Using Dynamic, Full Cache Locking and Genetic Algorithms for Cache Size Minimization in Multitasking, Preemptive, Real-Time Systems

Cache locking have shown during the last years their usefulness easing the schedulability analysis of multitasking, preemptive, realtime systems. Cache locking provides a high degree of predictability while system performance is maintained at a similar level to that provided by regular, highly unpredictable, non-locked cache. Cache locking may also be useful to reduce hardware costs by means of reducing the size of the cache memory needed to make a real-time system schedulable. This work shows how full, dynamic cache locking may help to reduce the size of the cache memory versus a regular cache. This reduction is possible thanks to a genetic algorithm that selects the set of instructions that have to be locked in cache to provide the maximum cache size minimization while keeping the system schedulable.