MPI 기반 PC 클러스터에서 GHT의 병렬 분산 구현

Parallel Distributed Implementation of GHT on MPI-based PC Cluster

  • 김영수 (영남이공대학 컴퓨터정보계열) ;
  • 김정삼 (영남이공대학 컴퓨터정보계열) ;
  • 최흥문 (경북대학교 전자전기컴퓨터학부)
  • Kim, Yeong-Soo (Div. of Computer Information, Yeungnam College of Science & Technology) ;
  • Kim, Jeong-Sahm (Div. of Computer Information, Yeungnam College of Science & Technology) ;
  • Choi, Heung-Moon (School of Electrical Engineering & Computer Science, Kyungpook National University)
  • 발행 : 2007.05.25

초록

MPI(message passing interface) 기반 PC 클러스터 상에서 병렬분산 GHT(generalized Hough transform)를 모델화하고 시간 분석하여 고속화 구현하였다. 파이프라인 방송(pipelined broadcast) 통신방식과 누산기 배열(accumulator array) 분할 처리정책을 사용함으로써 통신부담을 최대한 줄였고, 전체 처리 과정에 걸쳐 통신과 계산처리를 시간 중첩시켜 구현함으로써 최대한의 속도제고를 하였다. 100 Mbps Ethernet 스위치를 이용하여 MPI 기반 PC 클러스터를 구현하고 제안한 병렬분산 GHT를 실험하여 선형에 가까운 속도 제고율 (speedup)을 확인하였다.

This paper presents a parallel distributed implementation of the GHT (generalized Hough transform) for the fast processing on the MPI-based PC cluster. We tried to achieve the higher speedup mainly by alleviating the communication overhead through the pipelined broadcast and accumulator array partition strategy and by time overlapping of the communication and the computation over entire process. Experimental results show that nearly linear speedup is reachable by the proposed method on the MPI-based PC clusters connected through 100Mbps Ethernet switch.

키워드

참고문헌

  1. T. M. Silberg, 'The Hough transform on the geometric arithmetic parallel processor,' Proc. IEEE Comput. Soc. Workshop Comput. Arch. Pattern Anal. Image Database Manag, pp. 387-393, Nov. 1985
  2. C. Guerra and S. Hambrusch, 'Parallel algorithms for line detection on a mesh,' Journal of Parallel and Distributed Computing Archive, vol. 6, no. 1, pp.1-19, Feb 1989 https://doi.org/10.1006/jpdc.1999.1591
  3. Y. Pan and Y. H. Chuang, 'Parallel Hough transform algorithms on SIMD hypercube arrays,' Proc. of ICPP, vol. 3, pp. 83-86, Aug 1990
  4. M. Atiquzzaman, 'Pipelined implementation of the multiresolution Hough transform in a pyramid multiprocessor,' Pattern Recognition Letters, vol. 15, no. 9, pp. 841-851, Sep 1994 https://doi.org/10.1016/0167-8655(94)90145-7
  5. A. N. Choudhary and R. Ponnusamy, 'Implementation and evaluation of Hough algorithms on a shared-memory multiprocessor,' Journal of Parallel and Distributed Computing, vol. 12, no. 2, pp. 178-188, June 1991 https://doi.org/10.1016/0743-7315(91)90023-3
  6. A. Underhill, M. Atiquzzaman, and J. Ophel, 'Performance of the Hough transform on a distributed memory multiprocessor,' Microprocessors and Microsystems, vol. 22, no. 7, pp. 355-362, Jan 1999 https://doi.org/10.1016/S0141-9331(98)00093-3
  7. N. Guil and E. L. Zapata, 'A parallel pipelined hough transform,' Euro-Par, vol. II, pp. 131-138, Aug 1996
  8. Meribout, M., Nakanishi, M., and Ogura, T., 'A parallel algorithm for real-time object recognition,' Pattern Recognition, vol. 35, no. 9, pp. 1917-1931, Sep 2002 https://doi.org/10.1016/S0031-3203(01)00156-X
  9. R. Strzodka, I. Ihrke, and M. Magnor. 'A Graphics Hardware Implementation of the Generalized Hough Transform for fast Object Recognition, Scale, and 3D Pose Detection,' Proc. of IEEE International Conference on Image Analysis and Processing (ICIAP'03), pp. 188-193, 2003 https://doi.org/10.1109/ICIAP.2003.1234048
  10. Z. Li, B. Yao, and F. Tong. 'A linear generalized hough transform and its parallel implementation,' CVPR, pp. 672.-673, June 1991 https://doi.org/10.1109/CVPR.1991.139776
  11. T. Achalakul and S. Madarasmi, 'A concurrent modified algorithm for Generalized Hough Transform,' Proc. of IEEE International Conference on Industrial Technology (ICIT'02), vol. 2, pp. 965-969, Dec 2002 https://doi.org/10.1109/ICIT.2002.1189300
  12. D. Baumann and S. Ranka. 'The Generalized Hough Transform on an MIMD Machine,' Journal of Undergraduate Research in High-Performance Computing, 2, 1992
  13. N. Sanguandikul and N. Nupairoj, 'Implicit Information Load Sharing Policy for Grid Computing Environment,' The 8th International Conference on Advanced Communication Technology (ICACT 2006), vol. 3, Feb 2006
  14. P. Patarasu, A. Faraj, and X. Yuan. 'Pipelined Broadcast on Ethernet Switched. Clusters.' The 20th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Rhodes Island, Greece, Apr 25-29, 2006 https://doi.org/10.1109/IPDPS.2006.1639364
  15. K. C. Wong, H. C Sim, and J. Kittler, 'Recognition of two dimensional objects based on a novel generalized Hough transform method.', Proc. of International Conference on Image Processing, vol. 3, pp.376-379, 23-26 Oct. 1995 https://doi.org/10.1109/ICIP.1995.537650