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In this paper, we present an efficient and high performance linear recursive variable expansion (RVE) implementation of the Smith-Waterman (S-W) algorithm and compare it with a traditional linear systolic array implementation. The results demonstrate that the linear RVE implementation performs up to 2.33 times better than the traditional linear systolic array implementation, at the cost of utilizing...
In this paper we adapted a novel approach for accelerating the Smith-Waterman (S-W) algorithm using Recursive Variable Expansion (RVE), which exposes extra parallelism in the algorithm, as compared to any other technique. The results demonstrate that applying the recursive variable expansion technique speeds up the performance by a factor of 1.36 to 1.41, as compared to traditional acceleration approaches...
The Smith-Waterman (SW) algorithm is a local sequence alignment algorithm that attempts to align two biological sequences of varying length such that the alignment score is maximum. In this paper, we propose a new approach to reduce the time needed to perform the SW algorithm. This is done by applying the concept of recursive variable expansion, which exposes more parallelism in the algorithm than...
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