WO2024060454A1 - 参数计算辅助方法、系统、设备及存储介质 - Google Patents

参数计算辅助方法、系统、设备及存储介质 Download PDF

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WO2024060454A1
WO2024060454A1 PCT/CN2022/142569 CN2022142569W WO2024060454A1 WO 2024060454 A1 WO2024060454 A1 WO 2024060454A1 CN 2022142569 W CN2022142569 W CN 2022142569W WO 2024060454 A1 WO2024060454 A1 WO 2024060454A1
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test data
selection
selection operation
curve
visual interface
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PCT/CN2022/142569
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English (en)
French (fr)
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王可亮
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上海概伦电子股份有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/31—Design entry, e.g. editors specifically adapted for circuit design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/39—Circuit design at the physical level
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/20—Drawing from basic elements, e.g. lines or circles
    • G06T11/203—Drawing of straight lines or curves
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects

Definitions

  • the present invention relates to the technical field of computer-aided design, and in particular to a parameter calculation auxiliary method, system, equipment and storage medium.
  • the embodiments of the present application solve the problem in the prior art that when performing a selection operation before parameter calculation, one needs to be selected one by one or the entire selection is made in batches, resulting in cumbersome operations and complex calculations.
  • embodiments of the present application provide an auxiliary method for parameter calculation, which method includes:
  • the three-dimensional test data set includes several test data sets related to voltage, current, and capacitance obtained by testing the integrated circuit device under different test conditions;
  • filtering items configured in the visual interface, which is used to filter and classify the received three-dimensional test data sets to form multiple sets of custom test data sets; select any one set of the custom tests When the data set fits the device model of the integrated circuit device, the fitting of voltage-current-capacitance is drawn in the form of data points in the visualization interface based on several discrete test data sets. curve;
  • custom filter code is used in the selection operation algorithm, which includes:
  • the selection operation algorithm supports user-defined variables to set filtering conditions.
  • step S2 is also configured with an equalizer for adjusting the test data group in the current custom test data set so that it equals the actual fitting curve currently drawn. The shape moves closer to the target curve drawn in the visualization interface.
  • the fitting curve of voltage-current-capacitance in step S2 may be one or more of a current-voltage curve, a capacitance-voltage curve, and a current-capacitance curve.
  • a parameter calculation assistance system which includes:
  • a data receiving module configured to receive a three-dimensional test data set of the integrated circuit device.
  • the three-dimensional test data set includes several test data sets related to voltage, current, and capacitance obtained by testing the integrated circuit device under different test conditions;
  • the curve drawing module is configured to respond to the user-defined condition filter items configured in the visual interface, and is used to filter and classify the received three-dimensional test data sets to form multiple sets of custom test data sets; select any one set of the test data sets.
  • the custom test data set fits the device model of the integrated circuit device, according to several discrete test data groups, the voltage-current-voltage-current-correlation relationship is drawn in the form of data points in the visualization interface.
  • a parameter selection module configured to respond to a user selection rule editing box configured in the visual interface for inputting a selection operation algorithm required for parameter selection of the fitting curve in the visual interface; editing based on the user selection rule
  • the selection operation algorithm is pre-configured in the frame.
  • embodiments of the present application provide an electronic device, including a memory and a processor. Instructions are stored in the memory, and the memory and the processor are interconnected through lines; the processor calls the memory The instructions in implement the parameter calculation auxiliary method as described in any one of the first aspects.
  • embodiments of the present application provide a computer-readable storage medium.
  • a computer program is stored on the computer-readable storage medium.
  • the computer program executes any one of the first aspects.
  • the selection operation algorithm required for parameter selection of the fitting curve in the visual interface can be input in the user selection rule editing box, thereby limiting the selection operation, thus simplifying the complex manual selection.
  • Figure 1 is a flow chart of the parameter calculation auxiliary method in Embodiment 1 of the present application.
  • Figure 2 is a module diagram of the parameter calculation auxiliary system in Embodiment 2 of the present application.
  • Figure 3 is a module diagram of the electronic device in Embodiment 3 of the present application.
  • the parameter adjustment operation relies on the experience of the operators of the semiconductor manufacturing company. After combining the graphic display with the equalizer, manual adjustment is performed, and during the adjustment process, the equalizer is used.
  • the equalizer triggers the parameter adjustment message, and the semiconductor device modeling platform performs calculations based on the parameter adjustment information corresponding to the equalizer, and displays the calculation results graphically. That is to say, the test data group in the current custom test data set can be used to draw A fitting curve about voltage-current-capacitance is obtained.
  • equalization is used in this embodiment.
  • the equalizer is used to adjust the current fitting curve. Although the current fitting curve cannot completely coincide with the target curve, the equalizer is used to reduce the difference between the two to a certain extent.
  • the data points in this embodiment can be selected.
  • this application provides Custom selection rules. Based on the custom selection rules, during batch selection operations, only some data points are selected for parameter calculation.
  • an embodiment of the present application provides an auxiliary method for parameter calculation, which includes the following steps.
  • Step S1 Receive a three-dimensional test data set of the integrated circuit device.
  • the three-dimensional test data set includes several test data sets related to voltage, current, and capacitance obtained by testing the integrated circuit device under different test conditions.
  • the three-dimensional test data set in this embodiment is composed of several three-dimensional test data groups, each three-dimensional test data group [voltage, current, capacitance]. Therefore, when performing two-dimensional curve fitting, it can be understood that one of the data is a fixed value. For example, the voltage is fixed, the current and capacitance are linearly related, and a fitting curve is drawn. For another example, the current is fixed, the voltage and capacitance are linearly related, and a fitting curve is drawn. The capacitance is fixed, the voltage and current are linearly related, and a fitting curve is drawn.
  • the integrated circuit device in this embodiment may be, but is not limited to, the following devices: MOSFET transistor, silicon-on-insulator transistor (SOI), fin field effect transistor (FinFET), bipolar transistor (BJT), heterojunction transistor (HBT) ), thin film transistor (TFT), metal semiconductor contact field effect transistor (MESFET), diode, resistor or inductor, etc.
  • the determined device model may be, but is not limited to, BSIM3, BSIM4, BSIM6, BSIM-CMG, BSIM-IMG, BSIMSOI, UTSOI, HiSIM2, HiSIM_HV, PSP, GP-BJT or RPITFT.
  • the test data set in this embodiment may be obtained by testing the integrated circuit device under different test conditions.
  • the various test conditions in this embodiment can be combined to form new test conditions.
  • the test conditions can be different sizes of integrated circuit devices (such as different channel lengths, channel widths), different voltage bias conditions (such as the bias voltage Vbs between the body region and the source, different source and drain voltage Vds, etc.), different temperature conditions, etc.
  • Different types of test conditions can be combined into a new set of test conditions and used to describe the physical characteristics and test environment of the integrated circuit device under test, such as the device's channel length, width, and body bias voltage, etc.
  • the integrated circuit device in this embodiment does not refer to a specific physical device, but refers to a general term for a class of devices prepared using the same integrated circuit manufacturing process. For example, two integrated circuit devices manufactured using the same process but differing only in channel width can be considered to be the same integrated circuit device. Therefore, testing the integrated circuit device under each set of test conditions can generate corresponding test data sets. These test data sets can be current, voltage, and capacitance. Therefore, the test data obtained from testing under multiple sets of test conditions can constitute a test data set. In some other embodiments, the test data set can be changed or adjusted according to the test conditions and test requirements when testing, and the application is not limited thereto.
  • the derived electrical parameters may include Idin, saturation leakage current ldsat, maximum transconductance maxGm, Vtlin, saturation threshold voltage Vtsat, Vtgm and other parameters, and may also include electrical output parameters such as Gm and Gds. For more information on these parameters, you can also refer to the instructions in the BSIM model or other models. These electrical parameters may vary with voltage.
  • Step S2 In response to the user-defined condition filtering items configured in the visual interface, which is used to filter and classify the received three-dimensional test data sets to form multiple sets of customized test data sets; select any one of the customized test data sets.
  • a simulated voltage-current-capacitance diagram is drawn in the form of data points in the visualization interface based on several discrete test data sets. combined curve.
  • the data points in this embodiment can be understood as each test data group occupying one data point in the visual interface, and a single data point can be clicked to select.
  • the user-defined condition filtering items in this embodiment can be understood as dividing the received three-dimensional test data set with different bias conditions. For example, when the filtering condition is a fixed voltage, then based on the fixed voltage, it can be extracted All test data sets under a fixed voltage are connected and a custom test data set based on the fixed voltage is formed.
  • the filtering conditions are not limited to fixed voltage, but can also be fixed current or fixed capacitance.
  • the visual interface in this embodiment not only displays the fitting curve drawn by the current custom test data set, but also draws the target curve based on the test conditions.
  • the target curve can be understood as a kind of theoretical data. Under a certain test condition, the target curve is drawn from a theoretically achievable test data set.
  • This embodiment uses a visual interface to simultaneously present the fitting curve drawn by the test data group in the current custom test data set and the target curve under the same conditions. Technicians can directly adjust the fitting curve using the equalizer based on what they see. It is necessary to reconfigure the filtering conditions to reduce error operations and select the test data group closest to the target.
  • the visual interface in step S2 is also configured with an equalizer, which is used to adjust the test data group in the current custom test data set so that the actual simulated data currently drawn is
  • the shape of the combined curve is closer to the target curve drawn in the visualization interface. That is to say, use the equalizer to adjust the shape of the fitting curve to bring it closer to the target curve until no further adjustment is possible, and then determine the final fitting curve.
  • the fitting curve is drawn in the form of data points in the visual interface, and each data point represents a test data group. That is to say, the test data group determined based on the data points in the final fitting curve is the implementation of this implementation.
  • the test data set in the example that is closest to the theoretical data.
  • the fitting curve of voltage-current-capacitance in step S2 may be one or more of a current-voltage curve, a capacitance-voltage curve, and a current-capacitance curve.
  • the visual interface can display the fitting curves drawn by the test data groups in different custom test data sets in different display interfaces.
  • Step S3 In response to the user selection rule edit box being configured in the visual interface, it is used to input the selection operation algorithm required for parameter selection of the fitting curve in the visual interface; based on the user selection rule edit box in advance The configured selection operation algorithm, when performing the selection operation of the fitting curve in the visualization interface, selects the data point adapted to the selection operation rule in the selection area for calculating the value of the device model. parameter.
  • step S3 a selection assistance method before parameter calculation based on a visual interface is implemented.
  • step S3 when performing batch selection operations in a certain area, you can directly click to pull all data points in the selection area, but not all data points meet the selection requirements.
  • step S3 When performing parameter calculations, if the test data groups corresponding to all data points in the selected area are subjected to parameter calculations, the amount of calculations will be very large, there will be many invalid calculations, and the calculation efficiency will be very low. Based on this, this application provides the technical solution in step S3.
  • Custom filter code is used in the selection operation algorithm, which includes:
  • the selection operation algorithm supports user-defined variables to set filter conditions.
  • Expression operations, four arithmetic operations, and logical operations are supported through filter conditions in the G, X, and P axes.
  • ⁇ graph description> indicates selecting the graph type filter and entering Id_vg in the visual interface, which is a graph showing the change of the d port current as Vg changes;
  • the corresponding vgs; "[, ⁇ prop>][, ⁇ prop> ⁇ value>]”: indicates the P-axis filter input parameter, which is an optional parameter.
  • the above rules can be understood as, for a fitting curve of type Id_vg in the visual interface, the Y-axis output of the fitting curve uses the mathematical transformation dy/dx to calculate gm, and displays the graph in log, Select -2 in the P-axis direction, and 0.5 times the P-axis is represented as 2 curves within the maximum value range. If there are less than 2, select all curves. From each selected curve, select 15 points in the range from vth-0.5 to vth*1.1 along the X direction. If there are less than 15 points, select all points.
  • a user selection rule editing box is configured in the visual interface, and then the selection operation algorithm required for parameter selection of the fitting curve is input into the visual interface to limit the selection operation.
  • complex manual selection or graphical interface settings are converted into simple text settings, which is convenient to use, improves setting efficiency, improves the scalability of special function support, and can support user-defined settings, which is convenient Set up more complex operations.
  • an embodiment of the present application provides a parameter calculation auxiliary system, which adopts the method of Embodiment 1.
  • the system includes the following modules.
  • the data receiving module 100 is configured to receive a three-dimensional test data set of an integrated circuit device.
  • the three-dimensional test data set includes several test data sets related to voltage, current, and capacitance obtained by testing the integrated circuit device under different test conditions.
  • the curve drawing module 200 is configured to filter and classify the received three-dimensional test data sets in response to the user-defined condition filter items configured in the visual interface, and to form multiple sets of custom test data sets; select any one set When the custom test data set fits the device model of the integrated circuit device, the voltage-current relationship is drawn in the form of data points in the visualization interface based on several discrete test data groups. -Fitting curve of capacitance.
  • the parameter selection module 300 is configured to respond to a user selection rule editing box configured in the visualization interface, and is used to input a selection operation algorithm required for parameter selection of the fitting curve in the visualization interface; based on the selection operation algorithm pre-configured in the user selection rule editing box, when performing a selection operation of the fitting curve in the visualization interface, the data points that are adapted to the selection operation rules are selected in the selection area as parameters of the device model.
  • an embodiment of the present application provides an electronic device, including a memory and a processor. Instructions are stored in the memory, and the memory and the processor are interconnected through lines; the processor calls the instructions in the memory to implement the following implementation: Parameter calculation auxiliary method for any item in Example 1.
  • the electronic device 500 may vary greatly due to different configurations or performance, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and memory 520, one or more
  • the above storage medium 530 (such as one or more mass storage devices) stores application programs 533 or data 532. Among them, the memory 520 and the storage medium 530 may be short-term storage or persistent storage.
  • the program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the electronic device 500 .
  • the processor 510 may be configured to communicate with the storage medium 530 and execute a series of instruction operations in the storage medium 530 on the electronic device 500 .
  • the electronic device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input and output interfaces 560, and/or one or more operating systems 531, such as Windows server, etc. wait.
  • power supplies 540 one or more wired or wireless network interfaces 550
  • input and output interfaces 560 one or more input and output interfaces 560
  • operating systems 531 such as Windows server, etc. wait.
  • FIG. 3 does not limit the electronic device, and may include more or fewer components than shown, or combine certain components, or arrange different components.
  • Embodiments of the present application provide a computer-readable storage medium.
  • a computer program is stored on the computer-readable storage medium. The characteristic is that when the computer program is executed by a processor, the parameter calculation auxiliary method as in any one of Embodiment 1 is implemented.
  • the computer-readable storage medium can be a non-volatile computer-readable storage medium, and the computer-readable storage medium can also be a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are run on the computer, they cause the computer to execute the steps of the parameter calculation auxiliary method in Embodiment 1.
  • the parameter calculation auxiliary method is implemented in the form of program instructions and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • the technical solution of the present disclosure is essentially or contributes to the existing technology, or all or part of the technical solution can be embodied in the form of software.
  • the computer software is stored in a storage medium, including Several instructions are used to cause a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present disclosure.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code. .
  • embodiments of the present invention may be provided as methods, systems, or computer program products.
  • the invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.
  • the invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device that implements the functions specified in one or more processes in the flowchart and/or one or more boxes in the block diagram.
  • These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device.
  • Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

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Abstract

本发明公开了一种参数计算辅助方法、系统、设备及存储介质，方法包括：S1，接收三维测试数据集；S2，对集成电路器件的器件模型进行拟合时，根据测试数据组在可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线；S3，响应于可视化界面中配置有用户选择规则编辑框，用于输入可视化界面中对拟合曲线进行参数选择所需的选择操作算法；基于用户选择规则编辑框中配置有选择操作算法，在进行可视化界面中拟合曲线的选择操作时，选择区域内选中适配于选择操作规则的数据点位，用于计算器件模型的参数。本发明将复杂的人工选择或图形界面设置转换成简易的文本设置，方便使用且提高设置效率，提高对特殊功能支持的可拓展性。

Description

参数计算辅助方法、系统、设备及存储介质 技术领域
本发明涉及计算机辅助设计技术领域，尤其涉及一种参数计算辅助方法、系统、设备及存储介质。
背景技术
现有半导体器件建模的参数优化流程中，采用界面化程序协助参数调整，并且参数调整的过程以实时的图形信息展示，基于此，已开发出将实时的参数调整反馈给观测仿真曲线中，以进行器件模型的数据选择提取的技术方案。但是，目前的数据选择提取方案中，技术人员需要先在数据展示图上选取优化区间，然后根据所选区间进行优化，对于某些需要根据测量数据计算所得的区间选择，比如选择开启电压左右偏移0.5偏压的数据区间，又比如进行人工选择，都非常困难，需要人工计算每个数据对应的每条曲线的开启电压。目前只能通过复杂的界面设置辅助模型工程师机型数据区间选择实现自动选择。
发明内容
本申请实施例通过提供一种参数计算辅助方法、系统、设备及存储介质，解决了现有技术中进行参数计算前的选择操作时，需要逐一选择或者批量整个选择，导致操作繁琐计算量复杂的技术问题，利用用户选择规则编辑框后，可对参数计算前的选择操作进行限定，减少了计算量，简化了运算步骤，提高参数选取效率。
第一方面，本申请实施例提供了一种参数计算辅助方法，所述方法包括：
S1，接收集成电路器件的三维测试数据集，所述三维测试数据集中包括不同测试条件下对所述集成电路器件测试得到的有关电压、电流、电容的若干测 试数据组；
S2，响应于可视化界面中配置有用户自定义条件筛选项，用于对接收的所述三维测试数据集进行筛选分类后，构成多组自定义测试数据集；任选一组所述自定义测试数据集对所述集成电路器件的器件模型进行拟合时，根据其若干离散的所述测试数据组，在所述可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线；
S3，响应于可视化界面中配置有用户选择规则编辑框，用于输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法；基于所述用户选择规则编辑框中配置有所述选择操作算法，在进行所述可视化界面中拟合曲线的选择操作时，选择区域内选中适配于所述选择操作规则的所述数据点位，用于计算所述器件模型的参数。
进一步地，所述选择操作算法中采用多个过滤器进行参数变量的过滤处理。
进一步地，所述选择操作算法中采用自定义过滤器代码，其包括：
<graph description>
(g(<filter condition>[，prop][，<prop>＝<value>]…)，[，prop][，<prop>＝<value>]…)，
x(<filter condition>[，prop][，<prop>＝<value>]…)，
p(<filter condition>[，prop][，<prop>＝<value>]…)。
进一步地，所述选择操作算法中支持用户自定义变量设置过滤条件。
进一步地，通过g、x、p轴内的过滤条件支持表达式运算、四则运算、逻辑运算。
进一步地，在所述步骤S2的所述可视化界面中还配置有均衡器，用于调节当前所述自定义测试数据集中的所述测试数据组，使其将当前绘制出的实际拟合曲线的形状向所述可视化界面中已绘制的目标曲线靠拢。
进一步地，在所述步骤S2中关于电压-电流-电容的拟合曲线可以是电流-电压曲线、电容-电压曲线、电流-电容曲线中的一种或多种。
第二方面，本申请实施例提供了一种参数计算辅助系统，所述系统包括：
数据接收模块，配置为接收集成电路器件的三维测试数据集，所述三维测试数据集中包括不同测试条件下对所述集成电路器件测试得到的有关电压、电流、电容的若干测试数据组；
曲线绘制模块，配置为响应于可视化界面中配置有用户自定义条件筛选项，用于对接收的所述三维测试数据集进行筛选分类后，构成多组自定义测试数据集；任选一组所述自定义测试数据集对所述集成电路器件的器件模型进行拟合时，根据其若干离散的所述测试数据组，在所述可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线；
参数选取模块，配置为响应于可视化界面中配置有用户选择规则编辑框，用于输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法；基于所述用户选择规则编辑框中预先配置的所述选择操作算法，在进行所述可视化界面中拟合曲线的选择操作时，选择区域内选中适配于所述选择操作规则的所述数据点位，作为所述器件模型的参数。
第三方面，本申请实施例提供了一种电子设备，包括存储器和处理器，所述存储器中存储有指令，所述存储器和所述处理器通过线路互连；所述处理器调用所述存储器中的所述指令，实现如第一方面中任意一项所述的参数计算辅助方法。
第四方面，本申请实施例提供了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现如第一方面中任意一项所述的参数计算辅助方法。
本申请实施例中提供的技术方案，至少具有如下技术效果：
由于采用了用户选择规则编辑框，在用户选择规则编辑框可以输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法，以此限定选择操作，从而将复杂的人工选择或图形界面设置转换成简易的文本设置，方便使用且提高设置效率，提高对特殊功能支持的可拓展性，同时可以支持用户自定 义设置，方便设置更为复杂的操作。
附图说明
图1为本申请实施例一中参数计算辅助方法的流程图；
图2为本申请实施例二中参数计算辅助系统的模块图；
图3为本申请实施例三中电子设备的模块图。
具体实施方式
在下面的详细描述中，参考了构成其一部分的附图。详细描述、附图和权利要求书中描述的说明性实施方式并非旨在限定。在不偏离本申请的主题的精神或范围的情况下，可以采用其他实施方式，并且可以做出其他变化。可以理解，可以对本申请中一般性描述的、在附图中图解说明的本申请内容的各个方面进行多种不同构成的配置、替换、组合，设计，而所有这些都明确地构成本中请内容的一部分。
目前本申请人所采用的半导体器件建模技术中，调参操作依赖于半导体制造公司的操作人员经验，采用图形显示与均衡器相结合后，进行人工调整，并且，在调整过程中，利用均衡器触发参数调整消息，半导体器件建模平台根据均衡器所对应的调参信息进行计算，并将计算结果以图形方式展现，也就是说，利用当前的自定义测试数据集中的测试数据组可以绘制出关于电压-电流-电容的拟合曲线，但是由于当前的拟合曲线与目标所需要的曲线有一定的差异性，为了缩小当前拟合曲线与目标曲线的差异性，本实施例中采用均衡器调节当前拟合曲线，虽然不能将当前拟合曲线与目标曲线完全重合，但是采用均衡器，在一定程度上缩小了两者之间的差异。在确定可视化界面中的拟合曲线后，基于拟合曲线由若干数据点位构成，本实施例中的数据点位是可以被选择的，在进行选择区域内批量选择时，本申请给出了自定义选择规则，基于自定义选择规则，在批量选择操作时，只选中部分数据点位来进行参数计算。
因此，为了更好的理解上述技术方案，下面将结合说明书附图以及具体的实施方式对上述技术方案进行详细的说明。
实施例一
参考附图1所示，本申请实施例提供了一种参数计算辅助方法，其包括如下步骤。
步骤S1：接收集成电路器件的三维测试数据集，所述三维测试数据集中包括不同测试条件下对所述集成电路器件测试得到的有关电压、电流、电容的若干测试数据组。
本实施例中的三维测试数据集是由若干三维测试数据组构成，每个三维测试数据组[电压、电流、电容]，因此进行二维曲线拟合时，可以理解为其中一项数据为固定值，比如电压固定，电流、电容呈线性关系，绘制出拟合曲线，又比如，电流固定，电压、电容呈线性关系绘制出拟合曲线，电容固定，电压、电流呈线性关系，绘制出拟合曲线。
本实施例中的集成电路器件可以是但不限于如下器件：MOSFET晶体管、绝缘体上硅晶体管(SOI)、鳍式场效应晶体管(FinFET)、双极性晶体管(BJT)、异质结晶体管(HBT)、薄膜晶体管(TFT)、金属半导体接触场效应晶体管(MESFET)、二极管、电阻或电感等。基于此，确定的器件模型可以是但不限于BSIM3、BSIM4、BSIM6、BSIM-CMG、BSIM-IMG、BSIMSOI、UTSOI、HiSIM2、HiSIM_HV、PSP、GP-BJT或RPITFT。
本实施例中的测试数据组可以是在不同的测试条件下对集成电路器件进行测试所获得的。本实施例中的各类所述测试条件可以组合行成新的测试条件。比如，测试条件可以是集成电路器件的不同尺寸(例如不同的沟道长度、沟道宽度)、不同的电压偏置条件(例如体区和源极之间的偏置电压Vbs,不同的源极和漏极电压Vds等等)、不同的温度条件等。不同类型的测试条件可以被组合为一组新的测试条件，并用于描述被测集成电路器件的物理特性和测试环境,例如器件的沟道长度、宽度以及体偏电压等等。需要说明的是，本实施例中的 集成电路器件并非指某个特定的实体器件，而是指采用同一集成电路制程制备得到的一类器件的总称。例如，采用同一制程制备而差别仅在于沟道宽度的两个集成电路器件可以认为是同一集成电路器件。因此，每组测试条件下对集成电路器件进行测试可以产生对应的测试数据组，这些测试数据组可以是电流、电压、电容。因此，多组测试条件下测试得到的测试数据可以构成一个测试数据集。在一些其他实施例中，测试数据组可以根据进行测试时的测试条件和测试需求而变化或调整，本申请并不限于此。例如，衍生电学参数可以包括Idin、饱和漏电流ldsat、最大跨导maxGm、Vtlin、饱和阈值电压Vtsat、Vtgm等参数，也可以包括Gm、Gds等电学输出参数。关于这些参数的更多介绍，也可以参考BSIM模型或其他模型中的说明。这些电学参数可能随电压变化。
步骤S2：响应于可视化界面中配置有用户自定义条件筛选项，用于对接收的所述三维测试数据集进行筛选分类后，构成多组自定义测试数据集；任选一组所述自定义测试数据集对所述集成电路器件的器件模型进行拟合时，根据其若干离散的所述测试数据组，在所述可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线。
进一步说明，本实施例中的数据点位可以理解为在可视化界面中每一个测试数据组占据一个数据点位，并且单个的数据点位是可以被点击选中的。
本实施例中的用户自定义条件筛选项可以理解为对接收的三维测试数据集进行不同偏置条件的数据划分，比如，筛选条件为一固定电压时，那么基于该固定电压下，可以提取出相通固定电压下的所有测试数据组，并构成基于该固定电压的自定义测试数据集。筛选条件不局限于固定电压，也可以是固定电流或固定电容。
进一步说明，本实施例中的可视化界面中不仅仅显示利益当前自定义测试数据集绘制的拟合曲线，还绘制基于测试条件下的目标曲线。目标曲线可以理解为一种理论数据，在某一测试条件下，理论上可达到的测试数据组绘制成的目标曲线。本实施例利用可视化界面同时呈现当前自定义测试数据集中的测试 数据组绘制的拟合曲线与相同条件下的目标曲线，技术人员可以直接根据看到到利用均衡器进行拟合曲线的调整，不需要重新配置筛选条件即可减少误差操作，并且可以选出最接近目标的测试数据组。因此，本实施例中在所述步骤S2的所述可视化界面中还配置有均衡器，用于调节当前所述自定义测试数据集中的所述测试数据组，使其将当前绘制出的实际拟合曲线的形状向所述可视化界面中已绘制的目标曲线靠拢。也就是说，利用均衡器调整拟合曲线的形状，使其向目标曲线靠拢，直至无法继续调整后，确定最终的拟合曲线。而拟合曲线在可视化界面中以数据点位的形式绘制，每一个数据点位代表一个测试数据组，也就是说，根据最终的拟合曲线中的数据点位确定的测试数据组是本实施例中最接近理论数据的测试数据组。
在所述步骤S2中关于电压-电流-电容的拟合曲线可以是电流-电压曲线、电容-电压曲线、电流-电容曲线中的一种或多种。并且，可视化界面中可以以不同展示界面展示不同自定义测试数据集中测试数据组绘制的拟合曲线。
步骤S3：响应于可视化界面中配置有用户选择规则编辑框，用于输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法；基于所述用户选择规则编辑框中预先配置的所述选择操作算法，在进行所述可视化界面中拟合曲线的选择操作时，选择区域内选中适配于所述选择操作规则的所述数据点位，用于计算所述器件模型的参数。
本实施例通过步骤S3中可以看出，实现的是一种基于可视化界面的参数计算前的选取辅助方法。若没有步骤S3中的技术方案，在进行一定区域内的批量选择操作时，可以直接单击拉取选择区域中的所有数据点位，但并不是所有数据点位都是符合选择要求的，在进行参数计算时，若将选择区域中所有数据点位所对应的测试数据组都进行参数运算，那么运算量将很大，会有很多无效运算以及运算效率很低。基于此，本申请给出了步骤S3中的技术方案。
本实施例中的所述选择操作算法中采用多个过滤器进行参数变量的过滤处理。所述选择操作算法中采用自定义过滤器代码，其包括：
<graph description>
(g(<filter condition>[，prop][，<prop>＝<value>]…)，[，prop][，<prop>＝<value>]…)，
x(<filter condition>[，prop][，<prop>＝<value>]…)，
p(<filter condition>[，prop][，<prop>＝<value>]…)。
其中，所述选择操作算法中支持用户自定义变量设置过滤条件。通过G、X、P轴内的过滤条件支持表达式运算、四则运算、逻辑运算。
针对自定义过滤器代码，进一步补充举例并解释。
其中，“<graph description>”：表示选择图类型过滤器，在可视化界面中输入Id_vg，即表示d端口电流随Vg变化而变化的图；“[，<prop>][，<prop>＝<value>]”：为图类型过滤器入参，其为可选参数，例如“gm，scale＝1”表示为选择y轴输出是gm(dy/dx)及y轴坐标为log scale类型的图；“g(<filter condition>)”：图过滤器，其中“<filter condition>”可以是常量数字、自定义变量、自定义表达式或者程序内嵌提取算法，如MinVds(代表图常量Vds最小的一幅图)；“[，<prop>][，<prop>＝<value>]”：表示为图过滤器入参，其为可选参数，例如g(All，step＝2)表示为选择所有的符合图过滤的所有图中，图常量按递增序，已步长为2挑点选图；“x(<filter condition>)”：是X轴过滤器，其中<filter condition>可以是常量数字、自定义变量、自定义表达式，如vth(代表图器件开启电压对应的vgs)；“[，<prop>][，<prop>＝<value>]”：表示X轴过滤器入参，其为可选参；“p(<filter condition>)”：是P轴过滤器，其中<filter condition>可以是常量数字、自定义变量、自定义表达式，通过vth表示图器件开启电压对应的vgs；“[，<prop>][，<prop>＝<value>]”：表示P轴过滤器入参，其为可选参。
在一种实施例中，在用户选择规则编辑框输入：“Id_vg(g(MinVds)，gm，scale＝1)，x(vth–0.05，vth*1.1，point＝15)，p(-1.05，0，points＝2)”上述规则可以理解为，针对可视化界面中类型为Id_vg的一个拟合曲线，该拟合 曲线的Y轴输出使用数学变换dy/dx求取gm，并以log显示图，在P轴方向选中-2，到0.5倍P轴表示为最大值范围内的2条曲线，若不足2条则选中所有曲线。从每条所选曲线上，沿X方向从vth-0.5到vth*1.1范围内选中15个点，如果不足15个点则选中所有点。
可以看出，本实施例在可视化界面中配置有用户选择规则编辑框，然后通过输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法，以此限定选择操作。可以看出，本实施例中将复杂的人工选择或图形界面设置转换成简易的文本设置，方便使用且提高设置效率，提高对特殊功能支持的可拓展性，同时可以支持用户自定义设置，方便设置更为复杂的操作。
实施例二
参考附图2所示，本申请实施例提供了一种参数计算辅助系统，采用实施例一种的方法。该系统包括如下模块。
数据接收模块100，配置为接收集成电路器件的三维测试数据集，所述三维测试数据集中包括不同测试条件下对所述集成电路器件测试得到的有关电压、电流、电容的若干测试数据组。
曲线绘制模块200，配置为响应于可视化界面中配置有用户自定义条件筛选项，用于对接收的所述三维测试数据集进行筛选分类后，构成多组自定义测试数据集；任选一组所述自定义测试数据集对所述集成电路器件的器件模型进行拟合时，根据其若干离散的所述测试数据组，在所述可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线。
参数选取模块300，配置为响应于可视化界面中配置有用户选择规则编辑框，用于输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法；基于所述用户选择规则编辑框中预先配置的所述选择操作算法，在进行所述可视化界面中拟合曲线的选择操作时，选择区域内选中适配于所述选择操作规则的所述数据点位，作为所述器件模型的参数。
实施例三
参考附图3所示，本申请实施例提供了一种电子设备，包括存储器和处理器，存储器中存储有指令，存储器和处理器通过线路互连；处理器调用存储器中的指令，实现如实施例一中中任意一项的参数计算辅助方法。该电子设备500可因配置或性能不同而产生比较大的差异，可以包括一个或一个以上处理器(central processing units，CPU)510(例如，一个或一个以上处理器)和存储器520，一个或一个以上存储应用程序533或数据532的存储介质530(例如一个或一个以上海量存储设备)。其中，存储器520和存储介质530可以是短暂存储或持久存储。存储在存储介质530的程序可以包括一个或一个以上模块(图示没标出)，每个模块可以包括对电子设备500中的一系列指令操作。
进一步，处理器510可以设置为与存储介质530通信，在电子设备500上执行存储介质530中的一系列指令操作。
电子设备500还可以包括一个或一个以上电源540，一个或一个以上有线或无线的网络接口550，一个或一个以上输入输出接口560，和/或，一个或一个以上操作系统531，例如Windows server等等。本领域技术人员可以理解，图3示出的电子设备结构并不构成对电子设备的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
实施例四
本申请实施例提供了一种计算机可读存储介质，计算机可读存储介质上存储有计算机程序，其特征在于，计算机程序被处理器执行时实现如实施例一中任意一项的参数计算辅助方法。该计算机可读存储介质可以为非易失性计算机可读存储介质，该计算机可读存储介质也可以为易失性计算机可读存储介质。该计算机可读存储介质中存储有指令，当该指令在计算机上运行时，使得计算机执行实施例一中的参数计算辅助方法的步骤。
参数计算辅助方法如果以程序指令的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本公开的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件的形式体现出来，该计算机软件存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本公开各个实施例方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-only memory，ROM)、随机存取存储器(Random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使 得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (10)

  1. 一种参数计算辅助方法，其特征在于，所述方法包括：
    S1，接收集成电路器件的三维测试数据集，所述三维测试数据集中包括不同测试条件下对所述集成电路器件测试得到的有关电压、电流、电容的若干测试数据组；
    S2，响应于可视化界面中配置有用户自定义条件筛选项，用于对接收的所述三维测试数据集进行筛选分类后，构成多组自定义测试数据集；任选一组所述自定义测试数据集对所述集成电路器件的器件模型进行拟合时，根据其若干离散的所述测试数据组，在所述可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线；
    S3，响应于可视化界面中配置有用户选择规则编辑框，用于输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法；基于所述用户选择规则编辑框中配置有所述选择操作算法，在进行所述可视化界面中拟合曲线的选择操作时，选择区域内选中适配于所述选择操作规则的所述数据点位，用于计算所述器件模型的参数。
  2. 如权利要求1所述的参数计算辅助方法，其特征在于，所述选择操作算法中采用多个过滤器进行参数变量的过滤处理。
  3. 如权利要求2所述的参数计算辅助方法，其特征在于，所述选择操作算法中采用自定义过滤器代码，其包括：
    <graph description>
    (g(<filter condition>[，prop][，<prop>＝<value>]…)，[，prop][，<prop>＝<value>]…)，
    x(<filter condition>[，prop][，<prop>＝<value>]…)，
    p(<filter condition>[，prop][，<prop>＝<value>]…)。
  4. 如权利要求3所述的参数计算辅助方法，其特征在于，所述选择操作 算法中支持用户自定义变量设置过滤条件。
  5. 如权利要求3所述的参数计算辅助方法，其特征在于，通过g、x、p轴内的过滤条件支持表达式运算、四则运算、逻辑运算。
  6. 如权利要求1所述的参数计算辅助方法，其特征在于，在所述步骤S2的所述可视化界面中还配置有均衡器，用于调节当前所述自定义测试数据集中的所述测试数据组，使其将当前绘制出的实际拟合曲线的形状向所述可视化界面中已绘制的目标曲线靠拢。
  7. 如权利要求1所述的参数计算辅助方法，其特征在于，在所述步骤S2中关于电压-电流-电容的拟合曲线可以是电流-电压曲线、电容-电压曲线、电流-电容曲线中的一种或多种。
  8. 一种参数计算辅助系统，其特征在于，所述系统包括：
    数据接收模块，配置为接收集成电路器件的三维测试数据集，所述三维测试数据集中包括不同测试条件下对所述集成电路器件测试得到的有关电压、电流、电容的若干测试数据组；
    曲线绘制模块，配置为响应于可视化界面中配置有用户自定义条件筛选项，用于对接收的所述三维测试数据集进行筛选分类后，构成多组自定义测试数据集；任选一组所述自定义测试数据集对所述集成电路器件的器件模型进行拟合时，根据其若干离散的所述测试数据组，在所述可视化界面中以数据点位的形式绘制出关于电压-电流-电容的拟合曲线；
    参数选取模块，配置为响应于可视化界面中配置有用户选择规则编辑框，用于输入所述可视化界面中对所述拟合曲线进行参数选择所需的选择操作算法；基于所述用户选择规则编辑框中预先配置的所述选择操作算法，在进行所述可视化界面中拟合曲线的选择操作时，选择区域内选中适配于所述选择操作规则的所述数据点位，作为所述器件模型的参数。
  9. 一种电子设备，其特征在于，包括存储器和处理器，所述存储器中存储有指令，所述存储器和所述处理器通过线路互连；所述处理器调用所述存储器中的所述指令，实现如权利要求1-7中任意一项所述的参数计算辅助方法。
  10. 一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1-7中任意一项所述的参数计算辅助方法。
PCT/CN2022/142569 2022-09-22 2022-12-28 参数计算辅助方法、系统、设备及存储介质 WO2024060454A1 (zh)

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