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DTSTART:19700308T020000
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DTSTAMP:20260522T150124Z
LOCATION:C141/143/149
DTSTART;TZID=America/Chicago:20181115T103000
DTEND;TZID=America/Chicago:20181115T110000
UID:submissions.supercomputing.org_SC18_sess207_pap179@linklings.com
SUMMARY:Dynamic Data Race Detection for OpenMP Programs
DESCRIPTION:Yizi Gu and John Mellor-Crummey (Rice University)\n\nTwo concu
 rrent accesses to a shared variable that are unordered by synchronization 
 are said to be a data race if at least one access is a write. Data races c
 ause shared memory parallel programs to behave unpredictably. This paper d
 escribes ROMP -- a tool for detecting data races in executions of scalable
  parallel applications that employ OpenMP for node-level parallelism. The 
 complexity of OpenMP, which includes primitives for managing data environm
 ents, SPMD and SIMD parallelism, work sharing, tasking, mutual exclusion, 
 and ordering, presents a formidable challenge for data race detection. ROM
 P is a hybrid data race detector that tracks accesses, access orderings, a
 nd mutual exclusion. Unlike other OpenMP race detectors, ROMP detects race
 s with respect to logical parallelism rather than implementation threads. 
 Experiments show that ROMP yields precise race reports for a broader set o
 f OpenMP constructs than prior state-of-the-art race detectors.\n\nTag: Li
 near Algebra, Memory, MPI, OpenMP, Programming Systems, Tools\n\nRegistrat
 ion Category: Tech Program Reg Pass\n\nSession Chair: Naoya Maruyama (NVID
 IA Corporation)\n\n
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