Abstract
We discuss implementing blocked sparse matrix-vector multiplication for NVIDIA GPUs. We outline an algorithm and various optimizations, and identify potential future improvements and challenging tasks. In comparison with previously published implementation, our implementation is faster on matrices having many high fill-ratio blocks but slower on matrices with low number of non-zero elements per row.
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Monakov, A., Avetisyan, A. (2009). Implementing Blocked Sparse Matrix-Vector Multiplication on NVIDIA GPUs. In: Bertels, K., Dimopoulos, N., Silvano, C., Wong, S. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2009. Lecture Notes in Computer Science, vol 5657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03138-0_32
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DOI: https://doi.org/10.1007/978-3-642-03138-0_32
Publisher Name: Springer, Berlin, Heidelberg
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