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- W3201382364 abstract "Locality analysis is important since the speed ofaccessing memory is slower than the speed of computing. Inaddition, the emerging persistent memory brings speed andendurance imbalance between reads and writes. Caching is aneffective way to address these problems. To maximize cacheperformance, it requires understanding program locality for bothcache loads and writebacks. In this dissertation, I will firstintroduce locality analysis based on reuse intervals, which can bemeasured effciently using the compiler construct dependencedistance. Then, I will describe a more general method called staticparallel sampling. It analyzes loop-based code by generatingsampler code which is run to measure reuse intervals. It canpredict precise cache-line granularity miss ratio curves forcomplex loops with non-linear array references and even branches.Finally, I will describe the reuse interval based locality modelfor writebacks, which can be analyzed using static parallelsampling." @default.
- W3201382364 created "2021-09-27" @default.
- W3201382364 creator A5001330715 @default.
- W3201382364 date "2019-01-01" @default.
- W3201382364 modified "2023-09-27" @default.
- W3201382364 title "Program locality analysis based on reuseintervals" @default.
- W3201382364 hasPublicationYear "2019" @default.
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