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Parameterized scheduling of topological patterns in signal processing dataflow graphs

Tutkimustuotosvertaisarvioitu

Standard

Parameterized scheduling of topological patterns in signal processing dataflow graphs. / Wang, Lai Huei; Shen, Chung Ching; Wu, Shenpei; Bhattacharyya, Shuvra S.

julkaisussa: Journal of Signal Processing Systems, Vuosikerta 71, Nro 3, 2013, s. 275-286.

Tutkimustuotosvertaisarvioitu

Harvard

Wang, LH, Shen, CC, Wu, S & Bhattacharyya, SS 2013, 'Parameterized scheduling of topological patterns in signal processing dataflow graphs', Journal of Signal Processing Systems, Vuosikerta. 71, Nro 3, Sivut 275-286. https://doi.org/10.1007/s11265-012-0719-x

APA

Wang, L. H., Shen, C. C., Wu, S., & Bhattacharyya, S. S. (2013). Parameterized scheduling of topological patterns in signal processing dataflow graphs. Journal of Signal Processing Systems, 71(3), 275-286. https://doi.org/10.1007/s11265-012-0719-x

Vancouver

Wang LH, Shen CC, Wu S, Bhattacharyya SS. Parameterized scheduling of topological patterns in signal processing dataflow graphs. Journal of Signal Processing Systems. 2013;71(3):275-286. https://doi.org/10.1007/s11265-012-0719-x

Author

Wang, Lai Huei ; Shen, Chung Ching ; Wu, Shenpei ; Bhattacharyya, Shuvra S. / Parameterized scheduling of topological patterns in signal processing dataflow graphs. Julkaisussa: Journal of Signal Processing Systems. 2013 ; Vuosikerta 71, Nro 3. Sivut 275-286.

Bibtex - Lataa

@article{70c4c40233bb458a94510490f8f9bf1d,
title = "Parameterized scheduling of topological patterns in signal processing dataflow graphs",
abstract = "In recent work, a graphical modeling construct called {"}topological patterns{"} has been shown to enable concise representation and direct analysis of repetitive dataflow graph sub-structures in the context of design methods and tools for digital signal processing systems (Sane et al. 2010). In this paper, we present a formal design method for specifying topological patterns and deriving parameterized schedules from such patterns based on a novel schedule model called the scalable schedule tree. The approach represents an important class of parameterized schedule structures in a form that is intuitive for representation and efficient for code generation. Through application case studies involving image processing and wireless communications, we demonstrate our methods for topological pattern representation, scalable schedule tree derivation, and associated dataflow graph code generation.",
keywords = "Dataflow, Image registration, Scheduling, Software tools, Turbo decoder",
author = "Wang, {Lai Huei} and Shen, {Chung Ching} and Shenpei Wu and Bhattacharyya, {Shuvra S.}",
year = "2013",
doi = "10.1007/s11265-012-0719-x",
language = "English",
volume = "71",
pages = "275--286",
journal = "Journal of Signal Processing Systems",
issn = "1939-8018",
publisher = "Springer Verlag",
number = "3",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Parameterized scheduling of topological patterns in signal processing dataflow graphs

AU - Wang, Lai Huei

AU - Shen, Chung Ching

AU - Wu, Shenpei

AU - Bhattacharyya, Shuvra S.

PY - 2013

Y1 - 2013

N2 - In recent work, a graphical modeling construct called "topological patterns" has been shown to enable concise representation and direct analysis of repetitive dataflow graph sub-structures in the context of design methods and tools for digital signal processing systems (Sane et al. 2010). In this paper, we present a formal design method for specifying topological patterns and deriving parameterized schedules from such patterns based on a novel schedule model called the scalable schedule tree. The approach represents an important class of parameterized schedule structures in a form that is intuitive for representation and efficient for code generation. Through application case studies involving image processing and wireless communications, we demonstrate our methods for topological pattern representation, scalable schedule tree derivation, and associated dataflow graph code generation.

AB - In recent work, a graphical modeling construct called "topological patterns" has been shown to enable concise representation and direct analysis of repetitive dataflow graph sub-structures in the context of design methods and tools for digital signal processing systems (Sane et al. 2010). In this paper, we present a formal design method for specifying topological patterns and deriving parameterized schedules from such patterns based on a novel schedule model called the scalable schedule tree. The approach represents an important class of parameterized schedule structures in a form that is intuitive for representation and efficient for code generation. Through application case studies involving image processing and wireless communications, we demonstrate our methods for topological pattern representation, scalable schedule tree derivation, and associated dataflow graph code generation.

KW - Dataflow

KW - Image registration

KW - Scheduling

KW - Software tools

KW - Turbo decoder

UR - http://www.scopus.com/inward/record.url?scp=84879696501&partnerID=8YFLogxK

U2 - 10.1007/s11265-012-0719-x

DO - 10.1007/s11265-012-0719-x

M3 - Article

VL - 71

SP - 275

EP - 286

JO - Journal of Signal Processing Systems

JF - Journal of Signal Processing Systems

SN - 1939-8018

IS - 3

ER -