Recently, we have introduced an approach to basic sparse matrix computations on multicore cache based machines using recursive partitioning. Here, the memory representation of a sparse matrix consists of a set of submatrices, which are used as leaves of a quad-tree structure. In this paper, we evaluate the performance impact, on the Sparse Matrix-Vector Multiplication (SpMV), of a modification to our Recursive CSR implementation, allowing the use of multiple data structures in leaf matrices (CSR/COO, with either 16/32 bit indices).
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