Parameter determination method, system and device, program product and storage medium

Abstract

The invention discloses a parameter determination method, which comprises the following steps of: establishing an integrated chip heat transport equation, introducing boundary conditions, and performing accurate solution by adopting a finite element or finite difference method to obtain temperature distribution characteristics of an integrated chip; and secondly, aiming at the heat management problem of the heterogeneous integrated chip, taking the chip junction temperature as an optimization target, and constructing an integrated chip junction temperature optimization algorithm by introducing a design constraint condition and comprehensively considering parameter change conditions such as a process parameter, a material parameter, a core particle position and a packaging design structure. According to the invention, precise regulation and control of the chip temperature and optimal configuration of packaging design structure parameters are realized. Therefore, the thermal management performance of the integrated chip is improved, and guarantee is provided for high performance and high reliability of the chip.

Description

Technical Field

[0001] The present application relates to the field of three-dimensional heterogeneous heterogeneous integration technology, and in particular to a parameter determination method, system, device, program product and storage medium. Background Art

[0002] With the rapid development of integrated circuit technology, transistor technology represented by feature size miniaturization is gradually approaching physical limits. This trend has prompted the industry to seek new technical paths to continue Moore's Law, and integrated chip technology has become an important development direction. Integrated chip technology integrates multiple functional modules on the same chip, which can not only develop higher-performance products at a faster speed and lower cost, but also significantly improve the integration and reliability of the system.

[0003] However, the development of integrated chip technology has also brought new challenges. With the continuous improvement of integration, the increase in power consumption density and the concentrated accumulation of heat have caused the local temperature of the integrated chip to rise sharply, which not only affects the performance of the chip, but also seriously threatens its thermal reliability in long-term operation. Especially for the heterogeneous integration technology of core particles, the combination of different materials and processes makes the thermal management problem more complicated. At present, the thermal management technology of integrated chips is still in the research and development stage, and no unified standards and processes have been formed. Existing thermal management methods mostly rely on the experience and intuition of engineers, lack of systematic and theoretical support, and often require repeated verification work when facing complex and changeable chip designs, resulting in the optimization process being not accurate enough and it is difficult to find the optimal solution. This situation not only increases the cost of research and development, but also limits the further development of integrated chip technology. Summary of the invention

[0004] Based on the above problems, the present application provides a parameter determination method, system, device, program product and storage medium.

[0005] The embodiments of the present application disclose the following technical solutions:

[0006] In a first aspect, the present application discloses a parameter determination method, comprising:

[0007] Initialize the parameter variables of the junction temperature optimization model to obtain the parameter initialization values;

[0008] Solving the heat transfer equation based on the parameter initialization value to obtain temperature distribution data, and calculating the temperature optimal function value, and updating the global optimal and local optimal positions of the parameter variable sequence; the heat transfer equation is determined based on the energy conservation relationship and the functional relationship between the heat flux density and the temperature gradient, and the energy conservation relationship is used to characterize that the change in the chip energy per unit time is equal to the sum of the heat obtained by the chip through the chip interface and the heat generated inside the system per unit time;

[0009] Based on the updated global optimal position and local optimal position, the particle velocity and particle position are updated, and the heat transport equation is solved and subsequent steps are performed based on the updated parameter information until the preset number of iterations is reached and the temperature optimal function value is less than the preset temperature threshold, and the thermal simulation parameters of the integrated chip are output.

[0010] In a possible implementation, the particle velocity is updated based on the updated global optimal position and the local optimal position, including:

[0011] The particle speed is updated based on the speed update formula and the updated global optimal position and local optimal position. The speed update formula is v=w1*v+w2*(Gp-x)+w3*(Gb-x), w1, w2 and w3 are weight parameters within a preset numerical range, x is the global optimal and local optimal positions of the parameter variable sequence, Gp is ​​the updated global optimal position, and Gb is the updated local optimal position.

[0012] In a possible implementation, the particle position is updated based on the updated global optimal position and the local optimal position, including:

[0013] The sum of the original particle position and the updated particle velocity is calculated to obtain the updated particle position.

[0014] In a possible implementation, after solving the heat transport equation based on the updated parameters and subsequent steps, the method further includes:

[0015] If the preset number of iteration steps is reached, determine whether the current temperature optimal function value is less than the preset temperature threshold;

[0016] If the current temperature optimal function value is not less than the preset temperature threshold, the parameter variables of the junction temperature optimization model are initialized and subsequent steps are performed until the preset number of iterations is met and the temperature optimal function value is less than the preset temperature threshold, and the target parameters are output.

[0017] In a possible implementation, the method further includes:

[0018] If the improvement of the temperature optimal function value obtained by multiple consecutive iterations is less than a preset threshold, the iteration is terminated and the target parameter is output.

[0019] In a possible implementation, the thermal simulation parameters of the integrated chip include the core particle position, the geometric size range of the heat sink, the heat transfer coefficient process parameters and the thermal conductivity parameters of the thermal interface material, which affect the heat dissipation performance and temperature distribution of the chip.

[0020] A second aspect of the present application provides a parameter determination system, comprising:

[0021] An initialization unit, used to initialize parameter variables of the junction temperature optimization model to obtain parameter initialization values;

[0022] A calculation unit, used to solve the heat transfer equation based on the parameter initialization value, obtain temperature distribution data, calculate the temperature optimal function value, and update the global optimal and local optimal positions of the parameter variable sequence; the heat transfer equation is determined based on the energy conservation relationship and the functional relationship between the heat flux density and the temperature gradient, and the energy conservation relationship is used to characterize that the change in the chip energy per unit time is equal to the sum of the heat obtained by the chip through the chip interface and the heat generated inside the system per unit time;

[0023] The output unit is used to update the particle velocity and particle position based on the updated global optimal position and local optimal position, solve the heat transport equation and subsequent steps based on the updated parameter information, until a preset number of iterations is reached and the temperature optimal function value is less than a preset temperature threshold, and output the thermal simulation parameters of the integrated chip.

[0024] Compared with the prior art, this application has the following beneficial effects:

[0025] Initialize the parameter variables in the junction temperature optimization model to obtain the parameter initialization values. Based on these parameter initialization values, the heat transport equation is used for solution. The heat transport equation is based on the energy conservation relationship, that is, the change in chip energy per unit time is equal to the sum of the heat obtained by the chip through the interface and the heat generated inside the system per unit time. At the same time, the equation also considers the functional relationship between heat flux density and temperature gradient, so that it can accurately reflect the temperature distribution inside the chip. By solving the heat transport equation, the temperature distribution data is obtained, and the temperature optimal function value is calculated, which reflects the overall temperature performance of the chip under the current parameter configuration. According to the calculated temperature optimal function value, the global optimal position and local optimal position of the parameter variable sequence are updated. By continuously updating the speed and position of the particles, a better solution in the parameter space can be explored. Repeat the solution of the heat transport equation based on the parameter initialization value and subsequent steps until the preset number of iterations is reached and the temperature optimal function value is less than the preset temperature threshold. This process gradually optimizes the parameter settings through multiple iterations, and finally obtains the optimal solution that meets the thermal management requirements, providing specific guidance for actual chip design and manufacturing, so that the temperature performance of the chip meets the expected requirements. Therefore, the present application realizes the precise control of chip temperature and the optimal configuration of packaging design structural parameters, which not only improves the thermal management performance of the integrated chip, but also provides a guarantee for the high performance and high reliability of the chip. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0027] Figure 1 A flow chart of a parameter determination method provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of an iterative process provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of the integrated chip structure provided in the embodiment of the present application;

[0030] Figure 4 A structural diagram of a parameter determination system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0032] To facilitate understanding of the technical solutions provided by the embodiments of the present application, the background technology involved in the embodiments of the present application will be described below.

[0033] As mentioned above, with the continuous advancement of integrated circuit technology, the continuous miniaturization of feature sizes has indeed promoted the rapid development of transistor technology, but at the same time it has also gradually approached the limits of physics. In this context, the importance of integrated chip technology as a key path to continue Moore's Law has become increasingly prominent. This technology aims to achieve rapid and low-cost research and development of higher-performance products through innovative means. However, this is accompanied by a significant increase in power consumption density and heat accumulation problems, which directly leads to a sharp rise in the local temperature of the integrated chip, posing a severe challenge to the thermal reliability of heterogeneous integration of core particles.

[0034] To address this challenge, traditional thermal management methods mainly rely on engineers' experience and intuition and lack systematic theoretical support. This method cannot guarantee the best solution every time when faced with complex and ever-changing chip designs.

[0035] Existing thermal management methods lack a systematic theoretical framework and are unable to comprehensively consider all influencing factors, such as material properties, geometric structure, heat source distribution, etc. This often leads to the omission of key factors during the optimization process, affecting the final optimization effect.

[0036] Due to the lack of accurate mathematical models and optimization algorithms, existing thermal management methods often require multiple trials and verifications during the optimization process. This trial-and-error method is not only time-consuming and labor-intensive, but also difficult to guarantee the global optimal solution.

[0037] In practical applications, the thermal management of chips involves the optimization of multiple parameters, such as the shape and size of the heat sink, the design of the heat dissipation channel, the thermal conductivity of the material, etc. There are complex interactions between these parameters, and traditional empirical methods are difficult to effectively handle such multi-parameter optimization problems.

[0038] In order to solve the above problems, the embodiment of the present application constructs a transient heat flow simulation model of the integrated chip. By accurately solving the heat transfer equation of the integrated chip and introducing boundary conditions, the temperature distribution characteristics of the integrated chip are obtained. This step provides accurate temperature data support for subsequent junction temperature optimization.

[0039] In response to the thermal management problem of heterogeneous integrated chips, this application takes the chip junction temperature as the optimization target, introduces design constraints, and comprehensively considers parameter changes such as process parameters, material parameters, core particle position and packaging design structure to construct an integrated chip junction temperature optimization algorithm. This model can achieve accurate prediction and optimal control of the temperature distribution of the integrated chip.

[0040] Based on the transient heat flow simulation model and the integrated chip junction temperature optimization model, an integrated chip junction temperature optimization method was established. This method achieves the optimization and regulation of the integrated chip design structure, heat source location, material and process parameters through the steps of parameter variable initialization, temperature distribution simulation, parameter update and iteration. This not only solves the problem of lack of unified standards and processes in the existing technology, but also significantly improves the thermal management efficiency and thermal reliability of the integrated chip.

[0041] It is not only suitable for thermal management of integrated chips, but can also be further expanded to more complex electronic systems, such as wafer-scale heterogeneous integrated systems. This provides the possibility for optimizing different core positions, component materials, geometric structures and process parameters, and helps to obtain the optimal temperature distribution that meets the constraints.

[0042] In this way, accurate prediction and optimal control of the temperature distribution of the integrated chip can be achieved, providing technical support for the physical design and packaging parameter optimization of the chip.

[0043] It should be noted that a parameter determination method, system, device and medium provided in the present application can be applied to the field of computer technology. The above is only an example and does not limit the application field of the parameter determination method, system, device and medium provided in the present application. In addition, the embodiments of the present application may not limit the execution subject of parameter determination. For example, a parameter determination method of an embodiment of the present application can be applied to data processing devices such as terminal devices or servers. Among them, the terminal device can be an electronic device such as a computer, a personal digital assistant (Personal Digital Assistant, PDA). The server can be a stand-alone server, a cloud server or a cluster server composed of multiple servers.

[0044] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] The following is an explanation of the relevant calculation formulas and model setting process involved in the embodiments of this application. First, the integrated chip heat transport equation is established, and boundary conditions are introduced at the same time. The finite element or finite difference method is used for accurate solution to obtain the temperature distribution characteristics of the integrated chip; secondly, for the thermal management problem of heterogeneous integrated chips, the chip junction temperature is taken as the optimization target, and by introducing design constraints, the parameter change conditions such as process parameters, material parameters, core particle position and packaging design structure are comprehensively considered to construct an integrated chip junction temperature optimization algorithm.

[0046] See also Figure 1 , Figure 1 The schematic diagram of the integrated chip structure provided by the embodiment of the present application, wherein the main structure of the integrated chip includes a heat sink, a thermal interface material, a core particle, micro bumps, a silicon interposer, micro bumps and a packaging substrate. In order to improve the efficiency of thermal simulation and management of the integrated chip, the embodiment of the present application treats microscopic structures such as micro bumps as a material, so as to efficiently obtain the overall temperature distribution characteristics of the integrated chip, thereby realizing efficient parameter control.

[0047] According to the law of conservation of energy, the change in the internal energy of the system per unit time is equal to the sum of the heat obtained by the system through the interface and the heat generated inside the system per unit time. Therefore, for a micro rectangular unit cell in an integrated chip with a length of dx, a width of dy, a height of dz, and x, y, and z being the coordinate variables in the X, Y, and Z directions respectively, the expression of energy conservation can be expressed as:

[0048]

[0049] In formula (1), T is temperature, t is time, ρ is the mass density of the conductive material, Cp is the specific heat capacity of the conductive material, and q i (i=x,y,z,x+dx,y+dy,z+dz) is the heat flux density, g v is the total power of the heat source.

[0050] By introducing the functional relationship between heat flux density and temperature gradient through Fourier experimental law, the above formula (1) can be further derived into the integrated chip heat transport equation:

[0051]

[0052] In formula (2), к is the thermal conductivity, s is the subscript, M is the superscript, and g is s is the heat source power, is the partial differential symbol, It is a talisman for Nebla.

[0053] At the same time, according to the design characteristics of the integrated chip, the thermal convection boundary condition is introduced:

[0054]

[0055] In formula (3), n i is the external normal direction, h i is the convective heat transfer coefficient, f i is the ambient temperature.

[0056] By constructing a finite element or finite difference equation group and solving the above integrated chip partial differential equations (2)-(3), the transient temperature distribution characteristics of the integrated chip system can be obtained.

[0057] Optimizing the temperature distribution characteristics of the integrated chip is crucial to ensure the stability and reliability of the system. When the junction temperature of the integrated chip exceeds the design temperature threshold T max When the temperature of the integrated chip is too low, it may lead to thermal runaway, reduced reliability, or even chip burnout. In order to effectively manage the temperature of the integrated chip, optimization can be achieved through design adjustments in the following aspects:

[0058] First, adjust the material parameters. For example, thermal conductivity. Choosing materials with high thermal conductivity can effectively improve the heat conduction efficiency, thereby reducing the chip junction temperature. For example, use high thermal conductivity interface materials between the heat sink and the chip, or use high thermal conductivity substrate materials inside the chip. In addition to thermal conductivity, the thermal expansion coefficient and heat resistance of the material can also be considered to ensure that the material maintains stability and reliability when the temperature changes.

[0059] The second aspect is to adjust the process parameters. For example, the heat transfer coefficient can be improved by optimizing the manufacturing process, such as changing the thickness, shape and layout of the metallization layer, and using a more effective heat dissipation structure, thereby enhancing the heat dissipation effect. Reducing the thermal resistance inside the chip, such as by optimizing the wiring and reducing the concentration of heat sources, can also effectively reduce the chip junction temperature.

[0060] Third, adjust the package design parameters to improve the package design. For example, design an efficient heat sink structure, such as increasing the heat dissipation area, using fins or needle structures to increase the convection heat dissipation effect, and optimizing the material and size of the heat sink. Select packaging materials and processes with excellent heat dissipation performance, such as using low dielectric constant and low loss materials, and optimizing the hot pressing and curing conditions during the packaging process.

[0061] For the sake of convenience, rewrite formula (2) as F(T) = 0, then the temperature distribution can be expressed as: T = F -1 , expressed as the inverse function of formula (2), the junction temperature optimization problem of the integrated chip can be expressed as the following optimization model:

[0062]

[0063] In formula (4), pi is the position of the ith core particle, P is the core particle position range, si is the geometric size of the heat sink (such as length, width, height), S i is the geometric size range of the heat sink, h is the process parameter of the heat transfer coefficient, H is the process parameter range, k is the thermal conductivity parameter of the thermal interface material, K is the thermal conductivity parameter range of the thermal interface material, x i is the abscissa of the core particle, y i is the core particle ordinate, w i is the horizontal width of core particle i, h i is the vertical width of core i, d is the minimum core spacing, L is the total length of core wiring, L max The maximum total length of the core wiring.

[0064] To simplify the design, the constraints (minimum core spacing constraint, position constraint and wiring length constraint) are rewritten as a constraint function g(p i ,s i )≤0, then (4) can be further transformed into:

[0065] stg(p i ,s i )≤0,p i ∈P,s i ∈S i ,h∈H,k∈K (5)

[0066] In order to transform the constrained parameter optimization problem into an unconstrained optimization problem, a constraint penalty function is added to equation (5), and the optimal temperature distribution function (5) can be transformed into:

[0067]

[0068] In formula (6), σ is the penalty function coefficient.

[0069] The following is an example of an embodiment to illustrate a parameter determination method provided by the present application. Figure 2 ,Should Figure 2 A flow chart of a parameter determination method provided in an embodiment of the present application, the method comprising:

[0070] S101 . Initialize parameter variables of a junction temperature optimization model to obtain parameter initialization values.

[0071] For parameter variables (p i ,s i ,h,k) to perform random initialization operations to obtain the initialization parameter variable sequence (p i ,s i ,h,k)|1 N Position x0. The parameter initialization values ​​are the core position, the geometric size range of the heat sink, the heat transfer coefficient process parameters, and the thermal conductivity parameters of the thermal interface material, which affect the heat dissipation performance and temperature distribution of the chip.

[0072] S102, solving the heat transport equation based on the parameter initialization value to obtain temperature distribution data, and calculating the temperature optimal function value, and updating the global optimal and local optimal positions of the parameter variable sequence.

[0073] The heat transfer equation is determined based on the energy conservation relationship and the functional relationship between heat flux density and temperature gradient. The energy conservation relationship is used to characterize that the change in chip energy per unit time is equal to the sum of the heat obtained by the chip through the chip interface and the heat generated inside the system per unit time.

[0074] Combined with the initialization value of the parameter variable position, the temperature distribution of the integrated chip is simulated using the heat transport equations. The temperature optimal function value is calculated, which reflects the overall temperature distribution characteristics of the chip, such as the maximum temperature, average temperature or temperature gradient. According to the temperature optimal function value, the global optimal and local optimal positions x of the parameter variable sequence are updated.

[0075] S103. Based on the updated global optimal position and local optimal position, the particle velocity and particle position are updated, and the heat transport equation and subsequent steps are solved based on the updated parameter information until a preset number of iterations is reached and the temperature optimal function value is less than a preset temperature threshold, and the thermal simulation parameters of the integrated chip are output.

[0076] In one possible implementation, the speed is updated using the parameter variable sequence speed update formula v=w1*v+w2*(Gp-x)+w3*(Gb-x), wherein w1 is a weight parameter, w2 and w3 are weight parameters between [0,2], Gp is ​​the optimal solution for the parameter variable, and Gb is the optimal solution for the parameter variable sequence. The integrated chip heat transport equations are resolved to obtain new temperature distribution data, and the temperature optimal function value T is calculated to further update the global optimal and local optimal positions of the parameter variable sequence x=x+v.

[0077] Gp is ​​the best solution found by all particles in the entire particle swarm, that is, the position with the lowest objective function value among all particles. Gp is ​​the goal pursued by all particles in the particle swarm, and it represents the best search result of the entire group. Gb is the best solution found by a single particle in its search history, that is, the position with the lowest objective function value that the particle can achieve. Each particle has its own local optimal solution Gb, which represents the personal best search result of the particle.

[0078] For each particle, its position x represents the current position in the parameter space. The global optimal position x of a particle refers to the best position found by the particle in the entire search process that is the same as Gp. The local optimal position x of a particle refers to the best position found by the particle in its personal search history that is the same as Gb.

[0079] In the PSO algorithm, Gp and Gb jointly guide the search process of the particle swarm. Gp provides a common goal for the particle swarm, while Gb provides a personalized search direction for each particle. The update of the particle's position x is based on these two optimal solutions to achieve a balance between global search and local search. This mechanism helps the particle swarm algorithm to effectively explore and exploit in complex search spaces to find the optimal solution to the problem. Each particle calculates its temperature optimal function value in each iteration.

[0080] The local optimal solution Gb can be obtained by: if the temperature optimal function value of the current particle is better than the local optimal value in its historical record, then Gb is updated to the position of the particle. This process is independent of other particles, which means that each particle has its own local optimal solution.

[0081] The global optimal solution Gp can be obtained by: in each iteration, all particles will calculate their temperature optimal function values. If the temperature optimal function value of a particle is better than the current global optimal value, Gp is ​​updated to the position of the particle. This process is performed in each iteration to ensure that Gp always remains the best solution found.

[0082] See also Figure 3 , Figure 3 Schematic diagram of the iterative process provided in the embodiment of the present application, wherein the time is judged whether it meets the maximum number of iteration steps, if not, the parameter variable sequence speed and position are updated, and the process goes to step S102; if it meets, it is judged whether the junction temperature of the temperature optimal function value is less than the integrated chip temperature threshold, if it meets, the optimal thermal simulation parameter (p i ,s i ,h,k) values, if not satisfied, go to step S101 and continue to execute the subsequent process until the preset number of iterations is reached and the temperature optimal function value is less than the preset temperature threshold, and output the thermal simulation parameters of the integrated chip.

[0083] Through this iterative optimization process, the optimal parameter configuration that meets the temperature threshold requirements can be found, thereby achieving effective control and optimization of the junction temperature of the integrated chip. This method is particularly suitable for solving the temperature management problem of integrated chips at high power density, which helps to improve the performance and reliability of the chip.

[0084] In a possible implementation, if the preset number of iteration steps is not met, the iteration process provided in the embodiment of the present application may include:

[0085] Solving the heat transport equation for the nth time based on the parameter initialization value, obtaining the nth temperature distribution data, and calculating the nth temperature optimal function value, updating the global optimal position and the local optimal position of the parameter variable sequence, where n is a positive integer;

[0086] Based on the updated global optimal position and local optimal position, the particle velocity and particle position are updated, and the heat transfer equation is solved for the n+1th time based on the updated parameters to obtain the n+1th temperature distribution data, and the n+1th temperature optimal function value is calculated to obtain the n+1th temperature optimal function value, and the global optimal and local optimal positions of the parameter variable sequence are updated; when the preset number of iteration steps is met and the junction temperature of the temperature optimal function value is less than the preset temperature threshold, the target parameters are output.

[0087] The above are some specific implementations of the parameter determination method provided in the embodiment of the present application. Based on this, the present application also provides a corresponding parameter determination system. The system provided in the embodiment of the present application will be introduced from the perspective of functional modularization. Figure 4 A structural diagram of a parameter determination system provided in an embodiment of the present application.

[0088] The system comprises:

[0089] An initialization unit 110 is used to initialize parameter variables of the junction temperature optimization model to obtain parameter initialization values;

[0090] The calculation unit 111 is used to solve the heat transfer equation based on the parameter initialization value, obtain temperature distribution data, calculate the temperature optimal function value, and update the global optimal and local optimal positions of the parameter variable sequence; the heat transfer equation is determined based on the energy conservation relationship and the functional relationship between the heat flux density and the temperature gradient, and the energy conservation relationship is used to characterize that the change in the chip energy per unit time is equal to the sum of the heat obtained by the chip through the chip interface and the heat generated inside the system per unit time;

[0091] The output unit 112 is used to update the particle velocity and particle position based on the updated global optimal position and local optimal position, solve the heat transfer equation and subsequent steps based on the updated parameter information, until a preset number of iterations is reached and the temperature optimal function value is less than a preset temperature threshold, and output the thermal simulation parameters of the integrated chip.

[0092] The embodiments of the present application also provide corresponding devices and computer storage media for implementing the solutions provided by the embodiments of the present application.

[0093] The device includes a memory and a processor, the memory is used to store instructions or codes, and the processor is used to execute the instructions or codes so that the device executes the method described in any embodiment of the present application.

[0094] The computer storage medium stores codes, and when the codes are executed, a device executing the codes implements the method described in any embodiment of the present application.

[0095] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other. For the system or device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0096] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0097] It should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0098] It should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0099] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0100] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0101] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A parameter determination method, characterized in that: include: Initialize the parameter variables of the junction temperature optimization model to obtain the parameter initialization values; Solving the heat transfer equation based on the parameter initialization value to obtain temperature distribution data, and calculating the temperature optimal function value, and updating the global optimal and local optimal positions of the parameter variable sequence; the heat transfer equation is determined based on the energy conservation relationship and the functional relationship between the heat flux density and the temperature gradient, and the energy conservation relationship is used to characterize that the change in the chip energy per unit time is equal to the sum of the heat obtained by the chip through the chip interface and the heat generated inside the system per unit time; Based on the updated global optimal position and local optimal position, the particle velocity and particle position are updated, and the heat transport equation is solved and subsequent steps are performed based on the updated parameter information until the preset number of iterations is reached and the temperature optimal function value is less than the preset temperature threshold, and the thermal simulation parameters of the integrated chip are output.

2. The method according to claim 1, characterized in that Based on the updated global optimal position and local optimal position, the particle velocity is updated in the following ways: The particle speed is updated based on the speed update formula and the updated global optimal position and local optimal position. The speed update formula is v=w1*v+w2*(Gp-x)+w3*(Gb-x), wherein w1, w2 and w3 are weight parameters within a preset numerical range, x is the global optimal and local optimal positions of the parameter variable sequence, Gp is ​​the updated global optimal position, and Gb is the updated local optimal position.

3. The method according to claim 2, characterized in that Based on the updated global optimal position and local optimal position, the particle position is updated in the following ways: The sum of the original particle position and the updated particle velocity is calculated to obtain the updated particle position.

4. The method according to claim 1, characterized in that: After solving the heat transport equation based on the updated parameters and subsequent steps, the method further includes: If the preset number of iteration steps is reached, determine whether the current temperature optimal function value is less than the preset temperature threshold; If the current temperature optimal function value is not less than the preset temperature threshold, the parameter variables of the junction temperature optimization model are initialized and subsequent steps are performed until the preset number of iterations is met and the temperature optimal function value is less than the preset temperature threshold, and the target parameters are output.

5. The method according to claim 1, characterized in that Also includes: If the improvement of the temperature optimal function value obtained by multiple consecutive iterations is less than a preset threshold, the iteration is terminated and the target parameter is output.

6. The method according to claim 1, characterized in that The thermal simulation parameters of the integrated chip include the core particle position, the geometric size range of the heat sink, the heat transfer coefficient process parameters and the thermal conductivity parameters of the thermal interface material, which affect the heat dissipation performance and temperature distribution of the chip.

7. A parameter determination system, characterized in that: include: An initialization unit, used to initialize parameter variables of the junction temperature optimization model to obtain parameter initialization values; A calculation unit, used to solve the heat transfer equation based on the parameter initialization value, obtain temperature distribution data, calculate the temperature optimal function value, and update the global optimal and local optimal positions of the parameter variable sequence; the heat transfer equation is determined based on the energy conservation relationship and the functional relationship between the heat flux density and the temperature gradient, and the energy conservation relationship is used to characterize that the change in the chip energy per unit time is equal to the sum of the heat obtained by the chip through the chip interface and the heat generated inside the system per unit time; The output unit is used to update the particle velocity and particle position based on the updated global optimal position and local optimal position, solve the heat transport equation and subsequent steps based on the updated parameter information, until a preset number of iterations is reached and the temperature optimal function value is less than a preset temperature threshold, and output the thermal simulation parameters of the integrated chip.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the parameter determination method according to any one of claims 1 to 6 is implemented.

9. A computer program product, characterized in that When the computer program product runs on a computer, the computer executes the parameter determination method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the parameter determination method according to any one of claims 1 to 6.

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