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Syst."],"published-print":{"date-parts":[[2019,11,30]]},"abstract":"<jats:p>Dynamic cache reconfiguration (DCR) is an effective technique to optimize energy consumption in many-core architectures. While early work on DCR has shown promising energy saving opportunities, prior techniques are not suitable for many-core architectures since they do not consider the interactions and tight coupling between memory, caches, and network-on-chip (NoC) traffic. In this article, we propose an efficient cache reconfiguration framework in NoC-based many-core architectures. The proposed work makes three major contributions. First, we model a distributed directory based many-core architecture similar to Intel Xeon Phi architecture. Next, we propose an efficient cache reconfiguration framework that considers all significant components, including NoC, caches, and main memory. Finally, we propose a machine learning--based framework that can reduce the exploration time by an order of magnitude with negligible loss in accuracy. Our experimental results demonstrate 18.5% energy savings on average compared to base cache configuration.<\/jats:p>","DOI":"10.1145\/3350422","type":"journal-article","created":{"date-parts":[[2019,9,9]],"date-time":"2019-09-09T12:10:26Z","timestamp":1568031026000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":20,"title":["Efficient Cache Reconfiguration Using Machine Learning in NoC-Based Many-Core CMPs"],"prefix":"10.1145","volume":"24","author":[{"given":"Subodha","family":"Charles","sequence":"first","affiliation":[{"name":"University of Florida, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alif","family":"Ahmed","sequence":"additional","affiliation":[{"name":"University of Florida, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Umit Y.","family":"Ogras","sequence":"additional","affiliation":[{"name":"Arizona State University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prabhat","family":"Mishra","sequence":"additional","affiliation":[{"name":"University of Florida, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,9,9]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS\u201909)","author":"Agarwal Niket","unstructured":"Niket Agarwal , Tushar Krishna , Li-Shiuan Peh , and Niraj K. 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