Exploiting the forgiving nature of applications for scalable parallel execution

Proceedings of the 2010 IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2010

Volumn , Issue , 2010, Pages

  Meng, Jiayuan ^a,b   Raghunathan, Anand ^a,c   Chakradhar, Srimat ^a   Byna, Surendra ^a  

^a NEC LABORATORIES AMERICA   (United States)

^b University of Virginia   (United States)

^c PURDUE UNIVERSITY   (United States)

Author keywords

Best effort computing; Dependency relaxation; Mining; Multi core; Parallel computing; Parallel programming; Recognition

Indexed keywords

BEST-EFFORT; BEST-EFFORT COMPUTING; DATA DEPENDENCIES; DATA PARALLEL; DIFFERENT ORDER; DOCUMENT SEARCH; DOMAIN SPECIFIC; ERROR MITIGATION; EYE DETECTION; GENERALIZED LEARNING VECTOR QUANTIZATION; INPUT DATAS; LINEAR SPEED-UP; MODEL UPDATES; MULTI CORE; OFF-CHIP; OFF-CHIP MEMORIES; OUTPUT QUALITY; PARALLEL COMPUTING; PARALLEL COMPUTING PLATFORM; PARALLEL EXECUTIONS; PARALLEL IMPLEMENTATIONS; PARALLEL SCALABILITY; PARALLEL TASK; RUN-TIME LIBRARY; RUNTIMES; SELF-HEALING; SEMANTIC INDEXING; SEQUENTIAL IMPLEMENTATION; SPATIAL LOCALITY;

DATA PROCESSING; DISTRIBUTED PARAMETER NETWORKS; EYE PROTECTION; PARALLEL ARCHITECTURES; SCALABILITY; VECTOR QUANTIZATION;

PARALLEL PROGRAMMING;

EID: 77954013670     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IPDPS.2010.5470469     Document Type: Conference Paper

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