Publication
The growing complexity of digital signal processing applications implemented in programmable logic and embedded processors make a compelling case the use of high-level methodologies for their design and implementation. Past research has shown that for complex systems, raising the level of abstraction does not necessarily come at a cost in terms of performance or resource requirements. As a matter of fact, high-level synthesis tools supporting such a high abstraction often rival and on occasion improve low-level design. In spite of these successes, high-level synthesis still relies on programs being written with the target and often the synthesis process, in mind. In other words, imperative languages such as C or C++, most used languages for high-level synthesis, are either modified or a constrained subset is used to make parallelism explicit. In addition, a proper behavioral description that permits the unification for hardware and software design is still an elusive goal for heterogeneous platforms. A promising behavioral description capable of expressing both sequential and parallel application is RVC-CAL. RVC-CAL is a dataflow programming language that permits design abstraction, modularity, and portability. The objective of this thesis is to provide a high-level synthesis solution for RVC-CAL dataflow programs and provide an RVC-CAL design flow for heterogeneous platforms. The main contributions of this thesis are: a high-level synthesis infrastructure that supports the full specification of RVC-CAL, an action selection strategy for supporting parallel read and writes of list of tokens in hardware synthesis, a dynamic fine-grain profiling for synthesized dataflow programs, an iterative design space exploration framework that permits the performance estimation, analysis, and optimization of heterogeneous platforms, and finally a clock gating strategy that reduces the dynamic power consumption. Experimental results on all stages of the provided design flow, demonstrate the capabilities of the tools for high-level synthesis, software hardware Co-Design, design space exploration, and power optimization for reconfigurable hardware. Consequently, this work proves the viability of complex systems design and implementation using dataflow programming, not only for system-level simulation but real heterogeneous implementations.