Graphene-based multilayer chip thermal diffusion method and system

Abstract

The invention relates to the technical field of heat dissipation, and provides a multilayer chip heat diffusion method and system based on graphene. The method comprises the following steps: acquiring working condition information of a multi-layer chip; the working condition information comprises various working conditions of the multi-layer chip; performing combination operation on each working condition to obtain a plurality of working condition combinations; for each working condition combination, controlling the multi-layer chip to run for a preset time length under the working condition combination, and acquiring a surface temperature distribution diagram of the multi-layer chip in real time in the running process of the multi-layer chip to obtain surface temperature distribution change information of the multi-layer chip under the working condition combination; generating thickness distribution information of a graphene heat dissipation layer in the multi-layer chip based on the surface temperature distribution change information; and integrating a graphene heat dissipation layer in the multilayer chip based on the thickness distribution information. According to the method, all areas of the chip can be ensured to obtain an efficient heat dissipation effect, so that the phenomenon of local overheating is avoided.

Description

Technical Field

[0001] The present application relates to the field of heat dissipation technology, and in particular to a graphene-based multi-layer chip heat diffusion method and system. Background Art

[0002] In modern electronic devices, with the continuous advancement of integrated circuit technology, the integration and functional complexity of chips are increasing, and multi-layer chips are gradually becoming the core components of high-performance electronic devices. However, as the number of chip layers increases, the problem of heat accumulation between the layers inside the chip is becoming increasingly prominent. In order to ensure the effective operation of electronic devices, it is very important to effectively dissipate the heat of multi-layer chips.

[0003] However, existing chip heat dissipation methods usually use fans or microchannel liquid cooling systems for heat dissipation, which makes it difficult to effectively dissipate heat in all areas of a multi-layer chip. Summary of the invention

[0004] The present application provides a graphene-based multi-layer chip heat diffusion method and system to solve the problems raised by the above background technology.

[0005] In a first aspect, the present application provides a graphene-based multi-layer chip heat diffusion method, comprising: 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; A graphene heat dissipation layer is integrated in the multi-layer chip based on the thickness distribution information.

[0006] In a possible implementation, the 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.

[0007] In a possible implementation, 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.

[0008] In a possible implementation, generating a target temperature difference corresponding to the finite element unit based on a temperature difference 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.

[0009] In a possible implementation, 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.

[0010] In a possible implementation manner, 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.

[0011] In a possible implementation manner, an average value between each filtered value of the target temperature difference sequence is determined as the target temperature difference.

[0012] In a second aspect, the present application provides a graphene-based multi-layer chip heat diffusion system, comprising: 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 is used to perform combination operations on each of the working conditions to obtain multiple 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 is used to integrate a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0013] The present application provides a graphene-based multi-layer chip heat diffusion method and system, the method comprising: obtaining 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 operating conditions to obtain multiple operating condition combinations; for each of the operating condition combinations, controlling the multi-layer chip to operate for a preset time under the operating condition combination, and obtaining a surface temperature distribution diagram of the multi-layer chip 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 operating condition combination; 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; and integrating the graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information. This method, on the one hand, utilizes the high thermal conductivity of the graphene heat dissipation layer and combines it with a thickness distribution optimization method to achieve efficient conduction and uniform diffusion of heat in a multi-layer chip, fundamentally alleviating the problem of heat accumulation in the chip and ensuring stable operation of the chip. On the other hand, the design method for 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 of the chip and different heat load areas, ensuring that all areas of the chip can obtain efficient heat dissipation effects, thereby avoiding the occurrence of local overheating. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0015] Figure 1 A schematic diagram of a flow chart of a graphene-based multi-layer chip heat diffusion method provided in an embodiment of the present application; Figure 2 A schematic block diagram of the structure of a graphene-based multi-layer chip heat diffusion system provided in an embodiment of the present application; Figure 3 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0018] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0019] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0020] In conjunction with the accompanying drawings, some embodiments of the present application are described in detail below. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0021] See also Figure 1 , Figure 1 A schematic diagram of a multi-layer chip heat diffusion method based on graphene provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the graphene-based multi-layer chip heat diffusion method provided in the embodiment of the present application includes steps S1 to S5.

[0022] Step S1, obtaining operating condition information of the multi-layer chip; the operating condition information includes multiple operating conditions of the multi-layer chip.

[0023] Specifically, the operating condition information of the multi-layer chip is acquired from a functional information database of the multi-layer chip.

[0024] Step S2: performing combination operations on the various working conditions to obtain a plurality of working condition combinations.

[0025] The multiple operating condition combinations include all possible situations of randomly extracting a number of operating conditions from each of the operating conditions. For example, if the operating condition information includes operating condition 1, operating condition 2, and operating condition 3, the multiple operating condition combinations include seven operating condition combinations: {operating condition 1}, {operating condition 2}, {operating condition 3}, {operating condition 1, operating condition 2}, {operating condition 1, operating condition 3}, {operating condition 2, operating condition 3}, and {operating condition 1, operating condition 2, operating condition 3}.

[0026] Step S3: for each of the working condition combinations, control the multi-layer chip to run for a preset time under the working condition combination, and obtain the surface temperature distribution diagram of the multi-layer chip in real time during the operation of the multi-layer chip to obtain the surface temperature distribution change information of the multi-layer chip under the working condition combination.

[0027] Specifically, a programmable logic controller is used to control the multi-layer chip to run for a preset time under the operating condition combination, and an infrared camera is used to obtain a surface temperature distribution diagram of each layer of the multi-layer chip in real time during the operation of the multi-layer chip to obtain the surface temperature distribution change information of the multi-layer chip under the operating condition combination.

[0028] Step S4: generating thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on the surface temperature distribution change information.

[0029] Specifically, step S4 includes the following steps: A virtual model of the multi-layer chip is constructed, and a finite element segmentation process is performed on the surface of the virtual model to obtain a finite element model corresponding to the virtual model; specifically, a laser point cloud of the multi-layer chip is acquired by a laser point cloud acquisition device, and a virtual model of the multi-layer chip is constructed based on the laser point cloud, and a finite element segmentation process is performed on the surface of the virtual model based on a preset finite element segmentation method to obtain the finite element 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; wherein the heating efficiency refers to the heat generated by the finite element unit per unit time; For each of the finite element units, the maximum heating efficiency corresponding to the finite element unit is determined as the target heating efficiency corresponding to the finite element unit; it can be understood that determining the maximum heating efficiency corresponding to the finite element unit as the target heating efficiency corresponding to the finite element unit is helpful for subsequently designing a graphene thickness for the finite element unit that is sufficient to ensure effective heat dissipation of 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; wherein the graphene heat dissipation model is a heat dissipation model pre-constructed based on the principle of heat diffusion, the input of the graphene heat dissipation model is the area and target heating efficiency of the finite element unit, and the output is the thickness of the graphene heat dissipation layer corresponding to the finite element unit.

[0030] 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 comprises the following steps: 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; specifically, for each finite element unit, the temperature value of the finite element unit is obtained based on the color information corresponding to the finite element unit 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, the temperature difference between two adjacent temperature values ​​in the temperature value sequence corresponding to the finite element unit is calculated in sequence to obtain the temperature difference sequence corresponding to the finite element unit; specifically, for two adjacent temperature values, the temperature difference between the two adjacent temperature values ​​is obtained by subtracting the previous temperature value from the latter temperature value; 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 of 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; specifically, the area corresponding to the finite element unit, the thickness of the multi-layer chip at the finite element unit, the density of the multi-layer chip, the target temperature difference corresponding to the finite element unit, and the specific heat capacity of the multi-layer chip are multiplied to obtain a target product, and the ratio of the target product to the time difference is determined as the heating efficiency of the finite element unit.

[0031] It can be understood that the above-mentioned method of generating the heating efficiency of each finite element unit of the finite element model based on the surface temperature distribution change information, on the one hand, can identify specific hot spots and inefficient heat dissipation areas in the multi-layer chip by accurately calculating the heating efficiency of each finite element unit. Based on this information, the thickness distribution of the graphene heat dissipation layer can be adjusted in a targeted manner to achieve personalized thermal optimization and improve the overall heat dissipation effect. On the other hand, by accurately controlling the heating efficiency of each finite element unit, it can effectively prevent the occurrence of local overheating, reduce the chip performance degradation and increased failure rate caused by excessive temperature, help extend the service life of the multi-layer chip, and ensure the stability and reliability of the multi-layer chip under high-performance operating conditions.

[0032] Wherein, 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 comprises the following steps: A preset filtering method is used to filter the temperature difference sequence to obtain a target temperature difference sequence; specifically, for each temperature difference in the temperature difference sequence, a neighborhood interval of the temperature difference is determined; the neighborhood interval includes the temperature difference and temperature differences adjacent to the temperature difference; for each temperature difference in the temperature difference sequence, a filter value corresponding to the temperature difference is determined based on the neighborhood interval corresponding to the temperature difference; The target temperature difference is generated based on the target temperature difference sequence; specifically, an average value between each filtered value of the target temperature difference sequence is determined as the target temperature difference.

[0033] Wherein, determining the filter value corresponding to the temperature difference based on the neighborhood interval corresponding to the temperature difference comprises the following steps: 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 value within the neighborhood interval; it can be understood that any temperature difference value within the neighborhood interval includes the temperature difference value corresponding to 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.

[0034] It can be understood that the above method can effectively eliminate the noise that may be generated in the measurement process by filtering the temperature difference sequence, ensure the smoothness and continuity of the temperature difference sequence, and help provide a reliable data basis for the subsequent calculation of the thickness of the graphene heat dissipation layer.

[0035] Step S5: integrating a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0036] The method provided in this embodiment, on the one hand, utilizes the high thermal conductivity of the graphene heat dissipation layer, combined with the thickness distribution optimization method, to achieve efficient 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 of the chip and different heat load areas, ensuring that all areas of the chip can obtain efficient heat dissipation effects, thereby avoiding the occurrence of local overheating.

[0037] See also Figure 2 , Figure 2 The schematic block diagram of the structure of the graphene-based multi-layer chip heat diffusion system 100 provided in the embodiment of the present application is as follows: Figure 2 As shown, the graphene-based multi-layer chip heat diffusion system 100 provided in the embodiment of the present application includes: The first acquisition module 110 is used to acquire the operating condition information of the multi-layer chip; the operating condition information includes multiple operating conditions of the multi-layer chip.

[0038] The combination operation module 120 is used to perform combination operations on each of the working conditions to obtain multiple working condition combinations.

[0039] The second acquisition module 130 is used to control the multi-layer chip to operate for a preset time under the operating condition combination for each of the operating condition combinations, and to obtain the surface temperature distribution diagram of the multi-layer chip in real time during the operation of the multi-layer chip, so as to obtain the surface temperature distribution change information of the multi-layer chip under the operating condition combination.

[0040] The generating module 140 is used to generate the thickness distribution information of the graphene heat dissipation layer in the multi-layer chip based on the surface temperature distribution change information.

[0041] The processing module 150 is used to integrate a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

[0042] It should be noted that technicians in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described device and each module can refer to the process in the aforementioned graphene-based multi-layer chip thermal diffusion method embodiment, and will not be repeated here.

[0043] The graphene-based multi-layer chip heat diffusion system 100 provided in the above embodiment can be implemented in the form of a computer program. The computer program can be used in a computer program such as Figure 3 The system is run on the terminal device 200 shown.

[0044] See also Figure 3 , Figure 3The present invention provides a schematic block diagram of the structure of a terminal device 200 according to an 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 via a device bus 203, wherein the memory 202 may include a non-volatile storage medium and an internal memory.

[0045] The non-volatile storage medium can store a computer program. The computer program includes program instructions, and when the program instructions are executed by the processor 201, the processor 201 can execute any of the above-mentioned graphene-based multi-layer chip heat diffusion methods.

[0046] The processor 201 is used to provide computing and control capabilities to support the operation of the entire terminal device 200.

[0047] 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 execute any of the above-mentioned graphene-based multi-layer chip heat diffusion methods.

[0048] Those skilled in the art will understand that Figure 3 The structure shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the terminal device 200 involved in the scheme of the present application. The specific terminal device 200 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0049] 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 (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) 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.

[0050] In some embodiments, the processor 201 is used to run a computer program stored in the memory to implement the following steps: 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; A graphene heat dissipation layer is integrated in the multi-layer chip based on the thickness distribution information.

[0051] It should be noted that technicians in the relevant field 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 aforementioned graphene-based multi-layer chip thermal diffusion method, and will not be repeated here.

[0052] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by one or more processors, the one or more processors implement the graphene-based multi-layer chip thermal diffusion method provided in the embodiment of the present application.

[0053] The computer-readable storage medium may be an internal storage unit of the terminal device 200 in the aforementioned embodiment, such as a 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, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped with the terminal device 200.

[0054] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on 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; A graphene heat dissipation layer is integrated in the multi-layer chip based on the thickness distribution information.

2. The graphene-based multi-layer chip heat diffusion method according to claim 1, characterized in that: The step of 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 comprises: 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.

3. The graphene-based multi-layer chip heat diffusion method according to claim 2, characterized in that: 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.

4. The graphene-based multi-layer chip heat diffusion method according to claim 3, 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.

5. The graphene-based multi-layer chip heat diffusion method according to claim 4, 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.

6. The graphene-based multi-layer chip heat diffusion method according to claim 5, 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.

7. The graphene-based multi-layer chip heat diffusion method according to claim 4, 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.

8. 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 is used to integrate a graphene heat dissipation layer in the multi-layer chip based on the thickness distribution information.

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