Cache memories are one of the main factors that affect software performance, and their use is becoming increasingly common even in embedded systems. Efficient analysis of the effects of parameter variations (cache dimensions, degree of associativity, replacement policy, line size, ...) is at the same time an essential and very time-consuming aspect of embedded system design, whose complexity increases when multi-tasking and real-time aspects must be considered. We propose a new simulation-based methodology, focused on an approximate model of the cache and of the multi-tasking reactive software, that allows one to trade off smoothly between accuracy and simulation speed. In particular, we propose to accurately consider intra-task conflicts, but approximate inter-task conflicts by considering only a finite number of previous task executions. The rationale for this choice can be found in a common pattern in embedded systems, where a "normal" data flow results in a regular intra-task common flow, interrupted from time to time by some urgent event, that pessimistically can be consider as disrupting the cache behavior. The approach is conservative because re-execution of a task after a large amount of time will always be considered as not in cache, and the simulation speed-up is considerable, as shown by theoretical analysis and experimental results.
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