In our earlier work, we have investigated the feasibility of utilization of recursive partitioning in basic (BLAS oriented) sparse matrix computations, on multi-core cache-based computers. Following encouraging experimental results obtained for SpMV and SpSV operations, here we proceed to tune the storage format. To limit the memory bandwidth overhead we introduce usage of shorter (16 bit) indices in leaf sub matrices (at the end of the recursion). Experimental results obtained for the proposed approach on 8-core machines illustrate speed improvements, when performing sparse matrix-vector multiplication.
Martone, M., Filippone, S., Paprzycki, M., Tucci, S. (2010). On the usage of 16 bit indices in recursively stored sparse matrices. In Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2010 12th International Symposium on (pp.57-64). IEEE Computer Society [10.1109/SYNASC.2010.77].
On the usage of 16 bit indices in recursively stored sparse matrices
FILIPPONE, SALVATORE;TUCCI, SALVATORE
2010-01-01
Abstract
In our earlier work, we have investigated the feasibility of utilization of recursive partitioning in basic (BLAS oriented) sparse matrix computations, on multi-core cache-based computers. Following encouraging experimental results obtained for SpMV and SpSV operations, here we proceed to tune the storage format. To limit the memory bandwidth overhead we introduce usage of shorter (16 bit) indices in leaf sub matrices (at the end of the recursion). Experimental results obtained for the proposed approach on 8-core machines illustrate speed improvements, when performing sparse matrix-vector multiplication.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
