Modeling parallel computation via the fusion of timed Petri nets with an application to the mapping problem
Communications of the ACM
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Most computer architecture courses are geared toward the classical von Neumann style of computer architectures, mentioning only in passing other models such as data flow computation. This is unfortunate, due to the high degree of parallelism possible using data flow. We present an alternative course, designed as an elective in computer architecture for upper level undergraduate or graduate students, that presents a side-by-side comparison of von Neumann and data flow architectures.Our teaching environment is based on Simple Arithmetic SISAL (SAS), a subset of the applicative programming language SISAL, which we designed for both teaching about and research into data flow architectures. SAS runs in a highly integrated environment, allowing students to implement their program on a von Neumann architecture, then observe its execution through a data flow simulator. The environment runs on a standard IBM-style personal computer, providing a cost-effective platform for presenting the course.