ARI
Author(s) -
Viacheslav V. Fedorov,
Sheng Qiu,
A. L. Narasimha Reddy,
Paul V. Gratz
Publication year - 2013
Publication title -
acm transactions on architecture and code optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.263
H-Index - 41
eISSN - 1544-3973
pISSN - 1544-3566
DOI - 10.1145/2543697
Subject(s) - computer science , cache , energy consumption , cpu cache , phase change memory , embedded system , demand paging , memory management , parallel computing , operating system , interleaved memory , semiconductor memory , ecology , engineering physics , engineering , biology , phase change
Decreasing the traffic from the CPU LLC to main memory is a very important issue in modern systems. Recent work focuses on cache misses, overlooking the impact of writebacks on the total memory traffic, energy consumption, IPC, and so forth. Policies that foster a balanced approach, between reducing write traffic to memory and improving miss rates, can increase overall performance and improve energy efficiency and memory system lifetime for NVM memory technology, such as phase-change memory (PCM). We propose Adaptive Replacement and Insertion (ARI), an adaptive approach to last-level CPU cache management, optimizing the two parameters (miss rate and writeback rate) simultaneously. Our specific focus is to reduce writebacks as much as possible while maintaining or improving the miss rate relative to conventional LRU replacement policy. ARI reduces LLC writebacks by 33%, on average, while also decreasing misses by 4.7%, on average. In a typical system, this boosts IPC by 4.9%, on average, while decreasing energy consumption by 8.9%. These results are achieved with minimal hardware overheads.
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