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dc.contributor.authorChang, Chia-Jungen_US
dc.contributor.authorPeng, Yin-Chien_US
dc.contributor.authorChen, Chien-Chihen_US
dc.contributor.authorChen, Tien-Fuen_US
dc.contributor.authorYew, Pen-Chungen_US
dc.date.accessioned2017-04-21T06:48:27Z-
dc.date.available2017-04-21T06:48:27Z-
dc.date.issued2015en_US
dc.identifier.isbn978-1-4799-6275-4en_US
dc.identifier.urihttp://hdl.handle.net/11536/136068-
dc.description.abstractFor the last decade, there have been varying techniques for hardware prefetching to improve the system performance. However, untimely prefetching may pollution caches and resulting into significant performance degradation. In this work, we introduce an Adaptive Granularity and coordinated Prefetching (AGP) that consists of a coarse-grained and fine-grained prefetched mechanism to provide a better caching environment for parallel applications. AGP targets on the degree-adjusting and location-choosing and tries to minimize the influence caused by prefetcher for each core. AGP could produce more timely prefetched requests reducing the cache pollutions and contentions. Across a variety of PARSEC benchmarks, AGP can contribute 6.5% (up to 36%) of performance improvement on a 4-core multicore system compared to the non-prefetching.en_US
dc.language.isoen_USen_US
dc.titleAdaptive Granularity and Coordinated Management for Timely Prefetching in Multi-Core Systemsen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2015 International symposium on VLSI Design, Automation and Test (VLSI-DAT)en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000380584400085en_US
dc.citation.woscount0en_US
Appears in Collections:Conferences Paper