This paper makes two proposals to speed up the Parallel Iterative Method, which is based on the iterative strategy of the Berger-Munson algorithm.
The first proposal is to exploit finer-grained parallelism in the DP (Dynamic Programming) procedure itself. This proposal makes the processing speed proportional to the number of processors.
The second proposal is to apply the A* algorithm, a well known heuristic search algorithm, instead of DP. A* reduces the search space using heuristics, while DP traverses the whole space blindly.
We have implemented these two proposals on a parallel computer, the AP1000. In a test of parallelizing DP, ten 1000-character sequences are aligned by using 10 processors per one DP procedure at a speed 8.11 times faster than sequential processing. By applying the A* algorithm to 30 sets of test problems, we obtain optimal alignment by reducing the search space by 95%.
