TCAD simulation tool precision verification method and device and electronic equipment

Abstract

The embodiment of the invention provides a TCAD simulation tool precision verification method and device and electronic equipment, and relates to the technical field of verification simulation. The method comprises the following steps: acquiring a simulation node sequence output by TCAD simulation; selecting a first interpolation method or a second interpolation method for two adjacent nodes in the simulation node sequence according to the variable quantity of the two nodes on the simulation condition and the change rate measurement of the two nodes and the adjacent node; adopting the selected first interpolation method or the selected second interpolation method to carry out interpolation on an interval formed by the two adjacent nodes; and performing interpolation on the simulation node sequence to obtain a standard curve, and performing precision verification by adopting the standard curve. According to the implementation mode provided by the invention, the accuracy of performing precision verification by adopting the simulation data points with insufficient simulation data points is improved.

Description

Technical Field

[0001] This application relates to the field of verification and simulation technologies, and particularly to a method for verifying the accuracy of a TCAD simulation tool, a device for verifying the accuracy of a TCAD simulation tool, an electronic device, and a corresponding storage medium. Background Art

[0002] The TCAD simulation tool, namely the Technology Computer Aided Design simulation tool, is an important tool in semiconductor process and device design. Based on numerical simulation methods, the tool can help engineers virtually reproduce the characteristics of real semiconductor devices. With the rapid growth of the semiconductor industry, the role of the TCAD simulation tool has become increasingly prominent. Its significant advantages in improving design efficiency, reducing costs, and accelerating innovation have promoted the vigorous development of the TCAD industry, and emerging TCAD software companies are gradually occupying market share.

[0003] The accuracy of TCAD simulation design is the key to the reliability of the tool. Existing software accuracy verification usually takes the form of benchmarking. New TCAD tools benchmark key simulation result values against the software products of international leading manufacturers in order to obtain a match in the theoretical model. This direct comparison of point-to-point values brings potential simulation errors. For example, when the device electric fields in the simulations of two software are completely inconsistent, the simulation result error is within the acceptable range. To truly benchmark the simulation calculation process of the device, it is necessary to compare the output characteristic curves of the simulation results and complete the software accuracy verification by combining trend judgment. Summary of the Invention

[0004] The purpose of the embodiments of this application is to provide a method, device, and electronic device for verifying the accuracy of a TCAD simulation tool. By optimizing the selection of the interpolation algorithm for the TCAD simulation output curve, the accuracy in evaluating and discriminating the differences between simulation tools is improved, so as to solve at least some of the problems in the background art.

[0005] To achieve the above purpose, this application provides a method for verifying the accuracy of a TCAD simulation tool. The method includes: obtaining a sequence of simulation nodes output by the TCAD simulation; for two adjacent nodes in the sequence of simulation nodes, selecting a first interpolation method or a second interpolation method according to the change amount of the two nodes in the simulation conditions and the change rate metric between the two nodes and an adjacent node; interpolating the interval formed by the two adjacent nodes by using the selected first interpolation method or second interpolation method; obtaining a standard curve after interpolating the sequence of simulation nodes, and using the standard curve for accuracy verification.

[0006] Optionally, the first interpolation method is a linear interpolation algorithm, and the second interpolation method is a spline interpolation method.

[0007] Optionally, selecting a first interpolation method or a second interpolation method according to the change amount of the two nodes in the simulation conditions and the change rate metric between the two nodes and an adjacent node includes: obtaining a first selection result according to the change amount of the two nodes in the simulation conditions, where the first selection result is one of the first interpolation method and the second interpolation method; obtaining a second selection result according to the change rate metric between the two nodes and an adjacent node, where the second selection result is one of the first interpolation method and the second interpolation method; and obtaining the selected first interpolation method or second interpolation method by combining the first selection result and the second selection result.

[0008] Optionally, obtaining a first selection result according to the change amount of the two nodes in the simulation conditions includes: obtaining a first simulation condition value corresponding to a first node and a second simulation condition value corresponding to a second node among the two nodes; calculating a difference between the first simulation condition value and the second simulation condition value; calculating a ratio of the difference to the difference between the maximum value and the minimum value of the simulation condition value range; determining whether the ratio is greater than a preset ratio threshold; when the ratio is greater than the preset ratio threshold, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

[0009] Optionally, the preset ratio threshold is determined according to the maximum allowable simulation error during accuracy verification.

[0010] Optionally, obtaining a second selection result according to the change rate metric between the two nodes and an adjacent node includes: determining a node closer to the adjacent node among the two nodes as the first node; calculating a first change rate metric of the two nodes and a second change rate metric between the first node and the adjacent node; determining whether the product of the first change rate metric and the second change rate metric is less than 0; when the product is less than 0, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

[0011] Optionally, obtaining the selected first interpolation method or second interpolation method by combining the first selection result and the second selection result includes: when the first selection result and the second selection result are the same, using the interpolation method in the first selection result and the second selection result as the selected interpolation method; when the first selection result and the second selection result are different, using the higher one of the set priorities of the first interpolation method and the second interpolation method as the selected interpolation method.

[0012] Optionally, after interpolating the simulation node sequence to obtain a standard curve, the method further includes: determining whether the maximum value of the simulation conditions corresponding to the endpoints of the standard curve exceeds a preset simulation condition threshold; when the maximum value of the simulation conditions does not exceed the preset simulation condition threshold, performing trend fitting on the interval between the endpoint corresponding to the maximum value of the simulation conditions on the standard curve and the preset simulation condition threshold to obtain a standard curve after trend fitting; correspondingly, using the standard curve for accuracy verification is replaced by: using the standard curve after trend fitting for accuracy verification.

[0013] Optionally, the value corresponding to the preset simulation condition threshold during trend fitting is determined based on historical values under the same simulation conditions, and the linear form of the trend fitting is determined according to the adjacent intervals of the maximum value of the simulation conditions corresponding to the endpoints of the standard curve.

[0014] Optionally, using the standard curve or the standard curve after trend fitting for accuracy verification includes: obtaining a first point corresponding to a certain simulation condition on the simulation value to be verified and a second point corresponding to the standard curve or the standard curve after trend fitting; calculating the relative error between the first point and the second point; changing the certain simulation condition to obtain several relative errors under different simulation conditions; calculating the overall error based on all the obtained relative errors, and using the overall error as the result of accuracy verification.

[0015] Optionally, if there is a standard curve after trend fitting, determining whether the verification result based on the standard curve after trend fitting is consistent with the verification result based on the standard curve before trend fitting; when the two are inconsistent, outputting inconsistent information.

[0016] In this application, there is also provided a TCAD simulation tool accuracy verification device, which includes: a sequence acquisition module for acquiring a simulation node sequence output by TCAD simulation; an algorithm selection module for, for two adjacent nodes in the simulation node sequence, selecting a first interpolation method or a second interpolation method according to the change amount of the two nodes in the simulation conditions and the change rate measurement between the two nodes and an adjacent node; an interpolation execution module for interpolating the interval formed by the two adjacent nodes by using the selected first interpolation method or second interpolation method; and an accuracy output module for interpolating the simulation node sequence to obtain a standard curve and using the standard curve for accuracy verification.

[0017] In this application, there is also provided an electronic device, including: at least one processor; a memory connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the at least one processor implements the foregoing TCAD simulation tool accuracy verification method by executing the instructions stored in the memory.

[0018] In this application, a machine-readable storage medium is also provided. Instructions are stored on the machine-readable storage medium, and when the instructions are executed by a processor, the processor is configured to execute the TCAD simulation tool accuracy verification method described above.

[0019] In this application, a computer program product is also provided, including a computer program which, when executed by a processor, implements the TCAD simulation tool accuracy verification method described above.

[0020] The above technical solutions have the following beneficial effects:

[0021] (1) It solves the problem that the trend simulation accuracy cannot be avoided when only based on linear interpolation. This application proposes a selective interpolation method to make the trend simulation more accurate.

[0022] (2) The selective method proposed in this application is simple and easy to implement. The samples can be classified and processed only based on the number of sampling points and the extreme point conditions. It can be seen that the data processing method has both the simplicity and high efficiency of linear interpolation and the accurate trend of cubic spline interpolation.

[0023] (3) On the basis of the original comparison of key simulation result values, the output characteristic curve comparison process is added, making the simulation tool accuracy verification work more accurate and credible.

[0024] Other features and advantages of the embodiments of this application will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings are used to provide a further understanding of the embodiments of this application, and constitute a part of the specification. They are used together with the following specific implementation to explain the embodiments of this application, but do not constitute a limitation to the embodiments of this application. In the drawings:

[0026] Figure 1 Schematically shows a schematic diagram of the steps of the TCAD simulation tool accuracy verification method according to the embodiment of this application;

[0027] Figure 2 Schematically shows a schematic diagram of the comparison of the output characteristics of MOS devices of two software in an ideal situation;

[0028] Figure 3 Schematically shows a schematic diagram of the comparison of the output characteristics of MOS devices of two software under normal circumstances;

[0029] Figure 4 Schematically shows a schematic diagram of the trend comparison of the linear interpolation method under different numbers of sampling points;

[0030] Figure 5Schematically shows a schematic diagram of the linear interpolation method in the trend comparison of non-linear simulation conditions;

[0031] Figure 6 Schematically shows a schematic diagram of the lack of fitting of the number of sampling points of two interpolation methods according to an embodiment of the present application;

[0032] Figure 7 Schematically shows a schematic diagram of the fitting of two interpolation methods in non-linear simulation conditions according to an embodiment of the present application;

[0033] Figure 8 Schematically shows an implementation flowchart of a method for verifying the accuracy of a TCAD simulation tool according to an embodiment of the present application;

[0034] Figure 9 Schematically shows a line type comparison diagram of a method for verifying the accuracy of a TCAD simulation tool according to an embodiment of the present application;

[0035] Figure 10 Schematically shows a structural schematic diagram of a device for verifying the accuracy of a TCAD simulation tool according to an embodiment of the present application;

[0036] Figure 11 Schematically shows an internal structural diagram of an electronic device according to an embodiment of the present application. Specific embodiments

[0037] The following will describe in detail the specific embodiments of the embodiments of the present application with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining and illustrating the embodiments of the present application, and are not used to limit the embodiments of the present application.

[0038] Figure 1 Schematically shows a schematic diagram of the steps of a method for verifying the accuracy of a TCAD simulation tool according to an embodiment of the present application. As Figure 1 shown, the method includes:

[0039] S01. Obtain a simulation node sequence output by the TCAD simulation;

[0040] S02. For two adjacent nodes in the simulation node sequence, select a first interpolation method or a second interpolation method according to the change amount of the two nodes in the simulation conditions and the change rate measurement of the two nodes and an adjacent node;

[0041] S03. Interpolate the interval formed by the two adjacent nodes by using the selected first interpolation method or second interpolation method;

[0042] S04. After interpolating the simulation node sequence to obtain a standard curve, use the standard curve for accuracy verification.

[0043] Through the above embodiments, the accuracy verification differences caused by insufficient or mismatched simulation data points are greatly avoided. Figure 2 It schematically shows a schematic diagram of the comparison of the output characteristics of MOS devices of two software in an ideal situation. As Figure 2 shown, in an ideal situation, although both the standard value and the value to be verified are discrete points, they have a good corresponding relationship, that is, for the same x, there is a corresponding y value. However, the actual situation is not exactly like this. Figure 3 It schematically shows a schematic diagram of the comparison of the output characteristics of MOS devices of two software under normal circumstances. As Figure 3 shown, the discrete points of the standard value and the value to be verified do not exactly correspond on the X-axis, and there are certain differences. Therefore, when calculating the error, it is necessary to obtain the y value corresponding to the same x through an interpolation algorithm to perform subsequent calculations. Therefore, the interpolation result of the interpolation algorithm has an important decisive role in the accuracy verification result.

[0044] In some embodiments of the present application, the first interpolation method is a linear interpolation algorithm, and the second interpolation method is a spline interpolation method. The linear interpolation method is a simple interpolation method, and its basic idea is to estimate the value of an unknown intermediate point through two known data points. The geometric meaning of linear interpolation is to approximately represent the original function by using the straight line passing through point A and point B. The spline interpolation method (Spline Interpolation) is an interpolation method commonly used in numerical analysis and computer graphics, and is used to construct a smooth curve passing through a set of given data points. The spline interpolation method in the present application is preferably a cubic spline interpolation method. Cubic spline interpolation is an advanced interpolation method, and its principle is to approximate the data points by using cubic polynomials on each data segment to obtain a more accurate change trend of the overall sample. The curve generated by cubic spline interpolation is smoother than linear interpolation and has stronger adaptability to local changes. However, the disadvantages of the cubic spline interpolation algorithm are also obvious. Compared with linear interpolation, the calculation process of cubic spline interpolation is more complex. Moreover, since cubic spline interpolation can fit data points more precisely, it is also more prone to overfitting, especially when there are more data points or more noise.

[0045] Linear interpolation is a commonly used numerical analysis method for estimating the value of an unknown data point based on the point-line slope between two known data points. The solution process of the linear equation is relatively simple, with fast calculation speed and low complexity, and it is not easy to overfit the data. However, when there are fewer available data points, linear interpolation cannot well capture the overall trend of the data; and for non-linear data, linear interpolation is difficult to accurately reflect the true change of the data. Figure 4 It schematically shows a schematic diagram of the trend comparison of the linear interpolation method under different numbers of sampled points. As Figure 4 shown, in the case of insufficient sampled points, there are significant differences in the simulation data at some point intervals. At this time, when using this sample for TCAD simulation verification, the verification average error will be amplified.

[0046] Figure 5 Schematically shows a schematic diagram of the linear interpolation method in the trend comparison of non-linear simulation conditions. As Figure 5 shown, the C-V curve of the MOS device has strong non-linear characteristics. At the inflection point, there is a large deviation between the trend of the linear interpolation data and the complete trend; the linear interpolation method is not suitable for the accuracy verification work of the simulation software.

[0047] In summary, the single linear interpolation method is not suitable for the accuracy verification of the simulation software, and the present application solves the above technical problems by introducing the selection of different interpolation methods.

[0048] In some embodiments of the present application, the first interpolation method or the second interpolation method is selected according to the change amount of the two nodes under the simulation conditions and the change rate metric between the two nodes and an adjacent node, including: obtaining a first selection result according to the change amount of the two nodes under the simulation conditions, and the first selection result is one of the first interpolation method and the second interpolation method; obtaining a second selection result according to the change rate metric between the two nodes and an adjacent node, and the second selection result is one of the first interpolation method and the second interpolation method; combining the first selection result and the second selection result to obtain the selected first interpolation method or the second interpolation method. This embodiment provides two selection criteria, namely the sparsity of the simulation conditions and whether there are sample extreme points. Selection results are obtained based on different selection criteria respectively, and then after being combined according to the selection results, a final selection result is obtained. The obtained final selection result is used to interpolate the interval between the two nodes.

[0049] In some embodiments of the present application, obtaining a first selection result according to the change amount of the two nodes under the simulation conditions includes: obtaining a first simulation condition value corresponding to a first node and a second simulation condition value corresponding to a second node among the two nodes; taking the simulation condition as the voltage value and the simulation result as the current value in the TCAD simulation as an example, when it is displayed in coordinates, the abscissa X-axis is the voltage value and the ordinate Y-axis is the current value. Taking two adjacent nodes as (x0, y0) and (x1, y1) respectively, the difference (x1 - x0) between the x values of the adjacent nodes is the change amount of the foregoing simulation conditions. Calculate the difference between the first simulation condition value and the second simulation condition value, that is: (x1 - x0). Calculate the ratio of the difference to the difference between the maximum value and the minimum value of the simulation condition value range; for example, when the simulation condition value range, that is, the value range of the x value, is [0, 20], the difference between the maximum value and the minimum value is 20. Determine whether the ratio is greater than a preset ratio threshold; the preset ratio threshold can be selected as 1 / 10. When the ratio is greater than the preset ratio threshold, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

[0050] Based on the previous embodiment, the preset ratio threshold is determined according to the maximum allowable simulation error during accuracy verification. When the change amount (x1 - x0) in simulation conditions is greater than 1 / 10 of the maximum simulation condition difference, the cubic spline interpolation method is adopted; otherwise, the linear interpolation method is used. The condition of 1 / 10 of the maximum simulation condition difference can be adaptively modified according to the actual scenario. Since the change amount (x1 - x0) in simulation conditions reflects the sparsity of the sample quantity, if the maximum allowable simulation error is small, the requirement for the sample quantity will be high. Therefore, the aforementioned 1 / 10 needs to be adaptively adjusted according to the maximum allowable simulation error, for example, set as a fixed multiple of the maximum allowable simulation error.

[0051] In some embodiments of the present application, obtaining a second selection result according to the change rate metrics of the two nodes and an adjacent node includes: determining the node closer to the adjacent node among the two nodes as the first node; calculating the first change rate metric of the two nodes and the second change rate metric of the first node and the adjacent node; determining whether the product of the first change rate metric and the second change rate metric is less than 0; when the product is less than 0, the first selection result is the second interpolation method; otherwise, the first selection result is the first interpolation method. Also taking the TCAD simulation as an example, where the simulation condition is the voltage value and the simulation result is the current value. The linear interpolation algorithm is used for the monotonicity point samples, and the cubic spline interpolation algorithm is used for the samples with extreme points. The determination of the sample extreme points is determined by the product of the slopes of adjacent points. That is, for only the three points (x0, y0), (x1, y1), and (x2, y2), when the product of the slopes (y1 - y0) × (y2 - y1) / ((x1 - x0) × (x2 - x1)) < 0, it indicates that there is a positive and negative change in the slope in this interval, that is, the first node (x1, y1) is an extreme point, and the cubic spline interpolation algorithm is adopted. In the aforementioned calculation method, when the two adjacent nodes are (x0, y0) and (x1, y1), the adjacent node is (x2, y2), and at this time (x1, y1) is the first node; or, when the two adjacent nodes are (x2, y2) and (x1, y1), the adjacent node is (x0, y0), and at this time (x1, y1) is the first node. When any one of the two nodes is an extreme point, the interpolation algorithm to be used can be determined.

[0052] In some embodiments of the present application, obtaining the selected first interpolation method or second interpolation method by integrating the first selection result and the second selection result includes: when the first selection result and the second selection result are consistent, using the interpolation method in the first selection result and the second selection result as the selected interpolation method; when the first selection result and the second selection result are inconsistent, using the higher one of the set priorities of the first interpolation method and the second interpolation method as the selected interpolation method. When the priority set for the first interpolation method is higher, the first interpolation method is used when they are inconsistent; when the priority set for the second interpolation method is higher, the second interpolation method is used when they are inconsistent. In some embodiments, cubic spline interpolation has a higher priority, that is, the cubic spline interpolation sample screening principle is generally followed, and the linear interpolation method is used for the samples that finally fail to pass the screening. The determination steps of the above first selection result and second selection result can be exchanged in order, but the cubic spline interpolation sample screening principle is generally followed, and the linear interpolation method is used for the samples that finally fail to pass the screening.

[0053] Figure 6 Schematically shows a schematic diagram of the lack of fitting of the number of spotting points of two interpolation methods according to an embodiment of the present application. As Figure 6 shown, the number of spotting points in the figure is complete, and the two trend lines fit the samples with missing spotting points. It can be known from the comparison of the fitting deviations in the figure that in the case of a small number of samples, although the cubic spline interpolation algorithm will also generate a little fitting error for the complete spotting points, the fitting error brought by it is greatly reduced compared with the linear interpolation algorithm.

[0054] Figure 7 Schematically shows a schematic diagram of the fitting of the non-linear simulation conditions of two interpolation methods according to an embodiment of the present application. As Figure 7 shown, the number of spotting points in the figure is complete, and the two trend lines fit the spotting point samples. It can be known from the comparison of the fitting deviations in the figure that in the non-linear region, the fitting error generated by the cubic spline interpolation algorithm for the complete spotting points can be ignored, and the fitting error brought by it is greatly reduced compared with the linear interpolation algorithm.

[0055] Figure 8 Schematically shows a flowchart of the implementation of the TCAD simulation tool accuracy verification method according to an embodiment of the present application. As Figure 8 shown, this process can first determine the number of samples, and then determine the extreme values of the samples. However, the above two steps can be exchanged in order, but the cubic spline interpolation sample screening principle is generally followed, and the linear interpolation method is used for the samples that finally fail to pass the screening.

[0056] Since there may be inconsistencies between the simulation values to be verified and the endpoints of the standard curve, sample points on the simulation values to be verified cannot be matched from the standard curve. Therefore, in some embodiments of the present application, after interpolating the simulation node sequence to obtain the standard curve, the method further includes: determining whether the maximum simulation condition corresponding to the endpoint of the standard curve exceeds a preset simulation condition threshold; if the maximum simulation condition of the standard curve only reaches 18V, and there are values above 18V in the simulation values to be verified, the standard curve needs to be extended above 18V, and a trend fitting is performed on the simulation results of the lacking sample points, and then the error analysis is performed on the TCAD simulation values to be verified using the fitting trend. When the maximum simulation condition does not exceed the preset simulation condition threshold, a trend fitting is performed on the interval between the endpoint corresponding to the maximum simulation condition on the standard curve and the preset simulation condition threshold to obtain a trend-fitted standard curve; correspondingly, using the standard curve for accuracy verification is replaced by: using the trend-fitted standard curve for accuracy verification. This embodiment provides a trend fitting of the standard curve to meet the data requirements for error analysis.

[0057] In some embodiments of the present application, the value corresponding to the preset simulation condition threshold during trend fitting is determined based on historical values under the same simulation conditions, and the linear form of the trend fitting is determined according to the adjacent interval of the maximum simulation condition corresponding to the endpoint of the standard curve. During trend fitting, the points need to be determined first, and then the difference algorithm between the points is determined. In this embodiment, the points can be determined by the big data method. The linear form of the trend fitting is determined according to the adjacent interval of the maximum simulation condition corresponding to the endpoint of the standard curve. It can be that if the last interval of the standard curve uses linear interpolation, the linear form of the trend fitting is obtained through linear interpolation. If the last interval of the standard curve uses spline interpolation, the linear form of the trend fitting is obtained through spline interpolation.

[0058] In some embodiments of the present application, the accuracy verification is performed using the standard curve or the standard curve after trend fitting, including: obtaining a first point corresponding to a certain simulation condition on the simulation value to be verified and a second point corresponding to the standard curve or the standard curve after trend fitting; calculating the relative error between the first point and the second point; changing the certain simulation condition to obtain a number of relative errors under different simulation conditions; calculating the overall error based on all the obtained relative errors, and using the overall error as the result of the accuracy verification. For example, on the premise that the device model and boundary conditions are the same, the node generation is determined by various factors, including the tool embedded algorithm, the solver type, the simulation step size, etc. For the ideal case, the software can obtain the point-to-point relative error by comparing the output values (y values) under the same simulation boundary (x value). For example, the relative error between two points (x0, y0) and (x0, y1) corresponding to the same x0 is (y1 - y0) / y0; then by changing the value of x, a series of relative errors are obtained, and the average value of this series of relative errors is used to obtain the overall error, and this overall error is used to evaluate the result of the accuracy verification.

[0059] In some embodiments of the present application, if there is a standard curve after trend fitting, it is determined whether the verification result based on the standard curve after trend fitting is consistent with the verification result based on the standard curve before trend fitting; when the two are inconsistent, inconsistent information is output. Since there is fitting for the standard curve, there will be a situation where the error increases in the part generated by the trend fitting of the curve. However, on the other hand, if the standard curve after trend fitting is not used, it will also lead to a reduction in the number of sample points and may cause a deviation in the accuracy verification result. Therefore, both the standard curve before and after trend fitting have their advantages and disadvantages. When the verification results of the two are inconsistent, a prompt message needs to be output for the user to make their own selection and trade-off. This embodiment improves the objectivity and accuracy of the verification result.

[0060] Through the above embodiments, a selective interpolation method is proposed to improve the accuracy of TCAD simulation verification. By determining the number and linearity of the standard data for comparison, the interpolation algorithm is converted from linear interpolation to cubic spline interpolation, which greatly avoids the accuracy verification difference caused by insufficient simulation data points. The embodiments of the present application also combine the simplicity and efficiency of linear interpolation and the accurate trend of cubic spline interpolation, making the trend simulation more accurate.

[0061] Figure 9 Schematically shows a line type comparison diagram of the TCAD simulation tool accuracy verification method according to the embodiments of the present application. As Figure 9As shown, based on cubic spline interpolation, the trend fitting is performed on the simulation results of the sample-deficient samples, and then the fitting trend is used to perform error analysis on the TCAD simulation values to be verified. The error calculation is performed on the values to be verified by the cubic spline interpolation method, and the average point error is obtained as 4.84%; the average point error obtained by the linear interpolation method is 6.05%. Since a 1% simulation error can determine whether the results of the TCAD simulation tool are acceptable, the results obtained by the cubic spline interpolation method will have greater advantages in the accuracy comparison.

[0062] Based on the same inventive concept, the present application also provides a device for verifying the accuracy of a TCAD simulation tool. Figure 10 Schematically shows a structural diagram of a device for verifying the accuracy of a TCAD simulation tool according to an embodiment of the present application. As Figure 10 shown, the device includes: a sequence acquisition module for acquiring a simulation node sequence output by the TCAD simulation; an algorithm selection module for selecting a first interpolation method or a second interpolation method for two adjacent nodes in the simulation node sequence according to the change amount of the two nodes in the simulation conditions and the change rate measure of the two nodes and an adjacent node; an interpolation execution module for interpolating the interval formed by the two adjacent nodes by using the selected first interpolation method or second interpolation method; and an accuracy output module for obtaining a standard curve after interpolating the simulation node sequence and performing accuracy verification by using the standard curve.

[0063] In some alternative embodiments of the present application, the first interpolation method is a linear interpolation algorithm, and the second interpolation method is a spline interpolation method.

[0064] In some alternative embodiments of the present application, selecting a first interpolation method or a second interpolation method according to the change amount of the two nodes in the simulation conditions and the change rate measure of the two nodes and an adjacent node includes: obtaining a first selection result according to the change amount of the two nodes in the simulation conditions, where the first selection result is one of the first interpolation method and the second interpolation method; obtaining a second selection result according to the change rate measure of the two nodes and an adjacent node, where the second selection result is one of the first interpolation method and the second interpolation method; and combining the first selection result and the second selection result to obtain the selected first interpolation method or second interpolation method.

[0065] In some alternative embodiments of the present application, obtaining a first selection result according to the change amount of the two nodes in the simulation conditions includes: obtaining a first simulation condition value corresponding to a first node and a second simulation condition value corresponding to a second node among the two nodes; calculating the difference between the first simulation condition value and the second simulation condition value; calculating the ratio of the difference to the difference between the maximum and minimum values of the simulation condition value range; determining whether the ratio is greater than a preset ratio threshold; when the ratio is greater than the preset ratio threshold, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

[0066] In some alternative embodiments of the present application, the preset ratio threshold is determined according to the maximum allowable simulation error during accuracy verification.

[0067] In some alternative embodiments of the present application, obtaining a second selection result according to the change rate metric between the two nodes and an adjacent node includes: determining the node closer to the adjacent node among the two nodes as the first node; calculating a first change rate metric of the two nodes and a second change rate metric of the first node and the adjacent node; determining whether the product of the first change rate metric and the second change rate metric is less than 0; when the product is less than 0, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

[0068] In some alternative embodiments of the present application, obtaining the selected first interpolation method or second interpolation method by integrating the first selection result and the second selection result includes: when the first selection result and the second selection result are consistent, using the interpolation method in the first selection result and the second selection result as the selected interpolation method; when the first selection result and the second selection result are inconsistent, using the higher one of the set priorities of the first interpolation method and the second interpolation method as the selected interpolation method.

[0069] In some alternative embodiments of the present application, after interpolating the simulation node sequence to obtain a standard curve, the method further includes: determining whether the maximum simulation condition value corresponding to the endpoint of the standard curve exceeds a preset simulation condition threshold; when the maximum simulation condition value does not exceed the preset simulation condition threshold, performing trend fitting on the interval between the endpoint corresponding to the maximum simulation condition value on the standard curve and the preset simulation condition threshold to obtain a trend-fitted standard curve; correspondingly, using the standard curve for accuracy verification is replaced by: using the trend-fitted standard curve for accuracy verification.

[0070] In some alternative embodiments of the present application, the value corresponding to the preset simulation condition threshold during trend fitting is determined based on historical values under the same simulation conditions, and the linear form of the trend fitting is determined according to the adjacent interval of the maximum simulation condition corresponding to the endpoints of the standard curve.

[0071] In some alternative embodiments of the present application, the accuracy verification is performed using the standard curve or the standard curve after trend fitting, including: obtaining a first point corresponding to a certain simulation condition on the simulation value to be verified and a second point corresponding to the standard curve or the standard curve after trend fitting; calculating the relative error between the first point and the second point; changing the certain simulation condition to obtain several relative errors under different simulation conditions; calculating the overall error based on all the obtained relative errors, and using the overall error as the result of the accuracy verification.

[0072] In some alternative embodiments of the present application, if there is a standard curve after trend fitting, it is determined whether the verification result based on the standard curve after trend fitting is consistent with the verification result based on the standard curve before trend fitting; when the two are inconsistent, inconsistent information is output.

[0073] The specific definitions of the various functional modules in the above TCAD simulation tool accuracy verification device can be referred to the definitions of the TCAD simulation tool accuracy verification method in the foregoing text, and will not be elaborated here. Each module in the above system can be implemented in whole or in part by software, hardware, and their combinations. The above modules can be embedded in the processor of the electronic device in hardware form or be independent of it, or can be stored in the memory of the electronic device in software form, so that the processor can call and execute the operations corresponding to the above modules. It also realizes the advantage of greatly avoiding the accuracy verification differences caused by insufficient simulation data points.

[0074] In some embodiments of the present application, an electronic device is further provided, including: at least one processor; a memory connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the at least one processor executes the foregoing TCAD simulation tool accuracy verification method. Its internal structure diagram can be as Figure 11 shown. Figure 11Schematically shown is an internal structure diagram of an electronic device according to an embodiment of the present application. The electronic device includes a processor A01, a network interface A02, a memory (not shown in the figure), and a database (not shown in the figure) connected through a system bus. Among them, the processor A01 of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02, and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The network interface A02 of the electronic device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, it implements a method for verifying the accuracy of a TCAD simulation tool.

[0075] Those skilled in the art can understand that Figure 11 the structure shown in [the figure] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the electronic device to which the solution of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0076] In an embodiment provided by the present application, a machine-readable storage medium is provided. Instructions are stored on the machine-readable storage medium, and when the instructions are executed by a processor, the processor is configured to execute the aforementioned method for verifying the accuracy of a TCAD simulation tool.

[0077] In an embodiment provided by the present application, a computer program product is provided, including a computer program that implements the aforementioned method for verifying the accuracy of a TCAD simulation tool when executed by a processor.

[0078] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0080] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0081] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0082] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0083] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0084] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0085] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0086] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A TCAD simulation tool accuracy verification method, characterized in that: The method includes: Get the simulation node sequence output by TCAD simulation; For two adjacent nodes in the simulation node sequence, selecting a first interpolation method or a second interpolation method according to a change amount of the two nodes in simulation conditions and a change rate measure between the two nodes and an adjacent node; interpolating the interval formed by the two adjacent nodes using the selected first interpolation method or the second interpolation method; A standard curve is obtained by interpolating the simulation node sequence, and the accuracy is verified using the standard curve.

2. The method according to claim 1, characterized in that The first interpolation method is a linear interpolation algorithm, and the second interpolation method is a spline interpolation method.

3. The method according to claim 1 or 2, characterized in that: Selecting the first interpolation method or the second interpolation method according to the change amount of the two nodes in the simulation conditions and the change rate measurement of the two nodes and an adjacent node includes: Obtaining a first selection result according to the change amount of the two nodes in the simulation conditions, wherein the first selection result is one of a first interpolation method and a second interpolation method; Obtaining a second selection result according to a change rate measurement between the two nodes and an adjacent node, wherein the second selection result is one of the first interpolation method and the second interpolation method; The first selection result and the second selection result are combined to obtain the selected first interpolation method or the second interpolation method.

4. The method according to claim 3, characterized in that Obtaining a first selection result according to the change amount of the two nodes in the simulation conditions includes: Obtain a first simulation condition value corresponding to a first node and a second simulation condition value corresponding to a second node of the two nodes; Calculate the difference between the first simulation condition value and the second simulation condition value; Calculate the ratio of the difference between the maximum value and the minimum value of the simulation condition value range; Determining whether the ratio is greater than a preset ratio threshold; When the ratio is greater than the preset ratio threshold, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

5. The method according to claim 4, characterized in that The preset ratio threshold is determined according to the maximum allowable simulation error during accuracy verification.

6. The method according to claim 3, characterized in that The second selection result is obtained according to the change rate measurement of the two nodes and an adjacent node, including: Determine a node among the two nodes that is close to the adjacent node as a first node; Calculating a first change rate metric of the two nodes and a second change rate metric of the first node and an adjacent node; Determining whether a product of the first change rate metric and the second change rate metric is less than 0; When the product is less than 0, the first selection result is the second interpolation method, otherwise the first selection result is the first interpolation method.

7. The method according to claim 3, characterized in that Combining the first selection result and the second selection result to obtain the selected first interpolation method or second interpolation method includes: When the first selection result and the second selection result are consistent, using the interpolation method in the first selection result and the second selection result as the selected interpolation method; When the first selection result and the second selection result are inconsistent, the higher priority of the first interpolation method and the second interpolation method is selected as the interpolation method.

8. The method according to claim 3, characterized in that After obtaining a standard curve by interpolating the simulation node sequence, the method further includes: Determine whether the maximum value of the simulation condition corresponding to the endpoint of the standard curve exceeds a preset simulation condition threshold; When the maximum value of the simulation condition does not exceed the preset simulation condition threshold, trend fitting is performed on the interval between the endpoint corresponding to the maximum value of the simulation condition on the standard curve and the preset simulation condition threshold to obtain a standard curve after trend fitting; Correspondingly, the accuracy verification using the standard curve is replaced by: the accuracy verification using the standard curve after trend fitting.

9. The method according to claim 8, characterized in that The value corresponding to the preset simulation condition threshold during trend fitting is determined based on the historical value under the same simulation condition, and the linear shape of the trend fitting is determined according to the adjacent interval of the maximum value of the simulation condition corresponding to the endpoint of the standard curve.

10. The method according to claim 8, characterized in that The standard curve or the standard curve after trend fitting is used to verify the accuracy, including: Obtaining a first point corresponding to a certain simulation condition on the simulation value to be verified and a second point corresponding to the standard curve or the standard curve after trend fitting; calculating a relative error between the first point and the second point; Changing the simulation condition to obtain a number of relative errors under different simulation conditions; The overall error is calculated based on all the relative errors obtained, and the overall error is used as the result of the accuracy verification.

11. The method according to claim 10, characterized in that If there is a standard curve after trend fitting, determining whether the verification result based on the standard curve after trend fitting is consistent with the verification result based on the standard curve before trend fitting; When the two are inconsistent, an inconsistent message is output.

12. A TCAD simulation tool accuracy verification device, characterized in that: The device includes: A sequence acquisition module is used to obtain the simulation node sequence output by TCAD simulation; An algorithm selection module, for selecting a first interpolation method or a second interpolation method for two adjacent nodes in the simulation node sequence according to a change amount of the two nodes in simulation conditions and a change rate measurement between the two nodes and an adjacent node; an interpolation execution module, configured to interpolate the interval formed by the two adjacent nodes using the selected first interpolation method or the second interpolation method; and The accuracy output module is used to obtain a standard curve after interpolating the simulation node sequence, and use the standard curve to perform accuracy verification.

13. An electronic device, characterized in that: include: at least one processor; a memory connected to the at least one processor; Wherein, the memory stores instructions that can be executed by the at least one processor, and the at least one processor implements the steps of the TCAD simulation tool accuracy verification method described in any one of claims 1 to 11 by executing the instructions stored in the memory.

14. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the TCAD simulation tool accuracy verification method described in any one of claims 1 to 11 are implemented.

15. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the TCAD simulation tool accuracy verification method described in any one of claims 1 to 11 are implemented.

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