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DTSTART;TZID=America/Chicago:20181115T140000
DTEND;TZID=America/Chicago:20181115T143000
UID:submissions.supercomputing.org_SC18_sess192_pap244@linklings.com
SUMMARY:Fault Tolerant One-Sided Matrix Decompositions on Heterogeneous Sy
 stems with GPUs
DESCRIPTION:Jieyang Chen, Hongbo Li, Sihuan Li, and Xin Liang (University 
 of California, Riverside); Panruo Wu (University of Houston); Dingwen Tao 
 (University of Alabama); Kaiming Ouyang, Yuanlai Liu, and Kai Zhao (Univer
 sity of California, Riverside); Qiang Guan (Kent State University); and Zi
 zhong Chen (University of California, Riverside)\n\nCurrent algorithm-base
 d fault tolerance (ABFT) approach for one-sided matrix decomposition on he
 terogeneous systems with GPUs have following limitations: (1) they do not 
 provide sufficient protection as most of them only maintain checksum in on
 e dimension; (2) their checking scheme is not efficient due to redundant c
 hecksum verifications; (3) they fail to protect PCIe communication; (4) th
 e checksum calculation based on a special type of matrix multiplication is
  far from efficient. By overcoming the above limitations, we design an eff
 icient ABFT approach providing stronger protection for one-sided matrix de
 composition methods on heterogeneous systems. First, we provide full matri
 x protection by using checksums in two dimensions. Second, our checking sc
 heme 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.\n\nTag: Algorithms, Architectures, GPUs, Linear Algebra, N
 etworks, Resiliency\n\nRegistration Category: Tech Program Reg Pass\n\nSes
 sion Chair: Steven A. Wright (University of York, England)\n\n
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