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TAFFO: The compiler-based precision tuner

Cattaneo, Daniele; Chiari, Michele; Agosta, Giovanni; Cherubin, Stefano

Authors

Daniele Cattaneo

Michele Chiari

Giovanni Agosta

Stefano Cherubin



Abstract

We present taffo, a framework that automatically performs precision tuning to exploit the performance/accuracy trade-off. In order to avoid expensive dynamic analyses, taffo leverages programmer annotations which encapsulate domain knowledge about the conditions under which the software being optimized will run. As a result, taffo is easy to use and provides state-of-the-art optimization efficacy in a variety of hardware configurations and application domains. We provide guidelines for the effective exploitation of taffo by showing a typical example of usage on a simple application, achieving a speedup up to 60% at the price of an absolute error of 3.53×10−5. taffo is modular and based on the solid llvm technology, which allows extensibility to improved analysis techniques, and comprehensive support for the most common precision-reduced data types and programming languages. As a result, the taffo technology has been selected as the precision tuning tool of the European Training Network on Approximate Computing.

Journal Article Type Article
Acceptance Date Oct 15, 2022
Online Publication Date Nov 3, 2022
Publication Date 2022-12
Deposit Date Nov 3, 2022
Publicly Available Date Nov 3, 2022
Journal SoftwareX
Print ISSN 2352-7110
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 20
Article Number 101238
DOI https://doi.org/10.1016/j.softx.2022.101238
Keywords Mixed precision, Compiler, Approximate computing
Public URL http://researchrepository.napier.ac.uk/Output/2948016
Publisher URL https://www.sciencedirect.com/science/article/pii/S235271102200156X

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