Automated Design Flow for Multi-Functional Dataflow-Based Platforms

The implementation of processing platforms supporting multiple applications by runtime reconfigurations on dedicated hardware modules requires the solution of different problems. These problems are notably not-trivial since both platform and application complexities increase year after year. As a consequence, the design process is both time and resource demanding. System configuration along with resources management and mapping remain one of the most challenging problem, particularly when runtime adaptation is required. In this direction, the ISO/IEC SC29WG11 committee (MPEG) has developed the so called MPEG-RVC standards ISO/IEC 23001-4 and 23002-4. This standard provides specifications of video codecs in the form of dataflow programs. In this paper, an integrated design flow to derive optimized multi-functional platforms directly from disjoined high-level specifications is presented. To the authors’ best of knowledge, such an optimization, synthesis and mapping methodology for coarse-grained reconfigurable systems design does not exist within the MPEG-RVC framework. The design flow presented in this paper leverages on an integrated set of independently designed tools, all supporting the RVC standard. Results assessment has been carried out on three different scenarios: an MPEG-RVC decoder, a standard baseline MPEG-RVC JPEG codec and a generalized reconfigurable multi-quality JPEG encoder. For all these scenarios, the proposed design flow has been targeted for a Xilinx Virtex 5 FPGA. Results show how this approach is capable of yielding a reconfigurable design that preserves the original performance of the stand alone non-reconfigurable platform providing, at the same time, considerable area savings featuring a larger set of functionalities. Moreover, platforms programmability, on the basis of the required functionality ID, is automatically handled at runtime without any designer effort.

High-level synthesis of dataflow programs for heterogeneous platforms

Endri Bezati

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.

EPFL2015

Dataflow Programming for Systems Design Space Exploration for Multicore Platforms

Christophe Lucarz

Nowadays processing systems are asked to support increasing complex and demanding high-performance applications, especially in the signal processing and video processing domains. The design of these systems are becoming extremely challenging because of several factors. Among them the most relevant are: The advent of the parallel era The sequential general purpose processor era during which performance increased more than two-fold every year, is definitely over. There has been no further increase in leading edge processor performance for over five years now and all projects aimed at breaking the 4 GHz barrier have been canceled by the major processor manufacturers. So as to continue increasing the computing power of computer systems, manufacturers have to use several slower processing cores, while trying to minimize the power consumption. Sequential reference softwares are no longer adapted Up to now, sequential software have proven to be the winning approaches for exploiting the potential of each new generation of sequential processors. But the advent of the new parallel era changes the way systems are implemented and sequential reference software used as specification base are no longer appropriate starting points for designing complex systems. The increasing demanding functionality and performance In parallel with miniaturization and the necessity to handle severely resource-constrained implementation platforms, the functionality and complexity of large classes of systems continue to increase making them from many respects comparable to ordinary desktop personal computers. A mixture of different types of timing and quality constraints make overall system architecture design, resource allocation and scheduling more important and challenging topics than ever before. Additionally, the market asks companies to build efficient systems while using the minimum of resources as fast as possible. Due to the level of complexity reached by high-demanding digital systems, it is no longer reasonable to handle such systems at low levels of abstraction (e.g. VHDL/Verilog or C/C++). A solution to the problem is to higher the level of abstraction at which the design of such systems is performed. But for raising the level of abstraction, the need for portable parallelism is primordial so as to be able to implement all kind of systems on a wide range of target platforms. Thus, enabling portable parallelism should be a primordial requirement for the development of this level of abstraction and the associated methodology and tools. However, creating a new abstraction layer may incur in the risk of loosing contact with implementation details and accuracy necessary for achieving efficient implementations. This work focuses on tackling such problem by using the CAL data flow language as main abstraction at the basis of the design process. The attempt of solving such challenging problem consists in building an environment for enabling high level design space exploration of complex parallel application for seamless implementation on heterogeneous platforms using CAL. It includes the extraction of metrics (static analysis and profiling) with the intention to use them as a basis for partitioning and scheduling heuristics aiming at finding the most efficient partitions. It also implies developing methodologies for guiding designers in the optimization of the high level specifications. Finally, a holistic approach has been defined in form of a complete design flow starting from CAL specifications down to implementations. Where traditional approaches are faced to traverse, at each iteration of the design flow, all the levels of abstraction for testing a design solution, the use of CAL as an abstraction layer enables designers to separate clearly three domains of concerns that are made orthogonal: functionality, partitioning and implementation. The separation of these domains of concerns eases the design space exploration and leads to an increase in productivity in the design of complex systems. This work leads to the creation of several new design tools: (1) profiling tools which extracts metrics from CAL programs and (2) exploration tools which include partitioning and scheduling heuristics and performance evaluation. These tools have been implemented with the aim of guiding designers in the high level design space exploration of systems in order to achieve efficient implementation. A systematic methodology has been also elaborated and has been tested successfully on a real world applications. Thanks to the metrics extracted from the CAL program, the design bottlenecks of a MPEG-4 SP video decoder have been identified and removed at a high level of abstraction, leading to improvements up to 7 times faster implementation.

EPFL2011

High-level dataflow design of signal processing systems for reconfigurable and multicore heterogeneous platforms

Endri Bezati, Marco Mattavelli, Ghislain Roquier, Richard Thavot

The potential computational power of today multicore processors has drastically improved compared to the single processor architecture. Since the trend of increasing the processor frequency is almost over, the competition for increased performance has moved on the number of cores. Consequently, the fundamental feature of system designs and their associated design flows and tools need to change, so that, to support the scalable parallelism and the design portability. The same feature can be exploited to design reconfigurable hardware, such as FPGAs, which leads to rethink the mapping of sequential algorithms to HDL. The sequential programming paradigm, widely used for programming single processor systems, does not naturally provide explicit or implicit forms of scalable parallelism. Conversely, dataflow programming is an approach that naturally provides parallelism and the potential to unify SW and HDL designs on heterogeneous platforms. This study describes a dataflow-based design methodology aiming at a unified co-design and co-synthesis of heterogeneous systems. Experimental results on the implementation of a JPEG codec and a MPEG 4 SP decoder on heterogeneous platforms demonstrate the flexibility and capabilities of this design approach.