Abstract
Modern-day streaming digital signal processing (DSP) applications are often accompanied by real-time requirements. In addition, they expose increasing levels of dynamic behavior. Dynamic dataflow models of computation (MoCs) have been introduced to model and analyze such applications. Parametrized
dataflow MoCs are an important subclass of dynamic dataflow MoCs because they integrate dynamic parameters and run-time adaptation of parameters in a structured way. However, these MoCs have been primarily analyzed for functional behavior and correctness while the analysis of their temporal behavior has received little attention. In this work, we present a new analysis approach that allows analysis of worst-case latency for dynamic streaming DSP applications that can be captured using parametrized dataflow MoCs based on synchronous dataflow (SDF). We show that in the presence of parameter inter-dependencies our technique can yield tighter worst-case latency estimates than the existing techniques that operate on SDF structures that abstract the worst-case behaviour of the initial parametrized specifications. We base the approach on the (max,+) algebraic semantics of timed SDF and on its non-parametric generalization known as FSMbased scenario-aware dataflow (FSM-SADF). We evaluate the approach on a realistic case study from the multimedia domain.
dataflow MoCs are an important subclass of dynamic dataflow MoCs because they integrate dynamic parameters and run-time adaptation of parameters in a structured way. However, these MoCs have been primarily analyzed for functional behavior and correctness while the analysis of their temporal behavior has received little attention. In this work, we present a new analysis approach that allows analysis of worst-case latency for dynamic streaming DSP applications that can be captured using parametrized dataflow MoCs based on synchronous dataflow (SDF). We show that in the presence of parameter inter-dependencies our technique can yield tighter worst-case latency estimates than the existing techniques that operate on SDF structures that abstract the worst-case behaviour of the initial parametrized specifications. We base the approach on the (max,+) algebraic semantics of timed SDF and on its non-parametric generalization known as FSMbased scenario-aware dataflow (FSM-SADF). We evaluate the approach on a realistic case study from the multimedia domain.
| Original language | English |
|---|---|
| Title of host publication | 2015 Conference on Design and Architectures for Signal and Image Processing (DASIP 2015) |
| Subtitle of host publication | Proceedings of a meeting held 23-25 September 2015, Krakow (Cracow), Poland |
| Place of Publication | Piscataway |
| Publisher | Institute of Electrical and Electronics Engineers |
| Pages | 1-6 |
| Number of pages | 6 |
| ISBN (Print) | 9781467377393 |
| DOIs | |
| Publication status | Published - Jan 2016 |
| Event | 9th Conference on Design and Architectures for Signal and Image Processing, DASIP 2015 - AGH University of Science and Technology, Kracow, Poland Duration: 23 Sept 2015 → 25 Sept 2015 Conference number: 9 |
Conference
| Conference | 9th Conference on Design and Architectures for Signal and Image Processing, DASIP 2015 |
|---|---|
| Abbreviated title | DASIP 2015 |
| Country/Territory | Poland |
| City | Kracow |
| Period | 23/09/15 → 25/09/15 |
Keywords
- synchronous dataflow (SDF)
- SDF-based parametrized dataflow (SDF-PDF)
- (max,+) algebra
- worst-case latency