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VMCAI 2017
Sun 15 - Tue 17 January 2017
co-located with POPL 2017
Sun 15 Jan 2017 11:30 - 12:00 at Amphitheater 44 - Program Analysis Chair(s): Boris Yakobowski

Floating-point arithmetic is a loosely standardized approxi- mation of real arithmetic available on many computers today. Architec- tural and compiler differences can lead to different calculations across platforms, for identical inputs. If left untreated, platform dependence, called volatility in this paper, seriously interferes with result reproducibil- ity and program portability. We present an approach to stabilizing float- ing-point programs against volatility. Our approach, dubbed provenance analysis, traces differences observed in a given intermediate expression E back to volatility in preceding statements, and quantifies each such statement’s contribution to the volatility in E. Program fragments con- tributing the most are candidates for stabilization, which happens by disambiguating the arithmetic using expression rewriting and statement- level control pragmas. The benefit of local program stabilization is that compilers are free to engage performance- or precision-enhancing op- timizations across harmless program fragments. We have implemented our technique in a dynamic analysis tool that reports both volatility and provenance information. We demonstrate that local program stabiliza- tion often suffices to reduce platform dependence to an acceptable level.

Sun 15 Jan
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10:30 - 12:00: VMCAI - Program Analysis at Amphitheater 44
Chair(s): Boris YakobowskiCEA - LIST
VMCAI-2017-papers10:30 - 11:00
Wei WangGoogle, Inc., Clark BarrettStanford University, Thomas WiesNew York University
File Attached
VMCAI-2017-papers11:00 - 11:30
Asya FrumkinTel Aviv University, Yotam FeldmanTel Aviv University, Ondřej LhotákUniversity of Waterloo, Canada, Oded PadonTel Aviv University, Mooly SagivTel Aviv University, Sharon ShohamTel Aviv university
File Attached
VMCAI-2017-papers11:30 - 12:00
Yijia GuNortheastern University, Thomas WahlNortheastern University