Applying Measurement-Based Probabilistic Timing Analysis to Buffer Resources

The use of complex hardware makes it difficult for current timing analysis techniques to compute trustworthy and tight worst-case execution time (WCET) bounds. Those techniques require detailed knowledge of the internal operation and state of the platform, at both the software and hardware level. Obtaining that information for modern hardware platforms is increasingly difficult. Measurement-Based Probabilistic Timing Analysis (MBPTA) reduces the cost of acquiring the knowledge needed for computing trustworthy and tight WCET bounds. MBPTA based on Extreme Value Theory requires the execution time of processor instructions to be independent and identically distributed (i.i.d.), which can be achieved with some hardware support. Previous proposals show how those properties can be achieved for caches. This paper considers, for the first time, the implications on MBPTA of using buffer resources. Buffers in general, and first-come first-served (FCFS) buffers in particular, are of paramount importance as the complexity of hardware increases, since they allow managing contention in those resources where multiple requests may be pending. We show how buffers can be used in the context of MBPTA and provide illustrative examples.