Sparse matrix-vector multiplication is an integral part of many scientific algorithms. Several studies have shown that it is a bandwidth-limited operation on current hardware. On cache-based architectures the main factors that influence performance are spatial locality in accessing the matrix, and temporal locality in re-using the elements of the vector. © 2012 IEEE.
CITATION STYLE
Eguly, I. R., & Giles, M. (2012). Efficient sparse matrix-vector multiplication on cache-based GPUs. In 2012 Innovative Parallel Computing, InPar 2012. IEEE Computer Society. https://doi.org/10.1109/InPar.2012.6339602
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