Circuit aging curve determination method and apparatus, electronic device, and storage medium

Abstract

The application provides a circuit aging curve determination method and device, electronic equipment and storage medium. The method comprises the following steps: simulating process deviation of a to-be-tested circuit in a healthy state to determine a health curve; the health curve is used to represent the working frequency difference of the to-be-tested circuit in the healthy state caused by process deviation; performing one aging simulation on the to-be-tested circuit to determine an aging parameter under a preset failure standard; the aging coefficient represents the corresponding working frequency of the to-be-tested circuit under the preset failure standard after aging; and the aging curve of the to-be-tested circuit is determined according to the standard deviation of the health curve and the aging parameter; the aging curve is used to represent the working frequency difference of the to-be-tested circuit caused by process deviation after aging. In the foregoing manner, the problem of large calculation amount and long time consumption when evaluating the circuit aging under process deviation can be improved.

Description

Technical Field

[0001] This application relates to the field of circuit testing, and more specifically, to a method, apparatus, electronic device, and storage medium for determining circuit aging curves. Background Technology

[0002] Process variations in semiconductor manufacturing can cause random changes in device characteristic parameters, ultimately limiting circuit yield. Furthermore, aging effects can also lead to circuit failures, thus affecting circuit lifespan. Therefore, during the design phase, to fully understand the performance of circuits after aging, it is usually necessary to assess the impact of manufacturing process variations on circuit reliability. However, currently, evaluating circuit aging under process variations requires extensive simulation analysis, which is computationally intensive and time-consuming. Summary of the Invention

[0003] The purpose of this application is to provide a method, apparatus, electronic device and storage medium for determining circuit aging curves, so as to improve the problem of large amount of calculation and long time consumption when evaluating the aging of circuits under process deviations.

[0004] In a first aspect, this application provides a method for determining a circuit aging curve, comprising: simulating process deviations of a circuit under test (TBT) in a healthy state to determine a health curve; wherein the health curve characterizes the difference in operating frequency of the TBT in a healthy state due to process deviations; performing an aging simulation on the TBT to determine aging parameters under a preset failure standard; the aging coefficient characterizes the operating frequency of the TBT after aging under the preset failure standard; and determining the aging curve of the TBT based on the standard deviation of the health curve and the aging parameters; wherein the aging curve characterizes the difference in operating frequency of the TBT after aging due to process deviations.

[0005] In this embodiment of the application, when evaluating the aging of a circuit under process deviation, since the standard deviations of the health curve and the aging curve of the circuit under test are basically the same, the standard deviation of the health curve is directly used as the standard deviation of the aging curve. Only one aging simulation is needed for the circuit under test to determine the aging coefficient of the circuit under test under the preset failure standard. Then, the aging curve of the circuit under test is determined based on the aging coefficient and the standard deviation of the health curve. There is no need to perform multiple aging simulations, which reduces the computational resources consumed by simulation analysis and reduces the time spent determining the aging curve.

[0006] In an optional implementation, the process deviation of the circuit under test in a healthy state to determine the health curve includes: performing Monte Carlo simulation on the circuit under test to determine the normal distribution curve of the operating frequency of the circuit under test in a healthy state; the normal distribution curve is the health curve.

[0007] In this embodiment of the application, Monte Carlo simulation is performed on the circuit under test to accurately simulate the difference in operating frequency of the circuit under test caused by process deviation.

[0008] In an optional implementation, the step of performing an aging simulation on the circuit under test to determine the aging parameters under a preset failure standard includes: performing an aging simulation on the circuit under test according to an aging model under a preset process angle to determine the aging coefficient of the aged circuit under test under the preset failure standard.

[0009] In this application embodiment, aging simulation is performed at different process corners according to actual needs, and the aging coefficient at the corresponding process corner is determined, so that the circuit aging curve determination method provided in this application embodiment can determine the aging curve at various process corners.

[0010] In an optional implementation, the preset process angle includes: TT angle, FF angle, SS angle, FS angle, or SF angle.

[0011] In an optional implementation, determining the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters includes: determining the expected value corresponding to the aging curve of the circuit under test based on the aging parameters and the standard deviation of the health curve; and generating the aging curve of the circuit under test based on the standard deviation of the health curve and the expected value corresponding to the aging curve of the circuit under test.

[0012] In an optional implementation, after determining the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters, the method further includes: determining a relative frequency degradation curve based on the expected values ​​of the aging curve and the expected values ​​of the health curve.

[0013] In this embodiment of the application, after determining the health curve and aging curve of the circuit under test, a relative frequency degradation curve is determined based on the expected values ​​of the health curve and aging curve. The relative frequency degradation curve reflects the relative frequency degradation rate of the circuit under test, and the aging status of the circuit under test can be more intuitively reflected through the relative frequency degradation curve.

[0014] In an optional implementation, after determining the relative frequency degradation curve, the method further includes: correcting the relative frequency degradation curve according to a correction coefficient to determine the corrected relative frequency degradation curve; wherein the correction coefficient is used to characterize the relationship between the measured relative frequency degradation curve and the simulated relative frequency degradation curve.

[0015] In this embodiment, since the determined relative frequency degradation curve is based on simulation results, there will be a certain deviation between it and the actual working condition of the circuit under test. The correction coefficient is used to characterize the relationship between the measured relative frequency degradation curve and the simulated relative frequency degradation curve. The relative frequency degradation curve is calibrated according to the calibration coefficient, thereby reducing the deviation introduced by simulation, so that the calibrated relative frequency degradation curve more accurately reflects the circuit aging caused by process deviation.

[0016] Secondly, this application provides a circuit aging curve determination device, comprising: a simulation module for simulating process deviations in a healthy state of the circuit under test and determining a health curve; wherein the health curve characterizes the operating frequency difference of the circuit under test in a healthy state due to process deviations; a parameter determination module for performing an aging simulation on the circuit under test and determining aging parameters under a preset failure standard; wherein the aging coefficient characterizes the operating frequency of the aged circuit under test corresponding to the preset failure standard; and a curve determination module for determining the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters; wherein the aging curve characterizes the operating frequency difference of the circuit under test after aging due to process deviations.

[0017] In an optional implementation, the simulation module is specifically used to perform Monte Carlo simulation on the circuit under test to determine the normal distribution curve of the operating frequency of the circuit under test in a healthy state; the normal distribution curve is the healthy curve.

[0018] In an optional implementation, the parameter determination module is specifically used to perform an aging simulation on the circuit under test according to the aging model under a preset process angle, and determine the aging coefficient of the circuit under test after aging under the preset failure standard.

[0019] In an optional implementation, the preset process angle includes: TT angle, FF angle, SS angle, FS angle, or SF angle.

[0020] In an optional implementation, the curve determination module is specifically used to determine the expected value corresponding to the aging curve of the circuit under test based on the aging parameters and the standard deviation of the health curve; and to generate the aging curve of the circuit under test based on the standard deviation of the health curve and the expected value corresponding to the aging curve of the circuit under test.

[0021] In an optional implementation, the curve determination module is further configured to determine a relative frequency degradation curve based on the expected aging curve and the expected health curve.

[0022] In an optional embodiment, the circuit aging curve determination device further includes a correction module, used to correct the relative frequency degradation curve according to a correction coefficient, and determine the corrected relative frequency degradation curve; wherein, the correction coefficient is used to characterize the relationship between the measured relative frequency degradation curve and the simulated relative frequency degradation curve.

[0023] Thirdly, this application provides an electronic device, including: a memory and a processor, the processor being connected to the memory; the memory being used to store a program; the processor being used to invoke the program stored in the memory to execute the method as described in any of the foregoing embodiments.

[0024] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the method as described in any of the foregoing embodiments. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A flowchart illustrating a method for determining an aging curve provided in an embodiment of this application;

[0027] Figure 2 A schematic diagram of a health curve and an aging curve provided for embodiments of this application;

[0028] Figure 3 A schematic diagram of a relative probability curve and a corrected relative probability curve provided for embodiments of this application;

[0029] Figure 4 A structural block diagram of a circuit aging curve determination device provided in an embodiment of this application;

[0030] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0031] Icons: 400 - Circuit aging curve determination device; 401 - Simulation module; 402 - Parameter determination module; 403 - Curve determination module; 404 - Calibration module; 500 - Electronic equipment; 501 - Processor; 502 - Communication interface; 503 - Memory; 504 - Bus. Detailed Implementation

[0032] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0033] It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, relational terms such as "first," "second," etc., in the description of this application are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one…" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0034] This application provides a method, apparatus, electronic device, and storage medium for determining circuit aging curves, which reduces the amount of simulation calculations and improves processing efficiency when evaluating and analyzing the aging of circuits under process deviations.

[0035] The following is combined with Figure 1 The method for determining the aging curve provided in the embodiments of this application will be described. Figure 1 A flowchart illustrating a method for determining an aging curve provided in this application embodiment, the method comprising:

[0036] S101: Simulate the process deviation of the circuit under test in a healthy state to determine the health curve.

[0037] Circuits are composed of various semiconductor devices. During the manufacturing process of semiconductor devices, process deviations will cause random variations in the characteristic parameters of the semiconductor devices, ultimately limiting the yield of the circuit. In addition, aging effects will also cause circuit failures, thus affecting the circuit's lifespan. Therefore, in the circuit design phase, in order to fully understand the performance of the circuit after aging, it is usually necessary to evaluate the impact of process deviations during the manufacturing process on the circuit's reliability.

[0038] In this embodiment, the operating frequency of the circuit under test (DUT) is selected as a characteristic parameter. Since process deviations are random, when simulating the impact of these deviations on the circuit's operating frequency, random sampling can be used to simulate the frequency difference caused by process deviations in a healthy state, thus obtaining a health curve. This health curve characterizes the frequency difference of the DUT in a healthy state due to process deviations.

[0039] It should be noted that there are various ways to simulate the process deviation of the circuit under test in a healthy state by random sampling, such as Monte Carlo simulation, numerical probability simulation, Sherwood simulation, etc. This application does not make specific limitations on this.

[0040] In some embodiments, the specific process of S101 described above may be: performing Monte Carlo simulation on the circuit under test to determine the normal distribution curve of the operating frequency of the circuit under test in a healthy state.

[0041] In this embodiment, the Monte Carlo algorithm is used to simulate the operating frequency difference of the circuit under test due to process deviation in a healthy state, and a normal distribution curve is determined as the health curve of the circuit under test.

[0042] Because MOSFET parameters vary significantly between different transistors in the circuit under test and between different batches of transistors, process engineers must ensure that transistor performance remains within a certain range to alleviate the difficulty of circuit design. This is achieved by scrapping chips that exceed this performance range to strictly control expected parameter variations. The performance range of transistors is provided in the form of process corners, limiting the speed fluctuation range of NMOS and PMOS transistors to different process corners.

[0043] In the 5-Corner model, five process corners are defined: TT (Typical corner of NFET and Typical corner of PFET), FF (Fast corner of NFET and Fast corner of PFET), SS (Slow corner of NFET and Slow corner of PFET), FS (Fast corner of NFET and Slow corner of PFET), and SF (Slow corner of NFET and Fast corner of PFET). "Typical" indicates that the transistor drive current is at its average value, "Fast" indicates that the transistor drive current is at its maximum value, and "Slow" indicates that the transistor drive current is at its minimum value.

[0044] When determining the health curve of the circuit under test, Monte Carlo simulation can be performed at different process angles according to actual needs, thereby simulating the impact of process deviations at the corresponding process angles on the operating frequency of the circuit under test.

[0045] For example, please refer to Figure 2 Under the TT angle, Monte Carlo simulation was performed on the circuit under test in a healthy state, and the results were as follows: Figure 2 The normal distribution curve shown is shown. Figure 2 The curve on the right is the health curve of the circuit under test (DUT). The horizontal axis represents the operating frequency of the DUT, and the vertical axis represents the probability of the DUT operating at different frequencies under process variations. According to the health curve of the DUT, the main operating frequency of the DUT in a healthy state is 3.52 GHz.

[0046] In other embodiments, Monte Carlo simulation can be performed on the circuit under test in a healthy state at other process angles. Other process angles can be: FF angle, SS angle, FS angle and SF angle, etc., which are not limited in this application.

[0047] S102: Perform an aging simulation on the circuit under test to determine the aging parameters under the preset failure criteria.

[0048] When performing aging simulation, an aging model is selected to perform an aging simulation on the circuit under test to determine the aging parameters under preset failure criteria. The aging coefficient represents the operating frequency of the circuit under test after aging under the preset failure criteria.

[0049] The aging model can be designed based on the High Temperature Operating Life Test (HTOL). HTOL involves subjecting the chip to high temperatures, applying dynamic signals, and operating it for an extended period to evaluate its lifespan and determine its reliability. During aging simulation, temperature, time, operating voltage, and failure criteria are input as aging conditions, and the aging model performs the simulation. Here, temperature represents the temperature value set for the high-temperature conditions during HTOL, time represents the duration of HTOL, and operating voltage represents the voltage value of the dynamic signals applied during HTOL.

[0050] The failure criterion Tx% represents the cumulative failure criterion of the aging model. When x% of the samples fail, the batch of samples is considered to have failed. For example, if the failure criterion is T0.1%, and a batch of 10,000 circuits under test is considered to have failed when 10 circuits under test have failed.

[0051] In actual aging simulations, failure criteria can be set as T0.1%, T0.5%, T1%, etc., and this application does not limit them.

[0052] As an optional implementation, the specific process of S102 above may be: under a preset process angle, perform an aging simulation on the circuit under test according to the aging model to determine the aging coefficient of the circuit under test after aging under a preset failure standard.

[0053] In this embodiment of the application, to ensure that the aging simulation results correspond to the simulation performed in the healthy state, the preset process angle is the same as that used in the simulation performed in the healthy state during the aging simulation. Under the preset process angle, an aging simulation is performed on the circuit under test according to the aging model to determine the aging coefficient of the circuit under test after aging under the preset failure criteria.

[0054] S103: Determine the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters.

[0055] In this embodiment, the aging curve is used to characterize the difference in operating frequency caused by process deviations after the circuit under test has aged. Experimental data shows that the standard deviation of the healthy curve and the standard deviation of the aging curve are basically the same. Therefore, to reduce the amount of simulation calculations required to determine the aging curve of the circuit under test, the standard deviation of the healthy curve is directly used as the standard deviation of the aging curve.

[0056] As an optional implementation, the specific process of S103 above may be: determining the expected value corresponding to the aging curve of the circuit under test based on the aging parameters and the standard deviation of the health curve; generating the aging curve of the circuit under test based on the standard deviation of the health curve and the expected value corresponding to the aging curve of the circuit under test.

[0057] In this embodiment, the aging curve of the circuit under test is a normal distribution curve, which is determined by the standard deviation and the expected value. As described above, the standard deviation of the healthy curve and the standard deviation of the aging curve are basically the same. Therefore, the standard deviation of the healthy curve is used as the standard deviation of the aging curve.

[0058] Based on the characteristics of the normal distribution curve, the expected value of the aging curve can be determined by the following formula:

[0059] μ aged =μ1-z*σ

[0060] Where, μ aged Let μ1 be the expected value of the aging curve, z be the quantile, and σ be the standard deviation of the aging curve.

[0061] The quantile z is determined based on the failure criterion for determining aging parameters and the quantile table of the standard normal distribution. When the failure criterion is Tx%, the quantile z is the value corresponding to the cumulative distribution probability of 1-x% in the quantile table of the standard normal distribution.

[0062] After determining the expected value of the aging curve using the above formula, the aging curve of the circuit under test can be generated based on the standard deviation and the expected value of the aging curve.

[0063] For example, such as Figure 2 As shown, Figure 2 The curve on the left is the aging curve of the circuit under test under TT angle. Due to aging, the main operating frequency of the circuit under test is reduced from 3.52GHz to 2.94GHz.

[0064] Furthermore, after determining the aging curve, the aging curve determination method provided in this application embodiment may also include the following: determining the relative frequency degradation curve based on the expected aging curve and the expected health curve.

[0065] The relative frequency degradation curve characterizes the relationship between the operating frequency of the circuit under test (DUT) in a healthy state and the operating frequency of the DUT after aging. After determining the aging curve and the healthy curve of the DUT, the expected value of the relative frequency degradation curve is calculated using the following formula:

[0066] μ1=(μ fresh -μ aged ) / μ fresh

[0067] Where μ1 is the expectation of the relative frequency degradation curve, μ fresh For the expected value of the health curve, μ aged This represents the expected value of the aging curve. The standard deviation of the relative frequency degradation curve is the same as that of the aging curve. The relative frequency degradation curve is generated based on the expected value of the relative frequency degradation curve and the standard deviation of the aging curve.

[0068] For example, a relative probability curve can be like... Figure 3 The right curve in the middle, Figure 3 The horizontal axis of the relative frequency degradation curve represents the attenuation rate of the operating frequency of the circuit under test (the ratio of the difference between the operating frequency of the circuit under test in the healthy state and the operating frequency of the circuit under test after aging to the operating frequency of the circuit under test in the healthy state), and the vertical axis represents the probability of the attenuation rate of the operating frequency of the circuit under test under process deviation.

[0069] Furthermore, after determining the relative frequency degradation curve, the aging curve determination method provided in this application embodiment may further include the following: correcting the relative frequency degradation curve according to the correction coefficient to determine the corrected relative frequency degradation curve; wherein, the correction coefficient is used to characterize the relationship between the measured relative frequency degradation curve and the simulated relative frequency degradation curve.

[0070] In this embodiment, the relative probability degradation curve is determined based on the health curve and aging curve, which are determined through simulation of the circuit under test. The simulated health curve and aging curve will deviate somewhat from the actual operating conditions of the circuit under test, thus causing a deviation in the relative probability degradation curve. To reduce this deviation, after determining the relative probability degradation curve, the relative frequency degradation curve is corrected according to a preset correction coefficient to determine the corrected relative frequency degradation curve. The corrected relative probability curve can be as follows: Figure 3 The left curve in the image.

[0071] The correction factor can be determined as follows: Under a certain manufacturing process, the circuit undergoes actual aging tests and simulated aging tests to obtain the measured relative frequency degradation curve and the simulated relative frequency degradation curve. The ratio between the expected value of the measured relative frequency degradation curve and the expected value of the simulated relative frequency degradation curve is used as the correction factor.

[0072] After determining the calibration coefficient, for the circuit under test manufactured using the same manufacturing process as the calibration coefficient, after determining the relative frequency degradation curve (which is the simulated relative frequency degradation curve) in the above manner, the relative frequency degradation curve can be calibrated according to the calibration coefficient, thereby reducing the deviation introduced by simulation and making the calibrated relative frequency degradation curve more accurately reflect the circuit aging caused by process deviation.

[0073] Based on the same inventive concept, this application also provides a circuit aging curve determination device. Please refer to... Figure 4 , Figure 4 This application provides a structural block diagram of a circuit aging curve determination device 400, which may include:

[0074] The simulation module 401 is used to simulate the process deviation of the circuit under test in a healthy state and determine the health curve; wherein, the health curve is used to characterize the difference in operating frequency of the circuit under test due to process deviation in a healthy state.

[0075] The parameter determination module 402 performs an aging simulation on the circuit under test to determine the aging parameters under a preset failure standard; the aging coefficient characterizes the operating frequency of the circuit under test after aging under the preset failure standard.

[0076] The curve determination module 403 is used to determine the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters; wherein the aging curve is used to characterize the difference in operating frequency caused by process deviation after the circuit under test has aged.

[0077] In an optional implementation, the simulation module 401 is specifically used to perform Monte Carlo simulation on the circuit under test to determine the normal distribution curve of the operating frequency of the circuit under test in a healthy state; the normal distribution curve is the healthy curve.

[0078] In an optional implementation, the parameter determination module 402 is specifically used to perform an aging simulation on the circuit under test according to the aging model under a preset process angle, and determine the aging coefficient of the circuit under test after aging under the preset failure standard.

[0079] In an optional implementation, the preset process angle includes: TT angle, FF angle, SS angle, FS angle, or SF angle.

[0080] In an optional implementation, the curve determination module 403 is specifically used to determine the expected value corresponding to the aging curve of the circuit under test based on the aging parameters and the standard deviation of the health curve; and to generate the aging curve of the circuit under test based on the standard deviation of the health curve and the expected value corresponding to the aging curve of the circuit under test.

[0081] In an optional implementation, the curve determination module 403 is further configured to determine a relative frequency degradation curve based on the expected aging curve and the expected health curve.

[0082] In an optional embodiment, the circuit aging curve determination device further includes a correction module 404, used to correct the relative frequency degradation curve according to a correction coefficient, and determine the corrected relative frequency degradation curve; wherein, the correction coefficient is used to characterize the relationship between the measured relative frequency degradation curve and the simulated relative frequency degradation curve.

[0083] The circuit aging curve determination device 400 corresponds to the aforementioned circuit aging curve determination method, and each functional module corresponds to each step of the aforementioned circuit aging curve determination method. Therefore, the implementation methods of each functional module refer to the implementation methods of the circuit aging curve determination method in the aforementioned embodiments, and will not be repeated here.

[0084] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device 500 according to an embodiment of this application. The electronic device 500 includes: at least one processor 501, at least one communication interface 502, at least one memory 503, and at least one bus 504. The bus 504 is used to enable direct communication between these components, the communication interface 502 is used for signaling or data communication with other node devices, and the memory 503 stores machine-readable instructions executable by the processor 501. When the electronic device 500 is running, the processor 501 communicates with the memory 503 via the bus 504. When the machine-readable instructions are invoked by the processor 501, the circuit aging curve determination method described above is executed.

[0085] Processor 501 can be an integrated circuit chip with signal processing capabilities. The processor 501 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor.

[0086] The memory 503 may include, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0087] Understandable. Figure 5 The structure shown is for illustrative purposes only; the electronic device 500 may also include components that are more advanced than those shown. Figure 5 The more or fewer components shown, or having the same Figure 5 The different configurations shown. Figure 5 The components shown can be implemented using hardware, software, or a combination thereof. In the embodiments of this application, electronic device 500 can be, but is not limited to, physical devices such as desktop computers, laptops, smartphones, smart wearable devices, and in-vehicle devices, or virtual devices such as virtual machines. Furthermore, electronic device 500 is not necessarily a single device; it can be a combination of multiple devices, such as a server cluster.

[0088] Furthermore, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when run by a computer, executes the steps of the circuit aging curve determination method as described in the above embodiments.

[0089] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0090] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some communication interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0091] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0093] It should be noted that if the function is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0095] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for determining the aging curve of a circuit, characterized in that, include: The process deviation of the circuit under test in a healthy state is simulated to determine the health curve; wherein, the health curve is used to characterize the difference in operating frequency of the circuit under test due to process deviation in a healthy state. An aging simulation is performed on the circuit under test to determine the aging parameters under a preset failure standard; the aging coefficient characterizes the operating frequency of the circuit under test after aging under the preset failure standard. The aging curve of the circuit under test is determined based on the standard deviation of the health curve and the aging parameters; wherein, the aging curve is used to characterize the difference in operating frequency caused by process deviation after the circuit under test has aged. Wherein, the aging curve is a normally distributed curve, and the normally distributed curve is determined by the standard deviation and the expected value; the step of determining the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters includes: The expected value of the aging curve of the circuit under test is determined based on the aging parameters and the standard deviation of the health curve; wherein the standard deviation of the health curve is equal to the standard deviation of the aging curve. The aging curve of the circuit under test is generated based on the standard deviation of the health curve and the expected value corresponding to the aging curve of the circuit under test.

2. The method for determining the circuit aging curve according to claim 1, characterized in that, The process deviation of the simulated circuit under test in a healthy state is used to determine the health curve, including: Monte Carlo simulation is performed on the circuit under test to determine the normal distribution curve of the operating frequency of the circuit under test in a healthy state; the normal distribution curve is the healthy curve.

3. The method for determining the circuit aging curve according to claim 1, characterized in that, The step of performing an aging simulation on the circuit under test to determine the aging parameters under a preset failure standard includes: Under a preset process angle, an aging simulation is performed on the circuit under test according to the aging model to determine the aging coefficient of the circuit under test after aging under the preset failure standard.

4. The method for determining the circuit aging curve according to claim 3, characterized in that, The preset process angles include: TT angle, FF angle, SS angle, FS angle, or SF angle.

5. The method for determining the circuit aging curve according to claim 1, characterized in that, After determining the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters, the method further includes: The relative frequency degradation curve is determined based on the expected values ​​of the aging curve and the expected values ​​of the health curve.

6. The method for determining the circuit aging curve according to claim 5, characterized in that, After determining the relative frequency degradation curve, the method further includes: The relative frequency degradation curve is corrected according to the correction coefficient to determine the corrected relative frequency degradation curve; wherein, the correction coefficient is used to characterize the relationship between the measured relative frequency degradation curve and the simulated relative frequency degradation curve.

7. A device for determining the aging curve of a circuit, characterized in that, include: The simulation module is used to simulate the process deviation of the circuit under test in a healthy state and determine the health curve; wherein, the health curve is used to characterize the difference in operating frequency of the circuit under test due to process deviation in a healthy state. The parameter determination module performs an aging simulation on the circuit under test to determine the aging parameters under a preset failure standard; the aging coefficient characterizes the operating frequency of the circuit under test after aging under the preset failure standard. The curve determination module is used to determine the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters; wherein, the aging curve is used to characterize the difference in operating frequency caused by process deviation after the circuit under test has aged; Wherein, the aging curve is a normally distributed curve, and the normally distributed curve is determined by the standard deviation and the expected value; the step of determining the aging curve of the circuit under test based on the standard deviation of the health curve and the aging parameters includes: The expected value of the aging curve of the circuit under test is determined based on the aging parameters and the standard deviation of the health curve; wherein the standard deviation of the health curve is equal to the standard deviation of the aging curve. The aging curve of the circuit under test is generated based on the standard deviation of the health curve and the expected value corresponding to the aging curve of the circuit under test.

8. An electronic device, characterized in that, include: A memory and a processor, wherein the processor is connected to the memory; The memory is used to store programs; The processor is configured to invoke a program stored in the memory to execute the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, performs the method as described in any one of claims 1-6.

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