Parallel algorithms for unconstrained optimizations by multisplitting
Conference
·
OSTI ID:219568
- Arizona State Univ., Tempe, AZ (United States)
In this paper a new parallel iterative algorithm for unconstrained optimization using the idea of multisplitting is proposed. This algorithm uses the existing sequential algorithms without any parallelization. Some convergence and numerical results for this algorithm are presented. The experiments are performed on an Intel iPSC/860 Hyper Cube with 64 nodes. It is interesting that the sequential implementation on one node shows that if the problem is split properly, the algorithm converges much faster than one without splitting.
- Research Organization:
- Front Range Scientific Computations, Inc., Boulder, CO (United States); USDOE, Washington, DC (United States); National Science Foundation, Washington, DC (United States)
- OSTI ID:
- 219568
- Report Number(s):
- CONF-9404305--Vol.2; ON: DE96005736
- Country of Publication:
- United States
- Language:
- English
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