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On optimization techniques for the matrix multiplication on hybrid CPU+GPU platforms

Luis-Pedro Garcia, Javier Cuenca, Domingo Gimenez
Technical University of Cartagena
Annals of Multicore and GPU Programming, Vol 1, No 1, 2014

@article{canovas2014optimization,

   title={On optimization techniques for the matrix multiplication on hybrid CPU+ GPU platforms},

   author={C{‘a}novas, Domingo Gim{‘e}nez and Garc{‘i}a, Luis-Pedro and Cuenca, Javier},

   journal={Annals of Multicore and GPU Programming},

   volume={1},

   number={1},

   year={2014}

}

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The use of auto-tuning techniques in a matrix multiplication routine for hybrid CPU+GPU platforms is analyzed. Basic models of the execution time of the hybrid routine and information obtained during its installation are used to optimize the execution time with a balanced assignation of the computation to the computing components in the heterogeneous system. Satisfactory results are obtained, with experimental execution times close to the lowest achievable.
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