Global communication analysis and optimization
PLDI '96 Proceedings of the ACM SIGPLAN 1996 conference on Programming language design and implementation
Run-time parallelization: its time has come
Parallel Computing - Special issues on languages and compilers for parallel computers
Efficient Loop Partitioning for Parallel Codes of Irregular Scientific Computations
ICA3PP '02 Proceedings of the Fifth International Conference on Algorithms and Architectures for Parallel Processing
Effective communication coalescing for data-parallel applications
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
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For irregular applications on distributed-memory systems, computation partition is an important issue on parallel compiling techniques of parallelizing compilers. In this paper, we propose a local optimal solution, called heuristic computes rule (HCR), which could be used for irregular loop partitioning. This rule considers both the iteration being partitioned and the iterations partitioned, which ensures that iterations are assigned so as to produce less communication costs. And HCR rule proposes that irregular loop partitioning should trade off the maximum message degrees of processors, the number of messages, the message sizes, and workload balance. In our experiments, we compare HCR with almost owner computes rule and least communication computes rule. The results show that the executing of irregular loop partitioned by HCR rule has much less communication cost and achieve better performance.