Asymmetric Prefetching Architecture for Multicore Processor

Duheon Choi, Kwangsu Kim, Eui Young Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Prefetching is one of the main techniques for improving the performance of modern processors. Various prefetch algorithms have been proposed targeting various applications and memory access patterns. Modern SoCs are mainly equipped with multicore processors, and various processes are operated separately by each core. This implies that for each core, different prefetcher may work better. In this paper, we propose a hardware prefetcher that integrates three prefetching algorithms and statically allocates a prefetching algorithm that provides better performance to each workload in a multicore processor. We observe 4.6% overall performance improvement compared to using a single prefetcher and reduce buffer resources by 41%.

Original languageEnglish
Title of host publicationProceedings - International SoC Design Conference, ISOCC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages13-14
Number of pages2
ISBN (Electronic)9781728183312
DOIs
Publication statusPublished - 2020 Oct 21
Event17th International System-on-Chip Design Conference, ISOCC 2020 - Yeosu, Korea, Republic of
Duration: 2020 Oct 212020 Oct 24

Publication series

NameProceedings - International SoC Design Conference, ISOCC 2020

Conference

Conference17th International System-on-Chip Design Conference, ISOCC 2020
CountryKorea, Republic of
CityYeosu
Period20/10/2120/10/24

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This research was supported by R&D program for advanced integrated-intelligence for identification through the National Research Foundation of Korea(NRF) funded by Ministry of Trade, Industry and Energy (2018M3E3A1057248), And the chip fabrication and EDA Tool were supported by the IC Design Education Center.

Publisher Copyright:
© 2020 IEEE.

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Instrumentation
  • Artificial Intelligence
  • Hardware and Architecture

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