Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Scheduling Parallel Processable Tasks for a Uniprocessor
IEEE Transactions on Computers
A survey of techniques for recognizing parallel processable streams in computer programs
AFIPS '69 (Fall) Proceedings of the November 18-20, 1969, fall joint computer conference
| Hi-index | 14.98 |
Utilization of a uniprocessor system in a multiprogramming environment can be optimized by maximizing the overlap of processor and input-output operations. A computational process can be modeled by a directed graph each node of which represents a task comprising processor and input-output segments. Any optimal schedulng algorithm for the model cannot be polynomially bounded, but the optimal criteria can be used to develop a hierarchy of dispatching heuristics based upon selecting an optimal partial task schedule. These heuristics are analyzed and evaluated by a simulation study and are shown to be more effective than those previously proposed. The dispatching heuristics developed have a wide range of potential applications to systems requiring dynamic task scheduling.