Performance analysis and tuning for general purpose graphics processing units (GPGPU)

Hyesoon Kim, Richard Vuduc, Sara Baghsorkhi, Wen Mei Hwu, Choi Jee Choi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models.We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms.We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques.

Original languageEnglish (US)
Title of host publicationPerformance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)
Pages1-94
Number of pages94
DOIs
StatePublished - Nov 21 2012

Publication series

NameSynthesis Lectures on Computer Architecture
Volume20
ISSN (Print)1935-3235
ISSN (Electronic)1935-3243

Keywords

  • CUDA
  • GPGPU
  • GPU
  • performance analysis
  • performance modeling

ASJC Scopus subject areas

  • Hardware and Architecture

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  • Cite this

    Kim, H., Vuduc, R., Baghsorkhi, S., Hwu, W. M., & Jee Choi, C. (2012). Performance analysis and tuning for general purpose graphics processing units (GPGPU). In Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU) (pp. 1-94). (Synthesis Lectures on Computer Architecture; Vol. 20). https://doi.org/10.2200/S00451ED1V01Y201209CAC020