Data distributions for sparse matrix vector multiplication
Parallel Computing
Software—Practice & Experience
Modeling and improving locality for the sparse-matrix-vector product on cache memories
Future Generation Computer Systems - I. High Performance Numerical Methods and Applications. II. Performance Data Mining: Automated Diagnosis, Adaption, and Optimization
Performance Prediction for Parallel Iterative Solvers
ICCS '02 Proceedings of the International Conference on Computational Science-Part II
AVISPA: visualizing the performance prediction of parallel iterative solvers
Future Generation Computer Systems - Tools for program development and analysis
Performance Prediction for Parallel Iterative Solvers
The Journal of Supercomputing
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In this paper, a tool for predicting and visualizing the performance of iterative methods is presented. These codes come from an exhaustive parallel library of sparse iterative methods and preconditioners in HPF and MPI, developed in a previous work. The tool can be used, both by users and by library developers, to optimize the efficiency of the codes, as well as to simplify their use. The information offered by this tool combines theoretical features of the methods and preconditioners, in addition to certain practical considerations and predictions about aspects of the performance of their execution in distributed memory multiprocessors.