Optimizing transistor networks using a graph-based technique

被引:5
|
作者
Possani, Vinicius N. [1 ]
de Souza, Renato S. [1 ]
Domingues, Julio S., Jr. [1 ]
Agostini, Luciano V. [1 ]
Marques, Felipe S. [1 ]
da Rosa, Leomar S., Jr. [1 ]
机构
[1] Univ Fed Pelotas, Technol Dev Ctr, Pelotas, Brazil
关键词
Transistor network; Logic synthesis; Graph; Wheatstone bridge; Logic gates; BOOLEAN FUNCTIONS; DESIGN; LOGIC; CIRCUITS;
D O I
10.1007/s10470-012-9874-z
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Currently, most integrated circuits have higher density of transistors on the small physical area, reduced power consumption and greater performance. An important factor that has contributed for this is the representation of logic functions with a reduced number of transistors. While the generation of a series-parallel network can be straightforward once a minimized Boolean expression is available, this may not be an optimum solution. This paper proposes a graph-based solution for minimizing the number of transistors that compose a network by edges sharing. The algorithm starts from a sum-of-products expression and can achieve non-series-parallel arrangements. The Wheatstone bridge arrangements contribute for the transistor count reduction. Experimental results demonstrate the efficiency of the approach when comparing to traditional factorization algorithms implemented in the SIS software. When applying to the set of four input p-class logic functions, the proposed method presents advantages if compared to the good-factor algorithm.
引用
收藏
页码:841 / 850
页数:10
相关论文
共 50 条
  • [1] Optimizing transistor networks using a graph-based technique
    Vinicius N. Possani
    Renato S. de Souza
    Julio S. Domingues
    Luciano V. Agostini
    Felipe S. Marques
    Leomar S. da Rosa
    [J]. Analog Integrated Circuits and Signal Processing, 2012, 73 : 841 - 850
  • [2] Thresholding of Semantic Similarity Networks Using a Spectral Graph-Based Technique
    Guzzi, Pietro Hiram
    Veltri, Pierangelo
    Cannataro, Mario
    [J]. NEW FRONTIERS IN MINING COMPLEX PATTERNS, NFMCP 2013, 2014, 8399 : 201 - 213
  • [3] Graph-based Recommendation using Graph Neural Networks
    Dossena, Marco
    Irwin, Christopher
    Portinale, Luigi
    [J]. 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, 2022, : 1769 - 1774
  • [4] Optimizing large join queries using a graph-based approach
    Lee, C
    Shih, CS
    Chen, YH
    [J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2001, 13 (02) : 298 - 315
  • [5] A technique for determining relevance scores of process activities using graph-based neural networks
    Stierle, Matthias
    Weinzierl, Sven
    Harl, Maximilian
    Matzner, Martin
    [J]. DECISION SUPPORT SYSTEMS, 2021, 144 (144)
  • [6] Source Localization using Graph-based Optimization Technique
    Srirangarajan, Seshan
    Pesch, Dirk
    [J]. 2013 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2013, : 1127 - 1132
  • [7] Optimizing image segmentation of pavement defects using graph-based method
    Nguyen, T. H.
    Nguyen, T. L.
    Afanasiev, A. D.
    Pham, T. L.
    [J]. INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2021, 15 (04): : 591 - 597
  • [8] Graph-based Fake News Detection using a Summarization Technique
    Kim, Gihwan
    Ko, Youngjoong
    [J]. 16TH CONFERENCE OF THE EUROPEAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (EACL 2021), 2021, : 3276 - 3280
  • [9] Circuit partitioning using graph-based alternative wiring technique
    Yuan, XL
    Wu, YL
    Gao, DY
    [J]. PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON COMPUTER AIDED DESIGN & COMPUTER GRAPHICS, 1999, : 647 - 651
  • [10] An Efficient Mining of Transactional Data Using Graph-based Technique
    AlZoubi, Wael Ahmad
    Omar, Khairuddin
    Abu Bakar, Azuraliza
    [J]. 2011 3RD CONFERENCE ON DATA MINING AND OPTIMIZATION (DMO), 2011, : 74 - 81