation techniques that describe the performance of the multifrontal method on distributed memory architectures. We focus on particular strategies for partitioning, clustering, and mapping of task nodes to processors in order to minimize the overall parallel execution time and minimize communication costs. The performance model has bees used to obtain estimates for the speedups of various engineering and scientific problems, on several distributed architectures. The result is that the available parallelism of these problems is strongly dependent on the sparsity structure of the input matrices.< > |
| Author | Pozo Smith |
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| PublicationTitle | Hawaii International Conference on System Sciences, 27th. Vol. 5: Biotechnology |
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| Snippet | We present analytic models and simulation techniques that describe the performance of the multifrontal method on distributed memory architectures. We focus on... |
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| StartPage | 473 |
| SubjectTerms | Computation time Computer performance Distributed memories Parallel algorithms Scheduling Sparse matrices |
| Title | Limited resource scheduling in sparse matrix algorithms |
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