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DTSTART:19700308T020000
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DTSTAMP:20181221T160910Z
LOCATION:C141/143/149
DTSTART;TZID=America/Chicago:20181115T133000
DTEND;TZID=America/Chicago:20181115T150000
UID:submissions.supercomputing.org_SC18_sess192@linklings.com
SUMMARY:Resilience 3: GPUs
DESCRIPTION:Paper\nAlgorithms, Architectures, GPUs, Linear Algebra, Networ
 ks, Resiliency, Tech Program Reg Pass\n\nPRISM: Predicting Resilience of G
 PU Applications Using Statistical Methods\n\nKalra, Previlon, Li, Rubin, K
 aeli\n\nAs Graphics Processing Units (GPUs) become more pervasive in HPC a
 nd safety-critical domains, ensuring that GPU applications can be protecte
 d from data corruption grows in importance. Despite prior efforts to mitig
 ate errors, we still lack a clear understanding of how resilient these app
 lications ar...\n\n---------------------\nFault Tolerant One-Sided Matrix 
 Decompositions on Heterogeneous Systems with GPUs\n\nChen, Li, Li, Liang, 
 Wu...\n\nCurrent algorithm-based fault tolerance (ABFT) approach for one-s
 ided matrix decomposition on heterogeneous systems with GPUs have followin
 g limitations: (1) they do not provide sufficient protection as most of th
 em only maintain checksum in one dimension; (2) their checking scheme is n
 ot efficient ...\n\n---------------------\nOptimizing Software-Directed In
 struction Replication for GPU Error Detection\n\nMahmoud, Hari, Sullivan, 
 Tsai, Keckler\n\nApplication execution on safety-critical and high-perform
 ance computer systems must be resilient to transient errors. As GPUs becom
 e more pervasive in such systems, they must supplement ECC/parity for majo
 r storage structures with reliability techniques that cover more of the GP
 U hardware logic.  In...\n
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