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

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