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GPUfs: Integrating a file system with GPUs

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

As GPU hardware becomes increasingly general-purpose, it is quickly outgrowing the traditional, constrained GPU-as-coprocessor programming model. To make GPUs easier to program and improve their integration with operating systems, we propose making the host's file system directly accessible to GPU code. GPUfs provides a POSIX-like API for GPU programs, exploits GPU parallelism for efficiency, and optimizes GPU file access by extending the host CPU's buffer cache into GPU memory. Our experiments, based on a set of real benchmarks adapted to use our file system, demonstrate the feasibility and benefits of the GPUfs approach. For example, a self-contained GPU program that searches for a set of strings throughout the Linux kernel source tree runs over seven times faster than on an eight-core CPU.

Original languageEnglish
Title of host publicationASPLOS 2013 - 18th International Conference on Architectural Support for Programming Languages and Operating Systems
Pages485-497
Number of pages13
DOIs
StatePublished - 16 Mar 2013
Event18th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2013 - Houston, TX, United States
Duration: 16 Mar 201320 Mar 2013

Publication series

NameInternational Conference on Architectural Support for Programming Languages and Operating Systems - ASPLOS

Conference

Conference18th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2013
Country/TerritoryUnited States
CityHouston, TX
Period16/03/1320/03/13

Keywords

  • Accelerators
  • File systems
  • GPGPUS
  • Operating systems design

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture

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