Computation Efficiency Analysis of Multiple GPUs and Multiple CPUs Based Cluster Computing Environments
Multiple CPUs and multiple GPUs based cluster computing environments are popularly used and very attractive approach in various computing areas because those computing environments provide very high computing performance when compared to a typical single node based computing environments. In this paper, we compare and evaluate the performance of multiple CPUs and multiple GPUs based on cluster computing environment with MPI (Message Passing Interfaces). In the performance evaluations, we evaluate and analyze the performance of sparse matrix-vector multiply (SpMV). SpMV is one of the most widely used operations in many scientific, computational, and mathematical applications. Based on the performance evaluation results, generally, the execution time of SpMV is decreased as the number of CPUs and GPUs increase. However, there were cases that were not so in the case of GPU.
KeywordsMultiple CPUs Multiple GPUs High performance computing Message passing interface Cluster computing
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No.2017R1C1B5017476). The corresponding author is Jeong-Dong Kim.
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