Result Details

A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark

JAROŠ, J.; POSPÍCHAL, P. A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark. Lecture Notes in Computer Science, 2012, vol. 2012, no. 7248, p. 426-435. ISSN: 0302-9743.
Type
journal article
Language
English
Authors
Jaroš Jiří, prof. Ing., Ph.D., DCSY (FIT)
Pospíchal Petr, Ing., DCSY (FIT)
Abstract

The paper introduces anoptimized multicore CPU implementation of the genetic algorithm and comparesits performance with a fine-tuned GPU version. The main goal is to show the trueperformance relation between modern CPUs and GPUs and eradicate some of myths surroundingGPU performance. It is essential for the evolutionary community to provide thesame conditions and designer effort to both implementations when benchmarkingCPUs and GPUs. Here we show the performance comparison supported byarchitecture characteristics narrowing the performance gain of GPUs.

Keywords

GPU, multi-core CPU, knapsack,performance comparison

URL
Published
2012
Pages
426–435
Journal
Lecture Notes in Computer Science, vol. 2012, no. 7248, ISSN 0302-9743
DOI
10.1007/978-3-642-29178-4_43
EID Scopus
2-s2.0-84859319778
BibTeX 
@article{BUT91455,
  author="Jiří {Jaroš} and Petr {Pospíchal}",
  title="A Fair Comparison of Modern CPUs and GPUs Running the Genetic Algorithm under the Knapsack Benchmark",
  journal="Lecture Notes in Computer Science",
  year="2012",
  volume="2012",
  number="7248",
  pages="426--435",
  doi="10.1007/978-3-642-29178-4\{_}43",
  issn="0302-9743",
  url="http://rd.springer.com/chapter/10.1007/978-3-642-29178-4_43"
}
Files
Projects
Natural Computing on Unconventional Platforms, GACR, Standardní projekty, GAP103/10/1517, start: 2010-01-01, end: 2013-12-31, running
Security-Oriented Research in Information Technology, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, start: 2007-01-01, end: 2013-12-31, running
Research groups
Supercomputing Technologies Research Group SC@FIT (RG SC@FIT)
Applied Evolutionary Algorithms Research Group (VZ EVA)
Departments
Department of Computer Systems (DCSY)
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