Dataflow has proven to be an attractive computation model for programming digital signal processing (DSP) applications. A restricted version of dataflow, termed synchronous dataflow (SDF), that offers strong compile-time predictability properties, but has limited expressive power, has been studied extensively in the DSP context. Many extensions to synchronous dataflow have been proposed to increase its expressivity while maintaining its compile-time predictability properties as much as possible. We propose a parameterized dataflow framework that can be applied as a meta-modeling technique to significantly improve the expressive power of any dataflow model that possesses a well-defined concept of a graph iteration. Indeed, the parameterized dataflow framework is compatible with many of the existing dataflow models for DSP including SDF, cyclo-static dataflow, scalable synchronous dataflow, and Boolean dataflow. In this paper, we develop precise, formal semantics for parameterized synchronous dataflow (PSDF)-the application of our parameterized modeling framework to SDF-that allows data-dependent, dynamic DSP systems to be modeled in a natural and intuitive fashion. Through our development of PSDF, we demonstrate that desirable properties of a DSP modeling environment such as dynamic reconfigurability and design reuse emerge as inherent characteristics of our parameterized framework. An example of a speech compression application is used to illustrate the efficacy of the PSDF approach and its amenability to efficient software synthesis techniques. In addition, we illustrate the generality of our parameterized framework by discussing its application to cyclostatic dataflow, which is a popular alternative to the SDF model.Index Terms-CAD tools, dataflow modeling, embedded systems, reconfigurable design, software synthesis.

Specification, validation, and synthesis are important aspects of embedded systems design. The use of dataflow-based design environments for these purposes is becoming increasingly popular in the domain of digital signal processing (DSP). The dataflow inter-change format (DIF) [11] and the associated DIF package have been developed for specoeying, working with, and transferring dataflow-based DSP designs across tools. In this paper, we present the newly developed DIF-to-C software synthesis framework for automatically generating monolithic C-code implementations from DSP system specifications that are programmed in DIF. This framework allows designers to efficiently explore the complex range of implementation tradeofJ~ that are available through various dataflow-based techniques for scheduling and memory management. Furthermore, the DIF-to-C framework provides a standard, vendor-neutral mechanism for linking coarse grain data-flow optimizations with fine grain handoptimized libraries and the large body of optimization techniques in the area of C compilers for DSP. 7Through experiments involving several DSP applications, we demonstrate the novel and useful capabilities of our DIF-to-C software synthesis framework.

Abstract

International audience—Dataflow models of computation are widely used for the specification, analysis, and optimization of Digital Signal Processing (DSP) applications. In this paper a new meta-model called PiMM is introduced to address the important challenge of managing dynamics in DSP-oriented representations. PiMM extends a dataflow model by introducing an explicit parameter dependency tree and an interface-based hierarchical compositionality mechanism. PiMM favors the design of highly-efficient heterogeneous multicore systems, specifying algorithms with customizable trade-offs among predictability and exploita-tion of both static and adaptive task, data and pipeline paral-lelism. PiMM fosters design space exploration and reconfigurable resource allocation in a flexible dynamic dataflow context

Video coding technology in the last 20 years has evolved producing a variety of different and complex algorithms and coding standards. So far the specification of such standards, and of the algorithms that build them, has been done case by case providing monolithic textual and reference software specifications in different forms and programming languages. However, very little attention has been given to provide a specification formalism that explicitly presents common components between standards, and the incremental modifications of such monolithic standards. The MPEG Reconfigurable Video Coding (RVC) framework is a new ISO standard currently under its final stage of standardization, aiming at providing video codec specifications at the level of library components instead of monolithic algorithms. The new concept is to be able to specify a decoder of an existing standard or a completely new configuration that may better satisfy applicationspecific constraints by selecting standard components from a library of standard coding algorithms. The possibility of dynamic configuration and reconfiguration of codecs also requires new methodologies and new tools for describing the new bitstream syntaxes and the parsers of such new codecs. The RVC framework is based on the usage of a new actor/dataflow oriented language called Cal for the specification of the standard library and instantiation of the RVC decoder model. This language has been specifically designed for modeling complex signal processing systems. Cal dataflow models expose the intrinsic concurrency of the algorithms by employing the notions of actor programming and dataflow. The paper gives an overview of the concepts and technologies building the standard RVC framework and the non standard tools supporting the RVC model from the instantiation and simulation of the Cal model to software and/or hardware code synthesis.