Exploiting auto-tuning to analyze and improve performance portability on many-core architectures

James Price*, Simon McIntosh-Smith

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

3 Citations (Scopus)

Abstract

Performance portability has rapidly become one of the key concerns for application developers targeting modern computer architectures. Although there are various programming models that can offer functional portability when moving application code between different devices, it remains an open research question as to whether it is possible to guarantee some degree of performance portability in these situations. Automatic performance tuning approaches have been shown to be effective tools for removing the burden of code optimization from the developer, but somewhat sidestep the issue of performance portability by enabling an environment where code is repeatedly optimized for each architecture individually.

In this work, we present an in-depth analysis of the performance portability of code that has been highly optimized for specific devices via auto-tuning. We perform this analysis across a wide range of modern, many-core architectures from multiple hardware vendors, examining performance portability both across different vendors and between devices from the same vendor. We then demonstrate how the auto-tuning process can be modified to bring performance portability into the equation, in order to automatically generate a single implementation that achieves high efficiency across many different devices.
Original languageEnglish
Title of host publicationHigh Performance Computing - ISC High Performance 2017 International Workshops, DRBSD, ExaComm, HCPM, HPC-IODC, IWOPH, IXPUG, P^3MA, VHPC, Visualization at Scale, WOPSSS, Revised Selected Papers
PublisherSpringer, Cham
Pages538-556
Number of pages19
ISBN (Print)9783319676296
DOIs
Publication statusPublished - 20 Oct 2017
Event32nd International Conference on High Performance Computing, ISC High Performance 2017 - Frankfurt, Germany
Duration: 18 Jun 201722 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10524 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference32nd International Conference on High Performance Computing, ISC High Performance 2017
CountryGermany
CityFrankfurt
Period18/06/1722/06/17

Keywords

  • performance portability
  • auto-tuning
  • GPGPU
  • OpenCL

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