Accelerating pairwise statistical significance estimation using NUMA machine

作者：Zhang Yuhong^*; Zhou Fan; Gou Jianping; Xiao Hua; Qin Zhiguang; Agrawal Ankit

来源：Journal of Computational Information Systems, 2012, 8(9): 3887-3894.

• Computation kernel
• CPU cores
• Data intensive
• Database statistical significance
• Distributed computations
• Multi core
• Non-uniform memory acess (NUMA)
• NUMA machines
• Pairwise statistical significance
• Parallel accelerators
• Sequential implementation

Pairwise statistical significance (PSS) has been found as a promising alternative to database statistical significance for homology detection. However, the estimation of PSS is both computationally and data intensive, which poses a big challenge on performance and scalability in terms of distributed computations. In this work, we develop the parallel accelerator for the estimation of PSS using Non-Uniform Memory Acess (NUMA) machine, which is implemented in C++ using OpenMP, MPI and hybrid paradig-ms, respectively. Through distributing the computation kernels of the estimation of PSS procedure across multiple cores, we achieve up to 22.65× speedup using 24 CPU cores compared to sequential implementation.

• 出版日期2012
• 单位电子科技大学; NorthWestern University