Graphene-based Multilayer Chip Thermal Diffusion Method and System

Abstract

This application relates to the field of heat dissipation technology, and provides a multi-layer chip heat diffusion method and system based on graphene. The method includes obtaining the operating condition information of the multi-layer chip; the operating condition information includes various operating conditions of the multi-layer chip; performing combined operations on each of the operating conditions to obtain a variety of operating condition combinations; for each of the operating condition combinations, controlling the multi-layer chip to operate for a preset duration under the operating condition combination, and in the process of the multi-layer chip running, obtaining the surface temperature distribution map of the multi-layer chip in real time to obtain the surface temperature distribution change information of the multi-layer chip under the operating condition combination; generating the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information; integrating the graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information. This method can ensure that all areas of the chip can obtain an efficient heat dissipation effect, thereby avoiding the occurrence of local overheating phenomena.

Description

Technical Field

[0001] This application relates to the field of heat dissipation technology, and particularly to a multi-layer chip heat diffusion method and system based on graphene. Background Art

[0002] In modern electronic devices, with the continuous progress of integrated circuit technology, the integration level and functional complexity of chips are increasing day by day, and multi-layer chips have gradually become the core components of high-performance electronic devices. However, with the increase in the number of chip layers, the problem of heat accumulation between layers inside the chip has become increasingly prominent. To ensure the effective operation of electronic devices, it is crucial to effectively dissipate heat from multi-layer chips.

[0003] However, existing chip heat dissipation methods usually use fans or micro-channel liquid cooling systems for heat dissipation, and it is difficult to effectively dissipate heat from all areas of multi-layer chips using this method. Summary of the Invention

[0004] This application provides a multi-layer chip heat diffusion method and system based on graphene to solve the problems raised in the above background art.

[0005] In a first aspect, this application provides a multi-layer chip heat diffusion method based on graphene, including:

[0006] Obtain the operating condition information of the multi-layer chip; the operating condition information includes various operating conditions of the multi-layer chip;

[0007] Perform combinatorial operations on each of the operating conditions to obtain multiple operating condition combinations;

[0008] For each of the operating condition combinations, control the multi-layer chip to operate for a preset duration under the operating condition combination, and in the process of the multi-layer chip operating, obtain the surface temperature distribution map of the multi-layer chip in real time to obtain the surface temperature distribution change information of the multi-layer chip under the operating condition combination;

[0009] Generate the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information;

[0010] Integrate the graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0011] In a possible implementation manner, the generating the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information includes:

[0012] Construct a virtual model of the multi-layer chip, and perform finite element segmentation processing on the surface of the virtual model to obtain the finite element model corresponding to the virtual model;

[0013] For each of the surface temperature distribution change information, generate the heat generation efficiency of each finite element of the finite element model based on the surface temperature distribution change information;

[0014] For each of the finite elements, determine the maximum heat generation efficiency corresponding to the finite element as the target heat generation efficiency corresponding to the finite element;

[0015] For each of the finite elements, determine the thickness of the graphene heat dissipation layer corresponding to the finite element based on the target heat generation efficiency corresponding to the finite element and a preset graphene heat dissipation model; the thicknesses of the graphene heat dissipation layers corresponding to each of the finite elements constitute the thickness distribution information.

[0016] In a possible implementation manner, the generating the heat generation efficiency of each finite element of the finite element model based on the surface temperature distribution change information includes:

[0017] For each surface temperature distribution diagram in the surface temperature distribution change information, render the finite element based on the surface temperature distribution diagram, and obtain the temperature values of each finite element of the finite element model based on the surface temperature distribution diagram;

[0018] For each of the finite elements, arrange the temperature values in sequence based on the acquisition time of the surface temperature distribution diagram corresponding to each temperature value corresponding to the finite element, to obtain a temperature value sequence corresponding to the finite element;

[0019] For each of the finite elements, sequentially calculate the temperature difference between two adjacent temperature values in the temperature value sequence corresponding to the finite element, to obtain a temperature difference sequence corresponding to the finite element;

[0020] For each of the finite elements, generate a target temperature difference corresponding to the finite element based on the temperature difference sequence corresponding to the finite element;

[0021] For each of the finite elements, generate the heat generation efficiency of the finite element based on the area corresponding to the finite element, the target temperature difference corresponding to the finite element, the thickness corresponding to the multi-layer chip at the finite element, the density and specific heat capacity of the multi-layer chip, and the time difference corresponding to the target temperature difference.

[0022] In a possible implementation manner, the generating the target temperature difference corresponding to the finite element based on the temperature difference sequence corresponding to the finite element includes:

[0023] Perform a filtering process on the temperature difference sequence using a preset filtering method to obtain a target temperature difference sequence;

[0024] Generate the target temperature difference based on the target temperature difference sequence.

[0025] In a possible implementation manner, the step of filtering the temperature difference sequence by using a preset filtering method to obtain a target temperature difference sequence includes:

[0026] For each temperature difference in the temperature difference sequence, determine the neighborhood interval of the temperature difference; the neighborhood interval includes the temperature difference and the temperature differences adjacent to the temperature difference;

[0027] For each temperature difference in the temperature difference sequence, determine the filtering value corresponding to the temperature difference based on the neighborhood interval corresponding to the temperature difference.

[0028] In a possible implementation manner, the step of determining the filtering value corresponding to the temperature difference based on the neighborhood interval corresponding to the temperature difference includes:

[0029] Determine the standard deviation between each temperature difference in the neighborhood interval ;

[0030] By respectively obtain the Gaussian weights corresponding to each temperature difference in the neighborhood interval; where represents the temperature difference corresponding to the neighborhood interval, represents any temperature difference in the neighborhood interval;

[0031] Add the Gaussian weights corresponding to each temperature difference in the neighborhood interval to obtain the sum of the Gaussian weights;

[0032] For each temperature difference in the neighborhood interval, determine the ratio of the Gaussian weight corresponding to the temperature difference to the sum of the Gaussian weights as the target weight of the temperature difference;

[0033] Perform weighted summation on each temperature difference in the neighborhood interval based on the target weights of each temperature difference in the neighborhood interval to obtain the filtering value.

[0034] In a possible implementation manner, determine the average value between each filtering value of the target temperature difference sequence as the target temperature difference.

[0035] In a second aspect, the present application provides a graphene-based multi-layer chip thermal diffusion system, including:

[0036] A first acquisition module, configured to acquire the operating condition information of the multi-layer chip; the operating condition information includes multiple operating conditions of the multi-layer chip;

[0037] A combined operation module for performing combined operations on each of the working conditions to obtain multiple combinations of working conditions;

[0038] A second acquisition module for, for each of the combinations of working conditions, controlling the multi-layer chip to operate for a preset duration under the combination of working conditions, and in the process of the operation of the multi-layer chip, acquiring in real time a surface temperature distribution map of the multi-layer chip to obtain surface temperature distribution change information of the multi-layer chip under the combination of working conditions;

[0039] A generation module for generating thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information;

[0040] A processing module for integrating a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0041] This application provides a method and system for thermal diffusion of multi-layer chips based on graphene. The method includes: acquiring working condition information of the multi-layer chip; the working condition information includes multiple working conditions of the multi-layer chip; performing combined operations on each of the working conditions to obtain multiple combinations of working conditions; for each of the combinations of working conditions, controlling the multi-layer chip to operate for a preset duration under the combination of working conditions, and in the process of the operation of the multi-layer chip, acquiring in real time a surface temperature distribution map of the multi-layer chip to obtain surface temperature distribution change information of the multi-layer chip under the combination of working conditions; generating thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information; integrating a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information. On the one hand, by utilizing the high thermal conductivity of the graphene heat dissipation layer and combining with the thickness distribution optimization method, this method can achieve efficient heat conduction and uniform diffusion of heat in the multi-layer chip, fundamentally alleviating the problem of heat accumulation in the chip and ensuring the stable operation of the chip. On the other hand, the design method of the thickness of the graphene heat dissipation layer provided in this embodiment can make the design of the graphene heat dissipation layer adapt to the complex structure and different thermal load regions of the chip, ensuring that all regions of the chip can obtain an efficient heat dissipation effect, thereby avoiding the occurrence of local overheating phenomena. Description of the Drawings

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 It is a schematic flowchart of the method for thermal diffusion of multi-layer chips based on graphene provided by the embodiment of this application;

[0044] Figure 2 Schematic block diagram of a multi-layer chip thermal diffusion system based on graphene provided by an embodiment of the present application;

[0045] Figure 3 Schematic block diagram of a terminal device provided by an embodiment of the present application. Detailed implementation manners

[0046] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] The flowcharts shown in the accompanying drawings are only illustrative examples, and do not necessarily include all contents and operations / steps, nor do they necessarily need to be executed in the described order. For example, some operations / steps can be decomposed, combined, or partially merged, so the actual execution order may be changed according to the actual situation.

[0048] It should also be understood that the terms used in the specification of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0049] It should be further understood that the term " / and" used in the specification of the present application and the appended claims refers to any combination and all possible combinations of one or more of the related listed items, and includes these combinations.

[0050] Next, some embodiments of the present application will be described in detail with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0051] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of a method for thermal diffusion of multi-layer chips based on graphene provided by an embodiment of the present application. As Figure 1 shown, the method for thermal diffusion of multi-layer chips based on graphene provided by an embodiment of the present application includes steps S1 to S5.

[0052] Step S1, obtaining the working condition information of the multi-layer chip; the working condition information includes various working conditions of the multi-layer chip.

[0053] Specifically, the working condition information of the multi-layer chip is obtained from the function information database of the multi-layer chip.

[0054] Step S2: Perform combined operations on each of the said working conditions to obtain multiple combinations of working conditions.

[0055] Among them, the multiple combinations of working conditions include all possible cases of randomly extracting several working conditions from each of the said working conditions. For example, if the working condition information includes working condition 1, working condition 2, and working condition 3, then the multiple combinations of working conditions include {working condition 1}, {working condition 2}, {working condition 3}, {working condition 1, working condition 2}, {working condition 1, working condition 3}, {working condition 2, working condition 3}, and {working condition 1, working condition 2, working condition 3}, a total of seven combinations of working conditions.

[0056] Step S3: For each of the said combinations of working conditions, control the multi-layer chip to operate for a preset duration under the combination of working conditions, and in the process of the multi-layer chip running, obtain the surface temperature distribution map of the multi-layer chip in real time, so as to obtain the surface temperature distribution change information of the multi-layer chip under the combination of working conditions.

[0057] Specifically, use a programmable logic controller to control the multi-layer chip to operate for a preset duration under the combination of working conditions, and in the process of the multi-layer chip running, use an infrared camera to obtain the surface temperature distribution map of each layer of the multi-layer chip in real time, so as to obtain the surface temperature distribution change information of the multi-layer chip under the combination of working conditions.

[0058] Step S4: Generate the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the said surface temperature distribution change information.

[0059] Specifically, step S4 includes the following steps:

[0060] Construct a virtual model of the multi-layer chip, and perform finite element segmentation processing on the surface of the virtual model to obtain the finite element model corresponding to the virtual model; specifically, use a laser point cloud acquisition device to obtain the laser point cloud of the multi-layer chip, and construct the virtual model of the multi-layer chip based on the laser point cloud, and perform finite element segmentation on the surface of the virtual model based on a preset finite element segmentation method to obtain the finite element model;

[0061] For each of the said surface temperature distribution change information, generate the heat generation efficiency of each finite element unit of the finite element model based on the surface temperature distribution change information; wherein, the heat generation efficiency refers to the heat generation amount of the finite element unit per unit time.

[0062] For each of the finite element cells, determine the maximum heat generation efficiency corresponding to the finite element cell as the target heat generation efficiency for the finite element cell; it can be understood that determining the maximum heat generation efficiency corresponding to the finite element cell as the target heat generation efficiency for the finite element cell helps to subsequently design a graphene thickness sufficient to ensure effective heat dissipation for the finite element cell;

[0063] For each of the finite element cells, based on the target heat generation efficiency corresponding to the finite element cell and a preset graphene heat dissipation model, determine the thickness of the graphene heat dissipation layer corresponding to the finite element cell; the thicknesses of the graphene heat dissipation layers corresponding to each of the finite element cells constitute the thickness distribution information; wherein, the graphene heat dissipation model is a heat dissipation model pre-constructed based on the heat diffusion principle, the input of the graphene heat dissipation model is the area and the target heat generation efficiency of the finite element cell, and the output is the thickness of the graphene heat dissipation layer corresponding to the finite element cell.

[0064] Among them, generating the heat generation efficiency of each finite element cell of the finite element model based on the surface temperature distribution change information includes the following steps:

[0065] For each surface temperature distribution diagram in the surface temperature distribution change information, render the finite element cell based on the surface temperature distribution diagram, and obtain the temperature values of each finite element cell of the finite element model based on the surface temperature distribution diagram; specifically, for each of the finite element cells, obtain the temperature value of the finite element cell based on the color information corresponding to the finite element cell on the surface temperature distribution diagram;

[0066] For each of the finite element cells, arrange the temperature values in sequence based on the acquisition time of the surface temperature distribution diagram corresponding to each temperature value corresponding to the finite element cell, to obtain the temperature value sequence corresponding to the finite element cell;

[0067] For each of the finite element cells, calculate the temperature difference between two adjacent temperature values in the temperature value sequence corresponding to the finite element cell in sequence, to obtain the temperature difference sequence corresponding to the finite element cell; specifically, for two adjacent temperature values, subtract the previous temperature value from the latter temperature value to obtain the temperature difference between the two adjacent temperature values;

[0068] For each of the finite element cells, generate the target temperature difference corresponding to the finite element cell based on the temperature difference sequence corresponding to the finite element cell;

[0069] For each of the finite element cells, generate the heat generation efficiency of the finite element cell based on the area corresponding to the finite element cell, the target temperature difference corresponding to the finite element cell, the thickness of the multi-layer chip corresponding to the finite element cell, the density and specific heat capacity of the multi-layer chip, and the time difference corresponding to the target temperature difference; specifically, multiply the area corresponding to the finite element cell, the thickness of the multi-layer chip corresponding to the finite element cell, the density of the multi-layer chip, the target temperature difference corresponding to the finite element cell, and the specific heat capacity of the multi-layer chip to obtain a target product, and determine the ratio of the target product to the time difference as the heat generation efficiency of the finite element cell.

[0070] It can be understood that the method for generating the heat generation efficiency of each finite element cell of the finite element model based on the surface temperature distribution change information, on the one hand, can identify specific hot spots and low-efficiency heat dissipation areas in the multi-layer chip by accurately calculating the heat generation efficiency of each finite element cell. Based on this information, the thickness distribution of the graphene heat dissipation layer can be adjusted accordingly to achieve personalized thermal optimization and improve the overall heat dissipation effect. On the other hand, by precisely controlling the heat generation efficiency of each finite element cell, the occurrence of local overheating can be effectively prevented, reducing the chip performance degradation and increased failure rate caused by excessive temperature, helping to extend the service life of the multi-layer chip, and ensuring the stability and reliability of the multi-layer chip under high-performance operating conditions.

[0071] Among them, generating the target temperature difference corresponding to the finite element cell based on the temperature difference sequence corresponding to the finite element cell includes the following steps:

[0072] Perform a filtering process on the temperature difference sequence using a preset filtering method to obtain a target temperature difference sequence; specifically, for each temperature difference in the temperature difference sequence, determine the neighborhood interval of the temperature difference; the neighborhood interval includes the temperature difference and the temperature differences adjacent to the temperature difference; for each temperature difference in the temperature difference sequence, determine the filtering value corresponding to the temperature difference based on the neighborhood interval corresponding to the temperature difference.

[0073] Generate the target temperature difference based on the target temperature difference sequence; specifically, determine the average value between the filtering values of the target temperature difference sequence as the target temperature difference.

[0074] Among them, determining the filtering value corresponding to the temperature difference based on the neighborhood interval corresponding to the temperature difference includes the following steps:

[0075] Determine the standard deviation between the temperature differences within the neighborhood interval ;

[0076] Through Obtain the Gaussian weights corresponding to each temperature difference within the neighborhood interval respectively; wherein, represents the temperature difference corresponding to the neighborhood interval, represents any temperature difference within the neighborhood interval; it can be understood that any temperature difference within the neighborhood interval includes the temperature difference corresponding to the neighborhood interval;

[0077] Add up the Gaussian weights corresponding to each temperature difference within the neighborhood interval to obtain the sum of Gaussian weights;

[0078] For each temperature difference within the neighborhood interval, determine that the ratio of the Gaussian weight corresponding to the temperature difference to the sum of Gaussian weights is the target weight of the temperature difference;

[0079] Perform weighted summation on each temperature difference within the neighborhood interval based on the target weights of each temperature difference within the neighborhood interval to obtain the filtering value.

[0080] It can be understood that the above method can effectively eliminate the noise that may be generated during the measurement process by filtering the temperature difference sequence, ensure the smoothness and continuity of the temperature difference sequence, and contribute to providing a reliable data basis for the subsequent calculation of the thickness of the graphene heat dissipation layer.

[0081] Step S5: Integrate a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0082] The method provided in this embodiment, on the one hand, utilizes the high thermal conductivity of the graphene heat dissipation layer and combines the thickness distribution optimization method to achieve efficient heat conduction and uniform diffusion of heat in the multi-layer chip, fundamentally alleviating the problem of heat accumulation in the chip and ensuring the stable operation of the chip. On the other hand, the design method of the thickness of the graphene heat dissipation layer provided in this embodiment can make the design of the graphene heat dissipation layer adapt to the complex structure and different thermal load areas of the chip, ensuring that all areas of the chip can obtain an efficient heat dissipation effect, thereby avoiding the occurrence of local overheating phenomena.

[0083] Please refer to Figure 2 , Figure 2 which is a schematic block diagram of the structure of the multi-layer chip thermal diffusion system 100 based on graphene provided by the embodiment of the present application. As Figure 2 shown, the multi-layer chip thermal diffusion system 100 based on graphene provided by the embodiment of the present application includes:

[0084] A first acquisition module 110, configured to acquire the working condition information of the multi-layer chip; the working condition information includes various working conditions of the multi-layer chip.

[0085] The combinatorial operation module 120 is configured to perform combinatorial operations on each of the working conditions to obtain a variety of working condition combinations.

[0086] The second acquisition module 130 is configured to, for each of the working condition combinations, control the multi-layer chip to operate for a preset duration under the working condition combination, and in the process of the operation of the multi-layer chip, acquire a surface temperature distribution map of the multi-layer chip in real time, so as to obtain the surface temperature distribution change information of the multi-layer chip under the working condition combination.

[0087] The generation module 140 is configured to generate thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information.

[0088] The processing module 150 is configured to integrate a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0089] It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described device and each module can refer to the processes in the foregoing embodiments of the method for thermal diffusion of a multi-layer chip based on graphene, and will not be elaborated herein.

[0090] The multi-layer chip thermal diffusion system 100 based on graphene provided in the above embodiment can be implemented in the form of a computer program, and this computer program can run on a terminal device 200 as shown in Figure 3 Figure.

[0091] Please refer to Figure 3 , Figure 3 which is a schematic block diagram of the structure of the terminal device 200 provided in the embodiment of the present application. The terminal device 200 includes a processor 201 and a memory 202. The processor 201 and the memory 202 are connected through a device bus 203. Among them, the memory 202 may include a non-volatile storage medium and an internal memory.

[0092] The non-volatile storage medium can store a computer program. This computer program includes program instructions, and when the program instructions are executed by the processor 201, the processor 201 can be enabled to execute any of the above methods for thermal diffusion of a multi-layer chip based on graphene.

[0093] The processor 201 is configured to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0094] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor 201, the processor 201 can be enabled to execute any of the above methods for thermal diffusion of a multi-layer chip based on graphene.

[0095] Those skilled in the art can understand thatFigure 3 The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the terminal device 200 involved in the solution of this application. Specifically, the terminal device 200 may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0096] It should be understood that the processor 201 may be a central processing unit (CPU), and the processor 201 may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0097] Among them, in some embodiments, the processor 201 is used to run a computer program stored in the memory to implement the following steps:

[0098] Obtain the working condition information of the multi-layer chip; the working condition information includes various working conditions of the multi-layer chip;

[0099] Perform combined operations on each of the working conditions to obtain a variety of working condition combinations;

[0100] For each of the working condition combinations, control the multi-layer chip to operate for a preset duration under the working condition combination, and in the process of the multi-layer chip running, obtain the surface temperature distribution map of the multi-layer chip in real time, and obtain the surface temperature distribution change information of the multi-layer chip under the working condition combination;

[0101] Generate the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information;

[0102] Integrate the graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0103] It should be noted that those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the terminal device 200 described above can refer to the process of the multi-layer chip heat diffusion method based on graphene described above, and will not be repeated here.

[0104] An embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by one or more processors, the one or more processors are caused to implement the graphene-based multi-layer chip thermal diffusion method provided by the embodiment of the present application.

[0105] Among them, the computer-readable storage medium may be an internal storage unit of the terminal device 200 in the foregoing embodiment, such as the hard disk or memory of the terminal device 200. The computer-readable storage medium may also be an external storage device of the terminal device 200, such as a plug-in hard disk equipped with the terminal device 200, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc.

[0106] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A multi-layer chip heat diffusion method based on graphene, characterized in that: include: Acquiring operating condition information of the multi-layer chip; the operating condition information includes multiple operating conditions of the multi-layer chip; Performing combination operations on each of the working conditions to obtain multiple working condition combinations; For each of the working condition combinations, the multi-layer chip is controlled to operate for a preset time under the working condition combination, and a surface temperature distribution diagram of the multi-layer chip is acquired in real time during the operation of the multi-layer chip to obtain surface temperature distribution change information of the multi-layer chip under the working condition combination; Generate thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information; integrating a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information; Wherein, the step of generating the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on the surface temperature distribution change information includes: Constructing a virtual model of the multi-layer chip, and performing finite element segmentation processing on the surface of the virtual model to obtain a finite element model corresponding to the virtual model; For each of the surface temperature distribution change information, generating the heating efficiency of each finite element unit of the finite element model based on the surface temperature distribution change information; For each of the finite element units, determining the maximum heating efficiency corresponding to the finite element unit as the target heating efficiency corresponding to the finite element unit; For each of the finite element units, the thickness of the graphene heat dissipation layer corresponding to the finite element unit is determined based on the target heating efficiency corresponding to the finite element unit and a preset graphene heat dissipation model; the thickness of the graphene heat dissipation layer corresponding to each of the finite element units constitutes the thickness distribution information; The step of generating the heating efficiency of each finite element unit of the finite element model based on the surface temperature distribution change information includes: For each surface temperature distribution graph in the surface temperature distribution change information, the finite element unit is rendered based on the surface temperature distribution graph, and the temperature value of each finite element unit of the finite element model is obtained based on the surface temperature distribution graph; For each of the finite element units, the temperature values ​​are arranged in sequence based on the acquisition time of the surface temperature distribution diagram corresponding to each temperature value corresponding to the finite element unit to obtain a temperature value sequence corresponding to the finite element unit; For each of the finite element units, sequentially calculating the temperature difference between two adjacent temperature values ​​in the temperature value sequence corresponding to the finite element unit to obtain a temperature difference value sequence corresponding to the finite element unit; For each of the finite element units, generating a target temperature difference value corresponding to the finite element unit based on a temperature difference value sequence corresponding to the finite element unit; For each of the finite element units, the heating efficiency of the finite element unit is generated based on the area corresponding to the finite element unit, the target temperature difference corresponding to the finite element unit, the thickness corresponding to the multi-layer chip at the finite element unit, the density and specific heat capacity of the multi-layer chip, and the time difference corresponding to the target temperature difference.

2. The graphene-based multi-layer chip heat diffusion method according to claim 1, characterized in that: The generating the target temperature difference value corresponding to the finite element unit based on the temperature difference value sequence corresponding to the finite element unit includes: Using a preset filtering method to filter the temperature difference sequence to obtain a target temperature difference sequence; The target temperature difference value is generated based on the target temperature difference value sequence.

3. The graphene-based multi-layer chip heat diffusion method according to claim 2, characterized in that: The filtering process of the temperature difference value sequence by using a preset filtering method to obtain a target temperature difference value sequence includes: For each temperature difference value in the temperature difference value sequence, determine a neighborhood interval of the temperature difference value; the neighborhood interval includes the temperature difference value and temperature difference values ​​adjacent to the temperature difference value; For each temperature difference in the temperature difference sequence, a filter value corresponding to the temperature difference is determined based on a neighborhood interval corresponding to the temperature difference.

4. The graphene-based multi-layer chip heat diffusion method according to claim 3, characterized in that: The determining the filter value corresponding to the temperature difference based on the neighborhood interval corresponding to the temperature difference includes: Determine the standard deviation between the temperature differences within the neighborhood interval ; pass Obtain the Gaussian weights corresponding to each temperature difference in the neighborhood interval respectively; wherein, represents the temperature difference corresponding to the neighborhood interval, represents any temperature difference within the neighborhood interval; Adding the Gaussian weights corresponding to the temperature differences in the neighborhood interval to obtain the sum of the Gaussian weights; For each temperature difference in the neighborhood interval, determine a ratio of a Gaussian weight corresponding to the temperature difference to a sum of the Gaussian weights as a target weight for the temperature difference; The temperature difference values ​​in the neighborhood interval are weighted and summed based on the target weights of the temperature difference values ​​in the neighborhood interval to obtain the filtered value.

5. The graphene-based multi-layer chip heat diffusion method according to claim 2, characterized in that: The generating the target temperature difference based on the target temperature difference sequence comprises: An average value between each filtered value of the target temperature difference sequence is determined as the target temperature difference.

6. A multi-layer chip heat diffusion system based on graphene, characterized in that: include: A first acquisition module is used to acquire operating condition information of the multi-layer chip; the operating condition information includes multiple operating conditions of the multi-layer chip; A combination operation module, used for performing combination operation on each of the working conditions to obtain a plurality of working condition combinations; A second acquisition module is used to control the multi-layer chip to operate for a preset time under each of the operating condition combinations, and to acquire a surface temperature distribution diagram of the multi-layer chip in real time during the operation of the multi-layer chip, so as to obtain surface temperature distribution change information of the multi-layer chip under the operating condition combination; A generating module, used for generating thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on each of the surface temperature distribution change information; a processing module, configured to integrate a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information; Wherein, the step of generating the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on the surface temperature distribution change information includes: Constructing a virtual model of the multi-layer chip, and performing finite element segmentation processing on the surface of the virtual model to obtain a finite element model corresponding to the virtual model; For each of the surface temperature distribution change information, generating the heating efficiency of each finite element unit of the finite element model based on the surface temperature distribution change information; For each of the finite element units, determining the maximum heating efficiency corresponding to the finite element unit as the target heating efficiency corresponding to the finite element unit; For each of the finite element units, the thickness of the graphene heat dissipation layer corresponding to the finite element unit is determined based on the target heating efficiency corresponding to the finite element unit and a preset graphene heat dissipation model; the thickness of the graphene heat dissipation layer corresponding to each of the finite element units constitutes the thickness distribution information; The step of generating the heating efficiency of each finite element unit of the finite element model based on the surface temperature distribution change information includes: For each surface temperature distribution graph in the surface temperature distribution change information, the finite element unit is rendered based on the surface temperature distribution graph, and the temperature value of each finite element unit of the finite element model is obtained based on the surface temperature distribution graph; For each of the finite element units, the temperature values ​​are arranged in sequence based on the acquisition time of the surface temperature distribution diagram corresponding to each temperature value corresponding to the finite element unit to obtain a temperature value sequence corresponding to the finite element unit; For each of the finite element units, sequentially calculating the temperature difference between two adjacent temperature values ​​in the temperature value sequence corresponding to the finite element unit to obtain a temperature difference value sequence corresponding to the finite element unit; For each of the finite element units, generating a target temperature difference value corresponding to the finite element unit based on a temperature difference value sequence corresponding to the finite element unit; For each of the finite element units, the heating efficiency of the finite element unit is generated based on the area corresponding to the finite element unit, the target temperature difference corresponding to the finite element unit, the thickness corresponding to the multi-layer chip at the finite element unit, the density and specific heat capacity of the multi-layer chip, and the time difference corresponding to the target temperature difference.

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