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Parallel and Distributed Processing Symposium, International (2007)
Long Beach, CA, USA
Mar. 26, 2007 to Mar. 30, 2007
ISBN: 1-4244-0909-8
pp: 311
Konrad Malkowski , Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802. Tel: 814-865-9505, E-mail: malkowsk@cse.psu.edu
Padma Raghavan , Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802. Tel: 814-865-9505, E-mail: raghavan@cse.psu.edu
Mary Jane Irwin , Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802. Tel: 814-865-9505, E-mail: mji@cse.psu.edu
ABSTRACT
We consider memory subsystem optimizations for improving the performance of sparse scientific computation while reducing the power consumed by the CPU and memory. We first consider a sparse matrix vector multiplication kernel that is at the core of most sparse scientific codes, to evaluate the impact of prefetchers and power-saving modes of the CPU and caches. We show that performance can be improved at significantly lower power levels, leading to over a factor of five improvement in the operations/Joule metric of energy efficiency. We then indicate that these results extend to more complex codes such as a multigrid solver. We also determine a functional representation of the impacts of such optimizations and we indicate how it can be used toward further tuning. Our results thus indicate the potential for cross-layer tuning for multiobjective optimizations by considering both features of the application and the architecture.
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CITATION

P. Raghavan, K. Malkowski and M. J. Irwin, "Memory Optimizations For Fast Power-Aware Sparse Computations," 2007 IEEE International Parallel and Distributed Processing Symposium(IPDPS), Rome, 2007, pp. 311.
doi:10.1109/IPDPS.2007.370501
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