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Dynamic load balancing on heterogeneous multicore/multiGPU systems

Alejandro Acosta, Robert Corujo, Vicente Blanco, Francisco Almeida
HPC Group. ETS de Ingenieria Informatica, Universidad de La Laguna, 38270 Tenerife. Spain
International Conference on High Performance Computing and Simulation (HPCS), 2010

@inproceedings{acosta2010dynamic,

   title={Dynamic load balancing on heterogeneous multicore/multiGPU systems},

   author={Acosta, A. and Corujo, R. and Blanco, V. and Almeida, F.},

   booktitle={High Performance Computing and Simulation (HPCS), 2010 International Conference on},

   pages={467–476},

   year={2010},

   organization={IEEE}

}

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Parallel computing in heterogeneous environments is drawing considerable attention due to the growing number of these kind of systems. Adapting existing code and libraries to such systems is a fundamental problem. The performance of this code is affected by the large interdependence between the code and these parallel architectures. We have developed a dynamic load balancing library that allows parallel code to be adapted to heterogeneous systems for a wide variety of problems. The overhead introduced by our system is minimal and the cost to the programmer negligible. The strategy was applied to a Dynamic Programming Algorithm, the Resource Allocation Problem. This code has been implemented on different heterogeneous architectures, including an heterogeneous cluster, a multicore system, a single GPU, and a multi-GPU system. The unbalance nature of the RAP algorithm shows the success of our load balancing library on such architectures.
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