NDLI: Exploiting Statically Schedulable Regions in Dataflow Programs

Content Provider	Springer Nature Link
Author	Gu, Ruirui Janneck, Jörn W. Raulet, Mickaël Bhattacharyya, Shuvra S.
Copyright Year	2010
Abstract	Dataflow descriptions have been used in a wide range of Digital Signal Processing (DSP) applications, such as multi-media processing, and wireless communications. Among various forms of dataflow modeling, Synchronous Dataflow (SDF) is geared towards static scheduling of computational modules, which improves system performance and predictability. However, many DSP applications do not fully conform to the restrictions of SDF modeling. More general dataflow models, such as CAL (Eker and Janneck 2003), have been developed to describe dynamically-structured DSP applications. Such generalized models can express dynamically changing functionality, but lose the powerful static scheduling capabilities provided by SDF. This paper focuses on the detection of SDF-like regions in dynamic dataflow descriptions—in particular, in the generalized specification framework of CAL. This is an important step for applying static scheduling techniques within a dynamic dataflow framework. Our techniques combine the advantages of different dataflow languages and tools, including CAL (Eker and Janneck 2003), DIF (Hsu et al. 2005) and CAL2C (Roquier et al. 2008). In addition to detecting SDF-like regions, we apply existing SDF scheduling techniques to exploit the static properties of these regions within enclosing dynamic dataflow models. Furthermore, we propose an optimized approach for mapping SDF-like regions onto parallel processing platforms such as multi-core processors.
Starting Page	129
Ending Page	142
Page Count	14
File Format	PDF
ISSN	19398018
Journal	Journal of Signal Processing Systems
Volume Number	63
Issue Number	1
e-ISSN	19398115
Language	English
Publisher	Springer US
Publisher Date	2010-01-29
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cal DIF Dataflow Quasi-static scheduling Multicore processors Pattern Recognition Circuits and Systems Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Image and Speech Processing Image Processing and Computer Vision Electrical Engineering
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Signal Processing Control and Systems Engineering Information Systems Modeling and Simulation Hardware and Architecture

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