Cache-aware timing analysis of streaming applications

Of late, there has been a considerable interest in models, algorithms and method-ologies specifically targeted towards designing hardware and software for streaming ap-plications. Such applications process potentially infinite streams of audio/video data or network packets and are found in a wide range of devices, starting from mobile phones to set-top boxes. Given a streaming application and an architecture, the timing analysis problem is to determine the timing properties of the processed data stream, given the timing properties of the input stream. This problem arises while determining many common performance metrics related to streaming applications and the mapping of such applications onto hardware architectures. Such metrics include the maximum de-lay experienced by any data item of the stream and the maximum backlog or the buffer requirement to store the incoming stream. Most of the previous work related to esti-mating or optimizing these metrics take a high-level view of the architecture and neglect micro-architectural features such as caches. In this paper, we show that an accurate estimation of these metrics, however, heavily relies on an appropriate modeling of th