Analysis and Optimization of Power Consumption in the Iterative Solution of Sparse Linear Systems on Multi-core and Many-core Platforms

  • Hartwig Anzt (Author)
  • Maribel Castillo (Author)
  • José I. Aliaga (Author)
  • Juan C. Fernández (Author)
  • Vincent Heuveline (Author)
    Engineering Mathematics and Computing Lab (EMCL), Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University
  • Rafael Mayo (Author)
  • Enrique S. Quintana-Ortí (Author)


Energy efficiency is a major concern in modern high-performance-computing. Still, few studies provide a deep insight into the power consumption of scientific applications. Especially for algorithms running on hybrid platforms equipped with hardware accelerators, like graphics processors, a detailed energy analysis is essential to identify the most costly parts, and to evaluate possible improvement strategies. In this paper we analyze the computational and power performance of iterative linear solvers applied to sparse systems arising in several scientific applications. We also study the gains yield by dynamic voltage/frequency scaling (DVFS), and illustrate that this technique alone cannot to reduce the energy cost to a considerable amount for iterative linear solvers. We then apply techniques that set the (multi-core processor in the) host system to a low-consuming state for the time that the GPU is executing. Our experiments conclusively reveal how the combination of these two techniques deliver a notable reduction of energy consumption without a noticeable impact on computational performance.




The Engineering Mathematics and Computing Lab (EMCL), directed by Prof. Dr. Vincent Heuveline, is a research group at the Interdisciplinary Center for Scientific Computing (IWR).

The EMCL Preprint Series contains publications that were accepted for the Preprint Series of the EMCL and are planned to be published in journals, books, etc. soon.

The EMCL Preprint Series was published under the roof of the Karlsruhe Institute of Technology (KIT) until April 30, 2013. As from May 01, 2013 it is published under the roof of Heidelberg University.