An integrated circuit reliability analysis method and apparatus

Abstract

This invention proposes a method and apparatus for integrated circuit reliability analysis. The method involves acquiring multi-source heterogeneous data of the integrated circuit; extracting reliability evaluation data of the integrated circuit from the multi-source heterogeneous data; calculating dynamic fault indices of the integrated circuit, where each indice is a positive integer between 1 and 2, representing the number of reliability evaluation dimensions of the integrated circuit; calculating the reliability coupling degree between each pair of dynamic fault indices, where each pair is a positive integer between 1 and the number of couplings; constructing a reliability coupling model with the dynamic fault indices as reliability evaluation nodes and the adaptive coupling degree as edges; and calculating the reliability of the integrated circuit based on the reliability coupling model. This approach results in higher accuracy and greater practicality in the reliability analysis of the integrated circuit.

Description

Technical Field

[0001] This invention relates to the field of integrated circuit technology, and in particular to a method and apparatus for integrated circuit reliability analysis. Background Technology

[0002] Reliability analysis of integrated circuits refers to the systematic quantitative evaluation of an integrated circuit's ability to maintain its designed functional integrity within specified environmental stresses, operating conditions, and expected lifespan. Common methods for integrated circuit stability analysis include failure mechanism modeling, accelerated life testing, failure data statistics, and simulation deduction. These methods analyze the device failure rate, mean time between failures (MTBF), and distribution of weak points in the integrated circuit, providing a data foundation for chip architecture optimization, process window calibration, and the construction of quality control systems.

[0003] As semiconductor processes enter the angstrom-scale era, the widespread application of technologies such as 3D stacking and heterogeneous integration has led to a surge in interconnect density in storage circuits and highlighted multi-physics coupling effects. The reliability issues of integrated circuits have evolved from single-device degradation problems to systemic problems spanning scales and levels. Traditional integrated circuit reliability analysis methods rely on using Black's equations to predict electromigration lifetime, assessing the risk of open circuits caused by thermomechanical stress through the finite element method, performing linear superposition calculations of component failure rates using standard manuals, and conducting test coverage simulations based on the Stuck-at Fault model. While these methods possess engineering applicability in specific dimensions, their highly isolated analytical perspectives result in significant prediction biases at advanced process nodes, leading to excessive design redundancy or insufficient protection, and failing to effectively identify potential security risks in integrated circuit design. Summary of the Invention

[0004] Based on the above-mentioned problems, this invention proposes a method and apparatus for integrated circuit reliability analysis, which makes the reliability analysis results of integrated circuits more accurate and more practical.

[0005] In view of this, a first aspect of the present invention provides a method for integrated circuit reliability analysis, comprising: Acquire multi-source heterogeneous data from integrated circuits; Reliability evaluation data of the integrated circuit is extracted from the multi-source heterogeneous data; Calculate the dynamic fault index of the integrated circuit. ,in From 1 to Positive integers between The number of reliability evaluation dimensions for the integrated circuit; Calculate the reliability coupling degree between each pair of the dynamic failure indicators. ,in From 1 to the number of couplings Positive integers between; Constructing the dynamic fault index As a reliability assessment node, with the aforementioned adaptive coupling degree The reliability coupling model for the edges; The reliability of the integrated circuit is calculated based on the aforementioned reliability coupling model. .

[0006] Optionally, the reliability coupling degree between each pair of the dynamic failure indices can be calculated. The specific steps include: Obtain multi-chip sample test data of the integrated circuit; Based on the multi-chip sample test data, a set of sample datasets corresponding to each dynamic fault indicator is generated: , Each of the sample datasets Includes Each corresponding dynamic fault indicator Numerical elements; Define a count variable , ,in The number of pre-configured distribution intervals, and ; Calculate the first The first dynamic fault indicator and the first The joint probability of several dynamic fault indicators and marginal probability , ; Determine a with and corresponding Value, to calculate the first value in the reliability coupling model. Coupling degree of the strip: .

[0007] Optionally, calculate the first The first dynamic fault indicator and the first The joint probability of several dynamic fault indicators and marginal probability , The specific steps include: Constructing a reflection of the first The first dynamic fault indicator and the first The joint distribution matrix of the numerical distribution of each dynamic fault indicator. ; Calculate the first one respectively The first dynamic fault indicator and the first Marginal probabilities of dynamic fault indicators: ; Calculate the first The first dynamic fault indicator and the first The joint probability of the dynamic fault indicators: .

[0008] Optionally, construct a reflection of the first The first dynamic fault indicator and the first The joint distribution matrix of the distribution states of the dynamic fault indicators The specific steps include: Based on the numerical values ​​of the dynamic fault indicators in the sample dataset for each dynamic fault indicator, a dynamic distribution interval set corresponding to each dynamic fault indicator is generated: , Traverse the first The first dynamic fault indicator and the first The dynamic distribution interval set of each dynamic fault indicator is used to determine the number of intersections in the indicator distributions. The number of intersections for The group of sample data simultaneously satisfies and Quantity; The number of intersections Determined as the joint distribution matrix The Middle Okay, number The numerical element at the column position.

[0009] Optionally, the step of generating a dynamic distribution interval set corresponding to each dynamic fault indicator based on the numerical value of the dynamic fault indicator in the sample dataset of each dynamic fault indicator specifically includes: The first Sample dataset of dynamic fault indicators Represented as: ; Determine the first Sample dataset of dynamic fault indicators The maximum index value in and minimum index value : ; Based on the sample dataset The numerical distribution in the range of values Divided into A continuous subinterval: .

[0010] Optionally, based on the sample dataset The numerical distribution in the range of values Divided into The steps for traversing a continuous subinterval specifically include: Configure distribution deviation threshold ; Based on the sample dataset The numerical distribution in the range of values China has determined One boundary value: ; Use the boundary value to define the numerical range Divided into A continuous subinterval: ; make Then for 2 to any between The value satisfies: , in The sample dataset represents In The dynamic fault index value falls within the dynamic distribution interval set. The number of sub-intervals.

[0011] Optionally, the reliability of the integrated circuit can be calculated based on the reliability coupling model. The specific steps include: Calculate the normalized evaluation coefficient for each reliability evaluation node in the reliability coupling model. ; Calculate the dynamic failure index for each reliability evaluation node of the integrated circuit under evaluation. ; Based on the normalized evaluation coefficients and the aforementioned dynamic fault indicators Calculate the reliability of each reliability evaluation node of the integrated circuit to be evaluated: .

[0012] Optionally, the normalized evaluation coefficient of each reliability evaluation node in the reliability coupling model is calculated. The specific steps include: Calculate the overall coupling degree of each reliability assessment node. The overall coupling degree Reflecting the The structural importance of each reliability assessment node in the reliability coupling model; Define a count variable ; The normalized evaluation coefficients for each reliability evaluation node are obtained by normalizing the overall coupling degree. .

[0013] Optionally, calculate the overall coupling degree of each reliability assessment node. The specific steps include: Define a count variable ; Obtain the reliability coupling model except for the first Besides the first reliability assessment node, the other reliability assessment nodes are related to the first... Reliability coupling between reliability assessment nodes ; Calculate the first The overall coupling degree of the reliability assessment nodes: .

[0014] A second aspect of the present invention provides an integrated circuit reliability analysis apparatus, comprising a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the integrated circuit reliability analysis method according to any one of the first aspects of the present invention.

[0015] This invention proposes a method and apparatus for integrated circuit reliability analysis, which acquires multi-source heterogeneous data of integrated circuits; Reliability evaluation data of the integrated circuit is extracted from the multi-source heterogeneous data; dynamic failure indices of the integrated circuit are calculated. ,in From 1 to Positive integers between The number of reliability evaluation dimensions for the integrated circuit; calculate the reliability coupling degree between each pair of the dynamic failure indicators. ,in From 1 to the number of couplings Positive integers between; constructing the dynamic fault index As a reliability assessment node, with the aforementioned adaptive coupling degree A reliability coupling model is used to define the edges; the reliability of the integrated circuit is calculated based on the reliability coupling model. This makes the reliability analysis results of integrated circuits more accurate and more practical. Attached Figure Description

[0016] Figure 1 This is a flowchart of an integrated circuit reliability analysis method provided in one embodiment of the present invention. Detailed Implementation

[0017] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0019] In the description of this invention, the term "multiple" refers to two or more. Unless otherwise explicitly defined, the terms "upper," "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. The terms "connect," "install," "fix," etc., should be interpreted broadly. For example, "connect" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "multiple" means two or more.

[0020] In the description of this specification, the terms "one embodiment," "some implementations," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0021] The following description, with reference to the accompanying drawings, illustrates a method and apparatus for integrated circuit reliability analysis according to some embodiments of the present invention.

[0022] like Figure 1 As shown, the first aspect of the present invention proposes an integrated circuit reliability analysis method, comprising: Acquire multi-source heterogeneous data from integrated circuits; Reliability evaluation data of the integrated circuit is extracted from the multi-source heterogeneous data; Calculate the dynamic fault index of the integrated circuit. ,in From 1 to Positive integers between The number of reliability evaluation dimensions for the integrated circuit; Calculate the reliability coupling degree between each pair of the dynamic failure indicators. ,in From 1 to the number of couplings Positive integers between; Constructing the dynamic fault index As a reliability assessment node, with the aforementioned adaptive coupling degree The reliability coupling model for the edges; The reliability of the integrated circuit is calculated based on the aforementioned reliability coupling model. .

[0023] The heterogeneous data of the integrated circuits includes, but is not limited to, the circuit design files of the integrated circuits (such as design files in .gds or .lef format), test logs, FMEA (Failure Mode and Effects Analysis) databases, etc.

[0024] The reliability evaluation data is extracted from the multi-source heterogeneous data, and after structured processing, it is basic data reflecting the circuit attributes and working status of the integrated circuit. The structured processing includes, but is not limited to, performing abnormal data removal, dimension unification processing, and formatting processing on the original data in the multi-source heterogeneous data (for example, generating data in JSON or XML format from the multi-source heterogeneous data after dimension unification processing).

[0025] In some embodiments of the present invention, the reliability evaluation data of the integrated circuit includes, but is not limited to, component layer data, logic gate layer data, and wire layer data. The component layer data, logic gate layer data, and wire layer data respectively reflect the basic attributes and operating states of the integrated circuit at the component layer, logic gate layer, and wire layer, respectively. The dynamic fault indicators of the integrated circuit... This includes, but is not limited to, the component failure rate indicators, logic gate error probability indicators, and wire failure probability indicators of the integrated circuit. The reliability coupling degree... It reflects the dynamic fault index. Coupling data representing the degree of coupling between pairs of data.

[0026] The dynamic fault indicators This refers to the failure probability of the integrated circuit under various operating conditions (corresponding to environmental parameter configurations in various actual working scenarios, including normal working scenarios and working scenarios under extreme conditions), reflecting the risk of failure of the integrated circuit's partial or overall functions. In some embodiments, the dynamic failure index may also include more specific failure indicators such as open-circuit failure rate, short-circuit failure rate, gate oxide breakdown rate, leakage current failure rate, thermal failure rate, and gain reduction failure rate.

[0027] The technical solution of the above-described implementation method performs automated feature extraction by parsing multi-source heterogeneous data of the integrated circuit, such as netlist file data, and generates a topological network structure (i.e., the topological structure of the reliability coupling model) that can reflect the coupling relationship between dynamic fault indicators of the integrated circuit, making the reliability analysis results of the integrated circuit more comprehensive and accurate.

[0028] In the technical solution of the above embodiments, the reliability coupling model is a topological model reflecting the stability of the integrated circuit, which consists of a plurality of reliability evaluation nodes and edges connecting each reliability evaluation node in pairs. The reliability evaluation nodes in the reliability coupling model are dynamic failure indicators of the integrated circuit. The edges in the reliability coupling model reflect the degree of reliability coupling between the reliability evaluation nodes at their two ends. .

[0029] In the reliability coupling model, there is an edge connecting any two reliability evaluation nodes; therefore, the number of couplings... satisfy: .

[0030] Furthermore, the reliability of the integrated circuit is calculated based on the aforementioned reliability coupling model. Following these steps, the following are also included: Configure the reliability level evaluation range of integrated circuits; The reliability of the integrated circuit The reliability level of the integrated circuit is determined by mapping it to the reliability level evaluation range.

[0031] For example, in the step of configuring the reliability level evaluation range of an integrated circuit, the reliability level of the integrated circuit can be divided into several levels such as "very unreliable", "unreliable", "average", "reliable" and "very reliable". Configured as "very unreliable" Configured as "unreliable" Configured as "normal" Configured as "reliable" The configuration is set to "Very Reliable". Of course, the above data is merely an example and does not imply that the technical solution of this invention is limited to the numerical range configured in this embodiment.

[0032] Optionally, the reliability coupling degree between each pair of the dynamic failure indices can be calculated. The specific steps include: Obtain multi-chip sample test data of the integrated circuit; Based on the multi-chip sample test data, a set of sample datasets corresponding to each dynamic fault indicator is generated: , Each of the sample datasets Includes Each corresponding dynamic fault indicator Numerical elements; Define a count variable , ,in The number of pre-configured distribution intervals, and ; Calculate the first The first dynamic fault indicator and the first The joint probability of several dynamic fault indicators and marginal probability , ; Determine a with and corresponding Value, to calculate the first value in the reliability coupling model. Coupling degree of the strip: .

[0033] In the technical solution of the above embodiments, the multi-chip sample test data is reliability evaluation data obtained by testing multiple chip samples of the integrated circuit in a test environment. To simplify the implementation process, the above embodiments configure the sample data volume (i.e., the number of numerical elements in the sample dataset) of each dynamic fault indicator to be uniform. In practical applications, different sample data volumes can be configured for each dynamic fault indicator based on the data characteristics of each dynamic fault indicator in the multi-chip sample test data.

[0034] In the step of generating a sample dataset corresponding to each dynamic fault index based on the multi-chip sample test data, the reliability evaluation data obtained from each test is calculated to obtain the value of each dynamic fault index. Therefore, the sample dataset corresponds one-to-one with each dynamic fault index, i.e., the index is... Sample dataset With subscript Dynamic Fault Indicators Correspondingly. More specifically, the sample dataset. For a containing A discrete numerical sequence of n numerical elements, where each numerical element is a dynamic fault index. The metric value. A sample dataset. It can be represented as follows: , In some implementations, a scheme can be adopted to calculate the dynamic fault indicators of different test chips separately based on the test data, for example... The first test sample used to represent the first test chip Dynamic Fault Indicators The index value, The first test sample used to represent the second test chip Dynamic Fault Indicators The index value, and so on, in the technical solution of this implementation, The size is the same as the number of test chips.

[0035] In other implementations, the sample dataset can also be constructed using a mixed sample data approach. This means simultaneously testing multiple or all test chips, and dividing the multi-chip sample test data into batches based on different test times, i.e., dividing the multi-chip sample test data into... In this implementation method, a batch of samples is used to extract sample datasets of various dynamic fault indicators. Used to represent the test data in the first test batch. Dynamic Fault Indicators The index value, The test data used to represent the second test batch Dynamic Fault Indicators The indicator values ​​are calculated in the same way.

[0036] Optionally, calculate the first The first dynamic fault indicator and the first The joint probability of several dynamic fault indicators and marginal probability , The specific steps include: Constructing a reflection of the first The first dynamic fault indicator and the first The joint distribution matrix of the numerical distribution of each dynamic fault indicator. ; Calculate the first one respectively The first dynamic fault indicator and the first Marginal probabilities of dynamic fault indicators: ; Calculate the first The first dynamic fault indicator and the first The joint probability of the dynamic fault indicators: .

[0037] The joint distribution matrix It is the first The first dynamic fault indicator and the first A matrix representation of the numerical distribution of each dynamic fault indicator. More specifically, the joint distribution matrix... Each numerical element reflects the first The first dynamic fault indicator and the first The number of dynamic fault indicators distributed across different numerical ranges.

[0038] In the technical solution of the above implementation, the marginal probability of a dynamic fault indicator reflects the likelihood of the fault event corresponding to that dynamic fault indicator occurring, or the frequency of the fault event occurring. Therefore, the joint probability of two dynamic fault indicators reflects the co-occurrence probability of the fault events corresponding to the two dynamic fault indicators, that is, the possibility that two fault events will occur simultaneously on the same test chip (or under the same operating conditions).

[0039] To simplify the implementation process, the above implementation method divides the numerical range of each dynamic fault indicator into the same number of distribution intervals. In practical applications, the number of distribution intervals for each dynamic fault indicator can be configured according to factors such as the sample size, numerical range, and distribution density. When the numerical range of each dynamic fault indicator is divided into the same number of distribution intervals... At that time, the joint distribution matrix For one OK A square matrix of columns.

[0040] Optionally, construct a reflection of the first The first dynamic fault indicator and the first The joint distribution matrix of the distribution states of the dynamic fault indicators The specific steps include: Based on the numerical values ​​of the dynamic fault indicators in the sample dataset for each dynamic fault indicator, a dynamic distribution interval set corresponding to each dynamic fault indicator is generated: , Traverse the first The first dynamic fault indicator and the first The dynamic distribution interval set of each dynamic fault indicator is used to determine the number of intersections in the indicator distributions. The number of intersections for The group of sample data simultaneously satisfies and Quantity; The number of intersections Determined as the joint distribution matrix The Middle Okay, number The numerical element at the column position.

[0041] The dynamic distribution interval set is a set of numerical intervals composed of several consecutive dynamic distribution intervals of the dynamic fault index. Each dynamic distribution interval is dynamically defined based on the numerical magnitude and quantity distribution of the corresponding dynamic fault index. The joint distribution matrix... The size of the numerical elements is determined by the number of dynamic fault index values ​​in the sample dataset of the corresponding dynamic fault index falling into each dynamic distribution interval.

[0042] Optionally, the step of generating a dynamic distribution interval set corresponding to each dynamic fault indicator based on the numerical value of the dynamic fault indicator in the sample dataset of each dynamic fault indicator specifically includes: The first Sample dataset of dynamic fault indicators Represented as: ; Determine the first Sample dataset of dynamic fault indicators The maximum index value in and minimum index value : ; Based on the sample dataset The numerical distribution in the range of values Divided into A continuous subinterval: .

[0043] In the above-described implementation, the boundary of the numerical range of a dynamic distribution interval set of a dynamic fault indicator is defined by the upper and lower limits of the sample dataset of the dynamic fault indicator. Therefore, the numerical range of the dynamic distribution interval set also changes dynamically under different test environments and test conditions. Thus, it is necessary to adapt the test environment parameters in combination with the working characteristics of the integrated circuit so that its reliability assessment results are more in line with the actual application environment.

[0044] Optionally, based on the sample dataset The numerical distribution in the range of values Divided into The steps for traversing consecutive subintervals specifically include: Configure distribution deviation threshold ; Based on the sample dataset The numerical distribution in the range of values China has determined One boundary value: ; Use the boundary value to define the numerical range Divided into A continuous subinterval: ; make Then for 2 to any between The value satisfies: , in The sample dataset represents In The dynamic fault index value falls within the dynamic distribution interval set. The number of sub-intervals.

[0045] Specifically, the distribution deviation threshold Data size depends on the number of samples The size of the distribution deviation threshold is used for adaptive configuration, and it is usually configured to a small value to ensure data balance among the sub-intervals in the dynamic distribution interval set. Preferably, the distribution deviation threshold... .

[0046] Optionally, the reliability of the integrated circuit can be calculated based on the reliability coupling model. The specific steps include: Calculate the normalized evaluation coefficient for each reliability evaluation node in the reliability coupling model. ; Calculate the dynamic failure index for each reliability evaluation node of the integrated circuit under evaluation. ; Based on the normalized evaluation coefficients and the aforementioned dynamic fault indicators Calculate the reliability of each reliability evaluation node of the integrated circuit to be evaluated: .

[0047] Specifically, the normalized evaluation coefficient It is a normalized coefficient reflecting the individual coupling degree characteristics of a reliability assessment node in the coupled topology of the reliability coupling model. Various dynamic fault indicators of the integrated circuit are used. and its corresponding normalized evaluation coefficient The reliability of the integrated circuit can be obtained by performing comprehensive calculations. .

[0048] Optionally, the normalized evaluation coefficient of each reliability evaluation node in the reliability coupling model is calculated. The specific steps include: Calculate the overall coupling degree of each reliability assessment node. The overall coupling degree Reflecting the The structural importance of each reliability assessment node in the reliability coupling model; Define a count variable ; The normalized evaluation coefficients for each reliability evaluation node are obtained by normalizing the overall coupling degree. .

[0049] Optionally, calculate the overall coupling degree of each reliability assessment node. The specific steps include: Define a count variable ; Obtain the reliability coupling model except for the first Besides the first reliability assessment node, the other reliability assessment nodes are related to the first... Reliability coupling between reliability assessment nodes ; Calculate the first The overall coupling degree of the reliability assessment nodes: .

[0050] In the technical solution of the above implementation method, the comprehensive coupling degree of each reliability assessment node is calculated. In the steps It refers to Within the range of Perform a series of multiplications.

[0051] by For example: .

[0052] As mentioned above, the reliability coupling model has Reliability assessment nodes (corresponding to) Dynamic Fault Indicators Therefore, each reliability assessment node (when it is the first) When a reliability assessment node is reached, it is related to other nodes. Each reliability assessment node can calculate a reliability coupling degree. ( Therefore, in calculating the overall coupling degree of each reliability assessment node... In the steps, The reliability assessment node is, except for the first one. Other reliability assessment nodes besides the existing reliability assessment node, i.e. The reliability assessment node I does not include the first... Each reliability assessment node itself. For ease of understanding, when calculating the overall coupling degree of each reliability assessment node, when its node number is determined... After that, it is necessary to do other things. Each reliability assessment node is between 1 and... Renumber them so that they can be used in practice. In 1 to When traversing the reliability assessment nodes, the 1st node will not be traversed. Each reliability assessment node itself.

[0053] A second aspect of the present invention provides an integrated circuit reliability analysis apparatus, comprising a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the integrated circuit reliability analysis method according to any one of the first aspects of the present invention.

[0054] It should be noted that, in this document, relational terms such as "first" and "second" 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. Furthermore, 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 limitation, 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.

[0055] As described above, these embodiments of the present invention do not exhaustively cover all details, nor do they limit the invention to the specific embodiments described. Clearly, many modifications and variations can be made based on the above description. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to effectively utilize the invention and its modifications. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for reliability analysis of integrated circuits, characterized in that, include: Acquire multi-source heterogeneous data from integrated circuits; Reliability evaluation data of the integrated circuit is extracted from the multi-source heterogeneous data; Calculate the dynamic fault index of the integrated circuit. ,in From 1 to Positive integers between The number of reliability evaluation dimensions for the integrated circuit; Calculate the reliability coupling degree between each pair of the dynamic failure indicators. ,in From 1 to the number of couplings Positive integers between; Constructing the dynamic fault index As a reliability assessment node, with the aforementioned adaptive coupling degree The reliability coupling model for the edges; The reliability of the integrated circuit is calculated based on the aforementioned reliability coupling model. .

2. The integrated circuit reliability analysis method according to claim 1, characterized in that, Calculate the reliability coupling degree between each pair of the dynamic failure indicators. The specific steps include: Obtain multi-chip sample test data of the integrated circuit; Based on the multi-chip sample test data, a set of sample datasets corresponding to each dynamic fault indicator is generated: ， Each of the sample datasets Includes Each corresponding dynamic fault indicator Numerical elements; Define a count variable , ,in The number of pre-configured distribution intervals, and ; Calculate the first The first dynamic fault indicator and the first The joint probability of several dynamic fault indicators and marginal probability , ; Determine a with and corresponding Value, to calculate the first value in the reliability coupling model. Coupling degree of the strip: 。 3. The integrated circuit reliability analysis method according to claim 2, characterized in that, Calculate the first The first dynamic fault indicator and the first The joint probability of several dynamic fault indicators and marginal probability , The specific steps include: Constructing a reflection of the first The first dynamic fault indicator and the first The joint distribution matrix of the numerical distribution of each dynamic fault indicator. ; Calculate the first one respectively The first dynamic fault indicator and the first Marginal probabilities of dynamic fault indicators: ； Calculate the first The first dynamic fault indicator and the first The joint probability of the dynamic fault indicators: 。 4. The integrated circuit reliability analysis method according to claim 3, characterized in that, Constructing a reflection of the first The first dynamic fault indicator and the first The joint distribution matrix of the distribution states of the dynamic fault indicators The specific steps include: Based on the numerical values ​​of the dynamic fault indicators in the sample dataset for each dynamic fault indicator, a dynamic distribution interval set corresponding to each dynamic fault indicator is generated: ， Traverse the first The first dynamic fault indicator and the first The dynamic distribution interval set of each dynamic fault indicator is used to determine the number of intersections in the indicator distributions. The number of intersections for The group of sample data simultaneously satisfies and Quantity; The number of intersections Determined as the joint distribution matrix The Middle Okay, number The numerical element at the column position.

5. The integrated circuit reliability analysis method according to claim 4, characterized in that, The specific steps for generating a dynamic distribution interval set corresponding to each dynamic fault indicator based on the numerical values ​​of the dynamic fault indicators in the sample dataset for each dynamic fault indicator include: The first Sample dataset of dynamic fault indicators Represented as: ； Determine the first Sample dataset of dynamic fault indicators The largest index value in and minimum index value : ； According to the sample dataset The numerical distribution in the range of values Divided into A continuous subinterval: 。 6. The integrated circuit reliability analysis method according to claim 5, characterized in that, According to the sample dataset The numerical distribution in the range of values Divided into The steps for traversing consecutive subintervals specifically include: Configure distribution deviation threshold ; According to the sample dataset The numerical distribution in the range of values China has determined One boundary value: ; Use the boundary value to define the numerical range Divided into A continuous subinterval: ； make Then for 2 to any between The value satisfies: ， in The sample dataset represents In The dynamic fault index value falls within the dynamic distribution interval set. The number of sub-intervals.

7. The integrated circuit reliability analysis method according to any one of claims 1-6, characterized in that, The reliability of the integrated circuit is calculated based on the aforementioned reliability coupling model. The specific steps include: Calculate the normalized evaluation coefficient for each reliability evaluation node in the reliability coupling model. ; Calculate the dynamic failure index for each reliability evaluation node of the integrated circuit under evaluation. ; Based on the normalized evaluation coefficients and the aforementioned dynamic fault indicators Calculate the reliability of each reliability evaluation node of the integrated circuit to be evaluated: 。 8. The integrated circuit reliability analysis method according to claim 7, characterized in that, Calculate the normalized evaluation coefficient for each reliability evaluation node in the reliability coupling model. The specific steps include: Calculate the overall coupling degree of each reliability assessment node. The overall coupling degree Reflecting the The structural importance of each reliability assessment node in the reliability coupling model; Define a count variable ; The normalized evaluation coefficients for each reliability evaluation node are obtained by normalizing the overall coupling degree. 。 9. The integrated circuit reliability analysis method according to claim 8, characterized in that, Calculate the overall coupling degree of each reliability assessment node. The specific steps include: Define a count variable ; Obtain the reliability coupling model except for the first Besides the first reliability assessment node, the other reliability assessment nodes are related to the first... Reliability coupling between reliability assessment nodes ; Calculate the first The overall coupling degree of the reliability assessment nodes: 。 10. An integrated circuit reliability analysis device, characterized in that, It includes a processor and a memory, wherein the processor executes a computer program stored in the memory to implement the integrated circuit reliability analysis method as described in any one of claims 1-9.

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