Phased scheduling of stream programs
Proceedings of the 2003 ACM SIGPLAN conference on Language, compiler, and tool for embedded systems
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Efficient computation of buffer capacities for cyclo-static dataflow graphs
Proceedings of the 44th annual Design Automation Conference
A SystemC-based design methodology for digital signal processing systems
EURASIP Journal on Embedded Systems
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
Lucy-n: a n-synchronous extension of Lustre
MPC'10 Proceedings of the 10th international conference on Mathematics of program construction
Systolic algorithm mapping for coarse grained reconfigurable array architectures
ARC'10 Proceedings of the 6th international conference on Reconfigurable Computing: architectures, Tools and Applications
Static scheduling of latency insensitive designs with Lucy-n
Proceedings of the International Conference on Formal Methods in Computer-Aided Design
Cyclo-static DataFlow phases scheduling optimization for buffer sizes minimization
Proceedings of the 16th International Workshop on Software and Compilers for Embedded Systems
FlexTiles: a globally homogeneous but locally heterogeneous manycore architecture
Proceedings of the 6th Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools
Journal of Systems Architecture: the EUROMICRO Journal
Hi-index | 0.00 |
We compare synchronous dataflow (SDF) and cyclo-static dataflow (CSDF), which are each special cases of a model of computation we call dataflow process networks. In SDF actors have static firing rules: they consume and produce a fixed number of data tokens in each firing. This model is well suited to multirate signal processing applications and lends itself to efficient static scheduling, avoiding the run-time scheduling overhead incurred by general implementations of process networks. In CSDF which is a generalization of SDF actors have cyclically changing firing rules. In some situations, the added generality of CSDF can unnecessarily complicate the scheduling. We show how higher-order functions can be used to transform a CSDF graph into a SDF graph, simplifying the scheduling problem. In other situations, CSDF has a genuine advantage over SDF: simpler precedence constraints. We show how this makes it possible to eliminate unnecessary computations and expose additional parallelism. We use digital sample rate conversion as an example to illustrate these advantages of CSDF.