Data Caches in Multitasking Hard Real-Time Systems

Data caches are essential in modern processors, bridging the widening gap between main memory and processor speeds. However, they yield very complex performance models, which makes it hard to bound execution times tightly. This paper contributes a new technique to obtain predictability in preemptive multitasking systems in the presence of data caches. We explore the use of cache partitioning, dynamic cache locking and static cache analysis to provide worst-case performance estimates in a safe and tight way. Cache partitioning divides the cache among tasks to eliminate inter-task cache interferences. We combine static cache analysis and cache locking mechanisms to ensure that all intra-task conflicts, and consequently, memory access times, are exactly predictable. To minimize the performance degradation due to cache partitioning and locking, two strategies are employed. First, the cache is loaded with data likely to be accessed so that their cache utilization is maximized. Second, com...

• Type: Conference
• Year: 2003
• Where: RTSS
• Authors: Xavier Vera, Björn Lisper, Jingling Xue
• Keywords: Applied Computing, Cache, Cache Locking, RTSS 2003, Static Cache