A Parallel Approximation Algorithm for Maximizing Submodular b-Matching
A Parallel Approximation Algorithm for Maximizing Submodular b-Matching
复制标题
最大化子模b匹配的并行逼近算法
DOI:
10.1137/1.9781611976830.5
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
Halappanavar, M.
中科院分区:
文献类型:
--
作者:
Ferdous, S;Pothen, A;Khan, A.;Panyala, A.;Halappanavar, M.
We design new serial and parallel approximation algorithms for computing a maximum weightb-matching in an edge-weighted graph with a submodular objective function. This problem is NP-hard; the new algorithms have approximation ratio 1/3, and are relaxations of the Greedy algorithm that rely only on local information in the graph, making them parallelizable. We have designed and implemented Local Lazy Greedy algorithms for both serial and parallel computers. We have applied the approximate submodularb-matching algorithm to assign tasks to processors in the computation of Fock matrices in quantum chemistry on parallel computers. The assignment seeks to reduce the run time by balancing the computational load on the processors and bounding the number of messages that each processor sends. We show that the new assignment of tasks to processors provides a four fold speedup over the currently used assignment in the NWChemEx software on 8000 processors on the Summit supercomputer at Oak Ridge National Lab.
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DOI:
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发表时间:
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期刊:
--
影响因子:
--
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DOI:
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期刊:
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DOI:
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期刊:
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DOI:
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发表时间:
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期刊:
影响因子:
--
作者:
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通讯作者:
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DOI:
--
发表时间:
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期刊:
IEEE International Parallel and Distributed Processing Symposium
影响因子:
--
作者:
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