Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Global register allocation at link time
SIGPLAN '86 Proceedings of the 1986 SIGPLAN symposium on Compiler construction
ISCA '86 Proceedings of the 13th annual international symposium on Computer architecture
Program optimization for instruction caches
ASPLOS III Proceedings of the third international conference on Architectural support for programming languages and operating systems
Profile guided code positioning
PLDI '90 Proceedings of the ACM SIGPLAN 1990 conference on Programming language design and implementation
Register allocation across procedure and module boundaries
PLDI '90 Proceedings of the ACM SIGPLAN 1990 conference on Programming language design and implementation
Parallel processing: a smart compiler and a dumb machine
SIGPLAN '84 Proceedings of the 1984 SIGPLAN symposium on Compiler construction
Accelerating multicore reuse distance analysis with sampling and parallelization
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
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There is a growing interest in optimizations that depend on or benefit from an execution profile that tells where time is spent. How well does a profile from one run describe the behavior of a different run, and how does this compare with the behavior predicted by static analysis of the program? This paper defines two abstract measures of how well a profile predicts actual behavior. According to these measures, real profiles indeed do better than estimated profiles, usually. A perfect profile from an earlier run with the same data set, however, does better still, sometimes by a factor of two. Unfortunately, using such a profile is unrealistic, and can lead to inflated expectations of a profile-driven optimization.