A Program Allocation Method for Real-Time Processing Based on Data-Driven Processors

In this paper the authors propose a program allocation method for the purpose of achieving real-time processing using a chip multiprocessor-type data-driven processor. The data-driven processor can perform parallel processing of executable processes without interference as long as the pipeline is not overloaded. The turnaround time for the individual processes being subjected to multiprocessing is independent of other processes being executed at the same time, and is maintained as is for the execution time when a single process is executed. Therefore, real time for a program can be estimated, and if the program can be allocated to a process such that overload does not occur, then real-time processing can be achieved without scheduling during execution. In this paper the authors first formalize a program allocation method in a data-driven processor. They then propose a combined method using genetic algorithms and a heuristic algorithm that uses lists as a program allocation method that is better at satisfying the time constraints and offers greater scalability for large-scale program and multiprocessor systems to be subjected to allocation. Finally, the authors use experiments in which a communications protocol process is allocated to verify the effectiveness of their program allocation method. © 2007 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 90(6): 48– 60, 2007; Published online in Wiley InterScience (www.interscience. wiley.com). DOI 10.1002/ecjc.20324