Data-Types Optimization for Floating-Point Formats by Program Transformation

Abstract : In floating-point arithmetic, a desirable property of computations is to be accurate, since in many industrial context small or large perturbations due to round-off errors may cause considerable damages. To cope with this matter of facts, we have developed a tool which corrects these errors by transforming automatically programs in a source to source manner. Our transformation, relying on static analysis by abstract abstraction, concerns pieces of code with assignments, conditionals and loops. By transforming programs, we significantly optimize the numer- ical accuracy of computations by minimizing the error relatively to the exact result. An interesting side-effect of our technique is that more accurate computations may make it possible to use smaller data-types. In this article, we show that our transformed programs, executed in single precision, may compete with not transformed codes executed in double precision.
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Contributor : Alexandre Chapoutot <>
Submitted on : Thursday, March 17, 2016 - 9:32:46 PM
Last modification on : Friday, December 8, 2017 - 3:08:03 PM



Nasrine Damouche, Matthieu Martel, Alexandre Chapoutot. Data-Types Optimization for Floating-Point Formats by Program Transformation. Control, Decision and Information Technologies (CoDIT), Apr 2016, Saint Julian's, Malta. ⟨10.1109/CoDIT.2016.7593626⟩. ⟨hal-01290292⟩



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