Leveraging Hierarchical Data Locality in Parallel Programming Models

We are proposing a novel framework that ameliorates locality-aware parallel programming models, by defining hierarchical data locality model extension. We also propose a hierarchical thread partitioning algorithm. This algorithm synthesizes hierarchical thread placement layouts that targets minimizing the program´s overall communication costs. We demonstrated the effectiveness of our approach using NAS Parallel Benchmarks implemented in Unified Parallel C (UPC) language using a modified Berkeley UPC Compiler and runtime system. We demonstrated an up to 85% improvement in performance by applying the placement layout suggested by our algorithm.