Local enumeration techniques for sparse algorithms

Several methods have been proposed in the literature for the local enumeration of dense references for arrays distributed by the CYCLIC(k) data-distribution in High Performance Fortran. These methods deal only with loops without any irregular references. However existing techniques are not enough when the code includes sparse references. In this work, some methods for enumeration of references are proposed and tested for some linear sparse algebra algorithms. We use the BRS(k) distribution for sparse matrices, which is a generalization of the dense CYCLIC(k) distribution. Efficiency evaluation for the proposed methods has been performed on different processors