Stream processing applications executed on embedded multiprocessor systems regularly contain cyclic data dependencies due to the presence of feedback loops and bounded FIFO buffers. Dataflow modeling is suitable for the temporal analysis of such applications. However, the accuracy can be unsatisfactory as existing temporal analysis techniques ignore that cyclic data dependencies limit interference between tasks executed on shared processors.This paper presents a dataflow analysis approach that increases the analysis accuracy by taking into account that cyclic data dependencies limit interference between tasks. It is shown that the approach is applicable for single-rate stream processing applications that are executed on multiprocessor systems using static priority preemptive schedulers.The improvement of accuracy is demonstrated in a case study employing a WLAN 802.11p transceiver application that is executed on a multiprocessor system with shared processors.

Existing temporal analysis and buffer sizing techniques for real-time stream processing applications ignore that FIFO buffers bound interference between tasks on the same processor. By considering this effect it can be shown that a reduction of buffer capacities can result in a higher throughput. However, the relation between buffer capacities and throughput is non-monotone in general, which makes an exploitation of the effect challenging.In this paper a buffer sizing approach is presented which exploits that FIFO buffers bound interference between tasks on shared processors. The approach combines temporal analysis using a cyclic dataflow model with computation of buffer capacities in an iterative manner and thereby enables higher throughput guarantees at smaller buffer capacities. It is shown that convergence of the proposed analysis flow is guaranteed.The benefits of the presented approach are demonstrated using a WLAN 802.11p transceiver application executed on a multiprocessor system with shared processors. If buffers without blocking writes are used an up to 25% higher guaranteeable throughput and up to 23% smaller buffer capacities can be determined compared to existing approaches. For systems using buffers with blocking writes the guaranteeable throughput is even up to 43% higher and buffer capacities up to 11% smaller.

Connection-oriented Guaranteed-Throughput (GT) mesh-based Networks on Chip (NoCs) have been proposed as a replacement for buses in real-time stream processing systems but are currently rarely used as hardware cost tends to be higher than conventional interconnects. Recently an interconnect with a ring topology was introduced as a low-cost alternative for use in medium scale homogeneous Multiple Processor System on Chip (MPSoC) designs. Cost-effective integration of stream processing accelerators would require an extension of this ring interconnect.We present a dual-ring communication infrastructure for heterogeneous MPSoC designs. Data and credits are transferred between tiles using their separate, oppositely directed, rings. The minimum throughput is determined by analysis of a Cyclo-Static Data Flow (CSDF) model for a system with communication between accelerators and processors.The performance benefits and costs are evaluated by integration of our dual ring and an accelerator in a 16 core MPSoC which is mapped on a Virtex6 FPGA. On this MPSoC a real-time PAL video decoder is executed. A performance gain of a factor 3.6 was obtained at an increase in hardware cost of only 8.5%.