Temporal Localization and Systolization of Signal Flow Graph (SFG) Computing Networks

S. Y. Kung; S. C. Lo; J. Annevelink

doi:10.1117/12.944009

Temporal Localization and Systolization of Signal Flow Graph (SFG) Computing Networks

S. Y. Kung, S. C. Lo, J. Annevelink

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

This paper addresses the theoretical and algorithmic issues related to optimal temporal localization (and systolization) of Signal Flow Graph (SFG) computing networks. Based on a cut-set localization procedure we propose an algorithm that computes the optimal localization of an SFG. The basic algorithm is then extended so that it can be used with hierarchically specified SFG’s, thus significantly improving the computational efficiency. The algorithms can be easily coded and incorporated into a computer-aided-design (CAD) system.

Original language	English (US)
Pages (from-to)	58-66
Number of pages	9
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	495
DOIs	https://doi.org/10.1117/12.944009
State	Published - Nov 28 1984
Externally published	Yes

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.944009

Cite this

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title = "Temporal Localization and Systolization of Signal Flow Graph (SFG) Computing Networks",

abstract = "This paper addresses the theoretical and algorithmic issues related to optimal temporal localization (and systolization) of Signal Flow Graph (SFG) computing networks. Based on a cut-set localization procedure we propose an algorithm that computes the optimal localization of an SFG. The basic algorithm is then extended so that it can be used with hierarchically specified SFG{\textquoteright}s, thus significantly improving the computational efficiency. The algorithms can be easily coded and incorporated into a computer-aided-design (CAD) system.",

author = "Kung, {S. Y.} and Lo, {S. C.} and J. Annevelink",

note = "Funding Information: This research was supported in part by the Commission of the EEC under the 3744/81 Program (ICD Contract), by ZWO, the Dutch Foundation for pure scientific research, by the Office of Naval Research under contracts N00014-81-K0191 and N00014-83-C-0377 and by the National Science Foundation under Grant ECS-82-12479.",

year = "1984",

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doi = "10.1117/12.944009",

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AU - Kung, S. Y.

AU - Lo, S. C.

AU - Annevelink, J.

N1 - Funding Information: This research was supported in part by the Commission of the EEC under the 3744/81 Program (ICD Contract), by ZWO, the Dutch Foundation for pure scientific research, by the Office of Naval Research under contracts N00014-81-K0191 and N00014-83-C-0377 and by the National Science Foundation under Grant ECS-82-12479.

PY - 1984/11/28

Y1 - 1984/11/28

N2 - This paper addresses the theoretical and algorithmic issues related to optimal temporal localization (and systolization) of Signal Flow Graph (SFG) computing networks. Based on a cut-set localization procedure we propose an algorithm that computes the optimal localization of an SFG. The basic algorithm is then extended so that it can be used with hierarchically specified SFG’s, thus significantly improving the computational efficiency. The algorithms can be easily coded and incorporated into a computer-aided-design (CAD) system.

AB - This paper addresses the theoretical and algorithmic issues related to optimal temporal localization (and systolization) of Signal Flow Graph (SFG) computing networks. Based on a cut-set localization procedure we propose an algorithm that computes the optimal localization of an SFG. The basic algorithm is then extended so that it can be used with hierarchically specified SFG’s, thus significantly improving the computational efficiency. The algorithms can be easily coded and incorporated into a computer-aided-design (CAD) system.

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Temporal Localization and Systolization of Signal Flow Graph (SFG) Computing Networks

Abstract

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