Imperial College London
Professor Wayne Luk

ProfessorWayneLuk

Faculty of Engineering, Department of Computing

Professor of Computer Engineering
 
 
 
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Contact

 

+44 (0)20 7594 8313w.luk Website

 
 
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Location

 

434Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Liu:2012:10.1007/978-3-642-28365-9_6,
author = {Liu, Q and Luk, W},
doi = {10.1007/978-3-642-28365-9_6},
pages = {64--75},
title = {Heterogeneous systems for energy efficient scientific computing},
url = {http://dx.doi.org/10.1007/978-3-642-28365-9_6},
year = {2012}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - 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. © 2012 Springer-Verlag.
AU  - Liu,Q
AU  - Luk,W
DO  - 10.1007/978-3-642-28365-9_6
EP  - 75
PY  - 2012///
SN  - 0302-9743
SP  - 64
TI  - Heterogeneous systems for energy efficient scientific computing
UR  - http://dx.doi.org/10.1007/978-3-642-28365-9_6
ER  -
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