A Software Environment for High-Performance Parallel Computing

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Before high-performance MIMD architectures become commonplace in production scientific, engineering, and business applications, three programming problems that plague current systems must be solved. First, writing parallel programs by hand is very difficult. The programmer must manage communication, synchronization, and scheduling of tens to thousands of independent processes. The burden of correctly managing the environment often overwhelms programmers. Second, once implemented on a particular MIMD architecture, the resulting codes are usually not usable on other MIMD architectures, necessitating a substantial effort to port. This discourages users from parallelizing their code, since new architectures are introduced so frequently. Third, there is no software support for transparently executing applications on heterogeneous "meta- systems" comprised of a variety of high-performance architectures. This proposal addresses all three of these problems. We have attacked the first two with Mentat, an easy-to-use, object- oriented, parallel processing system developed at the University of Virginia. We plan to test the efficacy of the Mentat approach on a set of real applications on a variety of platforms. The objective is to determine whether Mentat is easy to use on real applications and to measure performance. Our approach to the third problem is evolutionary. We will extend Mentat into a heterogeneous environment, and use the extended Mentat as a test- bed for meta-systems experimentation. Based on experimental results, a prototype meta-system that provides an easy-to-use, high performance abstraction for users will be constructed.