Global Communication Optimization for Tensor Contraction Expressions under Memory Constraints

The accurate modeling of the electronic structure of atoms and molecules involves computationally intensive tensor contractions involving large multi-dimensional arrays. The efficient computation of complex tensor contractions usually requires the generation of temporary intermediate arrays. These intermediates could be extremely large, but they can often be generated and used in batches through appropriate loop fusion transformations. To optimize the performance of such computations on parallel computers, the total amount of interprocessor communication must be minimized, subject to the available memory on each processor. In this paper, we address the memory-constrained communication minimization problem in the context of this class of computations. Based on a framework that models the relationship between loop fusion and memory usage, we develop an approach to identify the best combination of loop fusion and data partitioning that minimizes inter-processor communication cost withou...

• Type: Conference
• Year: 2003
• Where: IPPS
• Authors: Daniel Cociorva, Xiaoyang Gao, Sandhya Krishnan, Gerald Baumgartner, Chi-Chung Lam, P. Sadayappan, J. Ramanujam
• Keywords: Distributed And Parallel Computing, Intensive Tensor Contractions, IPPS 2003, Loop Fusion, Tensor Contractions