The scalability of distributed-memory parallel computers makes them attractive candidates for solving large-scale problems. New languages, such as HPF, FortranD, and VPP Fortran, have been developed to enable existing software to be easily ported to such machines. Many distributed-memory parallel computers have been built, but none of them support the mechanisms required by such languages. We studied the mechanisms required by parallelizing compilers and proposed a new architecture to support them. Based on this proposed architecture, we developed a new distributed-memory parallel computer, the AP1000+, which is an enhanced version of the AP1000. Using scientific applications in VPP Fortran and C, such as NAS parallel benchmarks, we simulated the performance of the AP1000+.

The performance of message-passing applications depends on cpu speed, communication throughput and latency, and message handling overhead. In this paper we investigate the effect of varying these parameters and applying techniques to reduce message handling overhead on the execution efficiency of ten different applications. Using a message level simulator set up for the architecture of the AP1000, we showed that improving communication performance, especially message handling, improves total performance. If a cpu that is 32 times faster is provided, the total performance increases by less than ten times unless message handling overhead is reduced. Overlapping computation with message reception improves performance significantly. We also discuss how to improve the AP1000 architecture.