Abstract

Mentat is an object-oriented parallel processing system developed at the University of Virginia which has been ported to a variety of MIMD architectures. The computation model employed by Mentat is macro data-flow (MDF), a medium grain, scalable, data-driven computation model that supports both high degrees of parallelism and the object-oriented paradigm. A key aspect of the model is that it can be efficiently implemented. Inspired by data-flow, MDF retains the graph-based, data-driven, self-synchronizing aspects of data-flow. MDF address the shortcomings that data-flow exhibits when applied to distributed memory MIMD architectures by extending data-flow in three ways: (1) it is medium grain - actors are of sufficient computational complexity to amortize overhead costs, (2) program graphs are dynamically constructed at runtime - this permits dynamic function binding as required by the object-oriented paradigm and increases the average computation granularity, and (3) actors may maintai...

Citations