Heterogeneous Systems for Energy Efficient Scientific Computing

  • Qiang Liu
  • Wayne Luk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7199)

Abstract

This paper introduces a novel approach for exploring heterogeneous computing engines which include GPUs and FPGAs as accelerators. Our goal is to systematically automate finding solutions for such engines that maximize energy efficiency while meeting requirements in throughput and in resource constraints. The proposed approach, based on a linear programming model, enables optimization of system throughput and energy efficiency, and analysis of energy efficiency sensitivity and power consumption issues. It can be used in evaluating current and future computing hardware and interfaces to identify appropriate combinations. A heterogeneous system containing a CPU, a GPU and an FPGA with a PCI Express interface is studied based on the High Performance Linpack application. Results indicate that such a heterogeneous computing system is able to provide energy-efficient solutions to scientific computing with various performance demands. The improvement of system energy efficiency is more sensitive to some of the system components, for example in the studied system concurrently improving the energy efficiency of the interface and the GPU by 10 times could lead to over 10 times improvement of the system energy efficiency.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Qiang Liu
    • 1
  • Wayne Luk
    • 2
  1. 1.School of Electronic Information EngineeringTianjin UniversityTianjinChina
  2. 2.Department of ComputingImperial College LondonLondonUK

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