Multicore architectures and worst-case execution time
Critical tasks in the context of real-time systems submit to both timing and correctness constraints. Whence, the validation of a real-time system rely on the estimation of its tasks’ Worst case execution times. Resource sharing, as it occurs on multicore architectures, hinders the computation of such estimates. The timing behaviour of a task is impacted by its concurrents, whether because of resource access arbitration or concurrent modifications of a resource state. This study focuses on estimating the contribution of the memory hierarchy to tasks’ worst case execution time. Existing analysis methods, defined for instruction caches, are extended to support private and shared data caches, hence allowing for the analysis of rich memory hierarchies. Cache bypass is then used to reduce the pressure laid by concurrent tasks on shared caches levels. We propose different bypass heuristics, based on the capture of cache blocks’ reuse between memory accesses. Our second proposal is the Preti partitioning scheme which allows for the allocation to tasks of a cache space, free from inter-task conflicts. Preti offers the added benefit of providing for average-case performance to non-critical tasks concurrent to real-time ones on hybrid criticality systems.