Heterogeneous Parallel Computing Platforms and Tools for Compute-Intensive Algorithms: A Case Study (Contributo in volume (capitolo o saggio))

Type
Label
  • Heterogeneous Parallel Computing Platforms and Tools for Compute-Intensive Algorithms: A Case Study (Contributo in volume (capitolo o saggio)) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1002/9781118711897.ch11 (literal)
Alternative label
  • Daniele D'Agostino, Andrea Clematis, and Emanuele Danovaro (2014)
    Heterogeneous Parallel Computing Platforms and Tools for Compute-Intensive Algorithms: A Case Study
    John Wiley & Sons Inc., Hoboken (Stati Uniti d'America) in High-Performance Computing on Complex Environments, 2014
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Daniele D'Agostino, Andrea Clematis, and Emanuele Danovaro (literal)
Pagina inizio
  • 193 (literal)
Pagina fine
  • 213 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • High-Performance Computing on Complex Environments (literal)
Note
  • Google Scholar (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • IMATI CNR, Genoa, Italy (literal)
Titolo
  • Heterogeneous Parallel Computing Platforms and Tools for Compute-Intensive Algorithms: A Case Study (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 9781118712054 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • Emmanuel Jeannot and Julius Zilinskas (literal)
Abstract
  • In this chapter we analyze the development of parallel programs for heterogeneous architectures, that is, workstation composed by multiple CPUs and accelerators, considering different programming models and tools, both commercial and freely available. In particular, we discuss the provided support and achievable performance for each of them with respect to some widely used, computationally intensive algorithms such as the convolution and the N-body algorithms. The aim is to provide a clear measure of the different efficiency figures with respect to the programming paradigm considered, the adopted tool, and the achievable peak performance. (literal)
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