Parallelization of Weighted Sequence Comparison by using EBWT
Shashank Srikant
TL;DR
This paper presents a parallel implementation of a sequence comparison algorithm using EBWT and CUDA, achieving significant performance improvements for small sequences.
Contribution
It introduces a CUDA-based parallelization of the EBWT algorithm for sequence comparison, enhancing efficiency over existing sequential methods.
Findings
Average 2X performance improvement
Effective parallelization on GPU hardware
Potential for faster sequence analysis
Abstract
The Extended Burrows Wheeler transform (EBWT) helps to find the distance between two sequences. Implementation of an existing algorithm takes considerable amount of time for small size sequences. In this paper, we give a parallel implementation of this algorithm using NVIDIA Compute Unified Device Architecture (CUDA). We have obtained, on an average, a 2X improvement in the performance.
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Taxonomy
TopicsAdvanced Data Compression Techniques · Digital Filter Design and Implementation · Algorithms and Data Compression