Putting pointer analysis to work
POPL '98 Proceedings of the 25th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
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Proceedings of the tenth annual ACM symposium on Parallel algorithms and architectures
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PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
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Proceedings of the 14th international conference on Supercomputing
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IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
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LCPC '99 Proceedings of the 12th International Workshop on Languages and Compilers for Parallel Computing
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Journal of Experimental Algorithmics (JEA)
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Proceedings of the 23rd international conference on Supercomputing
An empirical study on the granularity of pointer analysis in c programs
LCPC'02 Proceedings of the 15th international conference on Languages and Compilers for Parallel Computing
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Traditional compiler optimizations such as loop invariant removal and common sub-expression elimination are standard in all optimizing compilers. The purpose of the paper is to present new versions of these optimizations that apply to programs using dynamically allocated data structures, and to show the effect of these optimizations on the performance of multithreaded programs. We show how heap pointer analyses can be used to support better dependence testing, new applications of the above traditional optimizations, and high quality code generation for multithreaded architectures. We have implemented these analyses and optimizations in the EARTH-C compiler to study their impact on the performance of generated multithreaded code. We provide both static and dynamic measurements showing the effect of the optimizations applied individually, and together. We note several general trends, and discuss the performance tradeoffs and suggest when specific optimizations are generally beneficial.