A new technique to reduce false sharing in parallel irregular codes based on distance functions

In this paper a technique to deal with the problem of poor locality and false sharing in irregular codes on shared memory multiprocessors (SMPs) is proposed. This technique is based on the locality model for irregular codes previously developed and extensively proven by the authors on monoprocessors and multiprocessors. In the model, locality is established in run-time considering parameters that describe the structure of the sparse matrix which characterizes the irregular accesses. As an example of irregular code with false sharing a particular implementation of the sparse matrix-vector product (SpM×V) was selected. The problem of increasing locality and decreasing false sharing for a irregular problem is formulated as a graph. An adequate distribution of the graph among processors followed by a reordering of the nodes inside each processor produces the solution. The results show important improvements in the behavior of the irregular accesses: reductions in execution time and an improved program scalability.