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Harnessing pairwise-correlating data prefetching with runahead metadata

Golshan, F ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1109/LCA.2020.3019343
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2020
  4. Abstract:
  5. Recent research revisits pairwise-correlating data prefetching due to its extremely low overhead. Pairwise-correlating data prefetching, however, cannot accurately detect where data streams end. As a result, pairwise-correlating data prefetchers either expose low accuracy or they lose timeliness when they are performing multi-degree prefetching. In this letter, we propose a novel technique to detect where data streams end and hence, control the multi-degree prefetching in the context of pairwise-correlated prefetchers. The key idea is to have a separate metadata table that operates one step ahead of the main metadata table. This way, the runahead metadata table harnesses the degree of prefetching by allowing/disallowing the main metadata table to issue prefetch requests. We evaluate our proposal in the context of a four-core chip multiprocessor and show that it significantly reduces erroneous prefetches, providing up to 16.1 percent performance improvement on top of a state-of-The-Art pairwise-correlating prefetcher. © 2002-2011 IEEE
  6. Keywords:
  7. Cache memory ; Data prefetching ; Overprediction ; Pairwise-correlating data prefetching ; Performance ; Metadata ; Four-core ; Low overhead ; Novel techniques ; Prefetchers ; Prefetching ; Recent researches ; State of the art ; Data streams
  8. Source: IEEE Computer Architecture Letters ; Volume 19, Issue 2 , 2020 , Pages 130-133 ; ISSN: 15566056
  9. URL: https://ieeexplore.ieee.org/document/9177277