Improving efficiency of parallel vertex-centric algorithms for irregular graphs

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buir.contributor.authorÖzdal, Muhammet Mustafa
dc.citation.epage2282en_US
dc.citation.issueNumber10en_US
dc.citation.spage2265en_US
dc.citation.volumeNumber30en_US
dc.contributor.authorÖzdal, Muhammet Mustafaen_US
dc.date.accessioned2020-02-05T09:01:53Z
dc.date.available2020-02-05T09:01:53Z
dc.date.issued2019
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractMemory access is known to be the main bottleneck for shared-memory parallel graph applications especially for large and irregular graphs. Propagation blocking (PB) idea was proposed recently to improve the parallel performance of PageRank and sparse matrix and vector multiplication operations. The idea is based on separating parallel computation into two phases, binning and accumulation, such that random memory accesses are replaced with contiguous accesses. In this paper, we propose an algorithm that allows execution of these two phases concurrently. We propose several improvements to increase parallel throughput, reduce memory overhead, and improve work efficiency. Our experimental results show that our proposed algorithms improve shared-memory parallel throughput by a factor of up to 2× compared to the original PB algorithms. We also show that the memory overhead can be reduced significantly (from 170 percent down to less than 5 percent) without significant degradation of performance. Finally, we demonstrate that our concurrent execution model allows asynchronous parallel execution, leading to significant work efficiency in addition to throughput improvements.en_US
dc.description.provenanceSubmitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2020-02-05T09:01:53Z No. of bitstreams: 1 Improving_efficiency_of_parallel_vertex_centric_algorithms_for_irregular_graphs.pdf: 1710527 bytes, checksum: 63e60067d7eea71cd03f8c50593996d2 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-02-05T09:01:53Z (GMT). No. of bitstreams: 1 Improving_efficiency_of_parallel_vertex_centric_algorithms_for_irregular_graphs.pdf: 1710527 bytes, checksum: 63e60067d7eea71cd03f8c50593996d2 (MD5) Previous issue date: 2019en
dc.identifier.doi10.1109/TPDS.2019.2906166en_US
dc.identifier.issn1045-9219
dc.identifier.urihttp://hdl.handle.net/11693/53083
dc.language.isoEnglishen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.isversionofhttps://dx.doi.org/10.1109/TPDS.2019.2906166en_US
dc.source.titleIEEE Transactions on Parallel and Distributed Systemsen_US
dc.subjectParallel algorithmsen_US
dc.subjectGraph algorithmsen_US
dc.subjectSparse matrix vector multiplication (SpMV)en_US
dc.subjectSparse matrix sparse vector multiplication (SpMSpV)en_US
dc.subjectHigh performance computingen_US
dc.titleImproving efficiency of parallel vertex-centric algorithms for irregular graphsen_US
dc.typeArticleen_US

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