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Topology-Aware Load-Balance Schemes for Heterogeneous Graph Processing

Topology-Aware Load-Balance Schemes for Heterogeneous Graph Processing

Copyright: © 2018 |Pages: 31
ISBN13: 9781522537991|ISBN10: 1522537996|EISBN13: 9781522538004
DOI: 10.4018/978-1-5225-3799-1.ch005
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MLA

Alberto Garcia-Robledo, et al. "Topology-Aware Load-Balance Schemes for Heterogeneous Graph Processing." Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities, IGI Global, 2018, pp.113-143. https://doi.org/10.4018/978-1-5225-3799-1.ch005

APA

A. Garcia-Robledo, A. Diaz-Perez, & G. Morales-Luna (2018). Topology-Aware Load-Balance Schemes for Heterogeneous Graph Processing. IGI Global. https://doi.org/10.4018/978-1-5225-3799-1.ch005

Chicago

Alberto Garcia-Robledo, Arturo Diaz-Perez, and Guillermo Morales-Luna. "Topology-Aware Load-Balance Schemes for Heterogeneous Graph Processing." In Creativity in Load-Balance Schemes for Multi/Many-Core Heterogeneous Graph Computing: Emerging Research and Opportunities. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-3799-1.ch005

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Abstract

Inspired by the insights presented in Chapters 2, 3, and 4, in this chapter the authors present the KCMAX (K-Core MAX) and the KCML (K-Core Multi-Level) frameworks: novel k-core-based graph partitioning approaches that produce unbalanced partitions of complex networks that are suitable for heterogeneous parallel processing. Then they use KCMAX and KCML to explore the configuration space for accelerating BFSs on large complex networks in the context of TOTEM, a BSP heterogeneous GPU + CPU HPC platform. They study the feasibility of the heterogeneous computing approach by systematically studying different graph partitioning strategies, including the KCMAX and KCML algorithms, while processing synthetic and real-world complex networks.

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