LightSpMV is a novel CUDA-compatible sparse matrix-vector multiplication (SpMv) algorithm using the standard compressed sparse row (CSR) storage format. We have evaluated LightSpMV using various sparse matrices and further compared it to the CSR-based SpMV subprograms in the state-of-the-art CUSP and cuSPARSE. Performance evaluation reveals that on a single Tesla K40c GPU, LightSpMV is superior to both CUSP and cuSPARSE, with a speedup of up to 2.60 and 2.63 over CUSP, and up to 1.93 and 1.79 over cuSPARSE for single and double precision, respectively.

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Categories

Bio-Informatics, Machine Learning, Statistics

License

Apache License V2.0

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Additional Project Details

Operating Systems

BSD, Linux

User Interface

Console/Terminal

Programming Language

C++

Related Categories

C++ Bio-Informatics Software, C++ Machine Learning Software, C++ Statistics Software

Registered

2014-12-18
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