Abstract
The role of performance modeling in the implementation and evaluation of annealing-based parallel-placement algorithms is examined. The statistical behavior of an annealing algorithm changes profoundly as it runs, a characteristic that suggested adaptive parallel decompositions that dynamically alter the parallel partitioning to optimize speedup over each different regime of the annealing problem. A probabilistic model is derived for a two-strategy adaptive partitioning of standard cell placement on a shared-memory multiprocessor. The model correctly predicts how to switch strategies to maximize speedup.
Original language | English (US) |
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Title of host publication | Unknown Host Publication Title |
Publisher | IEEE |
Pages | 434-437 |
Number of pages | 4 |
ISBN (Print) | 0818607351 |
State | Published - Dec 1 1986 |
ASJC Scopus subject areas
- Engineering(all)