GPU-accelerated protein sequence alignment

GPU-accelerated protein sequence alignment

Smith-Waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing Units (GPUs) accelerated S-W implementation for protein sequence alignment. The paper proposes a new sequence database organization and several o...

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Published in:2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2011; pp. 2442 - 2446
Main Authors: Hasan, L., Kentie, M., Al-Ars, Z.
Format: Conference Proceeding Journal Article
Language:English
Published: United States IEEE 01-01-2011
Subjects:
Acceleration
Algorithms
Bandwidth
Bioinformatics
Database Organization
Databases, Protein
GPUs
Graphics processing unit
Instruction sets
Matrices
Protein Sequence Alignment
Proteins
Proteins - chemistry
Sequence Homology, Amino Acid
Smith-Waterman Algorithm
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Abstract Smith-Waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing Units (GPUs) accelerated S-W implementation for protein sequence alignment. The paper proposes a new sequence database organization and several optimizations to reduce the number of memory accesses. The new implementation achieves a performance of 21.4 GCUPS, which is 1.13 times better than the state-of-the-art implementation on an NVIDIA GTX 275 graphics card.
AbstractList Smith-Waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing Units (GPUs) accelerated S-W implementation for protein sequence alignment. The paper proposes a new sequence database organization and several optimizations to reduce the number of memory accesses. The new implementation achieves a performance of 21.4 GCUPS, which is 1.13 times better than the state-of-the-art implementation on an NVIDIA GTX 275 graphics card.
Smith-Waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing Units (CPUs) accelerated S-W implementation for protein sequence alignment. The paper proposes a new sequence database organization and several optimizations to reduce the number of memory accesses. The new implementation achieves a performance of 21.4 GCUPS, which is 1.13 times better than the state-of-the-art implementation on an NVIDIA GTX 275 graphics card.
Author Al-Ars, Z.
Kentie, M.
Hasan, L.
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  organization: Comput. Eng. Lab., Tech. Univ. Delft, Delft, Netherlands
BackLink https://www.ncbi.nlm.nih.gov/pubmed/22254835$$D View this record in MEDLINE/PubMed
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Snippet Smith-Waterman (S-W) algorithm is an optimal sequence alignment method and is widely used for genetic databases. This paper presents a Graphics Processing...
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StartPage 2442
SubjectTerms Acceleration
Algorithms
Bandwidth
Bioinformatics
Database Organization
Databases, Protein
GPUs
Graphics processing unit
Instruction sets
Matrices
Protein Sequence Alignment
Proteins
Proteins - chemistry
Sequence Homology, Amino Acid
Smith-Waterman Algorithm
Title GPU-accelerated protein sequence alignment
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https://www.ncbi.nlm.nih.gov/pubmed/22254835
Volume 2011
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