NDLI: CUDAlign:using GPU to accelerate the comparison of megabase genomic sequences

Content Provider	ACM Digital Library
Author	de Melo, Alba Cristina M.A. Sandes, Edans Flavius O.
Abstract	Biological sequence comparison is a very important operation in Bioinformatics. Even though there do exist exact methods to compare biological sequences, these methods are often neglected due to their quadratic time and space complexity. In order to accelerate these methods, many GPU algorithms were proposed in the literature. Nevertheless, all of them restrict the size of the smallest sequence in such a way that Megabase genome comparison is prevented. In this paper, we propose and evaluate CUDAlign, a GPU algorithm that is able to compare Megabase biological sequences with an exact Smith-Waterman affine gap variant. CUDAlign was implemented in CUDA and tested in two GPU boards, separately. For real sequences whose size range from 1MBP (Megabase Pairs) to 47MBP, a close to uniform GCUPS (Giga Cells Updates per Second) was obtained, showing the potential scalability of our approach. Also, CUDAlign was able to compare the human chromosome 21 and the chimpanzee chromosome 22. This operation took 21 hours on GeForce GTX 280, resulting in a peak performance of 20.375 GCUPS. As far as we know, this is the first time such huge chromosomes are compared with an exact method.
Starting Page	137
Ending Page	146
Page Count	10
File Format	PDF
ISSN	03621340 15581160
DOI	10.1145/1837853.1693473
Journal	ACM SIGPLAN Notices (SIGP)
Volume Number	45
Issue Number	5
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1983-05-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Smith-waterman Gpu Biological sequence comparison
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Fine-grain parallel megabase sequence comparison with multiple heterogeneous GPUs

Retrieving Smith-Waterman Alignments with Optimizations for Megabase Biological Sequences Using GPU

Fine-grain parallel megabase sequence comparison with multiple heterogeneous GPUs

Function to accelerate and/or induce sequence convergence

Accelerating Smith-Waterman Alignment of Species-Based Protein Sequences on GPU

Parallelizing dynamic programming through rank convergence

CUDAlign 3.0: Parallel Biological Sequence Comparison in Large GPU Clusters

GPU multisplit

CUDAlign:using GPU to accelerate the comparison of megabase genomic sequences

Similar Documents

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Fine-grain parallel megabase sequence comparison with multiple heterogeneous GPUs

Retrieving Smith-Waterman Alignments with Optimizations for Megabase Biological Sequences Using GPU

Fine-grain parallel megabase sequence comparison with multiple heterogeneous GPUs

Function to accelerate and/or induce sequence convergence

Accelerating Smith-Waterman Alignment of Species-Based Protein Sequences on GPU

Parallelizing dynamic programming through rank convergence

CUDAlign 3.0: Parallel Biological Sequence Comparison in Large GPU Clusters

GPU multisplit

CUDAlign:using GPU to accelerate the comparison of megabase genomic sequences