No abstract

This paper proposes a scheduling strategy and an automatic scheduling flow that enable the simultaneous execution of multiple hard-real-time dataflow jobs. Each job has its own execution rate and starts and stops independently from other jobs, at instants unknown at compile-time, on a multiprocessor system-on-chip. We show how a combination of Time-Division Multiplex (TDM) and static-order scheduling can be modeled as additional nodes and edges on top of the dataflow representation of the job using SingleRate Dataflow semantics to enable tight worst-case temporal analysis. We also propose algorithms to find combined TDM/static order schedules for jobs that guarantee a requested minimum throughput and maximum latency, while minimizing the usage of processing resources. We illustrate the usage of these techniques for a combination of Wireless LAN and TD-SCDMA radio jobs running on a prototype Software-Defined Radio platform.

Enabling application-level performance guarantees in network-based systems on chip by applying dataflow analysis. IET Computers and Digital Techniques, 3(5), 398-412.

A key step in the design of cyclo-static real-time systems is the determination of buffer capacities. In our multi-processor system, we apply back-pressure, which means that tasks wait for space in output buffers. Consequently buffer capacities affect the throughput. This requires the derivation of buffer capacities that both result in a satisfaction of the throughput constraint, and also satisfy the constraints on the maximum buffer capacities. Existing exact solutions suffer from the computational complexity that is associated with the required conversion from a cyclo-static dataflow graph to a single-rate dataflow graph. In this paper we present an algorithm, with polynomial computational complexity, that does not require this conversion and that obtains close to minimal buffer capacities. The algorithm is applied to an MP3 play-back application that is mapped on our multi-processor system. For this application, we see that a cyclo-static dataflow model can reduce the buffer capacities by 50% compared to a multi-rate dataflow model.

This paper describes a conservative approximation algorithm that derives close to minimal buffer capacities for an application described as a cyclo-static dataflow graph. The resulting buffer capacities satisfy constraints on the maximum buffer capacities and end-to-end throughput and latency constraints. Furthermore we show that the effects of run-time arbitration can be included in the response times of dataflow actors. We show that modelling an MP3 playback application as a cyclo-static dataflow graph instead of a multi-rate dataflow graph results in buffer capacities that are reduced up to 39%. Furthermore, the algorithm is applied to a real-life car-radio application, in which two independent streams are processed.