A Resource Selection Method for Cycle Stealing in the GPU Grid

  • Yuki Kotani
  • Fumihiko Ino
  • Kenichi Hagihara
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4331)


Modern programmable graphics processing units (GPUs) provide increasingly higher performance, motivating us to perform general-purpose computation on the GPU (GPGPU) beyond graphics applications. In this paper, we address the problem of resource selection in the GPU grid. The GPU grid here consists of desktop computers at home and the office, utilizing idle GPUs and CPUs as computational engines for compute-intensive applications. Our method tackles this challenging problem (1) by defining idle resources and (2) by developing a resource selection method based on a screensaver approach with low-overhead sensors. The sensors detect idle GPUs by checking video random access memory (VRAM) usage and CPU usage on each computer. Detected resources are then selected according to a matchmaking framework and benchmark results obtained when the screensaver is installed on the machines. The experimental results show that our method achieves a low overhead of at most 262 ms, minimizing interference to resource owners with at most 10% performance drop.


Graphic Processing Unit Grid Resource Resource Selection Grid Application Desktop Grid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yuki Kotani
    • 1
  • Fumihiko Ino
    • 1
  • Kenichi Hagihara
    • 1
  1. 1.Graduate School of Information Science and TechnologyOsaka UniversityToyonaka, OsakaJapan

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