This paper describes the use of CUDA to accelerate the Himeno benchmark on clusters with GPUs. The implementation is designed to optimize memory bandwidth utilization. Our approach achieves over 83% of the theoretical peak bandwidth on a NVIDIA Tesla C1060 GPU and performs at over 50 GFlops. A multi-GPU implementation that utilizes MPI alongside CUDA streams to overlap GPU execution with data transfers allows linear scaling and performs at over 800 GFlops on a cluster with 16 GPUs. The paper presents the optimizations required to achieve this level of performance. © 2010 IEEE.
CITATION STYLE
Phillips, E. H., & Fatica, M. (2010). Implementing the Himeno benchmark with CUDA on GPU clusters. In Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2010. https://doi.org/10.1109/IPDPS.2010.5470394
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