Parallel neural network simulation using sparse matrix techniques
β Scribed by Jeremy Cook; John Gilbert
- Book ID
- 107910190
- Publisher
- Elsevier Science
- Year
- 1988
- Weight
- 278 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0165-6074
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Sparse matrix problems are difficult to parallelize efficiently on distributed memory machines since data is often accessed indirectly. Inspector-executor strategies, which are typically used to parallelize loops with indirect references, incur substantial runtime preprocessing overheads when refere
AbstractIt is shown how computation to determine steady-state conditions in pipeline networks can be greatly facilitated using sparse computation techniques. Three network algorithms for direction assignment, node-arc ordering and construction of a minimal length cycle set have been devised for this