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Accelerating frequency-domain simulations using small shared-memory CPU/GPU cluster

  • Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Numerical approach to frequency response problems usually requires that the system governing equation is solved repeatedly at many frequencies. The computational efficiency of the overall process can be increased by departing from traditional sequential computing model in favor of utilizing the parallel processing capability commonly offered by modern hardware. In this paper, we consider a hybrid programming pattern, OpenMP + CUDA, from the perspective of a user of a rather typical low-cost multi-core CPU-based workstation that can accommodate up to four GPUs. Such the small-scale heterogeneous platforms have recently gained wide popularity in scientific computing as an inexpensive massively parallel architecture. The relevant programming model issues and performance questions are addressed. Experimental results for the example physics problem, that is, the electromagnetic scattering from perfectly electrically conducting body, show that significant performance improvement can be attained with the OpenMP + CUDA programming model.

Original languageEnglish
Title of host publication2016 21st International Conference on Microwave, Radar and Wireless Communications, MIKON 2016
EditorsArtur Rydosz
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509022144
DOIs
Publication statusPublished - 14 Jun 2016
Event21st International Conference on Microwave, Radar and Wireless Communications, MIKON 2016 - Krakow, Poland
Duration: 9 May 2016 → 11 May 2016

Publication series

Name2016 21st International Conference on Microwave, Radar and Wireless Communications, MIKON 2016

Conference

Conference21st International Conference on Microwave, Radar and Wireless Communications, MIKON 2016
Country/TerritoryPoland
CityKrakow
Period9/05/16 → 11/05/16

Keywords

  • CUDA
  • GPU
  • Milticore CPU
  • MoM
  • OpenMP

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Instrumentation

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