NUMA-ICTM: A Parallel Version of ICTM Exploiting Memory Placement Strategies for NUMA Machines

In geophysics, the appropriate subdivision of a region into segments is extremely important. ICTM (Interval Cat-egorizer Tesselation Model) is an application that cat-egorizes geographic regions using information extracted from satellite images. The categorization of large regions is a computational intensive problem, what justifies the proposal and development of parallel solutions in order to improve its applicability. Recent advances in multi-processor architectures lead to the emergence of NUMA (Non-Uniform Memory Access) machines. In this work, we present NUMA-ICTM: a parallel solution of ICTM for NUMA machines. First, we parallelize ICTM using OpenMP. After, we improve the OpenMP solution using the MAI (Memory Affinity Interface) library, which allows a control of memory allocation in NUMA machines. The re-sults show that the optimization of memory allocation leads to significant performance gains over the pure OpenMP parallel solution. 1