|Title||Unstructured computational meshes and data locality|
|Project(s)||Meeting Exascale Computing with Source-to-Source Compilers, Department of High Performance Computing|
|Publication Type||Talks, invited|
|Year of Publication||2019|
|Location of Talk||Fifth Workshop on Programming Abstractions for Data Locality (PADAL'19), Inria Bordeaux, France|
|Keywords||data locality, HPC|
Many scientific and engineering applications rely on unstructured computational meshes to capture the irregular shapes and intricate details involved. With respect to software implementation, unstructured meshes require indirectly-indexed, irregular accesses to data arrays. Attaining data locality in the memory hierarchy is thus challenging. This talk touches two related topics. First, we look at the ordering/clustering of entities in an unstructured mesh with respect to cache efficiency. Second, we re-examine the currently widely-used strategy of mesh partitioning, which is based on partitioning a corresponding graph with edge-cut as the optimisation objective. Mismatches between this mainstream methodology of data decomposition and the increasingly heterogeneous computing platforms will be discussed.