Memory efficient parallel matrix multiplication operation for irregular problems
Proceedings of the 3rd conference on Computing frontiers
Thread-safety in an MPI implementation: Requirements and analysis
Parallel Computing
Toward Efficient Support for Multithreaded MPI Communication
Proceedings of the 15th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
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In modern clustering environments where the memory hierarchy has many layers (distributed memory, shared memory layer, cache, 驴), an important question is how to fully utilize all available resources and identify the most dominant layer in certain computation. When combining algorithms on all layers together, what would be the best method to get the best performance out of all the resources we have? Mixed mode programming model that uses thread programming on the shared memory layer and message passing programming on the distributed memory layer is a method that many researchers are using to utilize the memory resources. In this paper, we take an algorithmic approach that uses matrix multiplication as a tool to show how cache algorithms affect the performance of both shared memory anddistributed memory algorithms. We show that with good underlying cache algorithm, overall performance is stable. When underlying cache algorithm is bad, superlinear speedup may occur, and increasing number of threads may also improve performance.