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Reducing Energy Consumption of Dense Linear Algebra Operations on Hybrid CPU-GPU Platforms

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5 Author(s)
Pedro Alonso ; Depto. de Sist. Informaticos y Comput., Univ. Politec. de Valencia, Valencia, Spain ; Manuel F. Dolz ; Francisco D. Igual ; Rafael Mayo
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We investigate the balance between the time-to-solution and the energy consumption of a task-parallel execution of the Cholesky and LU factorizations on a hybrid platform, equipped with a multi-core processor and several GPUs. To improve energy efficiency, we incorporate two energy-saving techniques in the runtime in charge of scheduling the computations, to block idle threads and enable the transition to a more energy-friendly state of the general-purpose cores. Experiments on an Intel Xeon-based platform connected to an NVIDIA Tesla server report an average reduction of the energy consumption close to 9% (38% when only the consumption associated with the application is considered), for a minor increase in the execution time of the algorithm.

Published in:

2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications

Date of Conference:

10-13 July 2012