CN114519330B

CN114519330B - A method, apparatus, storage medium, and terminal device for adjusting an integrated circuit.

Info

Publication number: CN114519330B
Application number: CN202011309096.1A
Authority: CN
Inventors: 林智远; 唐振宇; 唐延民
Original assignee: TCL Technology Group Co Ltd
Current assignee: TCL Technology Group Co Ltd
Priority date: 2020-11-19
Filing date: 2020-11-19
Publication date: 2025-12-05
Anticipated expiration: 2040-11-19
Also published as: CN114519330A

Abstract

This application discloses an adjustment method, apparatus, storage medium, and terminal device for integrated circuits. The method includes acquiring feature information corresponding to the integrated circuit, the feature information including position parameters corresponding to the circuit layout of the integrated circuit and photoelectric characteristic information corresponding to the integrated circuit; determining target position parameters corresponding to the integrated circuit based on the feature information; and determining the adjusted integrated circuit based on the target position parameters. In this way, the position parameters are automatically adjusted based on photoelectric characteristics to achieve automatic adjustment of the circuit layout, thereby improving the design efficiency of the circuit layout and thus improving the production efficiency of integrated circuits.

Description

Method and device for adjusting integrated circuit, storage medium and terminal equipment

Technical Field

The present application relates to the field of integrated circuits, and in particular, to a method and apparatus for adjusting an integrated circuit, a storage medium, and a terminal device.

Background

Electronic design automation (Electronic Design Automation, EDA) is widely used in the field of circuit design, by which the design of a circuit is made more efficient. However, in the field of TFT circuit design, professional operating software is generally required for drawing in the process of TFT layout design, which makes TFT circuit design depend on manpower greatly, and thus, production efficiency is low.

Disclosure of Invention

The application aims to solve the technical problem of providing an integrated circuit adjusting method, an integrated circuit adjusting device, a storage medium and terminal equipment aiming at the defects of the prior art.

In order to solve the above technical problem, a first aspect of an embodiment of the present application provides a method for adjusting an integrated circuit, where the method includes:

acquiring characteristic information corresponding to an integrated circuit, wherein the characteristic information comprises position parameters corresponding to a circuit layout of the integrated circuit and photoelectric characteristic information corresponding to the integrated circuit;

And determining a target position parameter corresponding to the integrated circuit based on the characteristic information, and determining an adjusted integrated circuit based on the target position parameter.

The method for acquiring the photoelectric characteristic, wherein the determining the target position parameter corresponding to the integrated circuit based on the characteristic information specifically comprises the following steps:

Acquiring a reference position parameter corresponding to the position parameter, wherein the dimension of the reference position parameter is lower than that of the position parameter;

determining an optimized position parameter corresponding to the reference position parameter based on the photoelectric characteristic and the reference position parameter, wherein the dimension of the optimized position parameter is equal to the dimension of the reference position parameter;

And determining a target position parameter corresponding to the position parameter based on the optimized position parameter.

The method for obtaining the photoelectric characteristic, wherein the determining, based on the photoelectric characteristic and the reference position parameter, the optimized position parameter corresponding to the reference position parameter specifically includes:

acquiring an objective function corresponding to the integrated circuit, and determining a target value corresponding to the photoelectric characteristic based on the objective function;

and optimizing the reference position parameters by adopting a Bayesian optimizer based on the target value to obtain optimized position parameters.

The method for obtaining the photoelectric characteristic, wherein the determining, based on the optimized position parameter, the target position parameter corresponding to the position parameter specifically includes:

and inputting the optimized position parameters into a trained third network model, and outputting target position parameters corresponding to the position parameters through the third network model.

The method for acquiring the photoelectric characteristics comprises the steps of detecting a network model, wherein the network model comprises a first network model and a second network model which are connected in cascade, an input item of the first network model is a first high-dimensional position parameter, an output item of the first network model is a first low-dimensional position parameter, an input item of the third network model is a second low-dimensional position parameter, an output item of the third network model is a second high-dimensional position parameter, the dimension of the first high-dimensional position parameter is equal to the dimension of the second high-dimensional position parameter, and the dimension of the first low-dimensional position parameter is equal to the dimension of the second low-dimensional position parameter.

The method for acquiring the photoelectric characteristic, wherein the training process of the third network model specifically comprises the following steps:

Inputting a first position parameter corresponding to each integrated circuit in a training sample into a trained first network model, and outputting a second position parameter through the first network model, wherein the first network model and the second network model are jointly trained;

inputting the second position parameter into a preset network model, and outputting a third position parameter through the preset network model;

and training the preset network model based on the first position parameter and the third position parameter to obtain a third network model.

The method for acquiring the photoelectric characteristic, wherein after determining the target position parameter corresponding to the integrated circuit based on the characteristic information and determining the adjusted integrated circuit based on the target position parameter, further comprises:

And acquiring the target photoelectric characteristic corresponding to the target position parameter, and storing a circuit parameter formed by the target position parameter and the target photoelectric characteristic.

The method for acquiring the photoelectric characteristic, wherein after the target photoelectric characteristic corresponding to the target position parameter is acquired and the circuit parameter formed by the target position parameter and the target photoelectric characteristic is stored, the method further comprises:

selecting a target circuit parameter corresponding to the expected photoelectric characteristic from a plurality of pre-stored circuit parameters based on the preset expected photoelectric characteristic;

And determining the integrated circuit corresponding to the expected photoelectric characteristic based on the target position parameter in the target circuit parameters.

The method for acquiring the photoelectric characteristic, wherein selecting the target circuit parameter corresponding to the expected photoelectric characteristic from a plurality of pre-stored circuit parameters based on the preset expected photoelectric characteristic specifically comprises:

Acquiring a weight coefficient set corresponding to the expected photoelectric characteristic, wherein the weight coefficient set comprises weight coefficients corresponding to all photoelectric parameters in the expected photoelectric characteristic;

and selecting a target circuit parameter from the plurality of circuit parameters based on the expected photoelectric characteristic and the weight coefficient set.

The method for acquiring the photoelectric characteristics comprises the step of storing a plurality of pre-stored circuit parameters in a KD tree form.

The method for obtaining the photoelectric characteristic, wherein selecting the target circuit parameter from the plurality of circuit parameters based on the expected photoelectric characteristic and the weight coefficient set specifically includes:

And performing KD tree search on a plurality of circuit parameters based on the expected photoelectric characteristic to obtain a target circuit parameter corresponding to the expected photoelectric characteristic, wherein the searching range of the node photoelectric characteristic in the backtracking process of the KD tree search is determined based on the node photoelectric characteristic, the expected photoelectric characteristic and the weight coefficient set.

The method for acquiring the photoelectric characteristic comprises the step of acquiring the photoelectric characteristic, wherein the integrated circuit is a TFT circuit.

A second aspect of an embodiment of the present application provides an adjusting apparatus for an integrated circuit, the adjusting apparatus including:

The first acquisition module is used for acquiring characteristic information corresponding to the integrated circuit, wherein the characteristic information comprises position parameters corresponding to a circuit layout of the integrated circuit and photoelectric characteristic information corresponding to the integrated circuit;

and the first determining module is used for determining a target position parameter corresponding to the integrated circuit based on the characteristic information and determining the adjusted integrated circuit based on the target position parameter.

A third aspect of the embodiments of the present application provides a computer-readable storage medium storing one or more programs executable by one or more processors to implement steps in a method of tuning an integrated circuit as described in any one of the above.

A fourth aspect of the embodiment of the present application provides a terminal device, which includes a processor, a memory, and a communication bus, where the memory stores a computer readable program executable by the processor;

The communication bus realizes connection communication between the processor and the memory;

The processor, when executing the computer readable program, implements the steps in the method of tuning an integrated circuit as described in any one of the above.

Compared with the prior art, the method comprises the steps of obtaining characteristic information corresponding to an integrated circuit, wherein the characteristic information comprises position parameters corresponding to a circuit layout of the integrated circuit and photoelectric characteristic information corresponding to the integrated circuit, determining target position parameters corresponding to the integrated circuit based on the characteristic information, and determining the adjusted integrated circuit based on the target position parameters, so that the position parameters are automatically adjusted based on the photoelectric characteristics to realize automatic adjustment of the circuit layout, thereby improving the design efficiency of the circuit layout and improving the production efficiency of the integrated circuit.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without creative effort for a person of ordinary skill in the art.

Fig. 1 is a diagram illustrating an exemplary conventional method of adjusting an integrated circuit according to the present application.

Fig. 2 is a flowchart of an adjustment method of an integrated circuit according to the present application.

Fig. 3 is an exemplary diagram of a TFT circuit.

Fig. 4 is an exemplary diagram of a sub-pixel structure in a TFT circuit.

Fig. 5 is an exemplary diagram of the positional parameters of one component in the sub-pixel structure in the TFT circuit.

Fig. 6 is a diagram illustrating an exemplary process for adjusting a position parameter of an adjustment method for an integrated circuit according to the present application.

Fig. 7 is a diagram illustrating an exemplary process for obtaining a plurality of reference position parameters according to the method for adjusting an integrated circuit of the present application.

Fig. 8 is a diagram illustrating an exemplary process for adjusting a position parameter of an adjustment method for an integrated circuit according to the present application.

Fig. 9 is a diagram illustrating an exemplary process for obtaining a target photoelectric characteristic in the adjustment method of an integrated circuit according to the present application.

Fig. 10 is a diagram illustrating an exemplary process for obtaining a target photoelectric characteristic in the adjustment method of an integrated circuit according to the present application.

Fig. 11 is a schematic structural diagram of an adjusting device of an integrated circuit according to the present application.

Fig. 12 is a schematic structural diagram of a terminal device provided by the present application.

Detailed Description

The application provides an integrated circuit adjusting method, an integrated circuit adjusting device, a storage medium and a terminal device, and aims to make the purposes, the technical scheme and the effects of the application clearer and more definite. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.

It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. It should be understood that the sequence number and the size of each step in this embodiment do not mean the sequence of execution, and the execution sequence of each process is determined by the function and the internal logic of each process, and should not be construed as limiting the implementation process of the embodiment of the present application.

The inventors have found that electronic design automation (Electronic Design Automation, EDA) is widely used in the field of circuit design, by which the design of a circuit is made more efficient. However, as shown in fig. 1, in the field of TFT circuit design, professional operating software is generally required for drawing in the process of TFT layout design, which makes the TFT circuit design depend on manpower greatly, thus resulting in low production efficiency.

In order to solve the above problems, in the embodiment of the present application, feature information corresponding to an integrated circuit is acquired, a target position parameter corresponding to the integrated circuit is determined based on the feature information, and an adjusted integrated circuit is determined based on the target position parameter, so that the position parameter is automatically adjusted based on the photoelectric characteristic, and the circuit layout is automatically adjusted, thereby improving the design efficiency of the circuit layout, and improving the production efficiency of the integrated circuit.

By way of example, the embodiments of the present application may be applied to a scenario in which a circuit layout of a TFT circuit is designed by a terminal device. In the scene, the terminal equipment can determine a TFT circuit to be designed and acquire a circuit layout corresponding to the TFT circuit, determine a position parameter corresponding to the integrated circuit based on the circuit layout after acquiring the circuit layout, determine photoelectric characteristics corresponding to the integrated circuit based on a trained detection network model and the position parameter to obtain characteristic information corresponding to the integrated circuit, determine an adjustment parameter corresponding to the position parameter based on the characteristic information, determine a target position parameter corresponding to the integrated circuit based on the characteristic information, and determine the adjusted integrated circuit based on the target position parameter.

It will be appreciated that in the above application scenario, although the actions of the embodiments of the present application are described as being performed entirely by the terminal device, these actions may also be performed partly by the terminal device and partly by a server to which the terminal device is connected. For example, after the terminal device obtains the circuit layout corresponding to the integrated circuit, the circuit layout is input into the server, so that the server obtains the circuit layout. The server can respond to the input circuit layout of the terminal equipment, determine the position parameters corresponding to the integrated circuit based on the circuit layout, determine the photoelectric characteristics corresponding to the integrated circuit based on the trained detection network model and the position parameters to obtain the characteristic information corresponding to the integrated circuit, determine the target position parameters corresponding to the integrated circuit based on the characteristic information, and determine the adjusted integrated circuit based on the target position parameters. Accordingly, the present application is not limited to the execution subject, and the operations disclosed in the embodiments of the present application may be executed.

It should be noted that the above application scenario is only shown for the convenience of understanding the present application, and embodiments of the present application are not limited in this respect. Rather, embodiments of the application may be applied to any scenario where applicable.

The application will be further described by the description of embodiments with reference to the accompanying drawings.

The present embodiment provides a method for adjusting an integrated circuit, as shown in fig. 2 and fig. 8, the method includes:

s10, obtaining the characteristic information corresponding to the integrated circuit.

Specifically, the integrated circuit may be a chip integrated circuit, an integrated circuit of a display panel, or an integrated circuit of a pixel unit. In one implementation of this embodiment, the integrated circuit is a TFT circuit that is used to fabricate a TFT backplane. For example, as shown in fig. 3, the TFT circuit may include GOA (GATE DRIVER on Array) and several pixels, each of which includes three sub-pixel units, namely, an R pixel unit, a G pixel unit, and a B pixel unit, wherein, as shown in fig. 4, the sub-pixel units may include circuit elements including capacitors, TFT transistors, light emitting diodes, etc., and connection lines including scan lines, data lines, etc.

The characteristic information comprises a position parameter corresponding to a circuit layout of the integrated circuit and a photoelectric characteristic corresponding to the integrated circuit. The position parameter is parameterized representation of the circuit layout, and the relative position relation among components included in the circuit layout, the position information of the components in the circuit layout and the like can be determined through the position parameter. In other words, the position parameter is a parameter vector for representing the circuit layout, and the circuit layout can be drawn based on the position parameter. The photoelectric characteristic is used for reflecting the photoelectric property of the driving circuit corresponding to the circuit layout, wherein the photoelectric characteristic can comprise an opening ratio, a charging rate, a maximum voltage and the like.

The circuit layout is used for mapping the circuit design of the integrated circuit to a physical description level, so that the integrated circuit can be mapped to a wafer for production, wherein the circuit layout contains relevant physical information such as component types, component sizes, relative positions among components, connection relations among various components and the like in the integrated circuit. The circuit layout of the integrated circuit can be automatically generated in advance or manually designed by a layout designer. In one implementation manner of the embodiment, the circuit layout is automatically generated, and the generating process may be that an integrated circuit to be designed is determined, a plurality of components corresponding to the integrated circuit and relative position relations among the components are obtained, and the circuit layout of the integrated circuit is generated based on the relative position relations.

In an implementation manner of this embodiment, the location parameter may be obtained in advance and stored in a local area of the terminal device, or the external device sends the location parameter to the terminal device, or the location parameter is obtained by the cloud end, or the location parameter is determined by the terminal device based on a circuit layout corresponding to the integrated circuit. In one implementation manner of this embodiment, the feature information is determined by the terminal device based on a circuit layout corresponding to the integrated circuit, and the acquiring the feature information corresponding to the integrated circuit specifically includes:

a10, acquiring a circuit layout corresponding to the integrated circuit.

A20, identifying the area information of the components in the circuit layout.

A30, determining a position parameter of the circuit layout based on the acquired region information;

A40, determining photoelectric characteristics corresponding to the integrated circuit based on the position information so as to obtain characteristic information corresponding to the integrated circuit.

Specifically, the component is a component for forming the circuit layout, wherein the component can comprise a metal layer, a TFT transistor, a capacitor, an ITO film and the like. The region information is used for positioning the component, and the position region of the component in the circuit layout and the component type of the component can be determined through the region information. It can be understood that the area information includes positioning information, size information and category information of the component, the positioning information is used for reflecting a position of the component in the circuit layout, the size information is used for reflecting a size of the component, and the category information is used for reflecting a device category of the component. For example, the size information is the height and width of the identification area corresponding to the component, and the position information is the distance between the center of the identification area corresponding to the component and the center of the image of the panel image. Of course, in practical applications, the location information may also be determined in other manners, for example, a distance from a center point of the identification area corresponding to the component to an upper left corner of the panel image, a distance from an upper left corner of the identification area corresponding to the component to an upper left corner of the panel image, and so on. The size information may be determined in other manners, for example, a perimeter of an identification area corresponding to the component, an area of the identification area corresponding to the component, and the like.

Based on this, in one implementation of the present embodiment, the area information may take the form of a circuit parameter, where the circuit parameter includes three data items, that is, positioning information, size information, and category information, respectively. For example, the area information is { (100 ), (20, 30), capacitance }, (100 ) represents coordinate information of a positioning point in the component in a coordinate system corresponding to the circuit layout, 20 in (20, 30) may represent a width of a rectangular area corresponding to the component, 30 may represent a width of a rectangular area corresponding to the component, and capacitance represents a type of the component as capacitance. In addition, the rectangular region refers to the smallest rectangle containing the component. Of course, it should be noted that the rectangular area is only an example, and it may be a circle, an ellipse, a triangle, a regular pentagon, etc., and the representation forms of the size information are different when the shapes are different, and it is not explained here, only an example is explained, for example, when the component corresponds to a circular area, the area information may be a circular coordinate and a circular radius.

In one implementation manner of this embodiment, the identifying the area information of the component in the circuit layout specifically includes:

Inputting the circuit layout into a trained recognition network model;

and determining the area information of the components in the circuit layout through the identification network model.

Specifically, the recognition network model may be a pre-trained network model for recognizing area information of each component in the circuit layout. It can be understood that the recognition network model is a pre-trained network model, the input item of the recognition network model is a circuit layout, the output item of the recognition network model is area information, when one component is included in the circuit layout, the area information is one, when a plurality of components are included in the circuit layout, the area information is a plurality of, and the plurality of area information corresponds to the plurality of components one by one. For example, the circuit layout includes a component a and a component B, and the area information output by the recognition network model includes area information a and area information B, where the area information a corresponds to the component a and is used for positioning the component a, and the area information B corresponds to the component B and is used for positioning the component B.

In one implementation manner of this embodiment, the determining, based on the obtained region information, the location parameter of the circuit layout specifically includes:

For each component in the circuit layout, acquiring a reference component corresponding to the component;

determining a sub-position parameter corresponding to the component based on the region information of the component by taking the reference component as a reference;

and determining the position parameters of the circuit layout based on all the obtained sub-position parameters.

Specifically, the reference component is a reference object of the component, and is used for determining a relative positional relationship between the component and the reference component, for example, a distance between the component and the reference component, a distance between an edge of the component and an edge of the reference component, an inclination angle of the component relative to the reference component, and the like. The reference component may be determined based on the acquired area information corresponding to each component, or may be determined based on a preset component position relationship list, where the component position relationship list may store the position relationship between all components included in the circuit layout, for example, the circuit version includes component a and component B, where component a and component B in the component position relationship list are adjacent to each other.

In one implementation manner of the embodiment, the reference component is determined based on the acquired area information corresponding to each component, and the acquiring process specifically includes that after the area information corresponding to each component is acquired, candidate components located around the component are selected from all components based on the area information, and all the acquired candidate components are used as the reference component of the component. Therefore, the reference component corresponding to the component can be automatically determined according to the acquired region information, and the parameterization speed of the circuit layout can be improved.

In one implementation manner of the embodiment, the reference component is determined based on a preset component position relation list, and the determining process specifically includes selecting, for each component, each candidate component associated with the component in the component position relation list, and taking all the selected candidate components as the reference components corresponding to the component. Thus, the reference component is determined through the preset component position relation list, the problem of error of the reference component caused by error of the area information can be avoided, and the accuracy of the reference component can be improved.

The sub-position parameters are used for reflecting the size information of the component and the position information between the component and the reference component, and the size of the component, the distance between the component and the reference component and the like can be determined through the sub-position parameters. Therefore, the sub-position parameters are used for reflecting a plurality of attributes of the component, and the attributes comprise the size of the component, the distance between the component and the reference component and the like. Correspondingly, the sub-position parameters comprise a plurality of position parameter items, the plurality of position parameter items are in one-to-one correspondence with the plurality of attributes, and the value of each position parameter item is the attribute value of the corresponding attribute. The plurality of attributes are determined based on design rules of the circuit layout, such as line width rules, maximum (minimum) size limits, spacing rules, surrounding rules, overlapping rules and overlapping rules, wherein the line width rules are the minimum width of polygons in the layout, the maximum (minimum) size limits are the width or length of the polygons, the spacing rules are the minimum distance between the polygons, the surrounding rules are the minimum size of overlapping between one layer of lines and the other layer of lines and surrounding the lines, the overlapping rules are the minimum size of overlapping between the two layers, and the minimum area rules are used for guaranteeing the minimum layout area as far as possible on the premise of meeting the basic requirements.

Based on the above, after the reference component corresponding to the component is obtained, determining the position parameter item included in the sub-position parameter corresponding to the component according to the rule of the circuit layout, and sequentially calculating the parameter value corresponding to each position parameter item according to the region information to obtain the sub-position parameter corresponding to the component. For example, the integrated circuit is a TFT sub-pixel circuit, the capacitor in the TFT sub-pixel circuit is a rectangle with a cut angle, the reference component corresponding to the capacitor is a TFT and the bottom edge of the substrate, and then the sub-position parameters corresponding to the capacitor may include the length of the rectangle, the width of the matrix, the distance between the sub-position parameters and the bottom edge of the substrate, the distance between the sub-position parameters and the TFT, and the size of the cut angle area.

For example, as shown in fig. 5, a capacitor in the TFT sub-pixel circuit, where the capacitor corresponds to a sub-position parameter including 12 position parameter items, which are distances a, B, C, D, E, F, G, H, I, J, K, and L in the figure, respectively, then the capacitor corresponds to a sub-position parameter which may be expressed as (a, B, C, D, E, F, G, H, I, J, K, and L).

In one implementation manner of the embodiment, the sub-position parameters are sub-position vectors, and the determining the position parameters of the circuit layout based on all the acquired sub-position parameters specifically includes:

And splicing all the sub-position parameters to obtain the position parameters of the circuit layout.

Specifically, the position parameters are formed by splicing all the sub-position parameters, the dimension of the position parameters is equal to the sum of the dimensions of all the sub-position parameters, for example, the sub-position parameters corresponding to the circuit layout comprise a sub-position parameter A and a sub-position parameter B, the position parameter A is (A1, A2) and the sub-position parameter B is (B1, B2), and then the position parameters are (A1, A2, B1, B2). In addition, in order to determine components corresponding to each of the spliced position parameters, each of the position parameters may be configured with a component class of its corresponding component, where the component class may be used as an angular label of each of the sub-position parameters, may be used as a suffix of each of the sub-position parameters, may also be used as a prefix of each of the sub-position parameters, and the like.

In one implementation of this embodiment, the optoelectronic characteristics are determined based on a trained inspection network model. Correspondingly, determining the photoelectric characteristic corresponding to the integrated circuit based on the position information to obtain the characteristic information corresponding to the integrated circuit specifically as follows;

and inputting the position information into the detection network model, and outputting the photoelectric characteristic corresponding to the integrated circuit through the detection network model.

Specifically, the detection network model is trained in advance and is used for determining the photoelectric characteristics corresponding to the integrated circuit. It may be appreciated that the detection network model is configured to convert the location parameter into a photoelectric characteristic, and correspondingly, an input term of the detection network model is the location parameter, and an output term of the detection network model is the photoelectric characteristic, where the photoelectric characteristic may include an aperture ratio, a charging rate, RC, LCS, a voltage deviation Bestvcom, a feedthrough Feedthrough, a charging time, and the like.

In an implementation manner of this embodiment, the detection network model includes a first fully-connected module, a transformation module, and a second fully-connected module, and determining, based on the trained detection network model and the location parameter, the photoelectric characteristic corresponding to the integrated circuit specifically includes:

Inputting the position parameters into a first full-connection module, and outputting a first feature vector through the first full-connection module;

inputting the first feature vector into a transformation module, and outputting a second feature vector through the transformation module, wherein the dimension of the first feature vector is equal to the dimension of the second feature vector;

and inputting the second characteristic vector into a second full-connection module, and outputting the photoelectric characteristic corresponding to the integrated circuit through the second full-connection module.

Specifically, the first full-connection module is used for performing linear transformation on a position parameter so as to reduce the dimension of the position parameter. The first feature vector is a low-dimensional vector obtained by linear transformation of a position parameter through a first full-connection module, and correspondingly, the vector dimension of the first feature vector is smaller than the vector dimension of the position parameter, wherein the value range of the vector dimension of the position parameter can be 50-500, and the value range of the vector dimension of the first feature vector can be 5-500. In a specific implementation manner, the value range of the vector dimension of the position parameter may be 50-100, the value range of the vector dimension of the first feature vector may be 5-50, for example, the vector dimension of the position parameter is 100, the vector dimension of the first feature vector is 50, and so on.

The transformation module is configured to transform the first feature vector into a second feature vector, and the vector dimension of the second feature vector is equal to the vector dimension of the first feature vector, e.g., the vector dimension of the first feature vector is 50, then the vector dimension of the second feature vector is 50. In one implementation of this embodiment, the transformation module may use a sigmoid function, a tanh function, and so on. The output term of the second fully-connected layer is a photoelectric characteristic, and the dimension of the output term of the second fully-connected layer may be determined according to a characteristic term included in the photoelectric characteristic obtained according to practical application requirements, for example, the photoelectric characteristic includes an aperture ratio, a charging rate, RC, LCS, a voltage deviation Bestvcom, a feed-through Feedthrough, and a charging time, and then the dimension of the output term of the second fully-connected layer is 7.

In an implementation manner of this embodiment, the detection network model may include two cascaded network models, which are a first network model and a second network model, where the first network model is used to reduce a dimension of the location parameter, and the second network model is used to determine a photoelectric characteristic corresponding to the location parameter. Correspondingly, the determining the photoelectric characteristic corresponding to the integrated circuit based on the trained detection network model and the position parameter specifically comprises the following steps:

inputting the position parameters into a first network model, and outputting candidate position parameters through the first network model;

And inputting the candidate position parameters into the second network model, and outputting the photoelectric characteristics corresponding to the integrated circuit through the second network model.

Specifically, the candidate location parameter is an output term of the first network model, the input term of the second network model is a candidate location parameter, and the output term is a photoelectric characteristic. The first network model is used for reducing the dimension of the position parameter to obtain a candidate position parameter after the dimension reduction, and correspondingly, the vector dimension of the candidate position parameter is smaller than the vector dimension of the position parameter, wherein the value range of the vector dimension of the position parameter can be 50-500, and the value range of the vector dimension of the candidate position parameter can be 5-500. In a specific implementation manner, the value range of the vector dimension of the position parameter may be 50-100, the value range of the vector dimension of the candidate position parameter may be 5-50, for example, the vector dimension of the position parameter is 100, the vector dimension of the candidate position parameter is 50, and the like.

In one implementation manner of this embodiment, the first network model may include a third full-connection module and a nonlinear transformation module, the second network model may include a fourth full-connection module, the third full-connection module is configured to perform linear transformation on the location parameter to perform dimension reduction on the location parameter, the third full-connection module is connected with the nonlinear transformation module, an output term of the third full-connection module is an input term of the nonlinear transformation module, an output term of the nonlinear transformation module is a candidate location parameter, and a vector dimension of the candidate location parameter is equal to a vector dimension of the output term of the third full-connection module, for example, a vector dimension of the output term of the third full-connection module is 50, and then the vector dimension of the candidate location parameter is 50. In one implementation manner of this embodiment, the nonlinear transformation module may use a sigmoid function, a tanh function, and the like.

In one implementation manner of this embodiment, the second network model includes a fourth fully-connected module, and the dimension of the output term of the fourth fully-connected module may be determined according to the characteristic term included in the photoelectric characteristic obtained by the actual application requirement, for example, the photoelectric characteristic includes an aperture ratio, a charging rate, RC, LCS, a voltage deviation Bestvcom, a feedthrough Feedthrough, and a charging time, and then the dimension of the output term of the second fully-connected layer is 7.

In one implementation manner of this embodiment, the training process of the detection network model specifically includes:

acquiring a training sample set;

Inputting training position parameters in the training sample set into a preset network model, and outputting predicted photoelectric characteristics corresponding to the training position parameters through the preset network model;

and training the preset network model based on the predicted photoelectric characteristic and the target photoelectric characteristic to obtain the detection network model.

The detection network model is obtained by training the preset network model by adopting a training sample set and is used for determining the photoelectric characteristic corresponding to the position parameter. It can be understood that after the preset network model is trained based on the training sample set, a detection network model can be obtained, wherein the model structure of the detection network model is the same as that of the preset network model, and the difference between the detection network model and the preset network model is that the model parameters configured by the detection network model are model parameters obtained through training, and the model parameters configured by the preset network model are initial model parameters.

In one implementation manner of this embodiment, the training sample set includes a plurality of training position parameters and target photoelectric characteristics corresponding to each training position parameter, where each training position parameter in the plurality of training position parameters corresponds to a circuit layout, and the target photoelectric characteristic corresponding to the training position parameter is a photoelectric characteristic of an integrated circuit corresponding to the circuit layout. The target photoelectric characteristic is used as a labeling value of a training position parameter corresponding to the target photoelectric characteristic, and after the predicted photoelectric characteristic corresponding to the training position parameter is determined through the preset network model, a loss value corresponding to the predicted photoelectric characteristic is determined by taking the target photoelectric characteristic as a standard, so that the preset network model is reversely trained based on the loss value, and the model parameters of the preset network model are optimized.

acquiring a training integrated circuit set;

For each training integrated circuit, determining a training position parameter corresponding to a circuit layout of the training integrated circuit, and determining a target photoelectric characteristic corresponding to the training integrated circuit through a circuit simulator;

and determining a training sample set based on the training position parameters and the target photoelectric characteristics corresponding to each training integrated circuit.

In particular, the training integrated circuit set may include a number of training integrated circuits, each of the number of training integrated circuits being pre-designed and tested. Each of the plurality of training integrated circuits corresponds to a training position parameter, wherein the determining process of the training position parameter may refer to the determining process of the position parameter, and will not be described herein. In addition, the target photoelectric characteristic is determined based on a circuit simulator, and the determination process can be that for each training integrated circuit, a circuit layout corresponding to the training integrated circuit is obtained, and the target photoelectric characteristic corresponding to the training integrated circuit is output through the circuit simulator.

Further, after the training position parameter and the target photoelectric characteristic corresponding to the training integrated circuit are obtained, the training position parameter and the target photoelectric characteristic are used as a circuit parameter. The plurality of training integrated circuits may determine a plurality of sets of circuit parameters, each set of circuit parameters including a training position parameter and a target optoelectronic characteristic. Therefore, after a plurality of groups of circuit parameters corresponding to a plurality of training integrated circuits are obtained, a set formed by the plurality of groups of circuit parameters corresponding to the plurality of training integrated circuits can be used as a training sample set of a preset network model.

S20, determining a target position parameter corresponding to the integrated circuit based on the characteristic information, and determining the adjusted integrated circuit based on the target position parameter.

Specifically, the target position parameter is an adjusted position parameter corresponding to the position parameter, and the vector dimension of the target position parameter is the same as the vector dimension of the position parameter, for example, the vector dimension of the position parameter is 100, and then the vector dimension of the target position parameter is 100. In addition, after the target position parameter is determined, a circuit layout can be determined based on the target position parameter, and an integrated circuit can be processed based on the circuit layout.

In an implementation manner of this embodiment, the determining, based on the feature information, the target location parameter corresponding to the integrated circuit specifically includes:

acquiring a reference position parameter corresponding to the position parameter;

Determining an optimized position parameter corresponding to the reference position parameter based on the photoelectric characteristic and the reference position parameter;

Specifically, the vector dimension of the reference position parameter is smaller than the vector dimension of the position parameter, and the reference position parameter is obtained by performing dimension reduction transformation on the position parameter. In this embodiment, the reference location parameter may be determined by the above-mentioned detection network model, and when the detection network model includes a first network model and a second network model, the reference location parameter is an output term of the first network model, and when the detection network model includes a first fully-connected module, a transformation module, and a second fully-connected module, the reference location parameter is an output term of the transformation module.

In one implementation manner of this embodiment, the determining, based on the photoelectric characteristic and the reference position parameter, an optimized position parameter corresponding to the reference position parameter specifically includes:

Specifically, the vector dimension of the optimized position parameter is the same as the vector dimension of the reference position parameter, and the optimized position parameter is a position parameter with the highest probability so that the objective function is lifted. It will be appreciated that optimizing the position parameter may maximize the probability of determining that the error becomes small based on the objective function. The objective function is determined based on the photoelectric characteristic limiting condition corresponding to the integrated circuit, and the determining process of the objective function and the expression form of the objective function are the same as those of the objective function, and the description of the objective function can be specifically referred to below. The target value is determined by inputting the photoelectric characteristic into an objective function, wherein the objective function is an objective function having the photoelectric characteristic as an argument. After the target value is obtained, the Bayesian optimizer calculates an optimized position parameter with the maximum probability according to the target value and the reference position parameter and the target value so as to improve the objective function value. In this embodiment, a bayesian optimizer is used to perform gaussian regression optimization, and in other implementations, other optimizers may be used, such as genetic algorithms, annealing algorithms, and the like.

In an implementation manner of this embodiment, the determining, based on the optimized location parameter, a target location parameter corresponding to the location parameter specifically includes:

Specifically, the third network model is pre-trained and is used for carrying out dimension lifting on the optimized position parameter to obtain a target position parameter, wherein the vector dimension of the target position parameter is larger than that of the optimized position parameter, and the vector dimension of the target position parameter is equal to that of the position parameter. It can be appreciated that the dimension of the output term of the third network model is the same as the dimension of the input term of the detection model, when the detection network model includes the first fully connected module, the transformation module, and the second fully connected module, the dimension of the input term of the third network model is the same as the dimension of the output term of the transformation module, and when the detection network model includes the first network model and the second network model, the dimension of the input term of the third network model is the same as the dimension of the output term of the first network model.

The network model detection method comprises the steps of detecting a network model, wherein the network model detection method comprises a first network model and a second network model which are connected in cascade, an input item of the first network model is a first high-dimensional position parameter, an output item of the first network model is a first low-dimensional position parameter, an input item of the third network model is a second low-dimensional position parameter, an output item of the third network model is a second high-dimensional position parameter, the dimension of the first high-dimensional position parameter is equal to that of the second high-dimensional position parameter, and the dimension of the first low-dimensional position parameter is equal to that of the second low-dimensional position parameter.

In an implementation manner of this embodiment, the training process of the third network model specifically includes:

Specifically, the first network model is included in the detection network model, when the detection network model includes a first network model and a second network model, the first network model is the first network model in the detection network model, and when the detection network model includes a first fully-connected module, a transformation module and a second fully-connected module, the detection network model may be divided into the first network model and the second network model, where the first network model includes the first fully-connected module and the transformation module, and the second network model includes the second fully-connected module.

Further, the input item of the third network model is determined based on the first network model, and the input item of the third network model is the output item of the first network model, so that when the third network model is trained, a training sample corresponding to the third network model can be determined based on the trained first network model, the first network model and the third network model are combined to train the third network model, and the model coefficient of the first network model is kept unchanged in the process of training the third network model.

In one implementation of this embodiment, the third network model is obtained by combining the first network model and the third network model and training. In the training process, the first position parameter is an input item of the first network model, the second position parameter is an output item of the first network model, and is an input item of the third network model, and the third position parameter is an output item of the third network model, wherein the first position parameter is a target value corresponding to the third position parameter, so that a loss item can be determined based on the first position parameter and the third position parameter, and the third network model can be trained based on the loss item. Furthermore, the first network model is trained, which is based on a second network model of the detection network models, in other words, the first network model is obtained by training the detection network models.

In one embodiment, as shown in fig. 7, after the position parameter is adjusted to obtain a target position parameter, a target photoelectric characteristic corresponding to the target position parameter may be obtained, a target photoelectric characteristic corresponding to the target position parameter is obtained, and a circuit parameter formed by the target position parameter and the target photoelectric characteristic is stored. In addition, after the target photoelectric characteristic is obtained, the adjustment process can be further executed until the target photoelectric characteristic reaches a preset condition or the number of times of cyclic execution reaches a preset requirement. Therefore, a plurality of circuit parameters can be obtained, each circuit parameter in the plurality of circuit parameters comprises a position parameter and a photoelectric characteristic, wherein the position parameter corresponds to a circuit layout, and the photoelectric characteristic is the photoelectric characteristic corresponding to the circuit layout.

In summary, the embodiment provides an adjustment method of an integrated circuit, which includes obtaining feature information corresponding to the integrated circuit, determining an adjustment parameter corresponding to the position parameter based on the feature information, determining a target position parameter corresponding to the integrated circuit based on the feature information, and determining an adjusted integrated circuit based on the target position parameter, so that the position parameter is automatically adjusted based on the photoelectric characteristic, and the automatic adjustment of the circuit layout is realized, thereby improving the design efficiency of the circuit layout, and further improving the production efficiency of the integrated circuit.

In one embodiment, as shown in fig. 6, the method for adjusting an integrated circuit specifically includes:

Acquiring characteristic information corresponding to an integrated circuit, wherein the characteristic information comprises position parameters corresponding to a circuit layout of the integrated circuit and photoelectric characteristics corresponding to the integrated circuit;

Determining an adjustment parameter corresponding to the position parameter based on the characteristic information;

And adjusting the position parameter based on the adjustment parameter to obtain a target position parameter, and determining an adjusted integrated circuit based on the target position parameter. .

Specifically, the process of acquiring the feature information may refer to the description of the foregoing embodiments, which is not repeated herein, and mainly describes the process of determining, based on the photoelectric characteristic and the location parameter, a target location parameter corresponding to the location parameter, and determining, based on the target location parameter, an adjusted integrated circuit.

The adjusting parameter is used for adjusting the position parameter, and the position parameter can be adjusted through the adjusting parameter so as to obtain a target position parameter corresponding to the position parameter, wherein the target position parameter is used for determining a circuit layout of the integrated circuit. The vector dimension of the adjustment parameters is the same as the vector dimension of the position parameters, for each position parameter item in the position parameters, an adjustment parameter item corresponding to the position parameter item exists in the adjustment parameters, and the adjustment parameter item is used for adjusting the corresponding position parameter item, wherein the corresponding adjustment parameter item and the position parameter item refer to that the position serial number of the adjustment parameter item in the adjustment parameters is the same as the position serial number of the position parameter item in the position parameters. For example, the position parameter is a 50-dimensional vector, the adjustment parameter is a 50-dimensional vector, and the adjustment parameter at the 25 th position in the adjustment parameter corresponds to the position parameter at the 25 th position in the position parameter. In addition, the vector dimension of the target position parameter is the same as the vector dimension of the position parameter, each target position parameter item in the target position parameter corresponds to each position parameter item in the position parameter one by one, and each target position parameter item is calculated by the corresponding position parameter item and the corresponding adjustment parameter item of the position parameter item.

In an implementation manner of this embodiment, the determining, based on the photoelectric characteristic and the position parameter, an adjustment parameter corresponding to the position parameter specifically includes:

Obtaining an error value corresponding to the photoelectric characteristic;

based on the error value and the position parameter, determining an adjustment parameter corresponding to the position parameter

Specifically, the error value is used for reflecting the error of the photoelectric characteristic and the photoelectric characteristic limiting condition, wherein the photoelectric characteristic limiting condition corresponds to the integrated circuit and is used for limiting the minimum photoelectric characteristic requirement achieved by the integrated circuit. The photoelectric characteristic comprises a plurality of photoelectric parameters, and the photoelectric characteristic limiting condition comprises a lower threshold value corresponding to part of photoelectric parameters in the plurality of photoelectric parameters. For example, the photoelectric characteristic may include an aperture ratio, a charging rate, and a peak voltage, and the photoelectric characteristic limitation condition may include a lower threshold value of the aperture ratio, a lower threshold value of the charging rate, and a lower threshold value of the peak voltage, or the photoelectric characteristic limitation condition may include a lower threshold value of the charging rate and a lower threshold value of the peak voltage, or the photoelectric characteristic limitation condition may include a lower threshold value of the peak voltage. Of course, the photoelectric characteristic limiting condition may not include a lower threshold value of any photoelectric parameter, and the photoelectric characteristic limiting condition is that the larger each photoelectric parameter is, the better the reference position parameter corresponding to the reference photoelectric characteristic is, otherwise, the smaller each photoelectric parameter is, and the worse the reference position parameter corresponding to the reference photoelectric characteristic is.

In an implementation manner of this embodiment, the obtaining the error value corresponding to the photoelectric characteristic specifically includes:

Acquiring a photoelectric characteristic limiting condition corresponding to the integrated circuit, and determining an objective function corresponding to the integrated circuit based on the photoelectric characteristic limiting condition;

And determining the photoelectric characteristic corresponding error value based on the objective function.

Specifically, the objective function may be preset, and the objective function corresponds to a photoelectric characteristic limitation condition, and after determining the photoelectric characteristic limitation condition corresponding to the integrated circuit, the corresponding objective function may be selected according to the photoelectric characteristic limitation condition. It may be appreciated that, a set of objective functions is preset, where the set of objective functions includes a plurality of objective functions, each objective function in the plurality of objective functions corresponds to a photoelectric characteristic limitation condition, after determining the photoelectric characteristic limitation condition corresponding to the integrated circuit, one objective function may be selected from the set of objective functions based on the photoelectric characteristic limitation condition, and the objective function is used as an objective function for determining an error value corresponding to the photoelectric characteristic.

The objective functions in the objective function set may be established according to practical applications, and will be described herein with respect to an application scenario. In this application scenario, the photoelectric characteristics include three photoelectric parameters of an aperture ratio a, a charging rate b and a peak voltage c, and the correspondence between the objective function and the photoelectric characteristic limiting condition may be:

when the photoelectric characteristic limitation condition is that the aperture ratio a > a0, the charging ratio b > b0, and the peak voltage c > c0, wherein a0 is a lower threshold value of the aperture ratio, b0 is a lower threshold value of the charging ratio, and c0 is a lower threshold value of the peak voltage, the objective function f (a, b, c) may be:

f(a,b,c)=sigmoid(a-a0)*sigmoid(b-b0)*sigmoid(c-c0)

wherein a represents an aperture ratio, b represents a charging rate, c represents a peak voltage, and sigmoid represents a sigmoid function;

when the photoelectric characteristic limitation condition is that the charging rate b > b0 and the peak voltage c > c0, wherein b0 is the lower threshold of the charging rate and c0 is the lower threshold of the peak voltage, the objective function f (a, b, c) may be:

f(a,b,c)=(a-a0)*sigmoid(b-b0)*sigmoid(c-c0)

When the aperture ratio a, the charging ratio b and the peak voltage c in the photoelectric characteristic limitation condition do not set the lower threshold, the objective function f (a, b, c) may be:

f(a,b,c)=ka*(a-a0)+kb*(b-b0)+kc*(c-c0);

Wherein ka, kb, kc are weight coefficients, a0 is a lower threshold of aperture ratio, b0 is a lower threshold of charging ratio, and c0 is a lower threshold of peak voltage, wherein ka, kb, kc, a0, b0 and c0 can be set according to actual requirements.

Further, after the objective function is obtained, since the objective function is a function having the photoelectric characteristic as an argument, the objective function can be converted into a function having the position parameter as an argument. The photoelectric characteristic is determined based on the position parameter, a candidate function is arranged between the position parameter and the photoelectric characteristic, each photoelectric parameter in the photoelectric characteristic can be represented by the position parameter based on the candidate function, each photoelectric characteristic represented by the position parameter is substituted into the objective function to obtain a converted objective function, and the converted objective function is used as the objective function corresponding to the photoelectric characteristic. After the objective function taking the position parameter as the independent variable is obtained, the position parameter is input into the objective function, and the error value can be obtained. Naturally, in practical application, the photoelectric characteristic may be directly input as an objective function with the photoelectric characteristic as an argument, to obtain the error value.

In an implementation manner of this embodiment, the determining, based on the error value and the location parameter, an adjustment parameter corresponding to the location parameter specifically includes:

for each position parameter item in the position parameters, determining a gradient value corresponding to the position parameter item based on the error value and the objective function, and determining an adjustment parameter item corresponding to the position parameter item based on the gradient value;

all the obtained adjustment parameter items form the adjustment parameters corresponding to the position parameters.

Specifically, the gradient value is used for determining an adjustment parameter item corresponding to the position parameter item. In one implementation manner of the embodiment, the calculation formula of the gradient value may be dY/dxi=f (X1, X2, X3,..xi+. DELTA.xi,..Xn) -Y0, i=1, 2, 3..n, where dY/dXi represents the gradient value corresponding to the position parameter Xi, Y=f (X1, X2, X3,..xi,..Xn) is an objective function with the position parameter as an independent variable, xi is the ith position parameter in the position parameters, DELTA Xi is the variation corresponding to the position parameter Xi, n represents the number of the position parameter, and Y0 represents the error value. The variable quantity corresponding to each position parameter item can be the same, the variable quantity corresponding to part of position parameter items can be different, and the variable quantity corresponding to each position parameter item can be different, wherein the variable quantity can be preset according to the actual application condition.

The calculation formula of the adjustment parameter term may be:

Xi=Xi+gamma_i*(dY/dXi)*△Xi,i=1,2,3...n

wherein, delta Xi is the variable quantity corresponding to the position parameter item Xi, and gamma_i is the weight coefficient corresponding to the position parameter item Xi.

In one implementation manner, the adjusting the location parameter based on the adjustment parameter specifically includes:

for each position parameter item in the position parameters, determining an adjustment parameter item corresponding to the position parameter item in the adjustment parameters;

determining the element sum of the position parameter item and the adjustment parameter item, and taking the element sum as a target position parameter item corresponding to the position parameter item;

and taking the position parameters formed by all the target position parameter items as target position parameters.

Specifically, the vector dimension of the adjustment parameter is the same as the vector dimension of the position parameter, and the adjustment parameter items in the adjustment parameter are in one-to-one correspondence with the position parameter items in the position parameter, so that for each position parameter item, the corresponding adjustment parameter item can be determined, and after the adjustment parameter item is determined, the element sum of the position parameter item and the adjustment parameter item is calculated, so as to obtain an adjusted position parameter item, namely a target position parameter item corresponding to the position parameter item. Based on the above, after the target position parameter items corresponding to all the position parameter items are obtained, the position parameters formed by all the target position parameter items can be used as the target position parameters.

In one embodiment, after several circuit parameters are obtained, the circuit parameters may be saved to form a circuit parameter set. After the expected photoelectric characteristic is obtained, a target circuit parameter can be selected from a circuit parameter set based on the expected photoelectric characteristic, and a circuit layout corresponding to a position parameter in the target circuit parameter is used as a circuit layout corresponding to the expected photoelectric characteristic, so that the obtaining speed of the circuit layout can be improved.

Based on this, after acquiring the circuit parameter set, as shown in fig. 9 and 10, the method may further include:

Specifically, each of the plurality of circuit parameters includes a position parameter and a photoelectric characteristic, wherein the position parameter corresponds to a circuit layout, and the photoelectric characteristic is a photoelectric characteristic corresponding to the circuit layout. It will be appreciated that the position parameter and the photoelectric characteristic correspond to the same circuit layout, the position parameter is obtained by parameterizing the circuit layout, and the photoelectric characteristic is determined based on the position parameter or determined by a circuit simulator.

The target circuit parameter is included in the plurality of circuit parameters, and the matching degree of the target photoelectric characteristic in the plurality of circuit parameters with the expected photoelectric characteristic is highest, wherein the matching degree is used for reflecting the similarity degree of the target photoelectric characteristic and the expected photoelectric characteristic, and when the matching degree is higher, the similarity degree of the target photoelectric characteristic and the expected photoelectric characteristic is higher, otherwise, when the matching degree is lower, the similarity degree of the target photoelectric characteristic and the expected photoelectric characteristic is lower.

The matching degree may be a euclidean distance between the photoelectric characteristic and the expected photoelectric characteristic, or a weight coefficient may be configured for each photoelectric parameter in the photoelectric characteristic, and when determining the matching degree, the matching degree between the photoelectric characteristic and the expected photoelectric characteristic may be obtained by updating each photoelectric parameter based on the weight coefficient of each photoelectric parameter (for example, taking the product of the photoelectric parameter and the weight coefficient as the photoelectric parameter, etc.), and based on the euclidean distance between the updated photoelectric characteristic and the expected photoelectric characteristic.

In an implementation manner of this embodiment, the selecting, based on a preset desired photoelectric characteristic, a target circuit parameter corresponding to the desired photoelectric characteristic from a plurality of pre-stored circuit parameters specifically includes:

Specifically, the weight coefficient set includes a plurality of weight coefficients, the plurality of weight coefficients are in one-to-one correspondence with a plurality of photoelectric parameters included in the photoelectric characteristic, each weight coefficient is used for reflecting the importance degree of the corresponding photoelectric parameter, and the higher the weight coefficient is, the higher the importance degree of the photoelectric parameter is, otherwise, the lower the weight coefficient is, the lower the importance degree of the photoelectric parameter is. The weight coefficient sets may be preset, and the weight coefficient sets corresponding to different desired photoelectric characteristics are different.

In one implementation manner of this embodiment, after the weight coefficient set is obtained, when the target photoelectric characteristic corresponding to the desired photoelectric characteristic is determined based on the weight coefficient set, the matching degree between the photoelectric characteristic and the desired photoelectric characteristic in each of the circuit parameters may be calculated, and the circuit parameter corresponding to the photoelectric characteristic with the highest matching degree may be selected as the target circuit parameter.

In one implementation manner of this embodiment, a plurality of circuit parameters are stored in a KD tree form, and when a weight coefficient set is obtained and a target photoelectric characteristic corresponding to a desired photoelectric characteristic is determined based on the weight coefficient set, a KD tree search may be used to determine the target circuit parameters, so that the speed of obtaining the target circuit parameters may be improved. Correspondingly, the selecting the target circuit parameter from the plurality of circuit parameters based on the expected photoelectric characteristic and the weight coefficient set specifically includes:

Specifically, after obtaining the desired photoelectric characteristic, searching a plurality of circuit parameters in a KD tree search mode to obtain candidate circuit parameters. The KD tree searching process can compare the expected photoelectric characteristic with the value of the splitting dimension of the reference photoelectric characteristic in the circuit parameters of the splitting node, and the expected photoelectric characteristic is smaller than the reference photoelectric characteristic, and then enters the left sub-tree branch, if the expected photoelectric characteristic is equal to or larger than the reference photoelectric characteristic, then enters the right sub-tree branch, and then the method is performed by analogy until reaching the leaf node, and the circuit parameters corresponding to the leaf node are used as candidate circuit parameters. And searching for a leaf node in the same subspace as the candidate circuit parameter after determining the candidate circuit parameter, wherein the candidate circuit parameter is used as a query circuit parameter when searching for the leaf node in the same subspace as the candidate circuit parameter, and the photoelectric characteristic in the candidate circuit parameter is a node photoelectric characteristic and is determined based on the node photoelectric characteristic, the expected photoelectric characteristic and the searching radius determined by the weight coefficient set. For example, the radius searching process may be that the photoelectric parameters in the expected photoelectric characteristics are multiplied by the corresponding weight coefficients to update the photoelectric parameters, then the euclidean distance between the expected photoelectric characteristics and the node photoelectric characteristics is calculated, and finally the calculated euclidean distance is used as the radius searching process.

Further, after searching for a leaf node in the same subspace as the point to be searched, tracing back a search path, judging whether data points with the distance from the expected photoelectric characteristic smaller than the search radius exist in other sub-node spaces of the nodes on the search path, if so, jumping to the other sub-node spaces to search for the data points with the distance from the expected photoelectric characteristic smaller than the search radius exist, adding the other sub-nodes to the search path, and continuously executing the judgment of whether the data points with the distance from the expected photoelectric characteristic smaller than the search radius exist in the other sub-node spaces of the nodes on the search path until the search path is empty, so as to obtain the target circuit parameters corresponding to the expected photoelectric characteristic.

Based on the above-mentioned method for adjusting an integrated circuit, this embodiment provides an adjusting device for an integrated circuit, as shown in fig. 11, which includes:

The first obtaining module 100 is configured to obtain feature information corresponding to an integrated circuit, where the feature information includes a location parameter corresponding to a circuit layout of the integrated circuit and photoelectric characteristic information corresponding to the integrated circuit;

the first determining module 200 is configured to determine a target location parameter corresponding to the integrated circuit based on the feature information, and determine an adjusted integrated circuit based on the target location parameter.

In one implementation, the second determining module specifically includes:

The first acquisition unit is used for acquiring a reference position parameter corresponding to the position parameter, wherein the dimension of the reference position parameter is lower than that of the position parameter;

The first determining unit is used for determining an optimized position parameter corresponding to the reference position parameter based on the photoelectric characteristic and the reference position parameter, wherein the dimension of the optimized position parameter is equal to the dimension of the reference position parameter;

In one implementation manner, the first determining unit specifically includes:

The first acquisition subunit is used for acquiring an objective function corresponding to the integrated circuit and determining a target value corresponding to the photoelectric characteristic based on the objective function;

And the optimizing subunit is used for optimizing the reference position parameters by adopting a Bayesian optimizer based on the target value so as to obtain optimized position parameters.

In one implementation, the optimizing subunit is specifically configured to input the optimized location parameter into a trained third network model, and output, through the third network model, a target location parameter corresponding to the location parameter.

In one implementation, the detection network model comprises a first network model and a second network model which are cascaded, wherein an input item of the first network model is a first high-dimensional position parameter, an output item of the first network model is a first low-dimensional position parameter, an input item of the third network model is a second low-dimensional position parameter, an output item of the third network model is a second high-dimensional position parameter, the dimension of the first high-dimensional position parameter is equal to that of the second high-dimensional position parameter, and the dimension of the first low-dimensional position parameter is equal to that of the second low-dimensional position parameter.

In one implementation, the training process of the third network model specifically includes:

In one implementation, the adjusting device of the integrated circuit includes:

and the second acquisition module is used for acquiring the target photoelectric characteristic corresponding to the target position parameter and storing the circuit parameter formed by the target position parameter and the target photoelectric characteristic.

In one implementation, the adjusting device of the integrated circuit includes:

The second determining module is used for selecting target circuit parameters corresponding to the expected photoelectric characteristics from a plurality of pre-stored circuit parameters based on the preset expected photoelectric characteristics;

and the third determining module is used for determining the integrated circuit corresponding to the expected photoelectric characteristic based on the target position parameter in the target circuit parameters.

In one implementation, the second determining module specifically includes:

A second obtaining unit, configured to obtain a set of weight coefficients corresponding to the desired photoelectric characteristic, where the set of weight coefficients includes weight coefficients corresponding to each photoelectric parameter in the desired photoelectric characteristic;

And the selecting unit is used for selecting a target circuit parameter from the plurality of circuit parameters based on the expected photoelectric characteristic and the weight coefficient set.

In one implementation, the pre-stored circuit parameters are stored in a KD tree form.

In one implementation mode, the selecting unit is specifically configured to perform KD tree search on a plurality of circuit parameters based on the expected photoelectric characteristic to obtain a target circuit parameter corresponding to the expected photoelectric characteristic, where a search range of the node photoelectric characteristic in the backtracking process of the KD tree search is determined based on the node photoelectric characteristic, the expected photoelectric characteristic and the weight coefficient set.

In one implementation, the integrated circuit is a TFT circuit.

Based on the above-described method for adjusting an integrated circuit, the present embodiment provides a computer-readable storage medium storing one or more programs executable by one or more processors to implement the steps in the method for adjusting an integrated circuit as described in the above-described embodiment.

Based on the above-mentioned method for adjusting an integrated circuit, the present application further provides a terminal device, as shown in fig. 12, which includes at least one processor (processor) 20, a display 21, a memory 22, and may further include a communication interface (Communications Interface) 23 and a bus 24. Wherein the processor 20, the display 21, the memory 22 and the communication interface 23 may communicate with each other via a bus 24. The display screen 21 is configured to display a user guidance interface preset in the initial setting mode. The communication interface 23 may transmit information. The processor 20 may invoke logic instructions in the memory 22 to perform the methods of the embodiments described above.

Further, the logic instructions in the memory 22 described above may be implemented in the form of software functional units and stored in a computer readable storage medium when sold or used as a stand alone product.

The memory 22, as a computer readable storage medium, may be configured to store a software program, a computer executable program, such as program instructions or modules corresponding to the methods in the embodiments of the present disclosure. The processor 20 performs functional applications and data processing, i.e. implements the methods of the embodiments described above, by running software programs, instructions or modules stored in the memory 22.

The memory 22 may include a storage program area that may store an operating system, application programs required for at least one function, and a storage data area that may store data created according to the use of the terminal device, etc. In addition, the memory 22 may include high-speed random access memory, and may also include nonvolatile memory. For example, a plurality of media capable of storing program codes such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or a transitory storage medium may be used.

In addition, the specific processes that the storage medium and the plurality of instruction processors in the terminal device load and execute are described in detail in the above method, and are not stated here.

It should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application, and not for limiting the same, and although the present application has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that the technical solution described in the above-mentioned embodiments may be modified or some technical features may be equivalently replaced, and these modifications or substitutions do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present application.

Claims

1. A method of tuning an integrated circuit, the method comprising:

Determining a target position parameter corresponding to the integrated circuit based on the characteristic information, and determining an adjusted integrated circuit based on the target position parameter;

the obtaining the feature information corresponding to the integrated circuit includes:

acquiring a circuit layout, and determining a position parameter corresponding to the integrated circuit based on the circuit layout;

Determining photoelectric characteristics corresponding to the integrated circuit based on the trained detection network model and the position parameter to obtain characteristic information corresponding to the integrated circuit;

the determining the target position parameter corresponding to the integrated circuit based on the characteristic information specifically comprises the following steps:

2. The method for adjusting an integrated circuit according to claim 1, wherein determining an optimized position parameter corresponding to the reference position parameter based on the photoelectric characteristic and the reference position parameter specifically includes:

3. The method for adjusting an integrated circuit according to claim 1, wherein determining a target position parameter corresponding to the position parameter based on the optimized position parameter specifically includes:

4. The method of claim 3, wherein the detection network model comprises a first network model and a second network model in cascade, wherein an input term of the first network model is a first high-dimensional position parameter, an output term of the first network model is a first low-dimensional position parameter, an input term of the third network model is a second low-dimensional position parameter, an output term of the third network model is a second high-dimensional position parameter, a dimension of the first high-dimensional position parameter is equal to a dimension of the second high-dimensional position parameter, and a dimension of the first low-dimensional position parameter is equal to a dimension of the second low-dimensional position parameter.

5. The method of adjusting an integrated circuit according to claim 4, wherein the training process of the third network model specifically comprises:

6. The method for adjusting an integrated circuit according to any one of claims 1 to 5, wherein after determining a target position parameter corresponding to the integrated circuit based on the characteristic information and determining an adjusted integrated circuit based on the target position parameter, the method further comprises:

7. The method according to claim 6, wherein after the obtaining the target photoelectric characteristic corresponding to the target position parameter and saving the circuit parameter formed by the target position parameter and the target photoelectric characteristic, the method further comprises:

8. The method for adjusting an integrated circuit according to claim 7, wherein selecting a target circuit parameter corresponding to a desired photoelectric characteristic from a plurality of pre-stored circuit parameters based on the preset desired photoelectric characteristic specifically comprises:

9. The method of claim 8, wherein the pre-stored circuit parameters are stored in a KD tree form.

10. The method of adjusting an integrated circuit according to claim 9, wherein selecting a target circuit parameter from the plurality of circuit parameters based on the desired optoelectronic characteristic and the set of weight coefficients comprises:

11. The method of any of claims 1-5, wherein the integrated circuit is a TFT circuit.

12. An adjustment device for an integrated circuit for implementing the adjustment method for an integrated circuit according to any one of claims 1-11, characterized in that the adjustment device comprises:

13. A computer-readable storage medium storing one or more programs executable by one or more processors to implement the steps in the method of tuning an integrated circuit as recited in any one of claims 1-11.

14. The terminal equipment is characterized by comprising a processor, a memory and a communication bus, wherein the memory is stored with a computer readable program which can be executed by the processor;

the processor, when executing the computer readable program, implements the steps of the method of tuning an integrated circuit as claimed in any one of claims 1-11.