Efficient Sparse Matrix-Vector Multiplication on CUDA

@inproceedings{Bell2008EfficientSM,
  title={Efficient Sparse Matrix-Vector Multiplication on CUDA},
  author={Nathan Bell and Michael Garland},
  year={2008}
}
The massive parallelism of graphics processing units (GPUs) offers tremendous performance in many high-performance computing applications. While dense linear algebra readily maps to such platforms, harnessing this potential for sparse matrix computations presents additional challenges. Given its role in iterative methods for solving sparse linear systems and eigenvalue problems, sparse matrix-vector multiplication (SpMV) is of singular importance in sparse linear algebra. In this paper we… CONTINUE READING
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