Profile inference revisited
نویسندگان
چکیده
Profile-guided optimization (PGO) is an important component in modern compilers. By allowing the compiler to leverage program’s dynamic behavior, it can often generate substantially faster binaries. Sampling-based profiling state-of-the-art technique for collecting execution profiles data-center environments. However, lowered profile accuracy caused by sampling fully optimized binary hurts benefits of PGO; thus, problem overcome inaccuracy a after collected. In this paper we tackle problem, which also known as inference and rectification . We investigate classical approach inference, based on computing minimum-cost maximum flows control-flow graph, develop extended model capturing desired properties real-world profiles. Next provide solid theoretical foundation corresponding studying its algorithmic aspects. then describe new efficient algorithm along with implementation open-source compiler. An extensive evaluation existing techniques variety applications, including Facebook production workloads SPEC CPU benchmarks, indicates that method outperforms competitors significantly improving data performance generated
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ژورنال
عنوان ژورنال: Proceedings of the ACM on programming languages
سال: 2022
ISSN: ['2475-1421']
DOI: https://doi.org/10.1145/3498714