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Performance and Energy Analysis of the Iterative Solution of Sparse Linear Systems on Multicore and Manycore Architectures

  • José I. Aliaga
  • Hartwig Anzt
  • Maribel Castillo
  • Juan C. Fernández
  • Germán León
  • Joaquín Pérez
  • Enrique S. Quintana-Ortí
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8384)

Abstract

In this paper we investigate the performance-energy balance of a variety of concurrent architectures, from general-purpose and digital signal multicore systems to graphics processors (GPUs), representative of current technology. This analysis employs the conjugate gradient method, an important algorithm for the iterative solution of linear systems that is basically composed of the sparse matrix-vector product and other (minor) vector kernels. To allow a fair comparison, we leverage simple implementations of the numerical methods and underlying kernels, and rely only on those optimizations applied by the target compiler.

Keywords

Energy efficiency High-performance computing Sparse linear algebra Multicore processors Low-power processors GPUs 

Notes

Acknowledgements

This work was supported by the CICYT project TIN2011-23283 and FEDER, and by EU FET grant “EXA2GREEN” 318793.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • José I. Aliaga
    • 1
  • Hartwig Anzt
    • 2
  • Maribel Castillo
    • 1
  • Juan C. Fernández
    • 1
  • Germán León
    • 1
  • Joaquín Pérez
    • 1
  • Enrique S. Quintana-Ortí
    • 1
  1. 1.Dpto. de Ingeniería y Ciencia de ComputadoresUniversidad Jaume ICastellónSpain
  2. 2.Innovative Computing Lab (ICL)University of TennesseeKnoxvilleUSA

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