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A (ir)regularity-aware task scheduler for heterogeneous platforms

Artur Mariano, Ricardo Alves, Joao Barbosa, Luis Paulo Santos, Alberto Proenca
Department of Informatics, University of Minho, Braga, Portugal
International conference on High Performance Computing Kyiv, 2012

@article{mariano2012ir,

   title={A (ir) regularity-aware task scheduler for heterogeneous platforms},

   author={Mariano, A. and Alves, R. and Barbosa, J. and Santos, L.P. and Proenca, A.},

   year={2012}

}

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This paper addresses the design, implementation and validation of an effective scheduling scheme for both regular and irregular applications on heterogeneous platforms. The scheduler uses an empirical performance model to dynamically schedule the workload, organized into a given number of chunks, and follows the Heterogeneous Earliest Finish Time (HEFT) scheduling algorithm, which ranks the tasks based on both their computation and communication costs. The evaluation of the proposed approach is based on three case studies – the SAXPY, the FFT and the Barnes-Hut algorithms – two regular and one irregular application. The scheduler was evaluated on a heterogeneous platform with one quad-core CPU-chip accelerated by one or two GPU devices, embedded in the GAMA framework. The evaluation runs measured the effectiveness, the efficiency and the scalability of the proposed method. Results show that the proposed model was effective in addressing both regular and irregular applications, on heterogeneous platforms, while achieving ideal (>=100%) levels of efficiency in the irregular Barnes-Hut algorithm.
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