A method and system for optimizing integrated circuit layout design

Abstract

This invention discloses an auxiliary method and system for optimizing integrated circuit layout design, relating to the field of heat dissipation auxiliary technology in integrated circuit layout design. The system establishes a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL, adds electronic components and material properties to the model, and uses the data annotation platform Labelbox for annotation and filtering to obtain circuit thermal management data. It then performs comprehensive calculations using the thermal conductivity efficiency Tce, the heat dissipation path optimization index Hpi, and the temperature uniformity index Tui to obtain the comprehensive heat uniformity coefficient ZSC, conducts a preliminary evaluation of the heat uniformity coefficient ZSC, and generates early warning information based on the evaluation results. Finally, it calculates the comprehensive optimization coefficient ZHR using the heat source concentration index Hsc and the heat uniformity coefficient ZSC, performs a secondary evaluation, and generates optimization prompt information. This system effectively improves the thermal management optimization capability of integrated circuit layout design.

Description

Technical Field

[0001] This invention relates to the field of heat dissipation assistance technology for integrated circuit layout design, specifically to an integrated circuit layout design optimization assistance method and system. Background Technology

[0002] Optimization of integrated circuit (IC) layout design is crucial for the performance and reliability of electronic devices. As the complexity and functionality of ICs increase, effectively managing and optimizing their heat distribution has become a significant challenge for design engineers. Thermal management of ICs not only affects chip efficiency but also the stability and lifespan of the entire system. Excessive heat accumulation can lead to chip overheating, performance degradation, and hardware damage. Therefore, effective thermal management analysis and optimization are particularly important during the IC design phase.

[0003] Currently, traditional integrated circuit thermal management solutions mainly rely on experience and static analysis, which are not conducive to real-time dynamic heat monitoring and optimization mechanisms. These methods are often not good at effectively handling the complex thermal flow of integrated circuits in actual working environments, making it difficult to accurately identify and locate hot spots. Existing thermal management systems usually fail to fully integrate simulation data with actual circuit layout information, making it difficult for designers to make effective optimization adjustments. Therefore, these solutions may lead to insufficient circuit thermal management, thereby affecting the reliability and performance of the circuit.

[0004] The shortcomings of existing integrated circuit thermal management systems mainly stem from the limitations of static analysis methods and insufficient data processing. Due to the lack of dynamic simulation and real-time monitoring, these systems struggle to fully capture the thermal behavior of circuits under different operating conditions. Hot spots in the circuit are often not detected in time, which may lead to overheating problems that cause component failures, affecting the overall system stability and lifespan. These abnormal effects include performance degradation caused by system overheating, frequent equipment failures, and potential safety hazards. Taken together, these problems not only affect the long-term stability of the equipment but also increase maintenance costs and design cycles. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an auxiliary method and system for optimizing integrated circuit layout design, which solves the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an auxiliary method and system for optimizing integrated circuit layout design, comprising a circuit simulation module, a feature extraction module, a thermal algorithm module, a comprehensive analysis module, and a correlation analysis module;

[0007] The circuit simulation module establishes a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL. It adds electronic components and material properties to the three-dimensional thermal model, defines the simulation state, uses the software's built-in data extractor to extract data, and exports the file to Excel format.

[0008] The feature extraction module is used to load and read Excel files using data processing tools during the simulation process, annotate the read simulation data using the data annotation platform Labelbox, filter the circuit parameter type range using the filtering function to obtain circuit thermal management data, and preprocess the circuit thermal management data.

[0009] The heat algorithm module is used to perform correlation analysis on the preprocessed data, and to perform comprehensive calculations using statistical and machine learning algorithms to obtain the heat conduction efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc.

[0010] The comprehensive analysis module is used to perform correlation calculations on the obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi, and temperature uniformity index Tui to obtain the comprehensive heat uniformity coefficient ZSC, and to conduct a preliminary comparison and evaluation with the preset heat uniformity threshold Z. Based on the evaluation results, it generates early warning information and activates the second evaluation mechanism.

[0011] The correlation analysis module is used to perform correlation calculations based on the obtained comprehensive heat uniformity coefficient ZSC and heat source concentration index Hsc to obtain the comprehensive optimization coefficient ZHR, and to activate the second evaluation mechanism. The second evaluation mechanism is used to perform a second comparison evaluation with the preset heat evaluation threshold M and the obtained comprehensive optimization coefficient ZHR, and to generate early warning information based on the evaluation results.

[0012] Preferably, the circuit simulation module uses the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL to establish a three-dimensional thermal model based on the chip's geometry, material properties, and power consumption distribution. The simulation software adds electronic components and material properties to the 3D circuit model. COMSOL provides physical field coupling capabilities, sets material properties and boundary conditions, and calculates heat conduction and diffusion through finite element analysis. Flotherm simulates power consumption distribution and heat dissipation conditions, generating detailed temperature field diagrams and temperature reports. Based on the input circuit model and operating conditions, the simulation software defines simulation states after adding electronic components. These simulation states include static simulation, dynamic simulation, and temperature distribution simulation.

[0013] Static simulation is used to simulate the thermal performance of integrated circuits under constant operating conditions;

[0014] Dynamic simulation is used to simulate the thermal performance of integrated circuits under different operating conditions;

[0015] Temperature distribution simulation is used to simulate the temperature distribution of integrated circuits during operation, helping to identify hot spots.

[0016] The simulation software establishes a planar circuit coordinate system through EDA software. The EDA software defines the shape and size of the circuit board through the simulation software via the PCB editor, automatically generates a coordinate system with the lower left corner of the circuit board as the origin (0, 0), and sets the boundary of the circuit board as the boundary of the coordinate system. The grid function annotation tool is used to annotate the location of hot spots. By setting the grid spacing and unit, the coordinates of the annotated hot spots are obtained.

[0017] The software's built-in data extractor is used to extract the data, and the file is exported as an Excel file. Then, the API application interface is set up to integrate and connect with the data acquisition module to transmit simulation data in real time.

[0018] Preferably, the feature extraction module includes a data acquisition unit and a data preprocessing unit;

[0019] The data acquisition unit is used to receive simulation data in real time during the simulation process, load Excel files using data processing tools, and annotate the read simulation data through the data annotation platform Labelbox. It defines filtering conditions, and the annotated simulation data includes material properties, geometric features, temperature distribution, and heat source location. The simulation data is then filtered to obtain circuit thermal management data.

[0020] The filtering conditions are achieved by selecting labeled simulation data and using the filtering function to set the range of circuit parameter types.

[0021] The data preprocessing unit is used to perform preliminary data cleaning, outlier detection and correction on the collected circuit thermal management data, and to classify and summarize the data to generate material property datasets, geometric feature datasets, temperature datasets and heat source datasets.

[0022] The material property dataset includes thermal conductivity k, specific heat capacity C, and thermal diffusivity rs;

[0023] The geometric feature dataset includes component size cs, component spacing cp, and package type pt;

[0024] The temperature dataset includes node temperature nt, heat flux density rl, temperature gradient tg, and maximum temperature Tmax;

[0025] The heat source dataset includes power consumption density pd, heat source center coordinates (x, y), and heat source distribution density dd.

[0026] Preferably, the heat algorithm module includes a heat conduction unit, a heat dissipation path unit, and a temperature uniformity unit;

[0027] The heat conduction unit is used to perform dimensionless processing on the obtained material property dataset, and then analyze and calculate the heat conduction efficiency Tce.

[0028] The thermal conductivity Tce is obtained by the following formula;

[0029]

[0030] In the formula, ρ represents the density of the material, and β represents the thermal diffusivity correction coefficient, which is used to represent the effect of thermal diffusivity on thermal conductivity.

[0031] The heat dissipation path unit is used to perform dimensionless processing on the acquired geometric feature dataset, and then analyze and calculate the heat dissipation path optimization index Hpi.

[0032] The heat dissipation path optimization index HPi is obtained by the following formula;

[0033]

[0034] In the formula, cs i cp represents the size of the i-th element. i pt represents the spacing between the i-th element and its adjacent elements. i This indicates the package type of the i-th component, and n represents the number of components.

[0035] The temperature uniformity unit includes a temperature uniformity calculation unit and a temperature uniformity evaluation unit;

[0036] The calculation unit is used to perform dimensionless processing on the acquired temperature dataset and then analyze and calculate the temperature uniformity index Tui.

[0037] The temperature uniformity index Tui is obtained by the following formula;

[0038]

[0039] In the formula, N represents the total number of nodes, Tmax represents the highest temperature in the system, Tn represents the actual temperature of the i-th node, and rl i Let tg represent the heat flux density at the i-th node. i This represents the temperature gradient at the i-th node.

[0040] Preferably, the comprehensive analysis module includes a comprehensive heat uniformity calculation unit and a comprehensive heat uniformity evaluation unit;

[0041] The comprehensive heat uniformity calculation unit is used to perform dimensionless processing on the obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi and heat source concentration index Hsc, and then summarize and calculate the comprehensive heat uniformity coefficient ZSC.

[0042] The comprehensive heat uniformity coefficient ZSC is obtained by the following formula;

[0043] ZSC=[(Tce*a1)+(Hpi*a2)+(Tui*a3)]+A;

[0044] In the formula, a1, a2 and a3 represent the preset proportional coefficients of heat conduction efficiency Tce, heat dissipation path optimization index Hpi and temperature uniformity index Tui, respectively, and a1+a2+a3=1, 0<a1<1, 0<a2<1, 0<a3<1, their specific values ​​are adjusted and set by the user, and A is the first correction constant.

[0045] Preferably, the comprehensive heat uniformity evaluation unit performs a preliminary comparison evaluation by comparing the preset heat uniformity threshold Z with the obtained comprehensive heat uniformity coefficient ZSC, and generates optimization information based on the evaluation results. The specific evaluation scheme is as follows;

[0046] When the comprehensive heat uniformity coefficient ZSC ≤ the preset heat uniformity threshold Z, it indicates that there is an abnormality in the overall heat uniformity of the integrated circuit, and the second evaluation mechanism is activated at this time.

[0047] When the overall thermal uniformity coefficient ZSC is greater than the preset thermal uniformity threshold Z, it indicates that the overall thermal uniformity of the integrated circuit is normal, and no optimization is required.

[0048] Preferably, the correlation analysis module includes a heat source concentration unit, a correlation calculation unit, and a comprehensive heat assessment unit;

[0049] The heat source concentration unit includes a heat source distribution density calculation unit and a heat source concentration calculation unit;

[0050] The heat source distribution density calculation unit is used to perform dimensionless processing on the acquired heat source dataset, and then analyze and calculate the heat source distribution density dd. adji ;

[0051] The heat source distribution density dd adji Obtain it using the following formula;

[0052]

[0053] In the formula, α represents the adjustment coefficient, R represents the normalization factor, and (x0, y0) represents the initial center coordinates of the heat source determined by the power consumption density pd and the heat source distribution density dd.

[0054] The heat source concentration unit is used to calculate the heat source distribution density dd obtained by the heat source data set and heat source distribution density calculation unit based on the acquired heat source data set and heat source distribution density. adji After correlation and dimensionless processing, the heat source concentration index Hsc is obtained by analysis and calculation.

[0055] The heat source concentration index Hsc is obtained by the following formula;

[0056]

[0057] In the formula, pd i pd represents the power density of the i-th region. i Let x represent the heat source distribution density in the i-th region, (x i y i ) represents the coordinates of the i-th region.

[0058] Preferably, the associated calculation unit is used to perform dimensionless processing on the comprehensive heat uniformity coefficient ZSC obtained by the comprehensive heat uniformity calculation unit and the heat source concentration index Hsc obtained by the heat source concentration calculation unit, and then sum and calculate the comprehensive optimization coefficient ZHR.

[0059] The comprehensive optimization coefficient ZHR is obtained by the following formula;

[0060] ZHR=[(ZSC*b1)+(Hsc*b2)]+B;

[0061] In the formula, b1 and b2 represent the preset proportional coefficients of the comprehensive heat uniformity coefficient ZSC and the heat source concentration index Hsc, respectively, and b1+b2=1, 0<b1<1, 0<b2<1. Their specific values ​​are adjusted and set by the user, and B is the second correction constant.

[0062] Preferably, when the integrated heat assessment unit detects that the heat uniformity of the integrated circuit is abnormal, it initiates a second assessment mechanism. The second assessment mechanism compares and assesses the preset heat assessment threshold M with the obtained comprehensive optimization coefficient ZHR, and generates corresponding optimization information based on the relevant assessment results. The specific assessment scheme is as follows:

[0063] When the comprehensive optimization coefficient ZHR ≥ the preset heat assessment threshold M, it indicates that there is an anomaly in the distribution of heat sources in the located area. At this time, the first prompt message is generated to mark the heat source concentration point and assist the staff in optimizing and improving the heat source concentration point.

[0064] When the comprehensive optimization coefficient ZHR is less than the preset heat assessment threshold M, it indicates that there is an abnormality in the overall heat source distribution of the integrated circuit. At this time, a second prompt message is generated to assist the staff in optimizing the integrated circuit as a whole.

[0065] An auxiliary method for optimizing integrated circuit layout design includes the following steps:

[0066] S1. Establish a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL. Add electronic components and material properties to the three-dimensional thermal model using the simulation software, define the simulation state, extract data using the software's built-in data extractor, and export the file to Excel format.

[0067] S2. During the simulation, an Excel file is loaded and read using a data processing tool. The simulation data is labeled using the Labelbox data labeling platform and the filtering function is used to set the range of circuit parameter types to filter and obtain the circuit thermal management data. The circuit thermal management data is then preprocessed.

[0068] S3. Perform correlation analysis on the preprocessed data, and use statistical and machine learning algorithms to perform comprehensive calculations to obtain the heat conduction efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc.

[0069] S4. The obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi and temperature uniformity index Tui are correlated and calculated to obtain the comprehensive heat uniformity coefficient ZSC. A preliminary comparison and evaluation is performed with the preset heat uniformity threshold Z. Based on the evaluation results, an early warning message is generated and the second evaluation mechanism is activated.

[0070] S5. Based on the obtained comprehensive heat uniformity coefficient ZSC and heat source concentration index Hsc, perform correlation calculation to obtain the comprehensive optimization coefficient ZHR, and start the second evaluation mechanism. The second evaluation mechanism is used to perform a second comparison evaluation between the preset heat evaluation threshold M and the obtained comprehensive optimization coefficient ZHR, and generate early warning information based on the evaluation results.

[0071] This invention provides an auxiliary method and system for optimizing integrated circuit layout design. It has the following beneficial effects:

[0072] (1) The system establishes a three-dimensional thermal model using the multiphysics simulation software COMSOL and the thermal fluid simulation software Flotherm. The simulation data is then labeled and filtered using the data extraction and feature annotation tool Labelbox to ensure high-precision thermal management data. The system's thermal algorithm module utilizes statistical and machine learning algorithms to accurately calculate the heat transfer efficiency Tce, the heat dissipation path optimization index Hpi, and the temperature uniformity index Tui. These indicators are then integrated into a comprehensive thermal uniformity coefficient ZSC through a comprehensive analysis module. Through preliminary comparative evaluation and a preset thermal uniformity threshold Z, the system can quickly identify thermal uniformity anomalies, generate timely optimization information, significantly improve the thermal management efficiency of integrated circuits, ensure that circuits operate under optimal temperature conditions, and extend the lifespan of components.

[0073] (2) This system can accurately locate the heat source distribution in integrated circuits by calculating the heat source concentration index Hsc. The heat source concentration unit combines parameters such as power consumption density and heat source distribution density for dimensionless processing to ensure the accuracy of heat source concentration calculation. The correlation analysis module integrates the comprehensive heat uniformity coefficient ZSC and the heat source concentration index Hsc by calculating the comprehensive optimization coefficient ZHR, providing a more comprehensive assessment of heat source distribution. When the comprehensive optimization coefficient ZHR exceeds the preset heat assessment threshold M, the system can generate detailed prompts, clearly indicating the heat source concentration points, assisting staff in performing precise heat source optimization, reducing hotspot problems, and improving the overall performance of integrated circuits.

[0074] (3) Through the integration of the circuit simulation module and the feature extraction module, the system can receive and process data in real time during the simulation process, ensuring the real-time performance and accuracy of the data. When the comprehensive heat assessment unit initially detects an abnormality in heat uniformity, it initiates a second assessment mechanism, generating corresponding optimization information through a secondary comparison assessment of the preset heat assessment threshold M and the comprehensive optimization coefficient ZHR. This real-time monitoring and dynamic adjustment mechanism can promptly detect and correct problems in thermal management, ensuring that the integrated circuit maintains good thermal performance under different operating conditions, further improving the reliability and stability of the system. Attached Figure Description

[0075] Figure 1 This is a schematic diagram of the integrated circuit layout design optimization auxiliary system of the present invention;

[0076] Figure 2 This is a schematic diagram illustrating the steps of an integrated circuit layout design optimization auxiliary method according to the present invention. Detailed Implementation

[0077] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0078] Example 1

[0079] Please see Figure 1 This invention provides an auxiliary method and system for optimizing integrated circuit layout design, including a circuit simulation module, a feature extraction module, a thermal algorithm module, a comprehensive analysis module, and a correlation analysis module;

[0080] The circuit simulation module establishes a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL. It adds electronic components and material properties to the three-dimensional thermal model, defines the simulation state, uses the software's built-in data extractor to extract data, and exports the file to Excel format.

[0081] The feature extraction module is used to load and read Excel files using data processing tools during the simulation process, annotate the read simulation data using the data annotation platform Labelbox, filter the circuit parameter type range using the filtering function to obtain circuit thermal management data, and preprocess the circuit thermal management data.

[0082] The heat algorithm module is used to perform correlation analysis on the preprocessed data, and to perform comprehensive calculations using statistical and machine learning algorithms to obtain the heat conduction efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc.

[0083] The comprehensive analysis module is used to perform correlation calculations on the obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi, and temperature uniformity index Tui to obtain the comprehensive heat uniformity coefficient ZSC, and to conduct a preliminary comparison and evaluation with the preset heat uniformity threshold Z. Based on the evaluation results, it generates early warning information and activates the second evaluation mechanism.

[0084] The correlation analysis module is used to perform correlation calculations based on the obtained comprehensive heat uniformity coefficient ZSC and heat source concentration index Hsc to obtain the comprehensive optimization coefficient ZHR, and to activate the second evaluation mechanism. The second evaluation mechanism is used to perform a second comparison evaluation with the preset heat evaluation threshold M and the obtained comprehensive optimization coefficient ZHR, and to generate early warning information based on the evaluation results.

[0085] In this embodiment, the circuit simulation module uses the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL to build a three-dimensional thermal model, adding electronic components and material properties. The simulation results are extracted into an Excel file, providing an accurate data foundation for subsequent processing. The feature extraction module uses the data labeling platform Labelbox for data labeling and filtering, ensuring the accuracy and operability of the simulation data and laying a solid foundation for the analysis of thermal management data. The thermal algorithm module obtains the heat transfer efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc through comprehensive calculation, providing detailed thermal management data. These data are correlated and calculated in the comprehensive analysis module to generate a comprehensive thermal uniformity coefficient ZSC, which is evaluated against a preset thermal uniformity threshold Z, generating early warning information and activating a second evaluation mechanism. The correlation analysis module further calculates to generate a comprehensive optimization coefficient ZHR and performs a second evaluation, ensuring the comprehensiveness and reliability of the thermal management scheme. This multi-level and multi-index evaluation mechanism improves the optimization effect of the system. Through the coordinated work of the five modules, the system not only improves the thermal management efficiency and reliability of integrated circuits, but also effectively identifies and corrects potential problems in thermal management through real-time early warning and optimization mechanisms, thereby significantly improving the overall performance and stability of integrated circuits.

[0086] Example 2

[0087] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically: the circuit simulation module uses the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL to establish a three-dimensional thermal model based on the chip's geometry, material properties, and power consumption distribution. The simulation software adds electronic components and material properties to the 3D circuit model. COMSOL provides physical field coupling capabilities, sets material properties and boundary conditions, and calculates heat conduction and diffusion through finite element analysis. Flotherm simulates power consumption distribution and heat dissipation conditions, generating detailed temperature field diagrams and temperature reports. Based on the input circuit model and operating conditions, the simulation software defines simulation states after adding electronic components. These simulation states include static simulation, dynamic simulation, and temperature distribution simulation.

[0088] Static simulation is used to simulate the thermal performance of integrated circuits under constant operating conditions;

[0089] Dynamic simulation is used to simulate the thermal performance of integrated circuits under different operating conditions;

[0090] Temperature distribution simulation is used to simulate the temperature distribution of integrated circuits during operation, helping to identify hot spots.

[0091] The simulation software establishes a planar circuit coordinate system through EDA software. The EDA software defines the shape and size of the circuit board through the simulation software via the PCB editor, automatically generates a coordinate system with the lower left corner of the circuit board as the origin (0, 0), and sets the boundary of the circuit board as the boundary of the coordinate system. The grid function annotation tool is used to annotate the location of hot spots. By setting the grid spacing and unit, the coordinates of the annotated hot spots are obtained.

[0092] The software's built-in data extractor is used to extract the data, and the file is exported as an Excel file. Then, the API application interface is set up to integrate and connect with the data acquisition module to transmit simulation data in real time.

[0093] In this embodiment, by combining the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL, the circuit simulation module can accurately establish a three-dimensional thermal model based on the chip geometry, material properties, and power consumption distribution. Utilizing the physical field coupling capability of COMSOL, material properties and boundary conditions are set, and heat conduction and diffusion are calculated through finite element analysis. Flotherm simulates power consumption distribution and heat dissipation conditions, generating detailed temperature field diagrams and temperature reports. This simulation system can define static, dynamic, and temperature distribution simulation states, respectively used to evaluate the thermal performance of the integrated circuit under constant and changing operating conditions, as well as the temperature distribution during operation, helping to identify hotspot areas. The simulation software establishes a planar circuit coordinate system using EDA software, and defines the circuit board shape and size using a PCB editor, automatically generating a coordinate system with the lower left corner of the circuit board as the origin. The simulation data is exported to Excel format using a data extractor and integrated with the data acquisition module via an API application interface for real-time data transmission. This simulation method can significantly improve the thermal management efficiency of circuit design, optimize heat dissipation design, reduce design cycle time, and improve circuit reliability and performance.

[0094] Example 3

[0095] This embodiment is an explanation based on Embodiment 2. Please refer to it. Figure 1 Specifically: the feature extraction module includes a data acquisition unit and a data preprocessing unit;

[0096] The data acquisition unit is used to receive simulation data in real time during the simulation process, load Excel files using data processing tools, and annotate the read simulation data through the data annotation platform Labelbox. It defines filtering conditions, and the annotated simulation data includes material properties, geometric features, temperature distribution, and heat source location. The simulation data is then filtered to obtain circuit thermal management data.

[0097] The filtering conditions are achieved by selecting labeled simulation data and using the filtering function to set the range of circuit parameter types.

[0098] The data preprocessing unit is used to perform preliminary data cleaning, outlier detection and correction on the collected circuit thermal management data, and to classify and summarize the data to generate material property datasets, geometric feature datasets, temperature datasets and heat source datasets.

[0099] The material property dataset includes thermal conductivity k, specific heat capacity C, and thermal diffusivity rs;

[0100] The geometric feature dataset includes component size cs, component spacing cp, and package type pt;

[0101] The temperature dataset includes node temperature nt, heat flux density rl, temperature gradient tg, and maximum temperature Tmax;

[0102] The heat source dataset includes power consumption density pd, heat source center coordinates (x, y), and heat source distribution density dd.

[0103] In this embodiment, the accuracy and usability of circuit thermal management data are significantly improved through the data acquisition unit and data preprocessing unit. The data acquisition unit receives and reads simulation data in real time during the simulation process, performs precise annotation using the Labelbox data annotation platform, and filters the data by setting filtering conditions to ensure the high reliability and relevance of the acquired circuit thermal management data. The data preprocessing unit performs preliminary cleaning, outlier detection and correction on these data, and classifies and summarizes them into material property datasets, geometric feature datasets, temperature datasets, and heat source datasets, further improving the cleanliness of the data and the effectiveness of the analysis. The systematic management and classification of these datasets not only improves the efficiency of thermal management analysis but also provides reliable data support for subsequent optimization design and precise control, effectively promoting the optimization and improvement of integrated circuit thermal management.

[0104] Example 4

[0105] This embodiment is an explanation based on Embodiment 3. Please refer to it. Figure 1 Specifically: the heat algorithm module includes a heat conduction unit, a heat dissipation path unit, and a temperature uniformity unit;

[0106] The heat conduction unit is used to perform dimensionless processing on the obtained material property dataset, and then analyze and calculate the heat conduction efficiency Tce.

[0107] The thermal conductivity Tce is obtained by the following formula;

[0108]

[0109] In the formula, ρ represents the density of the material, and β represents the thermal diffusivity correction coefficient;

[0110] The heat dissipation path unit is used to perform dimensionless processing on the acquired geometric feature dataset, and then analyze and calculate the heat dissipation path optimization index Hpi.

[0111] The heat dissipation path optimization index HPi is obtained by the following formula;

[0112]

[0113] In the formula, cs i cp represents the size of the i-th element. i pt represents the spacing between the i-th element and its adjacent elements. i This indicates the package type of the i-th component, and n represents the number of components.

[0114] The temperature uniformity unit includes a temperature uniformity calculation unit and a temperature uniformity evaluation unit;

[0115] The calculation unit is used to perform dimensionless processing on the acquired temperature dataset and then analyze and calculate the temperature uniformity index Tui.

[0116] The temperature uniformity index Tui is obtained by the following formula;

[0117]

[0118] In the formula, N represents the total number of nodes, Tmax represents the highest temperature in the system, Tn represents the actual temperature of the i-th node, and rl i Let tg represent the heat flux density at the i-th node. i This represents the temperature gradient at the i-th node.

[0119] The comprehensive analysis module includes a comprehensive heat uniformity calculation unit and a comprehensive heat uniformity evaluation unit;

[0120] The comprehensive heat uniformity calculation unit is used to perform dimensionless processing on the obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi and heat source concentration index Hsc, and then summarize and calculate the comprehensive heat uniformity coefficient ZSC.

[0121] The comprehensive heat uniformity coefficient ZSC is obtained by the following formula;

[0122] ZSC=[(Tce*a1)+(Hpi*a2)+(Tui*a3)]+A;

[0123] In the formula, a1, a2 and a3 represent the preset proportional coefficients of heat conduction efficiency Tce, heat dissipation path optimization index Hpi and temperature uniformity index Tui, respectively, and a1+a2+a3=1, 0<a1<1, 0<a2<1, 0<a3<1, their specific values ​​are adjusted and set by the user, and A is the first correction constant.

[0124] The comprehensive heat uniformity evaluation unit performs a preliminary evaluation by comparing the preset heat uniformity threshold Z with the obtained comprehensive heat uniformity coefficient ZSC, and generates optimization information based on the evaluation results. The specific evaluation scheme is as follows.

[0125] When the comprehensive heat uniformity coefficient ZSC ≤ the preset heat uniformity threshold Z, it indicates that there is an abnormality in the overall heat uniformity of the integrated circuit, and the second evaluation mechanism is activated at this time.

[0126] When the overall thermal uniformity coefficient ZSC is greater than the preset thermal uniformity threshold Z, it indicates that the overall thermal uniformity of the integrated circuit is normal, and no optimization is required.

[0127] In this embodiment, a modular thermal algorithm, including a heat conduction unit, a heat dissipation path unit, and a temperature uniformity unit, is used to perform comprehensive thermal management analysis. The heat conduction unit calculates the heat conduction efficiency Tce based on material property data after dimensionless processing; the heat dissipation path unit calculates the heat dissipation path optimization index Hpi using geometric feature data; and the temperature uniformity unit calculates the temperature uniformity index Tui based on temperature data. The comprehensive analysis module integrates these thermal indicators to calculate the comprehensive thermal uniformity coefficient ZSC and performs a preliminary evaluation. When the comprehensive thermal uniformity coefficient ZSC is lower than the preset thermal uniformity threshold Z, a further evaluation mechanism is initiated. This systematic thermal management method, through precise calculation and evaluation, can effectively improve the heat dissipation performance of integrated circuits, ensure their stable operation, thereby improving the overall system reliability and lifespan, optimizing thermal management efficiency in the design process, and bringing significant application effects and technical advantages.

[0128] Example 5

[0129] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically: the correlation analysis module includes a heat source concentration unit, a correlation calculation unit, and a comprehensive heat assessment unit;

[0130] The heat source concentration unit includes a heat source distribution density calculation unit and a heat source concentration calculation unit;

[0131] The heat source distribution density calculation unit is used to perform dimensionless processing on the acquired heat source dataset, and then analyze and calculate the heat source distribution density dd. adji ;

[0132] The heat source distribution density dd adji Obtain it using the following formula;

[0133]

[0134] In the formula, α represents the adjustment coefficient, R represents the normalization factor, and (x0, y0) represents the initial center coordinates of the heat source determined by the power consumption density pd and the heat source distribution density dd.

[0135] The heat source concentration unit is used to calculate the heat source distribution density dd obtained by the heat source data set and heat source distribution density calculation unit based on the acquired heat source data set and heat source distribution density. adji After correlation and dimensionless processing, the heat source concentration index Hsc is obtained by analysis and calculation.

[0136] The heat source concentration index Hsc is obtained by the following formula;

[0137]

[0138] In the formula, pd i pd represents the power density of the i-th region. i Let x represent the heat source distribution density in the i-th region, (x i y i ) represents the coordinates of the i-th region.

[0139] The associated calculation unit is used to perform dimensionless processing on the comprehensive heat uniformity coefficient ZSC obtained by the comprehensive heat uniformity calculation unit and the heat source concentration index Hsc obtained by the heat source concentration calculation unit, and then sum and calculate the comprehensive optimization coefficient ZHR.

[0140] The comprehensive optimization coefficient ZHR is obtained by the following formula;

[0141] ZHR=[(ZSC*b1)+(Hsc*b2)]+B;

[0142] In the formula, b1 and b2 represent the preset proportional coefficients of the comprehensive heat uniformity coefficient ZSC and the heat source concentration index Hsc, respectively, and b1+b2=1, 0<b1<1, 0<b2<1. Their specific values ​​are adjusted and set by the user, and B is the second correction constant.

[0143] When the integrated heat assessment unit detects that the heat uniformity of the integrated circuit is abnormal, it activates the second assessment mechanism. The second assessment mechanism compares the preset heat assessment threshold M with the obtained comprehensive optimization coefficient ZHR for a second assessment, and generates corresponding optimization information based on the relevant assessment results. The specific assessment scheme is as follows.

[0144] When the comprehensive optimization coefficient ZHR ≥ the preset heat assessment threshold M, it indicates that there is an anomaly in the distribution of heat sources in the located area. At this time, the first prompt message is generated to mark the heat source concentration point and assist the staff in optimizing and improving the heat source concentration point.

[0145] When the comprehensive optimization coefficient ZHR is less than the preset heat assessment threshold M, it indicates that there is an abnormality in the overall heat source distribution of the integrated circuit. At this time, a second prompt message is generated to assist the staff in optimizing the integrated circuit as a whole.

[0146] In this embodiment, by calculating the heat source distribution density and heat source concentration index using the heat source concentration unit, the system can accurately identify and quantify the distribution and concentration of heat sources. In the calculation and evaluation of the comprehensive optimization coefficient, the system combines the comprehensive heat uniformity coefficient and the heat source concentration index to comprehensively assess the thermal management status of the integrated circuit. When the comprehensive optimization coefficient ZHR exceeds the preset heat assessment threshold M, the system generates a prompt message, marking the specific heat source concentration points to assist staff in optimizing and improving local heat sources. When the comprehensive optimization coefficient ZHR is lower than the preset heat assessment threshold M, it indicates a problem with the overall heat source distribution, prompting optimization of the integrated circuit. This precise anomaly location and optimization suggestion effectively improves the thermal management level of the integrated circuit, ensuring the stability of its performance and reliability.

[0147] Example 6

[0148] Please see Figure 2 An auxiliary method for optimizing integrated circuit layout design includes the following steps:

[0149] S1. Establish a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL. Add electronic components and material properties to the three-dimensional thermal model using the simulation software, define the simulation state, extract data using the software's built-in data extractor, and export the file to Excel format.

[0150] S2. During the simulation, an Excel file is loaded and read using a data processing tool. The simulation data is labeled using the Labelbox data labeling platform and the filtering function is used to set the range of circuit parameter types to filter and obtain the circuit thermal management data. The circuit thermal management data is then preprocessed.

[0151] S3. Perform correlation analysis on the preprocessed data, and use statistical and machine learning algorithms to perform comprehensive calculations to obtain the heat conduction efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc.

[0152] S4. The obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi and temperature uniformity index Tui are correlated and calculated to obtain the comprehensive heat uniformity coefficient ZSC. A preliminary comparison and evaluation is performed with the preset heat uniformity threshold Z. Based on the evaluation results, an early warning message is generated and the second evaluation mechanism is activated.

[0153] S5. Based on the obtained comprehensive heat uniformity coefficient ZSC and heat source concentration index Hsc, perform correlation calculation to obtain the comprehensive optimization coefficient ZHR, and start the second evaluation mechanism. The second evaluation mechanism is used to perform a second comparison evaluation between the preset heat evaluation threshold M and the obtained comprehensive optimization coefficient ZHR, and generate early warning information based on the evaluation results.

[0154] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An integrated circuit layout design optimization auxiliary system, characterized in that: It includes a circuit simulation module, a feature extraction module, a thermal algorithm module, a comprehensive analysis module, and a correlation analysis module; The circuit simulation module establishes a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL. It adds electronic components and material properties to the three-dimensional thermal model, defines the simulation state, uses the software's built-in data extractor to extract data, and exports the file to Excel format. The feature extraction module is used to load and read Excel files using data processing tools during the simulation process, annotate the read simulation data using the data annotation platform Labelbox, filter the circuit parameter type range using the filtering function to obtain circuit thermal management data, and preprocess the circuit thermal management data. The heat algorithm module is used to perform correlation analysis on the preprocessed data, and to perform comprehensive calculations using statistical and machine learning algorithms to obtain the heat conduction efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc. The correlation analysis module includes a heat source concentration unit, a correlation calculation unit, and a comprehensive heat assessment unit; The heat source concentration unit includes a heat source distribution density calculation unit and a heat source concentration calculation unit; The heat source distribution density calculation unit is used to perform dimensionless processing on the acquired heat source dataset, and then analyze and calculate the heat source distribution density dd. adji ; The heat source distribution density dd adji Obtain it using the following formula; In the formula, α represents the adjustment coefficient, R represents the normalization factor, and (x0, y0) represents the initial center coordinates of the heat source determined by the power consumption density pd and the heat source distribution density dd. The heat source concentration unit is used to calculate the heat source distribution density dd obtained by the heat source data set and heat source distribution density calculation unit based on the acquired heat source data set and heat source distribution density. adji After correlation and dimensionless processing, the heat source concentration index Hsc is obtained by analysis and calculation. The heat source concentration index Hsc is obtained by the following formula; In the formula, pd i pd represents the power density of the i-th region. i Let x represent the heat source distribution density in the i-th region, (x i y i () represents the coordinates of the i-th region; The comprehensive analysis module is used to perform correlation calculations on the obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi, and temperature uniformity index Tui to obtain the comprehensive heat uniformity coefficient ZSC, and to conduct a preliminary comparison and evaluation with the preset heat uniformity threshold Z. Based on the evaluation results, it generates early warning information and activates the second evaluation mechanism. The comprehensive analysis module includes a comprehensive heat uniformity calculation unit and a comprehensive heat uniformity evaluation unit; The comprehensive heat uniformity calculation unit is used to perform dimensionless processing on the obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi and heat source concentration index Hsc, and then summarize and calculate the comprehensive heat uniformity coefficient ZSC. The comprehensive heat uniformity coefficient ZSC is obtained by the following formula; ZSC=[(Tce*a1)+(Hpi*a2)+(Tui*a3)]+A; In the formula, a1, a2 and a3 represent the preset proportional coefficients of heat conduction efficiency Tce, heat dissipation path optimization index Hpi and temperature uniformity index Tui, respectively, and a1+a2+a3=1, 0<a1<1, 0<a2<1, 0<a3<1, their specific values ​​are adjusted and set by the user, and A is the first correction constant. The correlation analysis module is used to perform correlation calculations based on the obtained comprehensive heat uniformity coefficient ZSC and heat source concentration index Hsc to obtain the comprehensive optimization coefficient ZHR, and to activate the second evaluation mechanism. The second evaluation mechanism is used to perform a second comparison evaluation with the preset heat evaluation threshold M and the obtained comprehensive optimization coefficient ZHR, and to generate early warning information based on the evaluation results. The associated calculation unit is used to perform dimensionless processing on the comprehensive heat uniformity coefficient ZSC obtained by the comprehensive heat uniformity calculation unit and the heat source concentration index Hsc obtained by the heat source concentration calculation unit, and then sum and calculate the comprehensive optimization coefficient ZHR. The comprehensive optimization coefficient ZHR is obtained by the following formula; ZHR=[(ZSC*b1)+(Hsc*b2)]+B; In the formula, b1 and b2 represent the preset proportional coefficients of the comprehensive heat uniformity coefficient ZSC and the heat source concentration index Hsc, respectively, and b1+b2=1, 0<b1<1, 0<b2<1. Their specific values ​​are adjusted and set by the user, and B is the second correction constant.

2. The integrated circuit layout design optimization auxiliary system according to claim 1, characterized in that: The circuit simulation module uses the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL to establish a three-dimensional thermal model based on the chip's geometry, material properties, and power consumption distribution. It then adds electronic components and material properties to the 3D circuit model using the simulation software, provides physical field coupling capabilities through the multiphysics simulation software COMSOL, sets material properties and boundary conditions, and calculates heat conduction and diffusion through finite element analysis. The power consumption distribution and heat dissipation conditions are simulated using the thermal fluid simulation software Flotherm, generating detailed temperature field diagrams and temperature reports. The simulation software defines simulation states after adding electronic components based on the input circuit model and operating conditions. These simulation states include static simulation, dynamic simulation, and temperature distribution simulation. Static simulation is used to simulate the thermal performance of integrated circuits under constant operating conditions; Dynamic simulation is used to simulate the thermal performance of integrated circuits under different operating conditions; Temperature distribution simulation is used to simulate the temperature distribution of integrated circuits during operation, helping to identify hot spots. The simulation software establishes a planar circuit coordinate system through EDA software. The EDA software defines the shape and size of the circuit board through the simulation software via the PCB editor, automatically generates a coordinate system with the lower left corner of the circuit board as the origin (0, 0), and sets the boundary of the circuit board as the boundary of the coordinate system. The grid function annotation tool is used to annotate the location of hot spots. By setting the grid spacing and unit, the coordinates of the annotated hot spots are obtained. The software's built-in data extractor is used to extract the data, and the file is exported as an Excel file. Then, the API application interface is set up to integrate and connect with the data acquisition module to transmit simulation data in real time.

3. The integrated circuit layout design optimization auxiliary system according to claim 2, characterized in that: The feature extraction module includes a data acquisition unit and a data preprocessing unit; The data acquisition unit is used to receive simulation data in real time during the simulation process, load Excel files using data processing tools, and annotate the read simulation data through the data annotation platform Labelbox. It defines filtering conditions, and the annotated simulation data includes material properties, geometric features, temperature distribution, and heat source location. The simulation data is then filtered to obtain circuit thermal management data. The filtering conditions are achieved by selecting labeled simulation data and using the filtering function to set the range of circuit parameter types. The data preprocessing unit is used to perform preliminary data cleaning, outlier detection and correction on the collected circuit thermal management data, and to classify and summarize the data to generate material property datasets, geometric feature datasets, temperature datasets and heat source datasets. The material property dataset includes thermal conductivity k, specific heat capacity C, and thermal diffusivity rs; The geometric feature dataset includes component size cs, component spacing cp, and package type pt; The temperature dataset includes node temperature nt, heat flux density rl, temperature gradient tg, and maximum temperature Tmax; The heat source dataset includes power consumption density pd, heat source center coordinates (x, y), and heat source distribution density dd.

4. The integrated circuit layout design optimization auxiliary system according to claim 3, characterized in that: The heat algorithm module includes a heat conduction unit, a heat dissipation path unit, and a temperature uniformity unit. The heat conduction unit is used to perform dimensionless processing on the obtained material property dataset, and then analyze and calculate the heat conduction efficiency Tce. The thermal conductivity Tce is obtained by the following formula; In the formula, ρ represents the density of the material, and β represents the thermal diffusivity correction coefficient; The heat dissipation path unit is used to perform dimensionless processing on the acquired geometric feature dataset, and then analyze and calculate the heat dissipation path optimization index HPi. The heat dissipation path optimization index HPi is obtained by the following formula; In the formula, cs i cp represents the size of the i-th element. i pt represents the spacing between the i-th element and its adjacent elements. i This indicates the package type of the i-th component, and n represents the number of components. The temperature uniformity unit includes a temperature uniformity calculation unit and a temperature uniformity evaluation unit; The calculation unit is used to perform dimensionless processing on the acquired temperature dataset and then analyze and calculate the temperature uniformity index Tui. The temperature uniformity index Tui is obtained by the following formula; In the formula, N represents the total number of nodes, Tmax represents the highest temperature in the system, Tn represents the actual temperature of the i-th node, and rl i Let tg represent the heat flux density at the i-th node. i This represents the temperature gradient at the i-th node.

5. The integrated circuit layout design optimization auxiliary system according to claim 1, characterized in that: The comprehensive heat uniformity evaluation unit performs a preliminary evaluation by comparing the preset heat uniformity threshold Z with the obtained comprehensive heat uniformity coefficient ZSC, and generates optimization information based on the evaluation results. The specific evaluation scheme is as follows. When the comprehensive heat uniformity coefficient ZSC ≤ the preset heat uniformity threshold Z, it indicates that there is an abnormality in the overall heat uniformity of the integrated circuit, and the second evaluation mechanism is activated at this time. When the overall thermal uniformity coefficient ZSC is greater than the preset thermal uniformity threshold Z, it indicates that the overall thermal uniformity of the integrated circuit is normal, and no optimization is required.

6. The integrated circuit layout design optimization auxiliary system according to claim 1, characterized in that: When the integrated heat assessment unit detects that the heat uniformity of the integrated circuit is abnormal, it activates the second assessment mechanism. The second assessment mechanism compares the preset heat assessment threshold M with the obtained comprehensive optimization coefficient ZHR for a second assessment, and generates corresponding optimization information based on the relevant assessment results. The specific assessment scheme is as follows. When the comprehensive optimization coefficient ZHR ≥ the preset heat assessment threshold M, it indicates that there is an anomaly in the distribution of heat sources in the located area. At this time, the first prompt message is generated to mark the heat source concentration point and assist the staff in optimizing and improving the heat source concentration point. When the comprehensive optimization coefficient ZHR is less than the preset heat assessment threshold M, it indicates that there is an abnormality in the overall heat source distribution of the integrated circuit. At this time, a second prompt message is generated to assist the staff in optimizing the integrated circuit as a whole.

7. An integrated circuit layout design optimization auxiliary method, applied to the integrated circuit layout design optimization auxiliary system according to any one of claims 1 to 6, characterized in that: Includes the following steps: S1. Establish a three-dimensional thermal model using the thermal fluid simulation software Flotherm and the multiphysics simulation software COMSOL. Add electronic components and material properties to the three-dimensional thermal model using the simulation software, define the simulation state, extract data using the software's built-in data extractor, and export the file to Excel format. S2. During the simulation, an Excel file is loaded and read using a data processing tool. The simulation data is labeled using the Labelbox data labeling platform and the filtering function is used to set the range of circuit parameter types to filter and obtain the circuit thermal management data. The circuit thermal management data is then preprocessed. S3. Perform correlation analysis on the preprocessed data, and use statistical and machine learning algorithms to perform comprehensive calculations to obtain the heat conduction efficiency Tce, heat dissipation path optimization index Hpi, temperature uniformity index Tui, and heat source concentration index Hsc. S4. The obtained heat conduction efficiency Tce, heat dissipation path optimization index Hpi and temperature uniformity index Tui are correlated and calculated to obtain the comprehensive heat uniformity coefficient ZSC. A preliminary comparison and evaluation is performed with the preset heat uniformity threshold Z. Based on the evaluation results, an early warning message is generated and the second evaluation mechanism is activated. S5. Based on the obtained comprehensive heat uniformity coefficient ZSC and heat source concentration index Hsc, perform correlation calculation to obtain the comprehensive optimization coefficient ZHR, and start the second evaluation mechanism. The second evaluation mechanism is used to perform a second comparison evaluation between the preset heat evaluation threshold M and the obtained comprehensive optimization coefficient ZHR, and generate early warning information based on the evaluation results.

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