Loop optimization for a class of memory-constrained computations

  • Authors:

  • D. Cociorva;J. W. Wilkins;C. Lam;G. Baumgartner;J. Ramanujam;P. Sadayappan

  • Affiliations:

  • Dept. of Physics, The Ohio State University, Columbus, OH;Dept. of Physics, The Ohio State University, Columbus, OH;Dept. of Comp. & Info. Sci., The Ohio State University, Columbus, OH;Dept. of Comp. & Info. Sci., The Ohio State University, Columbus, OH;Dept. of Elec. & Comp. Engr., Louisiana State University, Baton Rouge, LA;Dept. of Comp. & Info. Sci., The Ohio State University, Columbus, OH

  • Venue:
  • ICS '01 Proceedings of the 15th international conference on Supercomputing
  • Year:
  • 2001

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Abstract

Compute-intensive multi-dimensional summations that involve products of several arrays arise in the modeling of electronic structure of materials. Sometimes several alternative formulations of a computation, representing different space-time trade-offs, are possible. By computing and storing some intermediate arrays, reduction of the number of arithmetic operations is possible, but the size of intermediate temporary arrays may be prohibitively large. Loop fusion can be applied to reduce memory requirements, but that could impede effective tiling to minimize memory access costs. This paper develops an integrated model combining loop tiling for enhancing data reuse, and loop fusion for reduction of memory for intermediate temporary arrays. An algorithm is presented that addresses the selection of tile sizes and choice of loops for fusion, with the objective of minimizing cache misses while keeping the total memory usage within a given limit. Experimental results are reported that demonstrate the effectiveness of the combined loop tiling and fusion transformations performed by using the developed framework.