Amber: Programming Support for Networks of Multiprocessors

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This research concerns the design and implementation of a programming system for building highly parallel applications on networks of multiprocessors. Multiprocessor based shared memory multiprocessors are becoming widely available and promise to provide cost effective high performance computing. Multiprocessor workstations will surely be widely available within the next year: one expects them to be even more cost effective than their mainframe counterparts for many applications, just as current uniprocessor workstations often are more cost effective than uniprocessor mainframes. Simply stated, the goal of this research is to provide a facility for programming a network of multiprocessors as if it were a large, integrated, shared memory computer. This effort requires study of several aspects of operating system structure. First, there is a search for programming primitives that provide the right level of abstraction for expressing parallel algorithms. The important tradeoff, in a system integrating parallelism and distribution, is providing uniformity of access across the network without sacrificing local performance. Second, one must explore alternatives in operating system organization for increasing performance on a single multiprocessor node. The objective here is to provide the lowest overhead mechanisms for parallel execution so that programmers can express and utilize medium grained parallelism. Third, one must develop tools that aid the programmer in assessing the performance of his or her application, and in properly optimizing it for an environment of networked multiprocessors. This project is a natural outgrowth of a program of research in distributed and parallel computing systems in which we have been involved for the past 8 years. This program of research has been supported by NSF under a variety of awards; it also has received significant support from industrial sources, particularly Digital Equipment Corporation, whose Firefly prototype multiprocessor workstations will be our experimental vehicle. (The DECSystems Research Center has supplied Fireflys to Washington, Stanford, MIT, Princeton, Toronto, and Cambridge, making these universities uniquely well equipped to conduct experimental research on medium scale multiprocessing.) The results that we have already obtained in our preliminary work on support for parallel computing are in active use by many university sites and by companies such as Sequent, Digital, Microsoft, and Tera.