Static scheduling of synchronous data flow programs for digital signal processing
IEEE Transactions on Computers
LabVIEW Graphical Programming: Practical Applications in Instrumentation and Control
LabVIEW Graphical Programming: Practical Applications in Instrumentation and Control
Metamodeling in EIA/CDIF---meta-metamodel and metamodels
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Modeling Stream-Based Applications Using the SBF Model of Computation
Journal of VLSI Signal Processing Systems
Scheduling dynamic dataflow graphs with bounded memory using the token flow model
Scheduling dynamic dataflow graphs with bounded memory using the token flow model
Software synthesis from the dataflow interchange format
SCOPES '05 Proceedings of the 2005 workshop on Software and compilers for embedded systems
Parameterized Looped Schedules for Compact Representationof Execution Sequences
ASAP '06 Proceedings of the IEEE 17th International Conference on Application-specific Systems, Architectures and Processors
A SystemC-based design methodology for digital signal processing systems
EURASIP Journal on Embedded Systems
RTSS '07 Proceedings of the 28th IEEE International Real-Time Systems Symposium
Functional DIF for Rapid Prototyping
RSP '08 Proceedings of the 2008 The 19th IEEE/IFIP International Symposium on Rapid System Prototyping
A generalized scheduling approach for dynamic dataflow applications
Proceedings of the Conference on Design, Automation and Test in Europe
Heterogeneous design in functional DIF
Transactions on High-Performance Embedded Architectures and Compilers IV
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Dataflow formalisms have provided designers of digital signal processing systems with analysis and optimizations for many years. As system complexity increases, designers are relying on more types of dataflow models to describe applications while retaining these implementation benefits. The semantic range of DSP-oriented dataflow models has expanded to cover heterogeneous models and dynamic applications, but efficient design, simulation, and scheduling of such applications has not. To facilitate implementing heterogeneous applications, we utilize a new dataflow model of computation and show how actors designed in other dataflow models are directly supported by this framework, allowing system designers to immediately compose and simulate actors from different models. Using an example, we show how this approach can be applied to quickly describe and functionally simulate a heterogeneous dataflow-based application such that a designer may analyze and tune trade-offs among different models and schedules for simulation time, memory consumption, and schedule size.