Locality-aware data replication in the Last-Level Cache
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Devadas_Locality-aware.pdf
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894.54 KB
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Adobe PDF
Checksum (MD5)
e0d9e10afee4c604547e0ecb975a2ea4
Author(s)
Kurian, George
Devadas, Srinivas
Khan, Omer
Date Issued
February 2014
Journal
Proceedings of the 2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Kurian, George, Srinivas Devadas, and Omer Khan. “Locality-Aware Data Replication in the Last-Level Cache.” 2014 IEEE 20th International Symposium on High Performance Computer Architecture (HPCA) (February 2014).
Version
Author's final manuscript
Abstract
Next generation multicores will process massive data with varying degree of locality. Harnessing on-chip data locality to optimize the utilization of cache and network resources is of fundamental importance. We propose a locality-aware selective data replication protocol for the last-level cache (LLC). Our goal is to lower memory access latency and energy by replicating only high locality cache lines in the LLC slice of the requesting core, while simultaneously keeping the off-chip miss rate low. Our approach relies on low overhead yet highly accurate in-hardware run-time classification of data locality at the cache line granularity, and only allows replication for cache lines with high reuse. Furthermore, our classifier captures the LLC pressure at the existing replica locations and adapts its replication decision accordingly. The locality tracking mechanism is decoupled from the sharer tracking structures that cause scalability concerns in traditional coherence protocols. Moreover, the complexity of our protocol is low since no additional coherence states are created. On a set of parallel benchmarks, our protocol reduces the overall energy by 16%, 14%, 13% and 21% and the completion time by 4%, 9%, 6% and 13% when compared to the previously proposed Victim Replication, Adaptive Selective Replication, Reactive-NUCA and Static-NUCA LLC management schemes.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/HPCA.2014.6835921
