An Efficient Implementation of GPU Virtualization in High Performance Clusters

  • José Duato
  • Francisco D. Igual
  • Rafael Mayo
  • Antonio J. Peña
  • Enrique S. Quintana-Ortí
  • Federico Silla
Conference paper

DOI: 10.1007/978-3-642-14122-5_44

Part of the Lecture Notes in Computer Science book series (LNCS, volume 6043)
Cite this paper as:
Duato J., Igual F.D., Mayo R., Peña A.J., Quintana-Ortí E.S., Silla F. (2010) An Efficient Implementation of GPU Virtualization in High Performance Clusters. In: Lin HX. et al. (eds) Euro-Par 2009 – Parallel Processing Workshops. Euro-Par 2009. Lecture Notes in Computer Science, vol 6043. Springer, Berlin, Heidelberg

Abstract

Current high performance clusters are equipped with high bandwidth/low latency networks, lots of processors and nodes, very fast storage systems, etc. However, due to economical and/or power related constraints, in general it is not feasible to provide an accelerating co-processor –such as a graphics processor (GPU)– per node. To overcome this, in this paper we present a GPU virtualization middleware, which makes remote CUDA-compatible GPUs available to all the cluster nodes. The software is implemented on top of the sockets application programming interface, ensuring portability over commodity networks, but it can also be easily adapted to high performance networks.

Keywords

Graphics processors (GPUs) virtualization high performance computing clusters Grid 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • José Duato
    • 1
  • Francisco D. Igual
    • 2
  • Rafael Mayo
    • 2
  • Antonio J. Peña
    • 1
  • Enrique S. Quintana-Ortí
    • 2
  • Federico Silla
    • 1
  1. 1.Departamento de Informática de Sistemas y ComputadoresUniversidad Politécnica de Valencia (UPV)ValenciaSpain
  2. 2.Depto. de Ingeniería y Ciencia de ComputadoresUniversidad Jaume I (UJI)CastellónSpain

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