BibTeX
@MISC{Young98path-basedcompilation,
author = {Reginald Clifford Young},
title = {Path-based Compilation},
year = {1998}
}
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Abstract
Many compilers use profiles of programs to direct the focus and degree of performance optimizations. Profiles are statistics from program runs, usually collected at individual points in the program text, e.g., branches, call sites, or memory accesses. But optimizations based on individual sample points in the program miss an important detail of program behavior: how pieces of the program relate to each other dynamically. A path profile collects statistics over paths (sequences of points) in the program, linking the statistics to the dynamic behavior. By instrumenting and collecting path profiles through a program, we can exploit this dynamic behavior, improving performance more than point profiling techniques have allowed. This thesis shows how to collect path profiles efficiently, then applies the path profiles to two optimizations, static correlated branch prediction and path-based superblock scheduling. These two optimizations address different performance aspects of modern machine...
