Exploring the Interplay of Resilience and Energy Consumption for a Task-Based Partial Differential Equations Preconditioner

Technical Report · Tue Mar 01 04:00:00 EST 2016

DOI:https://doi.org/10.2172/1561016· OSTI ID:1561016

Rizzi, Francesco ^[1]; Morris, Karla Vanessa ^[1]; Sargsyan, Khachik ^[1]; Mycek, Paul ^[2]; Safta, Cosmin ^[1]; Le Maître, Olivier ^[3]; Knio, Omar ^[2]; Debusschere, Bert ^[1]

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1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
2. Duke Univ., Durham, NC (United States)
3. Centre National de la Recherche Scientifique (CNRS), Orsay (France). Laboratoire d'Informatique pour la Mécanique et les Sciences de l'ingénieur (LIMSI)

We discuss algorithm-based resilience to silent data corruption (SDC) in a task- based domain-decomposition preconditioner for partial differential equations (PDEs). The algorithm exploits a reformulation of the PDE as a sampling problem, followed by a solution update through data manipulation that is resilient to SDC. The implementation is based on a server-client model where all state information is held by the servers, while clients are designed solely as computational units. Scalability tests run up to ~ 51 K cores show a parallel efficiency greater than 90%. We use a 2D elliptic PDE and a fault model based on random single bit-flip to demonstrate the resilience of the application to synthetically injected SDC. We discuss two fault scenarios: one based on the corruption of all data of a target task, and the other involving the corruption of a single data point. We show that for our application, given the test problem considered, a four-fold increase in the number of faults only yields a 2% change in the overhead to overcome their presence, from 7% to 9%. We then discuss potential savings in energy consumption via dynamics voltage/frequency scaling, and its interplay with fault-rates, and application overhead.

• Research Organization: Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC04-94AL85000; AC02-05CH11231
• OSTI ID: 1561016
• Report Number(s): SAND--2016-2091; 619982
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING