Efficient Machine-Independent Programming of High-Performance Multiprocessors

Abstract

Parallel computing is regarded by most computer scientists as the most likely approach for significantly improving computing power for scientists and engineers. Advances in programming languages and parallelizing compilers are making parallel computers easier to use by providing a high-level portable programming model that protects software investment. However, experience has shown that simply finding parallelism is not always sufficient for obtaining good performance from today's multiprocessors. The goal of this project is to develop advanced compiler analysis of data and computation decompositions, thread placement, communication, synchronization, and memory system effects needed in order to take advantage of performance-critical elements in modern parallel architectures.