A bridging model for parallel computation
Communications of the ACM
LogP: towards a realistic model of parallel computation
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
A static parameter based performance prediction tool for parallel programs
ICS '93 Proceedings of the 7th international conference on Supercomputing
Optimal orthogonal tiling of 2-D iterations
Journal of Parallel and Distributed Computing
Visualizing the Performance of Parallel Programs
IEEE Software
Optimal Mapping of Pipeline Algorithms (Research Note)
Euro-Par '00 Proceedings from the 6th International Euro-Par Conference on Parallel Processing
A Skeleton for Parallel Dynamic Programming
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
DiP: A Parallel Program Development Environment
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
Parallelism in random access machines
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
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Given an algorithm and architecture a tuning parameter is an input parameter that has consequences in the performance but not in the output. The list of tuning parameters in parallel computing is extensive: some depending on the architecture, as the number of processors and the size of the buffers used during data exchange and some depending on the application. We formalize the General Tuning Problem and propose a generic methodology to solve it. The technique is applied to the special case of pipeline algorithms. A tool that automatically solves the prediction of the tuning parameters is presented. The accuracy is tested on a CRAY T3E. The results obtained suggest that the technique could be successfully ported to other paradigms.