Efficient search-space pruning for integrated fusion and tiling transformations
Document Type
Conference Proceeding
Publication Date
12-1-2006
Abstract
Compile-time optimizations involve a number of transformations such as loop permutation, fusion, tiling, array contraction, etc. Determination of the choice of these transformations that minimizes the execution time is a challenging task. We address this problem in the context of tensor contraction expressions involving arrays too large to fit in main memory. Domain-specific features of the computation are exploited to develop an integrated framework that facilitates the exploration of the entire search space of optimizations. In this paper, we discuss the exploration of the space of loop fusion and tiling transformations in order to minimize the disk I/O cost. These two transformations are integrated and pruning strategies are presented that significantly reduce the number of loop structures to be evaluated for subsequent transformations. The evaluation of the framework using representative contraction expressions from quantum chemistry shows a dramatic reduction in the size of the search space using the strategies presented. © 2006 Springer-Verlag Berlin Heidelberg.
Publication Source (Journal or Book title)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
First Page
215
Last Page
229
Recommended Citation
Gao, X., Krishnamoorthy, S., Sahoo, S., Lam, C., Baumgartner, G., Ramanujam, J., & Sadayappan, P. (2006). Efficient search-space pruning for integrated fusion and tiling transformations. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4339 LNCS, 215-229. https://doi.org/10.1007/978-3-540-69330-7_15
