Versioned distributed arrays for resilience in scientific applications: Global view resilience

Chien, A.; Balaji, P.; Beckman, P.; Dun, N.; Fang, A.; Fujita, H.; Iskra, K.; Rubenstein, Z.; Zheng, Z.; Schreiber, R.; Hammond, J.; Dinan, J.; Laguna, I.; Richards, D.; Dubey, A.; van Straalen, B.; Hoemmen, M.; Heroux, M.; Teranishi, K.; Siegel, A.

doi:10.1016/j.procs.2015.05.187

Versioned distributed arrays for resilience in scientific applications: Global view resilience

Journal Article · Mon Jun 01 00:00:00 EDT 2015 · Procedia Computer Science

DOI:https://doi.org/10.1016/j.procs.2015.05.187· OSTI ID:1196863

Chien, A. ^[1]; Balaji, P. ^[2]; Beckman, P. ^[2]; Dun, N. ^[1]; Fang, A. ^[3]; Fujita, H. ^[1]; Iskra, K. ^[2]; Rubenstein, Z. ^[3]; Zheng, Z. ^[4]; Schreiber, R. ^[4]; Hammond, J. ^[5]; Dinan, J. ^[5]; Laguna, I. ^[6]; Richards, D. ^[6]; Dubey, A. ^[7]; van Straalen, B. ^[7]; Hoemmen, M. ^[8]; Heroux, M. ^[8]; Teranishi, K. ^[8]; Siegel, A. ^[2]

Univ. of Chicago. Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Univ. of Chicago. Chicago, IL (United States)
Intel Corp. Santa Clara, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Univ. of Chicago. Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Intel Corp. Santa Clara, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Exascale studies project reliability challenges for future high-performance computing (HPC) systems. We propose the Global View Resilience (GVR) system, a library that enables applications to add resilience in a portable, application-controlled fashion using versioned distributed arrays. We describe GVR’s interfaces to distributed arrays, versioning, and cross-layer error recovery. Using several large applications (OpenMC, the preconditioned conjugate gradient solver PCG, ddcMD, and Chombo), we evaluate the programmer effort to add resilience. The required changes are small (<2% LOC), localized, and machine-independent, requiring no software architecture changes. We also measure the overhead of adding GVR versioning and show that generally overheads <2% are achieved. We conclude that GVR’s interfaces and implementation are flexible and portable and create a gentle-slope path to tolerate growing error rates in future systems.

Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

Grant/Contract Number:: AC02-05CH11231; AC02-06CH11357; AC04-94AL85000; SC0008603

OSTI ID:: 1196863

Alternate ID(s):: OSTI ID: 1214658
OSTI ID: 1528959

Journal Information:: Procedia Computer Science, Journal Name: Procedia Computer Science Journal Issue: C Vol. 51; ISSN 1877-0509

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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