NSF Award
9309054
9309054 Hudak Shared-address distributed-memory massively parallel processing (MPP) system offer the simplicity of a single address space while maintaining the potential for teraflops performance. However, to obtain reasonable efficiency on these systems, the programmer or compiler must specify and appropriate distribution of work and data among the processors and the physically distributed memories. This project will address the problem of determining the optimal distributions for a given parallel application. Ongoing research in compilation for MPP's has yielded a collection of techniques for the specification of work and data distributions for individual data-parallel loops. This project will combine those techniques with flow-graph representations of data-parallel programs to generate code which specifics the creation and alteration of work and data distributions. The distributions will be designed maximum efficiency across program constructs for altering the flow of control of a program, such as conditional statements (e.g., if statements) and procedure calls. The research will lead to the development of a software system named DPF+, a new system that will analyze an partition data- parallel programs as well as provide an efficient environment for object-oriented data-parallel programming. Data parallel program can be built from user-defined objects, with the DFT+ compiler automatically tuning each object's procedures for high performance on an existing shared-address spaced multiprocessor system. This research will greatly increase the usability of MPPs, the portability of parallel programs and the performance level achieved by users. ***
