Hybrid parallel programming with MPI and Unified Parallel C

The Message Passing Interface (MPI) is one of the most widely used programming models for parallel computing. However, the amount of memory available to an MPI process is limited by the amount of local memory within a compute node. Partitioned Global Address Space (PGAS) models such as Unified Parallel C (UPC) are growing in popularity because of their ability to provide a shared global address space that spans the memories of multiple compute nodes. However, taking advantage of UPC can require a large re-coding effort for existing parallel applications. In this paper, we explore a new hybrid parallel programming model that combines MPI and UPC. This model allows MPI pro-grammers incremental access to a greater amount of memory, en-abling memory-constrained MPI codes to process larger data sets. In addition, the hybrid model offers UPC programmers an opportu