Our goal is to devise a computer comprising large numbers of cooperating processors (LSI). In doing so we reject the sequential and memory cell semantics of the von Neumann model, and instead adopt the asynchronous and functional semantics of dataflow. We briefly describe the high-level dataflow programming language Id, as well as an initial design for a dataflow machine and the results of detailed deterministic simulation experiments on a part of that machine. For example, we show that a dataflow machine can automatically unfold the nested loops of n X n matrix multiply to reduce its time complexity from 0(n3) to 0(n) so long as sufficient processors and communication capacity is available. Similarly, quicksort executes with average 0(n) time demanding 0(n) processors. Also discussed are the use of processor and communication time complexity analysis and "flow analysis," as aids in understanding the behavior of the machine.

The work described in this paper began with a desire to include some linguistic concept of a resource manager within a dataflow language we have been designing [AGP76]. In doing so, we discovered that dataflow monitors (resource managers) provide a natural way of thinking about resources and especially their scheduling. Dataflow semantics are based upon a program composed of asynchronous operators interconnected by lines along which data tokens (messages) flow, such that when all of the input tokens for a given operator have arrived then that operator may fire (execute) by absorbing the input tokens, computing, and producing an output token as its result. These operations closely match one's intuitive model of resource managers (operators) passing signals (tokens) to one another for the purpose of synchronizing and scheduling resource usage. Previously though, dataflow languages [D73, K73, W75] have dealt only with the expression of highly asynchronous yet determinate computations; however, resource management characteristically involves indeterminate computation. The introduction here of dataflow monitors and an explicit nondeterministic merge operator for dataflow streams makes dataflow very well suited for expressing interprocess communication and operations on resources.