Dataflow computer extension towards real-time processing

Abstract

This paper presents an extended architecture and a scheduling algorithm for a dataflow computer aimed at real-time processing. From the real-time processing point of view, current dataflow computers have several problems which stem from their hardware mechanisms for scheduling instructions based on data synchronization. This mechanism extracts as many eligible instructions as possible for execution of a program, then executes them in parallel. Hence, the computation in a dataflow computer is generally difficult to interrupt and schedule using software. To realize a controllable dataflow computation, two basic mechanisms are introduced for serializing concurrent processes and interrupting the execution of a process. A parallel and distributed algorithm for the scheduler is presented, with these two mechanisms, which controls and decides state transitions and execution order of the processes based on priority and execution depth, while still maintaining the number of the running state processes at a preferred value. To gear the scheduler algorithm to meet one of the requirements for real-time processing, such as time-constrained computing, a data-parallel algorithm for selection of the user-process with the current highest priority in O (x log _x n) time is proposed, where n is the number of priority levels.