Browse > Article
http://dx.doi.org/10.15207/JKCS.2016.7.5.015

A Study of Distribute Computing Performance Using a Convergence of Xeon-Phi Processor and Quantum ESPRESSO  

Park, Young-Soo (Dept. of Computer Engineering, Kongju National University)
Park, Koo-Rack (Dept. of Computer Science & Engineering, Kongju National University)
Kim, Dong-Hyun (Dept. of IT Convergence, Woosong University)
Publication Information
Journal of the Korea Convergence Society / v.7, no.5, 2016 , pp. 15-21 More about this Journal
Abstract
Recently the degree of integration of processor and developed rapidly. However, clock speed is not increased, a situation that increases the number of cores in the processor. In this paper, we analyze the performance of a typical Intel Xeon Phi of many core process used for the current operation accelerate. Utilizing the Quantum ESPRESSO, which was calculated using the FFTW library. By varying the number of ranks in MPI when running the benchmarks the performance Xeon Phi. The result shows a good performance in the handling of four job on one physical core. However, four or more to expand the number of MPI Rank is degraded. Through this convergence it was found to improve the performance of Quantum ESPRESSO. It is possible to check the hardware characteristics of the Xeon Phi.
Keywords
Convergence; Parallelism; Quantum ESPRESSO; Xeon Phi; Software Optimization;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Asanovic, Krste, et al. "The Landscape of Parallel Computing Research: A View from Berkeley", Technical Report UCB/EECS-2006-183, EECS, Department, University of California, Berkeley, 2006
2 H. J. Lee, E. J. Im, "SpMV on Xeon-Phi", Proceedings of the KIISE, pp. 42-44, 2014.
3 Yang, Xiaoling, and Wenhua Yu. "Phi Coprocessor Acceleration Techniques for Computational Electromagnetics Methods", Applied Computational Electromagnetics Society Journal, Vol. 29, Issue 12, 2014.
4 Heinecke A, Vaidyanathan K, Smelyanskiy M, et al. "Design and implementation of the linpack benchmark or single and multi-node systems based on intel xeon Phi coprocessor", Parallel & Distributed Processing (IPDPS), 2013 IEEE 27th International Symposium on. IEEE, pp. 126-137, 2013.
5 Liu Y, Maskell DL, Schmidt B. "CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units", BMC Research Notes, 2, 73, 2009.   DOI
6 Lan H, Liu W, Schmidt B, et al. "Accelerating large-scale biological database search on Xeon Phi-based neo-heterogeneous architectures", Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on. IEEE, pp. 503-510, 2015.
7 Lu M, Zhang L, Huynh HP, et al. "Optimizing the mapreduce framework on intel xeon phi coprocessor", Big Data, 2013 IEEE International Conference on. IEEE, pp. 125-130, 2013.
8 M. Bernaschi, M. Bisson, and F. Salvadore, "Multi-Kepler GPU vs. multi-Intel MIC for spin systems simulations", Computer Physics Communications, vol. 185, no. 10, pp. 2495-503, 2014.   DOI
9 A. Taflove and S. Hagness, "Computational electromagnetics: the finite-difference timedomain method", 3rd ed., Artech House, Norwood, MA, 2005.
10 W. Yu, X. Yang, Y. Liu, et al., "Parallel finite difference time-domain method", Artech House, Norwood, MA, 2006.
11 M. Frigo, S. G. Johnson, "The Design and Implementation of FFTW3", Proceedings of the IEEE 93(2), pp. 216-231, 2005.   DOI
12 W. Yu, X. Yang, and W. Li, "VALU, AVX, GPU acceleration techniques for parallel finite difference time domain methods", SciTech Publisher Inc., Raleigh, NC, 2013.
13 A. Elsherbeni and V. Demir, "The finite difference time domain method for electromagnetics: with MATLAB simulations", SciTech Publisher Inc., Raleigh, NC, 2009.
14 J. M. Jin, "The finite element method in electromagnetics", (2nd edition), New York: John Wiley & Sons, 2002.
15 Lan, Haidong, et al., "Parallel algorithms for large-scale biological sequence alignment on Xeon-Phi based clusters", IEEE International Conference on Bioinformatics and Biomedicine 2015 Washington, DC, USA. pp. 9-12, 2015.