Compute pairwise Manhattan distance and Pearson correlation coefficient of data points with GPU

10th ACIS Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2009, In conjunction with IWEA 2009 and WEACR 2009

Volumn , Issue , 2009, Pages 501-506

  Chang, Dar Jen ^a   Desoky, Ahmed H ^a   Ouyang, Ming ^a   Rouchka, Eric C ^a  

^a University of Louisville ^*  (United States)

Author keywords

Hierarchical clustering; Parallel and distributed computation; Similarity and dissimilarity metrics

Indexed keywords

CENTRAL PROCESSING UNITS; COMPUTATIONAL DEVICES; DATA ANALYSIS; DATA POINTS; DISTRIBUTED COMPUTATIONS; DNA MICROARRAY TECHNOLOGY; FUNDAMENTAL OPERATIONS; GENERAL-PURPOSE COMPUTING; GPU PROGRAMMING; GRAPHICS PROCESSING UNITS; HIER-ARCHICAL CLUSTERING; HIGH THROUGHPUT; IF THERE ARE; IN-CELL; MANHATTAN DISTANCE; PAIRWISE DISTANCES; PEARSON CORRELATION COEFFICIENTS; REAL TIME GRAPHICS; SPEED-UPS;

ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS EQUIPMENT; GENES; IMAGE CODING; LINGUISTICS; NUCLEIC ACIDS; PROGRAM PROCESSORS; SOFTWARE ENGINEERING;

CLUSTER ANALYSIS;

EID: 71249093935     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SNPD.2009.34     Document Type: Conference Paper

References (13)

1. Altschul S, Madden T, Schaffer A, Zhang J, Zhang Z, Miller W, Lipman D. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25:3389-402.
2. Brown P, Botstein D. Exploring the new world of the genome with DNA microarrays. Nat Genet 1999, 21:33-7.
3. Chang D, Jones NA, Li D, Ouyang M, Ragade RK. Compute pairwise Euclidean distances of data points with GPUs. Proceedings of the IASTED International Symposium on Computational Biology and Bioinformatics 2008, 278-283.
4. Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 1998, 95(25):14863-8.
5. Hartigan JA. Clustering Algorithms, Wiley, New York, 1975.
6. Kernighan BW, Ritchie DM. The C Programming Language, Second Edition, Prentice Hall, Inc., 1988.
7. Liu W, Schmidt B, Voss G, Muller-Wittig W. Streaming algorithms for biological sequence alignment on GPUs. IEEE Transactions on Parallel and Distributed Systems 2007, 18:1270-81.
8. Manavski SA, Valle G. CUDA compatible GPU cards as efficient hardware accelerators for Smith-Waterman sequence alignment. BMC Bioinformatics 2008, 9(Suppl 2):S10.
9. Nvidia Corporation, NVIDIA CUDA Programming Guide, Version 2.0 June 7, 2008. http://developer.download.nvidia.com/compute/cuda/2.0-Beta2/docs/ Programming Guide 2.0beta2.pdf
10. Quackenbush J. Microarray data normalization and transformation. Nat Genet 2002, 32 Suppl:496-501.
11. Schatz MC, Trapnell C, Delcher AL, Varshney A. High-throughput sequence alignment using Graphics Processing Units. BMC Bioinformatics 2007 8:474.
12. Sherlock G, Hernandez-Boussard T, Kasarskis A, Binkley G, Matese J, Dwight S, Kaloper M, Weng S, Jin H, Ball C, Eisen M, Spellman P, Brown P, Botstein D, Cherry J. The Stanford Microarray Database. Nucleic Acids Res 2001, 29:152-5.
13. Zhang Q, Zhang Y. Hierarchical clustering of gene expression profiles with graphics hardware acceleration. Pattern Recognition Letters 2006, 27:676-81.