Abstract
Runtime code generation that uses the values of one or more variables to generate specialized code is called value-specific optimization. Typically, value-specific optimization focuses on variables that are modified much less frequently than they are referenced; we call these glacial variables. In current systems that use runtime code generation, glacial variables are identified by programmer directives. Next, we describe glacial variable analysis, the first data-flow analysis for automatically identifying glacial variables. We introduce the term staging analysis to describe analyses that divide a program into stages or use the stage structure of a program. Glacial variable analysis is an interprocedural staging analysis that identifies the relative modification and reference frequencies for each variable and expression. Later, several experiments are given to characterize a set of benchmark programs with respect to their stage structure, and we show how often value-specific optimization might be applied. Finally, we explain how staging analysis relates to runtime code generation, briefly describe glacial variable analysis and present some initial results.
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Autrey, T., Wolfe, M. Initial Results for Glacial Variable Analysis. International Journal of Parallel Programming 26, 43–64 (1998). https://doi.org/10.1023/A:1018739006820
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DOI: https://doi.org/10.1023/A:1018739006820