Static scheduling of synchronous data flow programs for digital signal processing
IEEE Transactions on Computers
Bounded scheduling of process networks
Bounded scheduling of process networks
Software Synthesis from Dataflow Graphs
Software Synthesis from Dataflow Graphs
Parameterized dataflow modeling of DSP systems
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 06
RTAS '08 Proceedings of the 2008 IEEE Real-Time and Embedded Technology and Applications Symposium
OpenDF: a dataflow toolset for reconfigurable hardware and multicore systems
ACM SIGARCH Computer Architecture News
Scheduling dynamic dataflow graphs with bounded memory using the token flow model
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Symmetry breaking for multi-criteria mapping and scheduling on multicores
FORMATS'13 Proceedings of the 11th international conference on Formal Modeling and Analysis of Timed Systems
BPDF: a statically analyzable DataFlow model with integer and Boolean parameters
Proceedings of the Eleventh ACM International Conference on Embedded Software
| Hi-index | 0.00 |
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.