Performance analysis tool for cache-based real-time systems with preemptions

Abstract

Dependable real-time systems are essential to time-critical applications. The systems that run these applications require high degrees of performance and predictability. Although memory caching has long been known as a means of increasing system performance, it is typically unpredictable in nature. This paper presents a technique of using preferred preemption points to increase the predictability and performance of cache-based real-time systems and describes a performance analysis tool and methodology designed to select and evaluate preemption points. Performance results obtained by using the tool are presented for various system configurations. System configurations are defined by such parameters as cache type and preemption frequency. In some instances, results have shown a 10% reduction in execution time with preferred preemption points. Such savings in execution time provide greater flexibility in scheduling and increase throughput of time-critical tasks. Use of the technique increases the ability to calculate system preemption overhead. This leads to greater determinism and consequently performance, and provides for tighter bounds on calculated worst-case execution times.