Abstract
A GPU is a promising device for further increasing computing performance in high performance computing field. Currently, many programming langauges are proposed for the GPU offloaded from the host, as well as CUDA. However, parallel programming with a multi-node GPU cluster, where each node has one or more GPUs, is a hard work. Users have to describe multi-level parallelism, both between nodes and within the GPU using MPI and a GPGPU language like CUDA. In this paper, we will propose a parallel programming language targeting multi-node GPU clusters. We extend XcalableMP, a parallel PGAS (Partitioned Global Address Space) programming language for PC clusters, to provide a productive parallel programming model for multi-node GPU clusters. Our performance evaluation with the N-body problem demonstrated that not only does our model achieve scalable performance, but it also increases productivity since it only requires small modifications to the serial code.
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References
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© 2012 Springer-Verlag Berlin Heidelberg
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Lee, J., Tran, M.T., Odajima, T., Boku, T., Sato, M. (2012). An Extension of XcalableMP PGAS Lanaguage for Multi-node GPU Clusters. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29737-3_48
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DOI: https://doi.org/10.1007/978-3-642-29737-3_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29736-6
Online ISBN: 978-3-642-29737-3
eBook Packages: Computer ScienceComputer Science (R0)
