Automatic Hierarchical Discovery of Quasi-Static Schedules of RVC-CAL Dataflow Programs

International audienceRVC-CAL is an actor-based dataflow language that enables concurrent, modular and portable description of signal processing algorithms. RVC-CAL programs can be compiled to implementation languages such as C/C++ and VHDL for producing software or hardware implementations. This paper presents a methodology for automatic discovery of piecewise-deterministic (quasi-static) execution schedules for RVC-CAL program software implementations. Quasi-static scheduling moves computational burden from the implementable run-time system to design-time compilation and thus enables making signal processing systems more efficient. The presented methodology divides the RVC-CAL program into segments and hierarchically detects quasi-static behavior from each segment: first at the level of actors and later at the level of the whole segment. Finally, a code generator creates a quasi-statically scheduled version of the program. The impact of segment based quasi-static scheduling is demonstrated by applying the methodology to several RVC-CAL programs that execute up to 58 % faster after applying the presented methodology

Classification of Dataflow Actors with Satisfiability and Abstract Interpretation

International audienceDataflow programming has been used to describe signal processing applications for many years, traditionally with cyclo-static dataflow (CSDF) or synchronous dataflow (SDF) models that restrict expressive power in favor of compile-time analysis and predictability. More recently, dynamic dataflow is being used for the description of multimedia video standards as promoted by the RVC standard (ISO/IEC 23001:4). Dynamic dataflow is not restricted with respect to expressive power, but it does require runtime scheduling in the general case, which may be costly to perform on software. The authors presented in a previous paper a method to automatically classify actors of a dynamic dataflow program within more restrictive dataflow models when possible, along with a method to transform the actors classified as static to improve execution speed by reducing the number of FIFO accesses (Wipliez & Raulet, 2010). This paper presents an extension of the classification method using satisfiability solving, and details the precise semantics used for the abstract interpretation of actors. The extended classification is able to classify more actors than what could previously be achieved

MPEG Reconfigurable Video Coding: From specification to a reconfigurable implementation

International audienceThis paper demonstrates that it is possible to produce automatic, reconfigurable, and portable implementations of multimedia decoders onto platforms with the help of the MPEG Reconfigurable Video Coding (RVC) standard. MPEG RVC is a new formalism standardized by the MPEGconsortium used to specify multimedia decoders. It produces visual representations of decoder reference software, with the help of graphs that connect several coding tools from MPEG standards. The approach developed in this paper draws on Dataflow Process Networks to produce a Minimal and Canonical Representation (MCR) of \MPEG\ \RVC\ specifications. The \MCR\ makes it possible to form automatic and reconfigurable implementations of decoders which can match any actual platforms. The contribution is demonstrated on one case study where a generic decoder needs to process a multimedia content with the help of the \RVC\ specification of the decoder required to process it. The overall approach is tested on two decoders from MPEG, namely MPEG-4 part 2 Simple Profile and MPEG-4 part 10 Constrained Baseline Profile. The results validate the following benefits on the \MCR\ of decoders: compact representation, low overhead induced by its compilation, reconfiguration and multi-core abilities

Classification-Based Optimization of Dynamic Dataflow Programs

International audienceThis chapter reviews dataflow programming as a whole and presents a classification-based methodology to bridge the gap between predictable and dynamic dataflow modeling in order to achieve expressiveness of the programming language as well as efficiency of the implementation. The authors conduct experiments across three MPEG video decoders including one based on the new High Efficiency Video Coding standard. Those dataflow-based video decoders are executed onto two different platforms: a desktop processor and an embedded platform composed of interconnected and tiny Very Long Instruction Word-style processors. The authors show that the fully automated transformations presented can result in a 80% gain in speed compared to runtime scheduling in the more favorable case

Algorithm/Architecture Co-Exploration of Visual Computing: Overview and Future Perspectives

Concurrently exploring both algorithmic and architectural optimizations is a new design paradigm. This survey paper addresses the latest research and future perspectives on the simultaneous development of video coding, processing, and computing algorithms with emerging platforms that have multiple cores and reconfigurable architecture. As the algorithms in forthcoming visual systems become increasingly complex, many applications must have different profiles with different levels of performance. Hence, with expectations that the visual experience in the future will become continuously better, it is critical that advanced platforms provide higher performance, better flexibility, and lower power consumption. To achieve these goals, algorithm and architecture co-design is significant for characterizing the algorithmic complexity used to optimize targeted architecture. This paper shows that seamless weaving of the development of previously autonomous visual computing algorithms and multicore or reconfigurable architectures will unavoidably become the leading trend in the future of video technology

Quasi-Static Scheduling of CAL Actor Networks for Reconfigurable Video Coding

The upcoming Reconfigurable Video Coding (RVC) standard from MPEG (ISO / IEC SC29WG11) defines a library of coding tools to specify existing or new compressed video formats and decoders. The coding tool library has been written in a dataflow/actor- oriented language named CAL. Each coding tool can be represented with an extended finite state machine and the dependencies between the tools are described as dataflow graphs. This paper proposes an approach to model the CAL actor network with Parameterized Syn- chronous Data Flow and to derive a quasi-static multiprocessor execution schedule for the system. In addition to proposing a scheduling approach for RVC, an extension to the well- known permutation flow shop scheduling problem that enables rapid run-time scheduling of RVC tasks, is introduced