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DTSTAMP:20181221T160731Z
LOCATION:C141/143/149
DTSTART;TZID=America/Chicago:20181115T113000
DTEND;TZID=America/Chicago:20181115T120000
UID:submissions.supercomputing.org_SC18_sess207_pap382@linklings.com
SUMMARY:Detecting MPI Usage Anomalies via Partial Program Symbolic Executi
 on
DESCRIPTION:Paper\nLinear Algebra, Memory, MPI, OpenMP, Programming System
 s, Tools, Tech Program Reg Pass\n\nDetecting MPI Usage Anomalies via Parti
 al Program Symbolic Execution\n\nYe, Zhao, Sarkar\n\nMPI is a message pass
 ing based programming model for distributed-memory parallelism that has be
 en had been widely used for programming supercomputers for over 25 years. 
 However, debugging and verification of MPI programs is widely recognized t
 o be a deep technical challenge. This challenge is further exacerbated by 
 a recent increase in the use of nonblocking MPI operations that bring new 
 classes of bugs related to data races.\n\nIn this paper, we introduce a ne
 w MPI program debugging approach based on partial symbolic execution so as
  to avoid the false alarms inherent in the static analysis based methodolo
 gy. Compared with the dynamic approach, our approach can be applied to inc
 omplete programs and explore multiple execution paths, thereby bringing mo
 re flexibility and precision. By comparing with well known static/dynamic 
 tools on real-world MPI applications, our approach shows same precision as
  the dynamic tool and avoids false positive produced by the static tool.
URL:https://sc18.supercomputing.org/presentation/?id=pap382&sess=sess207
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