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Open Access Publications from the University of California

Sequence Compaction to Preserve Transition Frequencies


Simulation-based power estimation is commonly used for its high accuracy despite excessive computation times. Techniques have been proposed to speed it up by compacting an input sequence while preserving its power-consumption characteristics. We propose a novel method to compact a sequence that preserves transition frequencies. We prove the problem is NP-Complete, and propose a graph model to reduce it to that of finding a heaviest weighted trail on a directed graph, along with a heuristic utilizing this model. We also propose using multiple sequences for better accuracy with even shorter sequences. Experiments showed that power dissipation can be estimated with an error of only 2.3 percent, while simulation times are reduced by 10. Proposed methods effectively preserve transition frequencies and generated solutions that are very close to an optimal. Experiments also showed that multiple sequences granted more accurate results with even shorter sequences.

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