Abstract
The problem of 3-Point Correlation Function (3PCF) in astrophysics processes megabytes data with complex calculations, which is an important tool for calculating properties of heterogeneous systems, but its algorithmic complex is a notorious problem. The fast 3PCF Approximation algorithm can improve the efficiency by reduce the precision of result. In this paper, we are going to introduce a design of this algorithm on GPU, which is 13x speedup over a single CPU. Moreover, we will optimize it in the calculation details: converting the 3D arrays to 1D, padding 0s to arrays and shrinking the kernel array. Finally, this algorithm can achieve 27x speedup additional, and 347x speedup over a single CPU.
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The work is sponsored by the National Natural Science Foundation of China (61303021).
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Sun, C., Yang, M., Yu, C., Sun, J. (2015). Fast 3-Point Correlation Function Approximation on GPU. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9529. Springer, Cham. https://doi.org/10.1007/978-3-319-27122-4_38
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DOI: https://doi.org/10.1007/978-3-319-27122-4_38
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