文章基本信息

标题：Tool Support for Software Lookup Table Optimization
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作者：Chris Wilcox, Michelle Mills Strout ; James M. Bieman
期刊名称：Scientific Programming
印刷版ISSN：1058-9244
出版年度：2011
卷号：19
DOI：10.3233/SPR-2011-0329
出版社：Hindawi Publishing Corporation
摘要：A number of scientific applications are performance-limited by expressions that repeatedly call costly elementary functions. Lookup table (LUT) optimization accelerates the evaluation of such functions by reusing previously computed results. LUT methods can speed up applications that tolerate an approximation of function results, thereby achieving a high level of fuzzy reuse. One problem with LUT optimization is the difficulty of controlling the tradeoff between performance and accuracy. The current practice of manual LUT optimization adds programming effort by requiring extensive experimentation to make this tradeoff, and such hand tuning can obfuscate algorithms. In this paper we describe a methodology and tool implementation to improve the application of software LUT optimization. Our Mesa tool implements source-to-source transformations for C or C