GPUfs: integrating a file system with GPUs

  • Authors:
  • Mark Silberstein;Bryan Ford;Idit Keidar;Emmett Witchel

  • Affiliations:
  • University of Texas, Austin, TX, USA;Yale University, New Heaven, CT, USA;Technion - Israel Institute of Technology, Haifa, Israel;University of Texas, Austin, TX, USA

  • Venue:
  • Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

PU hardware is becoming increasingly general purpose, quickly outgrowing the traditional but constrained GPU-as-coprocessor programming model. To make GPUs easier to program and easier to integrate with existing systems, we propose making the host's file system directly accessible from GPU code. GPUfs provides a POSIX-like API for GPU programs, exploits GPU parallelism for efficiency, and optimizes GPU file access by extending the buffer cache into GPU memory. Our experiments, based on a set of real benchmarks adopted to use our file system, demonstrate the feasibility and benefits of our approach. For example, we demonstrate a simple self-contained GPU program which searches for a set of strings in the entire tree of Linux kernel source files over seven times faster than an eight-core CPU run.