BOOK-CHAPTER

Providing CUDA Acceleration to KVM Virtual Machines in InfiniBand Clusters with rCUDA

Ferran PérezCarlos ReañoFederico Silla

Year: 2016 Lecture notes in computer science Pages: 82-95   Publisher: Springer Science+Business Media

Abstract

There is a trend towards using graphics processing units (GPUs) not only for graphics visualization, but also for accelerating scientific applications. But their use for this purpose is not without disadvantages: GPUs increase costs and energy consumption. Furthermore, GPUs are generally underutilized. Using virtual machines could be a possible solution to address these problems, however, current solutions for providing GPU acceleration to virtual machines environments, such as KVM or Xen, present some issues. In this paper we propose the use of remote GPUs to accelerate scientific applications running inside KVM virtual machines. Our analysis shows that this approach could be a possible solution, with low overhead when used over InfiniBand networks.

Keywords:
InfiniBand Computer science Virtual machine Acceleration CUDA Operating system Overhead (engineering) Graphics Parallel computing General-purpose computing on graphics processing units Virtualization Computational science Cloud computing

Metrics

15
Cited By
6.58
FWCI (Field Weighted Citation Impact)
30
Refs
0.97
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
Parallel Computing and Optimization Techniques
Physical Sciences →  Computer Science →  Hardware and Architecture
Advanced Data Storage Technologies
Physical Sciences →  Computer Science →  Computer Networks and Communications
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