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An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Eduard Ayguade, Rosa Badia, Francisco Igual, Jesus Labarta, Rafael Mayo, Enrique Quintana-Orti
Barcelona Supercomputing Center { Centro Nacional de Supercomputacion (BSC{CNS) and Universitat Politecnica de Catalunya, Nexus II Building, C. Jordi Girona 29, 08034-Barcelona, Spain
In Euro-Par 2009 Parallel Processing, Vol. 5704 (2009), pp. 851-862

@article{ayguade2009extension,

   title={An extension of the starss programming model for platforms with multiple gpus},

   author={Ayguad{‘e}, E. and Badia, R. and Igual, F. and Labarta, J. and Mayo, R. and Quintana-Ort{‘i}, E.},

   journal={Euro-Par 2009 Parallel Processing},

   pages={851–862},

   year={2009},

   publisher={Springer}

}

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While general-purpose homogeneous multi-core architectures are becoming ubiquitous, there are clear indications that, for a number of important applications, a better performance/power ratio can be attained using specialized hardware accelerators. These accelerators require specific SDK or programming languages which are not always easy to program. Thus, the impact of the new programming paradigms on the programmer-s productivity will determine their success in the high-performance computing arena. In this paper we present GPU Superscalar (GPUSs), an extension of the Star Superscalar programming model that targets the parallelization of applications on platforms consisting of a general-purpose processor connected with multiple graphics processors. GPUSs deals with architecture heterogeneity and separate memory address spaces, while preserving simplicity and portability. Preliminary experimental results for a well-known operation in numerical linear algebra illustrate the correct adaptation of the runtime to a multi-GPU system, attaining notable performance results.
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