Skip to Main content Skip to Navigation
New interface
Conference papers

SPDF: A Schedulable Parametric Data-Flow MoC

Abstract : Dataflow programming models are suitable to express multi-core streaming applications. The design of high- quality embedded systems in that context requires static analysis to ensure the liveness and bounded memory of the application. However, many streaming applications have a dynamic behavior. The previously proposed dataflow models for dynamic applications do not provide any static guarantees or only in exchange of significant restrictions in expressive power or automation. To overcome these restrictions, we propose the schedulable parametric dataflow (SPDF) model. We present static analyses and a quasi-static scheduling algorithm. We demonstrate our approach using a video decoder case study.
Document type :
Conference papers
Complete list of metadata

Cited literature [11 references]  Display  Hide  Download
Contributor : Alain Girault Connect in order to contact the contributor
Submitted on : Tuesday, October 23, 2012 - 9:00:00 AM
Last modification on : Tuesday, August 2, 2022 - 4:24:19 AM
Long-term archiving on: : Thursday, January 24, 2013 - 3:36:02 AM


Files produced by the author(s)


  • HAL Id : hal-00744376, version 1


Pascal Fradet, Alain Girault, Petro Poplavko. SPDF: A Schedulable Parametric Data-Flow MoC. Design Automation and Test in Europe, DATE'12, Mar 2012, Dresden, Germany. ⟨hal-00744376⟩



Record views


Files downloads