Generating explicit communication from shared-memory program references
Jingke Li, Marina Chen · Conference on High Performance Computing (Supercomputing) · 1990
The authors address the problem of data distribution and communication synthesis in generating parallel programs targeted for massively parallel distributed-memory machines. The source programs can be sequential, functional, or parallel programs based on a shared-memory model. The approach is to analyze source program references and match syntactic reference patterns with appropriate aggregate communication routines which can be implemented efficiently on the target machine. An explicit communication metric is used to guide optimizations to reduce communication overhead. The target code with explicit communication is proven to be free from deadlock introduced by the compilation process. The techniques described are developed within the context of Crystal (functional language) though they can be applied to Fortran. The Crystal compiler generates C-code for an iPSC/2. >