Advertisement

Topic 15: GPU and Accelerator Computing

(Introduction)
  • Naoya Maruyama
  • Leif Kobbelt
  • Pavan Balaji
  • Nikola Puzovic
  • Samuel Thibault
  • Kun Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8097)

Abstract

Computational accelerators such as GPUs, FPGAs and many-core accelerators can dramatically improve the performance of computing systems and catalyze highly demanding applications. Many scientific and commercial applications are beginning to integrate computational accelerators in their code. However, programming accelerators for high performance remains a challenge, resulting from the restricted architectural features of accelerators compared to general purpose CPUs. Moreover, software must conjointly use conventional CPUs with accelerators to support legacy code and benefit from general purpose operating system services. The objective of this topic is to provide a forum for exchanging new ideas and findings in the domain of accelerator-based computing.

Keywords

Bipartite Graph Maximum Cardinality Acceleration Method Quality Review External Review 
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.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Naoya Maruyama
  • Leif Kobbelt
  • Pavan Balaji
  • Nikola Puzovic
  • Samuel Thibault
  • Kun Zhou

There are no affiliations available

Personalised recommendations