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Using graph partitioning to accelerate task-based parallel applications

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109-111 Using Graph Partitioning 3rd BSC International Doctoral Symposium 2016-27.pdf (1,172Mb)
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hdl:2117/91105

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Sánchez Barrera, IsaacMés informacióMés informació
Casas, MarcMés informació
Moretó Planas, MiquelMés informacióMés informacióMés informació
Ayguadé Parra, EduardMés informacióMés informacióMés informació
Labarta Mancho, Jesús JoséMés informacióMés informacióMés informació
Valero Cortés, MateoMés informacióMés informacióMés informació
Document typeConference report
Defense date2015-05-05
PublisherBarcelona Supercomputing Center
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
This work is protected by the corresponding intellectual and industrial property rights. Except where otherwise noted, its contents are licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
Current high performance computing architectures are composed of large shared memory NUMA nodes, among other components. Such nodes are becoming increasingly complex as they have several NUMA domains with different access latencies depending on the core where the access is issued. In this work, we propose techniques based on graph partitioning to efficiently mitigate the negative impact of NUMA effects on parallel applications performance, which are able to improve the execution time of OpenMP parallel codes 2.02× times on average when run on architectures with strong NUMA effects.
CitationSánchez Barrera, I. [et al.]. Using graph partitioning to accelerate task-based parallel applications. A: 3rd BSC International Doctoral Symposium. "Book of abstracts". Barcelona: Barcelona Supercomputing Center, 2015, p. 109-111. 
URIhttp://hdl.handle.net/2117/91105
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