Performance analysis of dynamic multitasking imprecise computation system - Computers and Digital Techniques [see also IEE Proceedings-Computers and Digital Techniques], IEE

The scheduling of tasks in dynamic multitasking computer systems using imprecise (partial) computations is studied. In our system, tasks arrive randomly during run-time, and they are to be processed as quickly as possible. We model the task in such a way that each task has two parts of computation: a mandatory part, and an optional part. The tasks are scheduled such that: if the total number of tasks in the system is no more than M (a system parameter), the tasks are executed fully to produce precise results, i.e. both the mandatory and the optional parts are executed. When the total number of tasks exceeds M , then only the mandatory parts of the tasks are executed. As less computation resourse is used on each task under this imprecise computation condition, the response time of tasks should improve significantly. To study this dynamic imprecise computation system, we propose three performance metrics to measure responsiveness and quality of computation of tasks. Queueing methods are used to analyse the scheduling problem, and performance metrics are computed numerically. The performance of the scheme is assessed, and found to be effective in keeping the mean task waiting time at a low value when the system is heavily loaded or overloaded. The effect of variations in parameter values on the system performance is also examined.