Exploring the concurrency of an MPEG RVC decoder based on dataflow program analysis

  • Authors:

  • Ruirui Gu;Jörn W. Janneck;Shuvra S. Bhattacharyya;Mickaël Raulet;Matthieu Wipliez;William Plishker

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Maryland, College Park, MD;Xilinx Inc., San Jose, CA;Department of Electrical and Computer Engineering, University of Maryland, College Park, MD;Institute of Electronics and Telecommunications, Rennes Laboratory, National Institute of Applied Sciences, Rennes Cedex, France;Institute of Electronics and Telecommunications, Rennes Laboratory, National Institute of Applied Sciences, Rennes Cedex, France;Department of Electrical and Computer Engineering, University of Maryland, College Park, MD

  • Venue:
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Year:
  • 2009

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Abstract

This paper presents an in-depth case study on dataflow-based analysis and exploitation of parallelism in the design and implementation of a MPEG reconfigurable video coding decoder. Dataflow descriptions have been used in a wide range of digital signal processing (DSP) applications, such as applications for multimedia processing and wireless communications. Because dataflow models are effective in exposing concurrency and other important forms of high level application structure, dataflow techniques are promising for implementing complex DSP applications on multicore systems, and other kinds of parallel processing platforms. In this paper, we use the client access license (CAL) language as a concrete framework for representing and demonstrating dataflow design techniques. Furthermore, we also describe our application of the differential item functioning dataflow interchange format package (TDP), a software tool for analyzing dataflow networks, to the systematic exploitation of concurrency in CAL networks that are targeted to multicore platforms. Using TDP, one is able to automatically process regions that are extracted from the original network, and exhibit properties similar to synchronous dataflow (SDF) models. This is important in our context because powerful techniques, based on static scheduling, are available for exploiting concurrency in SDF descriptions. Detection of SDF-like regions is an important step for applying static scheduling techniques within a dynamic dataflow framework. Furthermore, segmenting a system into SDF-like regions also allows us to explore cross-actor concurrency that results from dynamic dependences among different regions. Using SDF-like region detection as a preprocessing step to software synthesis generally provides an efficient way for mapping tasks to multicore systems, and improves the system performance of video processing applications on multicore platforms.