Unified dataflow model for the analysis of data and pipeline parallelism, and buffer sizing

Real-time stream processing applications such as software defined radios are usually executed concurrently on multiprocessor systems. Exploiting coarse-grained data parallelism by duplicating tasks is often required, besides pipeline parallelism, to meet the temporal constraints of the applications. However, no unified model and analysis method exists that can be used to determine the required amount of data and pipeline parallelism, and buffer sizes simultaneously. This paper presents an analysis method which can determine the required amount of data parallelism by describing data parallelism in a dataflow model without replicating dataflow actors. This allows to make a trade-off between the amount of data and pipeline parallelism that is required to meet the temporal constraints of the application. It is also shown how large the buffers need to be such that the determined amount of data and pipeline parallelism required for the satisfaction of the throughput constraint, can be realized. Furthermore, it is shown that the use of the applied circular buffers enables the proposed dataflow modeling. The presented analysis method is demonstrated using a WLAN 802.11p transceiver application. This application contains multi-rate behavior and has a cyclic data dependency because of a re-encoding loop. Given the real-time constraints of the application, sufficient buffer sizes and sufficient data parallelism are derived.