A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Unifying data and control transformations for distributed shared-memory machines
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Improving data locality with loop transformations
ACM Transactions on Programming Languages and Systems (TOPLAS)
A hyperplane based approach for optimizing spatial locality in loop nests
ICS '98 Proceedings of the 12th international conference on Supercomputing
A matrix-based approach to global locality optimization
Journal of Parallel and Distributed Computing - Special issue on compilation and architectural support for parallel applications
Automatic memory layout transformations to optimize spatial locality in parameterized loop nests
ACM SIGARCH Computer Architecture News - Special issue on interaction between compilers and computer architectures
Static and Dynamic Locality Optimizations Using Integer Linear Programming
IEEE Transactions on Parallel and Distributed Systems
The Journal of Supercomputing
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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.