Dataflow analysis for multiprocessor systems with non-starvation-free schedulers

Abstract

Dataflow analysis techniques are suitable for the temporal analysis of real-time stream processing applications. However, the applicability of these models is currently limited to systems with starvation-free schedulers, such as Time-Division Multiplexing (TDM) schedulers. Removal of this limitation would broaden the application domain of dataflow analysis techniques significantly. In this paper we present a temporal analysis technique for Homogeneous Synchronous Dataflow (HSDF) graphs, that is also applicable for systems with non-starvation-free schedulers. Unlike existing dataflow analysis techniques, the proposed analysis technique makes use of an enabling-jitter characterization and iterative fixed-point computation. The presented approach is applicable for arbitrary (cyclic) graph topologies. Buffer capacity constraints are taken into account during the analysis and sufficient buffer capacities can be determined afterwards. The approach presented in this paper is the first approach that considers non-starvation-free schedulers in combination with arbitrary HSDF graphs The proposed dataflow analysis technique is implemented in a tool. This tool is used to evaluate the analysis technique using examples that illustrate some important differences with other temporal analysis methods. The case-study discusses how the method presented in this paper can be used to solve a problem with the inaccuracy of the temporal analysis results of a real-time stream processing system. This stream processing system consists of an FM receiver together with a DAB receiver application which both share a Digital Signal Processor (DSP).

Generalized Extraction of Real-Time Parameters for Homogeneous Synchronous Dataflow Graphs

“…In [15] the authors propose a temporal analysis for dataflow application modeled as cyclic HSDF graphs under a nonstarvation-free scheduler i.e. static-priority preemptive scheduler (SPP).…”

“…Dataflow applications traditionally use static scheduling techniques, i.e. Time Division Multiple Access (TDMA) [2], [4]- [8], however, they have recently been shown to work well also with real-time scheduling techniques [9]- [12], run-time budget schedulers [13], [14] and non-starvation-free schedulers [15].…”

“…The real-time dataflow applications are represented as cyclic HSDF with periodic sources. Earlier works have already considered applications represented as Directed Acyclic Graphs (DAGs) [10], [17], pipelines [18], task model without deadlines [15] or limited to implicit-deadlines [10], or application specific analysis [15], [19]. A main advantage of this proposal is that the extraction of the timing parameters is independent of the specific scheduler being used, or of other applications running in the system or the particular platform.…”

Temporal Analysis of Static Priority Preemptive Scheduled Cyclic Streaming Applications using CSDF Models

“…In [8] an iterative algorithm is proposed that combines dataflow modeling with classical real-time analysis techniques, enabling the analysis of applications with cyclic data dependencies and SPP scheduling. This approach is extended in [21] by making use of the fact that cyclic data dependencies limit interference, resulting in a significantly higher analysis accuracy.…”

“…However, both [8] and [21] are limited to the analysis of applications that can be expressed with Homogeneous Synchronous Dataflow (HSDF) graphs, i.e. applications in which all tasks operate at the same rate.…”