SC15 Austin, TX

Reduced-Precision Floating-Point Analysis

Authors: Michael O. Lam (James Madison University), Jeffrey K. Hollingsworth (University of Maryland)

Abstract: Floating-point computation is ubiquitous in scientific computing, but rounding error can compromise the results of extended calculations. In previous work [1], we presented techniques for automated mixed-precision analysis and configuration. We now present new techniques that use binary instrumentation and modification to do fine-grained floating-point precision analysis, simulating any level of precision less than or equal to the precision of the original program. These techniques have lower overhead and provide more general insights than previous mixed-precision analyses. We also present a novel histogram-based visualization of a program’s floating-point precision sensitivity, and an incremental search technique that gives the user more control over the precision analysis process.

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