A bit-string longest-common-subsequence algorithm
Information Processing Letters
ACM Transactions on Database Systems (TODS)
Parallel processing of biological sequence comparison algorithms
International Journal of Parallel Programming
An O(NP) sequence comparison algorithm
Information Processing Letters
Text algorithms
Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
A fast bit-vector algorithm for approximate string matching based on dynamic programming
Journal of the ACM (JACM)
The String-to-String Correction Problem
Journal of the ACM (JACM)
Algorithms for the Longest Common Subsequence Problem
Journal of the ACM (JACM)
A linear space algorithm for computing maximal common subsequences
Communications of the ACM
A fast and practical bit-vector algorithm for the longest common subsequence problem
Information Processing Letters
Algorithms and Theory of Computation Handbook
Algorithms and Theory of Computation Handbook
A Survey of Longest Common Subsequence Algorithms
SPIRE '00 Proceedings of the Seventh International Symposium on String Processing Information Retrieval (SPIRE'00)
A bit-vector algorithm for computing Levenshtein and Damerau edit distances
Nordic Journal of Computing - Special issue: Selected papers of the Prague Stringology conference (PSC'02), September 23-24, 2002
Efficient Subsequence Matching Using the Longest Common Subsequence with a Dual Match Index
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Acceleration of the Smith-Waterman algorithm using single and multiple graphics processors
Journal of Computational Physics
Improving CUDASW++, a Parallelization of Smith-Waterman for CUDA Enabled Devices
IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
GPU accelerated computation of the longest common subsequence
Facing the Multicore-Challenge II
Parallel longest common subsequence using graphics hardware
EG PGV'08 Proceedings of the 8th Eurographics conference on Parallel Graphics and Visualization
Shortest Path Based Potential Common Friend Recommendation in Social Networks
CGC '12 Proceedings of the 2012 Second International Conference on Cloud and Green Computing
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Graphic Processing Units (GPUs) have been gaining popularity among high-performance users. Certain classes of algorithms benefit greatly from the massive parallelism of GPUs. One such class of algorithms is longest common subsequence (LCS). Combined with bit parallelism, recent studies have been able to achieve terascale performance for LCS on GPUs. However, the reported results for the one-to-many matching problem lack correlation with weighted scoring algorithms. In this paper, we describe a novel technique to improve the score significance of the length of LCS algorithm for multiple matching. We extend the bit-vector algorithms for LCS to include integer scoring and parallelize them for hybrid CPU-GPU platforms. We benchmark our algorithm against the well-known sequence alignment algorithm on GPUs, CUDASW++, for accuracy and report performance on three different systems.