留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于近似计算技术的多级逻辑电路面积优化

赵维凯 王伦耀 岑旭梦 夏银水 储著飞

赵维凯,王伦耀,岑旭梦,等. 基于近似计算技术的多级逻辑电路面积优化[J]. 北京航空航天大学学报,2024,50(9):2893-2901 doi: 10.13700/j.bh.1001-5965.2022.0742
引用本文: 赵维凯,王伦耀,岑旭梦,等. 基于近似计算技术的多级逻辑电路面积优化[J]. 北京航空航天大学学报,2024,50(9):2893-2901 doi: 10.13700/j.bh.1001-5965.2022.0742
ZHAO W K,WANG L Y,CEN X M,et al. Area optimization of multilevel logic circuits using approximate computing[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(9):2893-2901 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0742
Citation: ZHAO W K,WANG L Y,CEN X M,et al. Area optimization of multilevel logic circuits using approximate computing[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(9):2893-2901 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0742

基于近似计算技术的多级逻辑电路面积优化

doi: 10.13700/j.bh.1001-5965.2022.0742
基金项目: 国家自然科学基金(U1709218,61471211,61871242)
详细信息
    通讯作者:

    E-mail:wanglunyao@nbu.edu.cn

  • 中图分类号: TN431.2

Area optimization of multilevel logic circuits using approximate computing

Funds: National Natural Science Foundation of China (U1709218,61471211,61871242)
More Information
  • 摘要:

    针对现有多级逻辑近似优化算法在大型电路优化时无法较好兼顾优化效果与算法速度的问题,提出一种基于常量替换的多级逻辑电路面积优化算法。该算法通过在与非图(AIG)中引入节点输出距离、常量传输距离等参数,并结合提出的多扇出节点常量替换过程中错误率控制方法,在全局范围内提取合适替换的候选节点集和每个候选节点输出的常量替换值;同时,通过根据电路规模选取不同的错误率计算方法等策略,实现了错误率约束下的多级逻辑电路面积近似优化并使算法速度得到提高。所提算法用C语言和ABC内置命令编程实现,使用EPFL及MCNC电路进行测试。实验结果表明:所提算法与已提出的常量替换方法相比,面积优化效果提升48.77%;相较于近似关心集重代换的近似逻辑综合(ALSRAC)优化算法,所提算法在面积优化和运算时间上分别有1.28%和60.91%的提升。

     

  • 图 1  C17电路AIG

    Figure 1.  AIG of C17 circuit

    图 2  Miter电路

    Figure 2.  Miter circuit

    图 3  节点9扇出的不同常量替换结果

    Figure 3.  Results of the different constant replacement for node 9 fanout

    图 4  M_C17电路的AIG

    Figure 4.  AIG of benchmark M_C17

    图 5  对C17中节点9不同扇出优化结果

    Figure 5.  Optimization results for different fanouts of node 9 in C17

    表  1  本文使用的MCNC和EPFL测试电路参数

    Table  1.   Parameters of MCNC and EPFL benchmarks used in this paper

    MCNC 电路输入端口数量 电路输出端口数量 初始面积 EPFL 电路输入端口数量 电路输出端口数量 初始面积
    cm163 16 5 61 arbiter 25 129 23366
    z4ml 7 4 61 cavlc 10 11 1124
    alu2 10 6 636 ctrl 7 26 204
    frg1 28 3 179 dec 8 256 649
    alu4 14 8 1158 i2c 147 142 2103
    unreg 36 16 163 int2float 11 7 379
    x2 10 7 74 mem_ctrl 1204 1231 79153
    count 35 16 203 priority 128 8 1270
    term1 34 10 276 router 60 30 316
    voter 1001 1 16240
    下载: 导出CSV

    表  2  本文算法与文献[10]的比较结果

    Table  2.   Comparison results of the proposed algorithms and Ref.[10] %

    电路名称面积优化延时优化错误率
    文献[10]本文算法文献[10]本文算法文献[10]本文算法
    cm16353.8568.8547.3767.4821.0024.82
    z4ml0.0042.620.0027.720.0024.99
    alu29.0957.700.0046.0224.0024.43
    frg12.4998.320.0095.5816.0024.32
    alu46.0150.090.0026.9122.0024.76
    unreg0.0034.360.000.000.0024.99
    x210.8172.271.7238.4612.0024.25
    count57.8558.1379.4580.6224.0024.77
    term146.7393.1227.0378.727.0019.28
    下载: 导出CSV

    表  3  本文算法与文献[11]的比较结果

    Table  3.   The comparison results of the algorithms of this paper and Ref.[11]

    电路名称 面积优化/% 耗时/s
    文献[11] 本文算法 文献[11] 本文算法
    arbiter 90.15 90.79 9015.06 8593.68
    cavlc 5.70 7.47 375.57 67.05
    ctrl 3.80 4.90 2.24 3.67
    dec 0.62 0.62 8.45 10.06
    i2c 31.59 37.95 189.50 176.49
    int2float 16.30 23.48 10.86 51.71
    mem_ctrl 62.66 >86400.00 2278.56
    priority 96.92 98.27 14.95 36.89
    router 100.00 98.73 2.00 0.18
    voter 5.72 0.09 13504.23 177.04
    下载: 导出CSV
  • [1] WALDROP M M. The chips are down for Moore’s law[J]. Nature, 2016, 530(7589): 144-147. doi: 10.1038/530144a
    [2] HAN J, ORSHANSKY M. Approximate computing: An emerging paradigm for energy-efficient design[C]//Proceedings of the 18th IEEE European Test Symposium. Piscataway: IEEE Press, 2013: 1-6.
    [3] SCARABOTTOLO I, ANSALONI G, CONSTANTINIDES G A, et al. A formal framework for maximum error estimation in approximate logic synthesis[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022, 41(4): 840-853. doi: 10.1109/TCAD.2021.3075651
    [4] SCARABOTTOLO I, ANSALONI G, CONSTANTINIDES G A, et al. Approximate logic synthesis: A survey[J]. Proceedings of the IEEE, 2020, 108(12): 2195-2213. doi: 10.1109/JPROC.2020.3014430
    [5] PASANDI G, NAZARIAN S, PEDRAM M. Approximate logic synthesis: A reinforcement learning-based technology mapping approach[C]//Proceedings of the 20th International Symposium on Quality Electronic Design. Piscataway: IEEE Press, 2019: 26-33.
    [6] ZHOU Z Z, YAO Y, HUANG S Y, et al. DALS: Delay-driven approximate logic synthesis[C]//Proceedings of the IEEE/ACM International Conference on Computer-Aided Design. Piscataway: IEEE Press, 2018: 1-7.
    [7] VENKATARAMANI S, ROY K, RAGHUNATHAN A. Substitute-and-simplify: A unified design paradigm for approximate and quality configurable circuits[C]//Proceedings of the Design, Automation & Test in Europe Conference & Exhibition. Piscataway: IEEE Press, 2013: 1367-1372.
    [8] SU S B, WU Y, QIAN W K. Efficient batch statistical error estimation for iterative multi-level approximate logic synthesis[C]//Proceedings of the 55th ACM/ESDA/IEEE Design Automation Conference. Piscataway: IEEE Press, 2018: 1-6.
    [9] PASANDI G, PETERSON M, HERRERA M, et al. Deep-PowerX: A deep learning-based framework for low-power approximate logic synthesis[C]//Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design. New York: ACM, 2020: 73-78.
    [10] CHANDRASEKHARAN A, SOEKEN M, GROßE D, et al. Approximation-aware rewriting of AIGs for error tolerant applications[C]//Proceedings of the 35th International Conference on Computer-Aided Design. New York: ACM, 2016: 1-8.
    [11] MENG C, QIAN W K, MISHCHENKO A. ALSRAC: Approximate logic synthesis by resubstitution with approximate care set[C]//Proceedings of the 57th ACM/IEEE Design Automation Conference. Piscataway: IEEE Press, 2020: 1-6.
    [12] WU Y, QIAN W K. ALFANS: Multilevel approximate logic synthesis framework by approximate node simplification[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020, 39(7): 1470-1483. doi: 10.1109/TCAD.2019.2915328
    [13] SU S B, MENG C, YANG F, et al. VECBEE: A versatile efficiency-accuracy configurable batch error estimation method for greedy approximate logic synthesis[J]. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022, 41(11): 5085-5099.
    [14] BRAND D. Verification of large synthesized designs[C]//Proceedings of the International Conference on Computer Aided Design. Piscataway: IEEE Press, 1993: 534-537.
    [15] BRYANT. Graph-based algorithms for Boolean function manipulation[J]. IEEE Transactions on Computers, 1986, C-35(8): 677-691. doi: 10.1109/TC.1986.1676819
    [16] MISHCHENKO A, CHATTERJEE S, BRAYTON R. DAG-aware AIG rewriting: A fresh look at combinational logic synthesis[C]//Proceedings of the 43rd ACM/IEEE Design Automation Conference. Piscataway: IEEE Press, 2006: 532-535.
    [17] BRAYTON R, MISHCHENKO A. ABC: An academic industrial-strength verification tool[C]//International Conference on Computer Aided Verification. Berlin: Springer, 2010: 24-40.
  • 加载中
图(5) / 表(3)
计量
  • 文章访问数:  221
  • HTML全文浏览量:  109
  • PDF下载量:  12
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-08-29
  • 录用日期:  2022-09-16
  • 网络出版日期:  2022-11-01
  • 整期出版日期:  2024-09-27

目录

    /

    返回文章
    返回
    常见问答