GPUfs: Integrating a File System with GPUs

Mark Silberstein, Bryan Ford, Idit Keidar, Emmett Witchel
University of Texas at Austin
Eighteenth International Conference on Architectural Support for Programming Languages and Operating Systems, 2013

   title={GPUfs: Integrating a File System with GPUs},

   author={Silberstein, M. and Ford, B. and Keidar, I. and Witchel, E.},



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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.
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