MPI support is nearly ubiquitous on high performance systems today, and is generally highly tuned for performance. It would thus seem to offer a convenient “portable network assembly language” to developers of parallel programming languages who wish to target different network architectures. Unfortunately, neither the traditional MPI 1.1 API, nor the newer MPI 2.0 extensions for one-sided communication provide an adequate compilation target for global address space languages, and this is likely to be the case for many other parallel languages as well. Simulating one-sided communication under the MPI 1.1 API is too expensive, while the MPI 2.0 one-sided API imposes a number of significant restrictions on memory access patterns that that would need to be incorporated at the language level, as a compiler can not effectively hide them given current conflict and alias detection algorithms.

Unified Parallel C (UPC) is a parallel language that uses a Single Program Multiple Data (SPMD) model of parallelism within a global address space. The global address space is used to simplify programming, especially on applications with irregular data structures that lead to fine-grained sharing between threads. Recent results have shown that the performance of UPC using a commercial compiler is comparable to that of MPI [7]. In this paper we describe a portable open source compiler for UPC. Our goal is to achieve a similar performance while enabling easy porting of the compiler and runtime, and also provide a framework that allows for extensive optimizations. We identify some of the challenges in compiling UPC and use a combination of micro-benchmarks and application kernels to show that our compiler has low overhead for basic operations on shared data and is competitive, and sometimes faster than, the commercial HP compiler. We also investigate several communication optimizations, and show significant benefits by hand-optimizing the generated code.