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Lightning Talk – Automating Loop Optimization with Code Samples and AST Matching
DescriptionLoop modifications are critical steps of code optimization. They can allow other techniques to be used, improve performance by reducing memory traffic with better data locality, or reduce loop overhead. Unfortunately, the error-prone index arithmetic calculations involved can make these modifications cumbersome for a human programmer. These modifications also cannot be implemented using a text-based tool, such as sed, because they require semantic knowledge about the keywords and symbols used. Compilers also may not implement all of these transformations, or may not always apply them if correctness or profitability analyses are inconclusive.
Previously, we presented an approach to code rewriting, MARTINI, which exposes complex and semantic-driven rewrite capabilities, based in the program's abstract syntax tree (AST), to users in a simple and natural way. In this paper, we show how this approach can be used to implement source-based loop optimizations with only before-and-after code samples written in the source language.
Previously, we presented an approach to code rewriting, MARTINI, which exposes complex and semantic-driven rewrite capabilities, based in the program's abstract syntax tree (AST), to users in a simple and natural way. In this paper, we show how this approach can be used to implement source-based loop optimizations with only before-and-after code samples written in the source language.
Event Type
Workshop
TimeSunday, 12 November 202311:37am - 11:44am MST
Location601
Compilers
Heterogeneous Computing
Performance Optimization
W