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Mentat, a dynamic, object-oriented parallel-processing system that provides tools for constructing portable, medium-grain parallel software by combining an object-oriented approach with an underlying layered virtual-machine model is described. Mentat's three primary design objectives-high performance through parallel execution, easy parallelism, and software portability across a wide range of platforms-are reviewed. The performance of four applications of Mentat on two platforms-a 32-node Intel iPSC/2 hypercube and a network of 16 Sun IPC Sparcstations-are examined. The applications are DNA and protein sequence comparison, image convolution, Gaussian elimination and partial pivoting, and sparse matrix-vector multiplication. The performance of Mentat in these applications is compared to that of object-oriented parallel-processing systems, compiler-based distributed-memory systems, portable parallel-processing systems, and hand-coded implementations of the same applications.