Improved static data-flow model for TDM scheduler.dvi

Faculty of Electrical Engineering, Mathematics and Computer Science CE-MS-2012-05 A streaming application like software defined radio (SDR) executed on a heterogeneous multi-processor system on chip (MPSoC) consists of various transceiver jobs that have to be scheduled on different processors concurrently. The hard real time performance requirements of these jobs can be guaranteed on the multi-processor system on chip (MPSoC) using a Time Division Multiplexing (TDM) scheduler for each processor. The TDM scheduler allocates a fixed amount of time slot for each job and removes the timing inter-dependence between the concurrently executing jobs. In order to guarantee that a job scheduled using a TDM scheduler would meet its deadlines, temporal analysis can be performed by modelling an application as a data-flow graph, called as an application graph. Scheduling framework maps nodes of the data-flow graph, called actors, on to the processors. It generates a schedule or an order in which actors of an application can execute on a processor. This order is called a static order. Data-flow model for a TDM scheduler is a timed data-flow graph which uses the TDM scheduler settings to predict worst case finish times of a job scheduled on a TDM scheduler. Using this mapping information and a data-flow model, an analysis graph is obtained from the application graph by replacing each application actor by a data-flow model and is analysed for its temporal behaviour. Various such data-flow models, e.g., the latency rate model, are proposed in the literature, but they over-estimate the worst case finish time of an application. This over-estimation causes over-allocation of resources on the processor. In this thesis, we propose a data-flow model based on multi-rate data flow (MRDF) graph, called as a multi-rate model, that is conservative and more accurate than the existing models. We provide a detailed analysis of the multi-rate model and prove that the model is conservative. We also show that the multi-rate model provides worst case finish times that are more accurate than existing models like the latency rate model. We implemented the multi-rate model, simulation of the TDM behaviour and techniques to reduce the utilizations of the processors on an existing data-flow analysis tool developed at ST Ericsson. We used our implementation to study the impact of improved accuracy in the estimation of the finish times of the application tasks due to the multi-rate model. The reductions in the processor utilization obtained using the multi-rate model were found to be better than the latency rate model and in some cases, better than the simulation technique. The experimental results show that the improved modelling accuracy helped us to achieve up to 40% reduction in the utilization of a processor, over the latency rate model based method for a WLAN application. Thus, the multi-rate model is a more accurate model for the analysis of the TDM scheduler arbitration as compared to the state-of-the-art. Improved static data-flow model for TDM scheduler