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IPPS
2007
IEEE

Memory Optimizations For Fast Power-Aware Sparse Computations

14 years 23 days ago
Memory Optimizations For Fast Power-Aware Sparse Computations
— 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.
Konrad Malkowski, Padma Raghavan, Mary Jane Irwin
Added 03 Jun 2010
Updated 03 Jun 2010
Type Conference
Year 2007
Where IPPS
Authors Konrad Malkowski, Padma Raghavan, Mary Jane Irwin
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