Analog IC Placement Generation via Neural Networks from Unlabeled Data (Record no. 175818)

MARC details
000 -LEADER
fixed length control field 03973nam a22005175i 4500
001 - CONTROL NUMBER
control field 978-3-030-50061-0
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125237.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 200630s2020 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030500610
-- 978-3-030-50061-0
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-50061-0
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5-.7
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQM
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT029000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQM
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Gusmão, António.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Analog IC Placement Generation via Neural Networks from Unlabeled Data
Medium [electronic resource] /
Statement of responsibility, etc by António Gusmão, Nuno Horta, Nuno Lourenço, Ricardo Martins.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2020.
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2020.
300 ## - PHYSICAL DESCRIPTION
Extent XIII, 87 p. 68 illus., 39 illus. in color.
Other physical details online resource.
336 ## -
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-- txt
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-- computer
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-- rdamedia
338 ## -
-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement SpringerBriefs in Applied Sciences and Technology,
International Standard Serial Number 2191-5318
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Related Work: Machine Learning and Electronic Design Automation -- Unlabeled Data and Artificial Neural Networks -- Placement Loss: Placement Constraints Description and Satisfiability Evaluation -- Experimental Results in Industrial Case Studies -- Conclusions. .
520 ## - SUMMARY, ETC.
Summary, etc In this book, innovative research using artificial neural networks (ANNs) is conducted to automate the placement task in analog integrated circuit layout design, by creating a generalized model that can generate valid layouts at push-button speed. Further, it exploits ANNs’ generalization and push-button speed prediction (once fully trained) capabilities, and details the optimal description of the input/output data relation. The description developed here is chiefly reflected in two of the system’s characteristics: the shape of the input data and the minimized loss function. In order to address the latter, abstract and segmented descriptions of both the input data and the objective behavior are developed, which allow the model to identify, in newer scenarios, sub-blocks which can be found in the input data. This approach yields device-level descriptions of the input topology that, for each device, focus on describing its relation to every other device in the topology. By means of thesedescriptions, an unfamiliar overall topology can be broken down into devices that are subject to the same constraints as a device in one of the training topologies. In the experimental results chapter, the trained ANNs are used to produce a variety of valid placement solutions even beyond the scope of the training/validation sets, demonstrating the model’s effectiveness in terms of identifying common components between newer topologies and reutilizing the acquired knowledge. Lastly, the methodology used can readily adapt to the given problem’s context (high label production cost), resulting in an efficient, inexpensive and fast model. .
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Horta, Nuno.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lourenço, Nuno.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Martins, Ricardo.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030500603
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783030500627
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title SpringerBriefs in Applied Sciences and Technology,
-- 2191-5318
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-50061-0">https://doi.org/10.1007/978-3-030-50061-0</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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