Fault tolerant one-sided matrix decompositions on heterogeneous systems with GPUs

Jieyang Chen, Hongbo Li, Sihuan Li, Xin Liang, Panruo Wu, Dingwen Tao, Kaiming Ouyang, Yuanlai Liu, Kai Zhao, Qiang Guan, Zizhong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Current algorithm-based fault tolerance (ABFT) approach for one-sided matrix decomposition on heterogeneous systems with GPUs have following limitations: (1) they do not provide sufficient protection as most of them only maintain checksum in one dimension; (2) their checking scheme is not efficient due to redundant checksum verifications; (3) they fail to protect PCIe communication; and (4) the checksum calculation based on a special type of matrix multiplication is far from efficient. By overcoming the above limitations, we design an efficient ABFT approach providing stronger protection for one-sided matrix decomposition methods on heterogeneous systems. First, we provide full matrix protection by using checksums in two dimensions. Second, our checking scheme is more efficient by prioritizing the checksum verification according to the sensitivity of matrix operations to soft errors. Third, we protect PCIe communication by reordering checksum verifications and decomposition steps. Fourth, we accelerate the checksum calculation by 1.7x via better utilizing GPUs.

Original languageEnglish
Title of host publicationProceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018
Pages854-865
Number of pages12
ISBN (Electronic)9781538683842
DOIs
StatePublished - Mar 11 2019
Event2018 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018 - Dallas, United States
Duration: Nov 11 2018Nov 16 2018

Publication series

NameProceedings - International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018

Conference

Conference2018 International Conference for High Performance Computing, Networking, Storage, and Analysis, SC 2018
Country/TerritoryUnited States
CityDallas
Period11/11/1811/16/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

  • Algorithm-based fault tolerance
  • GPU
  • Heterogeneous system
  • Linear algebra
  • Matrix decomposition

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Theoretical Computer Science

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