Parallel computer systems: performance instrumentation and visualization
Parallel computer systems: performance instrumentation and visualization
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
A Performance Visualization Tool for HPF and MPI Iterative Solvers
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
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The selection of the best method and preconditioner for solving a sparse linear system is as determinant as the efficient parallelization of the selected method. We propose a tool for helping to solve both problems on distributed memory multiprocessors using iterative methods. Based on a previously developed library of HPF and message-passing interface (MPI) codes, a performance prediction is developed and a visualization tool (AVISP A) is proposed. The tool combines theoretical features of the methods and preconditioners with practical considerations and predictions about aspects of the execution performance (computational cost, communications overhead, etc.). It offers detailed information about all the topics that can be useful for selecting the most suitable method and preconditioner. Another capability is to offer information on different parallel implementations of the code (HPF and MPI) varying the number of available processors.