Evaluating the role of scratchpad memories in chip multiprocessors for sparse matrix computations

Aditya Yanamandra, Bryan Cover, Padma Raghavan, Mary Jane Irwin, Mahmut Kandemir

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

4 Scopus citations

Abstract

Scratchpad memories (SPMs) have been shown to be more energy efficient and have faster access times than traditional hardware-managed caches. This, coupled with the predictability of data presence, makes SPMs an attractive alternative to cache for many scientific applications. In this work, we consider an SPM based system for increasing the performance and the energy efficiency of sparse matrix-vector multiplication on a chip multi-processor. We ensure the efficient utilization of the SPM by profiling the application for the data structures which do not perform well in traditional cache. We evaluate the impact of using an SPM at all levels of the on-chip memory hierarchy. Our experimental results show an average increase in performance by 13.5-15% and an average decrease in the energy consumption by 28-33% on an 8-core system depending on which level of the hierarchy the SPM is utilized.

Original languageEnglish (US)
Title of host publicationIPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM
DOIs
StatePublished - 2008
EventIPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium - Miami, FL, United States
Duration: Apr 14 2008Apr 18 2008

Publication series

NameIPDPS Miami 2008 - Proceedings of the 22nd IEEE International Parallel and Distributed Processing Symposium, Program and CD-ROM

Other

OtherIPDPS 2008 - 22nd IEEE International Parallel and Distributed Processing Symposium
Country/TerritoryUnited States
CityMiami, FL
Period4/14/084/18/08

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering

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