Parallel partitioned-inverse sparse matrix solutions
- Univ. of Wisconsin, Madison, WI (United States)
The partitioned inverse method has been demonstrated to be quite effective for parallel sparse matrix solutions on massively parallel machines. Though experiments on CM-2 have illustrated the advantage of using partitions, Intel iPSC/860 multiprocessor only favors fewer and denser partitions, particularly in the case of extremely sparse matrices. Different decomposition and communication algorithms are investigated here on the iPSC/860 to improve the performance. The decomposition is done in an interleave fashion in two different directions (row-wise and column-wise). The need for synchronization due to the interchange of intermediate solution vectors makes load balancing an important factor in obtaining an optimum performance.
- OSTI ID:
- 54444
- Report Number(s):
- DOE/ER/25151--1-Vol.1; CONF-930331--Vol.1; CNN: Grant ECS-8907391; Grant ECS09215271
- Country of Publication:
- United States
- Language:
- English
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