Optimizing Smith-Waterman algorithm on Graphics Processing Unit

Khalafallah, Ayman; Elbabb, Hosain Fath; Omar, A.-Mohsen M.E.; Elshamy, Ahmed

doi:10.1109/icctd.2010.5645976

Cited by 12 publications

(10 citation statements)

References 17 publications

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“…Toward this end, several researchers have developed parallel versions of the Smith-Waterman algorithm that are suitable for Graphics Processing Units (GPUs) [6], [7], [8], [9], [10], [11]. Many of these implementations solve a variant of the pairwise sequence alignment problem that asks for the best k , k > 0, alignments.…”

Section: Introductionmentioning

confidence: 99%

Pairwise sequence alignment for very long sequences on GPUs

Ranka

Sahni

2012

2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)

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Section: Introductionmentioning

confidence: 99%

Pairwise sequence alignment for very long sequences on GPUs

Ranka

Sahni

2012

2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)

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“…CS-BLAST [7] a protein sequence search tool is an extension of BLAST, which is based on context-specific mutation probabilities. Several researchers have developed parallel versions of the Smith-Waterman algorithm that are suitable for Graphics Processing Units (GPUs) [8], [9], [10], [11], [12]. Zheng et.…”

Section: Related Workmentioning

confidence: 99%

A Shared Memory Based Implementation of Needleman-Wunsch Algorithm Using Skewing Transformation

Patel

Gandhi

Bhatti

2017

ijarcs

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Among various algorithms for protein and nucleotide alignment, Needleman-Wunsch algorithm is widely accepted as it can divide the problem into sub-problems. We present two parallel approaches of Needleman-Wunsch algorithm with single kernel and multi-kernel invocation using skewing transformation which is used for traversing and calculation of dynamic programming matrix. We also compare these with traditional CPU sequential approach which resulted in six fold performance improvement. Furthermore, we present same single kernel ideology on shared memory which resulted in two fold performance improvement over non-shared memory approach.

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“…9,10,14 These approaches are platform-specific because CUDA is only available for NVidia GPU cards. Another alternative is the use of a framework for heterogeneous platforms like Open Computing Language (OpenCL) 15 to implement this task, 16,17 allowing the execution of the same code in different architectures. However, these OpenCL solutions compare very small query sequences.…”

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confidence: 99%

MASA‐OpenCL: Parallel pruned comparison of long DNA sequences with OpenCL

Figueiredo

Sandes

Rodrigues

et al. 2018

Concurrency and Computation

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Summary Biological sequence comparison is often used as an auxiliary task in the analysis of genetic material. Pairwise comparison algorithms like Smith‐Waterman evaluate two strings representing sequences of proteins, DNA or RNA to obtain optimal alignment between them. Many applications have been proposed to address the sequence comparison problem, prioritizing the use of graphics cards and proprietary languages such as CUDA. In this paper, we propose and evaluate MASA‐OpenCL, an OpenCL solution for comparing long DNA sequences that is based on the MASA sequence alignment framework, with pruning capability proportional to the similarity of the sequences compared. The results of MASA‐OpenCL were compared to its CUDA counterpart (MASA‐CUDAlign) and, in most cases, MASA‐OpenCL achieved better performance. In order to better understand the behavior of MASA‐OpenCL, we performed a statistical analysis considering 11 comparisons of sequences with high, medium and low similarity in 4 GPUs. As a result, we obtained a multiple linear regression model that considers (a) the sizes of the sequences, (b) the similarity between them, (c) the computational power of the GPU, and (d) the GPU memory bandwidth. We used this model to predict the performance in two other GPUs, with low error rates.

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Optimizing Smith-Waterman algorithm on Graphics Processing Unit

Cited by 12 publications

References 17 publications

Pairwise sequence alignment for very long sequences on GPUs

Pairwise sequence alignment for very long sequences on GPUs

A Shared Memory Based Implementation of Needleman-Wunsch Algorithm Using Skewing Transformation

MASA‐OpenCL: Parallel pruned comparison of long DNA sequences with OpenCL

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