Advertisement

A Data Transformations Based Approach for Optimizing Memory and Cache Locality on Distributed Memory Multiprocessors

  • Xia Jun
  • Xue-Jun Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3756)

Abstract

Data locality is one of the key factors in affecting the performance of parallel programs running on distributed memory multiprocessors. This paper presents an approach for optimizing memory locality and cache locality of perfect or non-perfect loop nests using linear data transformations on distributed memory multiprocessors. The approach optimizes memory locality with the data space fusion technique and cache locality with the projection-delamination technique, and combines the both techniques effectively to make the overheads of remote memory accesses and local memory accesses as low as possible. We conduct experiments with nine programs and the results show the approach is effective in optimizing memory locality and cache locality simultaneously.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Chen, T.-S., Chang, C.-Y.: Skewed data partition and alignment techniques for compiling programs on distributed memory multicomputers. The Journal of Supercomputing 21(2), 191–211 (2002)zbMATHCrossRefGoogle Scholar
  2. 2.
    Chang, W.-L., Chu, C.-P., Wu, J.-H.: Communication-free alignment for array references with linear subscripts in three loop index variables or quadratic subscripts. The Journal of Supercomputer 20(1), 67–83 (2001)zbMATHCrossRefGoogle Scholar
  3. 3.
    Jun, X., Xue-Jun, Y., Hua-Dong, D.: Data space fusion based approach for effective alignment of computation and data. In: Proc. of 5th International Workshop on Advanced Parallel Processing Technology, Xiamen, China, pp. 215–225 (2003)Google Scholar
  4. 4.
    Wolf, M., Lam, M.: A data locality optimizing algorithm. In: SIGPLAN 1991 Conference on Programming Language Design and Implementation, Toronto, Canada, pp. 30–44 (1991)Google Scholar
  5. 5.
    McKinley, K., Carr, S., Tseng, C.W.: Improving data locality with loop transformation. ACM Transactions on Programming Languages and Systems 18(4), 424–453 (1996)CrossRefGoogle Scholar
  6. 6.
    Bik, A.J.C., Knijnenburg, P.M.W.: Reshaping Access Patterns for Improving Data Locality. In: Proc. of 6th Workshop on Compilers for Parallel Computers (1996)Google Scholar
  7. 7.
    Clauss, P., Meister, B.: Automatic memory layout transformations to optimize spatial locality in parameterized loop nests. ACM SIGARCH Computer Architecture News 28(1), 11–19 (2000)CrossRefGoogle Scholar
  8. 8.
    Kandemir, M., Choudhary, A., Shenoy, N., Banerjee, P., Ramanujam, J.: A hyperplane based approach for optimizing spatial locality in loop nests. In: Proc. of 1998 ACM International Conference on Supercomputing (ICS 1998), Melbourne, Australia, pp. 69–76 (1998)Google Scholar
  9. 9.
    Jun, X., Xue-Jun, Y., Li-Fang, Z., Hai-Fang, Z.: A projection-delamination based approach for optimizing spatial locality in loop nests. Chinese Journal of Computers 26(5), 539–551 (2003)Google Scholar
  10. 10.
    Cierniak, M., Li, W.: Unifying data and control transformations for distributed shared memory machines. In: SIGPLAN 1995 Conference on Programming Language Design and Implementation, La Jolla, CA, pp. 205–217 (1995)Google Scholar
  11. 11.
    Kandemir, M., Choudhary, A., Ramanujam, J., Banerjee, P.: A matrix-based approach to global locality optimization. Journal of Parallel and Distributed Computing 58, 190–235 (1999)CrossRefGoogle Scholar
  12. 12.
    Kandemir, M., Banerjee, P., Choudhary, A., Ramanujam, J., Ayguade, E.: Static and dynamic locality optimizations using integer linear programming. IEEE Transactions on Parallel and Distributed Systems 12(9), 922–940 (2001)CrossRefGoogle Scholar
  13. 13.
    High Performance Computational Chemistry Group. NWChem: A computational chemistry package for parallel computers, version 1.1. Pacific Northwest Laboratory (1995)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Xia Jun
    • 1
  • Xue-Jun Yang
    • 1
  1. 1.School of Computer ScienceNational University of Defense TechnologyHunanChina

Personalised recommendations