SlimSell: A Vectorizable Graph Representation for Breadth-First Search

MacIej Besta, Florian Marending, Edgar Solomonik, Torsten Hoefler

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Vectorization and GPUs will profoundly change graph processing. Traditional graph algorithms tuned for 32-or 64-bit based memory accesses will be inefficient on architectures with 512-bit wide (or larger) instruction units that are already present in the Intel Knights Landing (KNL) manycore CPU. Anticipating this shift, we propose SlimSell: A vectorizable graph representation to accelerate Breadth-First Search (BFS) based on sparse-matrix dense-vector (SpMV) products. SlimSell extends and combines the state-of-the-art SIMD-friendly Sell-C-σ matrix storage format with tropical, real, boolean, and sel-max semiring operations. The resulting design reduces the necessary storage (by up to 50%) and thus pressure on the memory subsystem. We augment SlimSell with the SlimWork and SlimChunk schemes that reduce the amount of work and improve load balance, further accelerating BFS. We evaluate all the schemes on Intel Haswell multicore CPUs, the state-of-the-art Intel Xeon Phi KNL manycore CPUs, and NVIDIA Tesla GPUs. Our experiments indicate which semiring offers highest speedups for BFS and illustrate that SlimSell accelerates a tuned Graph500 BFS code by up to 33%. This work shows that vectorization can secure high-performance in BFS based on SpMV products; the proposed principles and designs can be extended to other graph algorithms.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages32-41
Number of pages10
ISBN (Electronic)9781538639146
DOIs
StatePublished - Jun 30 2017
Event31st IEEE International Parallel and Distributed Processing Symposium, IPDPS 2017 - Orlando, United States
Duration: May 29 2017Jun 2 2017

Publication series

NameProceedings - 2017 IEEE 31st International Parallel and Distributed Processing Symposium, IPDPS 2017

Other

Other31st IEEE International Parallel and Distributed Processing Symposium, IPDPS 2017
Country/TerritoryUnited States
CityOrlando
Period5/29/176/2/17

Keywords

  • BFS
  • Graph Algorithms
  • Graph Processing
  • Graph Representations
  • Graph Storage
  • Vectorization

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Hardware and Architecture

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