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.
Type de document :
Communication dans un congrès
Control, Decision and Information Technologies (CoDIT), Apr 2016, Saint Julian's, Malta. 〈http://www.codit2016.com〉. 〈10.1109/CoDIT.2016.7593626〉
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https://hal.archives-ouvertes.fr/hal-01290292
Contributeur : Alexandre Chapoutot <>
Soumis le : jeudi 17 mars 2016 - 21:32:46
Dernière modification le : vendredi 17 février 2017 - 16:13:48

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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. 〈http://www.codit2016.com〉. 〈10.1109/CoDIT.2016.7593626〉. 〈hal-01290292〉

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