Applying GPUs for Smith-Waterman Sequence Alignment Acceleration
نویسندگان
چکیده
منابع مشابه
Sequence Alignment in DNA Using Smith Waterman and Needleman Algorithms
Algorithm and scoring parameters Eg ”best” Two methods for searching protein and DNA Evolution of protein and DNA sequence is done using database. 1. Local comparison i) Ignoring difference-outside most similar region ii) Find similarity between two sequence 2. Gobal Comparison. More appropriate when homology has been established when Building evolutionary trees comparison methods are preferred...
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We present a performance per watt analysis of CUDAlign 4.0, a parallel strategy to obtain the optimal alignment of huge DNA sequences in multi-GPU platforms using the exact Smith-Waterman method. Speed-up factors and energy consumption are monitored on different stages of the algorithm with the goal of identifying advantageous scenarios to maximize acceleration and minimize power consumption. E...
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Sequence alignment lies at heart of the bioinformatics. The Smith-Waterman algorithm is one of the key sequence search algorithms and has gained popularity due to improved implementations and rapidly increasing compute power. Recently, the Smith-Waterman algorithm has been successfully mapped onto the emerging general-purpose graphics processing units (GPUs). In this paper, we focused on how to...
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Nowadays stack of biological data growing steeply, so there is need of smart way to handle and process these data to extract meaningful information related to biological life. The purpose of this survey is to study various parallel models which perform alignment of the sequences as fast as possible, which is a big challenge for both engineer and biologist. The various parallel models discussed ...
متن کاملParallelizing the Smith-Waterman Local Alignment Algorithm using CUDA
Given two strings S1 = pqaxabcstrqrtp and S2 = xyaxbacsl, the substrings axabcs in S1 and axbacs in S2 are very similar. The problem of finding similar substrings is the local alignment problem. Local alignment is extensively used in computational biology to find regions of similarity in different biological sequences. Similar genetic sequences are identified by computing the local alignment of...
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ژورنال
عنوان ژورنال: GSTF INTERNATIONAL JOURNAL ON COMPUTING
سال: 2011
ISSN: 2010-2283
DOI: 10.5176/2010-2283_1.2.56