2017 IEEE International Conference on Cluster Computing Thoughtful Precision in Mini-apps Shane Fogerty∗, Siddhartha Bishnu∗, Yuliana Zamora∗†, Laura Monroe∗ Steve Poole∗, Michael Lam‡, Joe Schoonover§, and Robert Robey∗ ∗Los Alamos National Laboratory †University of Chicago ‡James Madison University §Cooperative Institute for Research in Environmental Sciences (CIRES) Emails:{sfogerty,siddhartha.bishnu,lmonroe,swpoole,brobey}@lanl.gov,
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[email protected] Abstract—Approximate computing addresses many of the to computational fidelity. Our work in this area is part of identified challenges for exascale computing, leading to perfor- the DOE’s Beyond Moore’s Law program as part of the mance improvements that may include changes in fidelity of Presidential Executive Order for the National Strategic Com- calculation. In this paper, we examine approximate approaches puting Initiative (NSCI) Strategic Plan [2], intended to sustain for a range of DOE-relevant computational problems run on a and enhance U.S. leadership in high-performance computing variety of architectures as a proxy for the wider set of exascale- (HPC) with particular reference to exascale and post-Moore’s class applications. We show anticipated improvements in computational and era goals. memory performance and in power savings. We also assess appli- cation correctness when operating under conditions of reduced precision, and show that this is within acceptable bounds. Finally, II. APPROXIMATE COMPUTING FOR HPC APPLICATIONS we discuss the trade space between performance, power, precision and resolution for these mini-apps, and optimized solutions Our early investigations into inexact computing for HPC attained within given constraints, with positive implications for applications concentrate on power and performance gains and application of approximate computing to exascale-class problems.