Control method, controller, storage medium, and electronic device for heat dissipation device

Abstract

The application discloses a heat dissipation device control method, a controller, a storage medium and an electronic device, and relates to the technical field of computers, and comprises the following steps: a first controller of a first server continuously iteratively updates a heat dissipation strategy of the first server based on a heat dissipation strategy of a second server, and determines a first heat dissipation strategy of the first server in the case that a preset condition is reached, and then controls a first heat dissipation device in the first server according to the determined first heat dissipation strategy. The technical problem of lagging control of the heat dissipation device in the related art is solved, the heat dissipation device is controlled in real time, and the technical effect of improving the heat dissipation efficiency is achieved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a control method, controller, storage medium and electronic device for a heat dissipation device. Background Technology

[0002] As global enterprises accelerate their digital transformation, data volume and business concurrency are growing exponentially, highlighting the shortcomings of traditional single-node server architectures in terms of reliability, performance, and flexibility. Multi-node servers, due to their high availability and flexibility, have become the mainstream choice for small to medium-sized business scenarios.

[0003] However, in controlling the heat dissipation of multi-node servers, a master node typically collects the control parameters of the heat dissipation devices on each node server, calculates the overall control parameters based on these parameters, and then transmits the overall control parameters to each node server to control its heat dissipation devices. Because this process involves each node server collecting and uploading control parameters to the master node, and the master node calculating and transmitting the overall control parameters to each node server, a lag in the control of the heat dissipation devices on each node server can occur. This is especially problematic in scenarios involving large-scale data processing and high-speed operation, where the computational delay of the master node reduces the timeliness and effectiveness of the heat dissipation strategy, thus affecting the heat dissipation efficiency of each node server.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This application provides a control method, controller, storage medium, and electronic device for a heat dissipation device, so as to at least solve the problem of lag in the regulation of heat dissipation devices in the related art.

[0006] This application provides a control method for a heat dissipation device, applied to a first controller, which is a control device within a first server. The method includes: repeatedly executing the following iterative operations until a preset condition is met to obtain a first heat dissipation strategy for the first server; obtaining a second heat dissipation strategy for the second server determined by a second controller of the second server during the i-th iteration, where i is a natural number greater than or equal to 0, the first server and the second server are thermally coupled, and the second heat dissipation strategy is used to control a second heat dissipation device configured within the second server; updating the obtained heat dissipation strategy of the first server based on the second heat dissipation strategy to obtain a heat dissipation strategy determined by the first server during the (i+1)-th iteration; and controlling the first heat dissipation device configured within the first server according to the first heat dissipation strategy.

[0007] This application also provides a first controller, comprising: an iteration module, configured to repeatedly execute the following iteration operations until a preset condition is met, to obtain a first heat dissipation strategy for a first server; to obtain a second heat dissipation strategy for a second server determined by a second controller of a second server during the i-th iteration, wherein i is a natural number greater than or equal to 0, the first server and the second server are thermally coupled, and the second heat dissipation strategy is used to control a second heat dissipation device configured within the second server; to update the obtained heat dissipation strategy of the first server based on the second heat dissipation strategy, to obtain a heat dissipation strategy determined by the first server during the (i+1)-th iteration; and a control module, configured to control the first heat dissipation device configured within the first server according to the first heat dissipation strategy.

[0008] This application also provides an electronic device, including: a memory for storing a computer program; and a processor for executing the computer program to implement the control method of any of the above-described heat dissipation devices.

[0009] This application also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of the control method for any of the above-described heat dissipation devices.

[0010] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the control method for any of the above-described heat dissipation devices.

[0011] Through this application, the first controller of the first server continuously iterates and updates the heat dissipation strategy of the first server based on the heat dissipation strategy of the second server, and determines the optimal first heat dissipation strategy of the first server when the preset conditions are met, and then controls the first heat dissipation device in the first server according to the determined first heat dissipation strategy.

[0012] By decentralizing the decision-making power for heat dissipation strategies among individual servers, each server can independently determine its own heat dissipation strategy. Each server can autonomously and rapidly respond to thermal changes within its node, without waiting for central controller aggregation and analysis. Adjustments to heat dissipation strategies take effect instantly, significantly reducing the time delay from monitoring to response. This reduces reliance on a central controller and avoids the lag in heat dissipation device control caused by the master node's aggregation and calculation of heat dissipation strategies in multi-node systems. It achieves decentralized dynamic optimization, overcoming the limitations of centralized control. Simultaneously, by sharing heat dissipation strategies among servers, each controller considers the influence of adjacent nodes when formulating its own strategy, achieving cross-node collaborative heat dissipation optimization. This helps mitigate heat conduction effects and prevent the formation of localized hotspots. Therefore, it solves the technical problem of lag in heat dissipation device control in related technologies, achieving real-time control of heat dissipation devices and improving heat dissipation efficiency. Attached Figure Description

[0013] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 A hardware structure block diagram of the control method for the heat dissipation device provided in the embodiments of this application;

[0015] Figure 2 A flowchart illustrating the control method for the heat dissipation device provided in the embodiments of this application;

[0016] Figure 3 This is a schematic diagram of the structure of the dual-node heat dissipation system provided in the embodiments of this application;

[0017] Figure 4 A flowchart illustrating the controller's heat dissipation strategy as provided in this application embodiment;

[0018] Figure 5 This is a structural block diagram of the first controller provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0020] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0021] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] The specific application environment architecture or specific hardware architecture on which the control method for the heat dissipation device depends is described here.

[0023] The methods and embodiments provided in this application can be executed on a server device or a similar computing device. Taking running on a server device as an example, Figure 1 This is a hardware structure block diagram of the control method for the heat dissipation device provided in an embodiment of this application. (See diagram below.) Figure 1 As shown, the server device may include one or more ( Figure 1 Only one is shown in the image. A processor 102 (which may include, but is not limited to, a central processing unit (CPU), microprocessor (MCU), or programmable logic device (FPGA), etc.) and a memory 104 for storing data are also shown. The server device may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the server equipment described above. For example, the server equipment may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0024] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the heat dissipation device control method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to server devices via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0025] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the server device. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module used for wireless communication with the Internet.

[0026] The embodiments of this application provide a control method for a heat dissipation device. The method is described in detail below in conjunction with the execution flow of the control method for the heat dissipation device.

[0027] The following explains the technical terms used in this application:

[0028] BMC: Baseboard Management Controller, is a dedicated microcontroller primarily used for remote monitoring and management of servers. The BMC can monitor the server's health status, such as temperature, voltage, fan speed, and power supply status, and also provides remote control functions such as power-on, power-off, and restart.

[0029] Nash equilibrium: A strategy combination state in game theory where, given that the strategies of all other players remain unchanged, each player chooses the strategy that is most advantageous to themselves, such that no one can gain a greater benefit by unilaterally changing their strategy.

[0030] Example 1:

[0031] This embodiment provides a control method for a heat dissipation device. Figure 2A flowchart of the control method for the heat dissipation device provided in the embodiments of this application is shown below. Figure 2 As shown, this method is applied to a first controller, which is a control device within a first server, and specifically includes the following steps:

[0032] Step S202: Repeat the following iterative operation until the preset condition is met to obtain the first heat dissipation strategy of the first server: Obtain the second heat dissipation strategy of the second server determined by the second controller of the second server in the i-th iteration, where i is a natural number greater than or equal to 0, the first server and the second server are thermally coupled, and the second heat dissipation strategy is used to control the second heat dissipation device configured in the second server; Update the heat dissipation strategy of the first server based on the second heat dissipation strategy to obtain the heat dissipation strategy of the first server determined in the (i+1)-th iteration.

[0033] In this embodiment of the application, the first server and the second server can be two independent servers (i.e., nodes) in a dual-node system or a multi-node system. The first server and the second server can communicate with each other through some mechanism or protocol, and there is a thermal coupling relationship between the first server and the second server. That is, the temperature of the first server and the second server will affect each other. For example, the high temperature of the second server may affect the first server through the shared air circulation path, causing the temperature of the first server to rise.

[0034] In the embodiments of this application, the first controller and the second controller can be control units (or control devices) in the first server and the second server, respectively, such as baseboard management controller (BMC), central processing unit (CPU), intelligent policy module or other forms of logic control unit, etc., used to collect data such as temperature, voltage, and fan status of the node (i.e. server), and control the heat dissipation devices inside the server according to these data and predefined policies to realize heat dissipation management of the server.

[0035] In this embodiment, the second heat dissipation device can be one or more physical devices or apparatuses used inside the second server for heat dissipation, designed to reduce the temperature of server components to ensure stable server operation and extend hardware lifespan. For example, the second heat dissipation device can be a fan, heat pipe radiator, airflow guiding device, etc.

[0036] In this embodiment, the aforementioned heat dissipation strategy can be specific operating or functional parameters for the heat dissipation devices of each server, aiming to regulate the internal temperature of the server, ensure that the server hardware operates within a suitable operating temperature range, and improve system stability and lifespan. This heat dissipation strategy may include the rotational speed of the heat dissipation devices, the airflow direction of the heat dissipation devices, etc. The aforementioned first heat dissipation strategy can be the optimal heat dissipation strategy for the first server at the current moment, determined by the first controller through iterative operations; the aforementioned second heat dissipation strategy can be the optimal heat dissipation strategy for the second server, determined by the second controller within the second server in the i-th iteration, and can be obtained based on the heat dissipation strategy determined by the first controller in the i-th iteration.

[0037] In the embodiments of this application, the above-mentioned iterative operation can be a coordination and optimization process used to optimize the heat dissipation strategy of two thermally coupled servers. Through iterative operation, the controller inside the server can determine the optimal operating parameters of the heat dissipation device inside the server based on the existing parameters, so as to operate within a suitable operating temperature range.

[0038] In this embodiment, the aforementioned preset conditions can be standards or indicators used to determine whether the heat dissipation strategy determined by the controller is the optimal heat dissipation strategy, such as energy efficiency, fan speed, noise level, and number of iterations. By evaluating the preset conditions, it is possible to effectively determine whether the currently determined heat dissipation strategy has achieved the expected optimization effect, thereby ensuring that the system operates in a stable and efficient state.

[0039] Optionally, the preset conditions include at least one of the following: the third heat dissipation strategy determined by the second controller during the (i+1)th iteration reaches the convergence condition; the value of i+1 reaches the preset maximum value.

[0040] In this embodiment, the preset condition may be that the third heat dissipation strategy determined by the second controller reaches the convergence condition, and / or the number of iterations of the iteration operation reaches a preset number. For example, in the (i+1)th iteration, if the optimal heat dissipation strategy (i.e., the third heat dissipation strategy) determined by the second controller based on the heat dissipation strategy obtained by the first controller in the (i+1)th iteration reaches the convergence condition, the preset condition can be met in this iteration operation, and the heat dissipation strategy obtained by the first controller in the (i+1)th iteration can be directly determined as the first heat dissipation strategy and output. Otherwise, the iteration operation continues. Another example is to preset a maximum number of iterations (i.e., the preset maximum value). If the number of iterations in the (i+1)th iteration is the preset maximum number of iterations (i.e., the value of i+1 reaches the preset maximum value), the heat dissipation strategy obtained by the first controller in the (i+1)th iteration can be directly determined as the first heat dissipation strategy and output. Otherwise, the iteration operation continues, etc.

[0041] For example, when it is necessary to regulate the first heat dissipation device within the first server to adjust the server temperature, the first controller of the first server first obtains the current heat dissipation strategies of the first and second servers (i.e., the current operating parameters of the first heat sink in the first server and the second heat sink in the second server). Simultaneously, it sets preset conditions and then performs iterative operations based on the current heat dissipation strategies of the first and second servers. Through iterative calculations, it continuously searches for and updates its own heat dissipation strategy based on the latest heat dissipation strategy of the other server until the iterative operation meets the preset conditions. At this point, the iterative operation stops, and the optimal heat dissipation strategy of the first server (i.e., the first heat dissipation strategy) is determined and output. This allows the two thermally coupled servers to reach a stable state through multiple iterations of exchanging their respective heat dissipation strategies, ensuring that both servers obtain the most suitable heat dissipation strategy during the iteration process. Furthermore, by having the first controller within the first server independently decide its own heat dissipation strategy, the problem of lagging heat dissipation device regulation caused by a single node centrally deciding the heat dissipation strategies of each server in a multi-node system is avoided. This overcomes the limitations of centralized control and improves the regulation efficiency of heat dissipation devices and the heat dissipation efficiency of the server.

[0042] Step S204: Control the first heat dissipation device configured in the first server according to the first heat dissipation strategy.

[0043] In this embodiment, the first heat dissipation device can be one or more physical devices or apparatuses used inside the first server for heat dissipation, designed to reduce the temperature of server components to ensure stable server operation and extend hardware lifespan. For example, the first heat dissipation device can be a fan, heat pipe radiator, airflow guiding device, etc.

[0044] For example, after the first controller determines the first heat dissipation strategy, the first controller controls the first heat dissipation device in the first server to operate according to the first heat dissipation strategy, thereby adjusting the temperature of the first server so that the first server operates within a suitable operating temperature range.

[0045] Optionally, the entity performing the above steps may be a background processor or other devices with similar processing capabilities, or a machine that integrates at least an image acquisition device and a data processing device. The image acquisition device may include an image acquisition module such as a camera, and the data processing device may include a terminal such as a computer or a mobile phone, but is not limited thereto.

[0046] Through the above steps, the first controller of the first server continuously iterates and updates its own heat dissipation strategy based on the heat dissipation strategy of the second server, and determines its own optimal first heat dissipation strategy when the preset conditions are met, and then controls the first heat dissipation device in the first server according to the determined first heat dissipation strategy.

[0047] By decentralizing the decision-making power for heat dissipation strategies among individual servers, each server can independently determine its own heat dissipation strategy. Each server can autonomously and rapidly respond to thermal changes within its node, without waiting for central controller aggregation and analysis. Adjustments to heat dissipation strategies take effect instantly, significantly reducing the time delay from monitoring to response. This reduces reliance on a central controller and avoids the lag in heat dissipation device control caused by the master node's aggregation and calculation of heat dissipation strategies in multi-node systems. It achieves decentralized dynamic optimization, overcoming the limitations of centralized control. Simultaneously, by sharing heat dissipation strategies among servers, each controller considers the influence of adjacent nodes when formulating its own strategy, achieving cross-node collaborative heat dissipation optimization. This helps mitigate heat conduction effects and prevent the formation of localized hotspots. Therefore, it solves the technical problem of lag in heat dissipation device control in related technologies, achieving real-time control of heat dissipation devices and improving heat dissipation efficiency.

[0048] As an optional implementation, the heat dissipation strategy of the first server is updated based on the second heat dissipation strategy to obtain the heat dissipation strategy determined by the first server in the (i+1)th iteration, including: obtaining multiple candidate heat dissipation strategies of the first server; determining the target benefit value of the first server when the second server controls the second heat dissipation device according to the second heat dissipation strategy, and when the first server controls the first heat dissipation device according to each candidate heat dissipation strategy, to obtain multiple target benefit values, wherein the target benefit value is determined based on the heat dissipation effect and heat dissipation power consumption of the first server; updating the heat dissipation strategy of the first server based on the multiple target benefit values ​​to obtain the heat dissipation strategy determined by the first server in the (i+1)th iteration.

[0049] In this embodiment, the aforementioned candidate heat dissipation strategy can be a heat dissipation strategy selectable by the first server in each iteration. For example, in each iteration, the first controller first determines multiple possible heat dissipation control schemes (i.e., candidate heat dissipation strategies), and then determines the optimal heat dissipation strategy for this iteration from among the multiple candidate heat dissipation strategies.

[0050] In this embodiment, the aforementioned target benefit value can refer to a quantitative indicator calculated based on the heat dissipation strategies of each server during the decision-making process. This indicator is used to comprehensively measure the heat dissipation effect and power consumption of the server, thereby evaluating the overall benefit of a specific heat dissipation strategy. Specifically, the target benefit value can be a trade-off between heat dissipation efficiency and energy consumption cost.

[0051] For example, the first controller first collects a series of potential candidate heat dissipation strategies. Then, it evaluates the heat dissipation target benefit (i.e., the value of the target benefit) of the first server implementing each candidate strategy, assuming the second server is fixed to use its current heat dissipation strategy (i.e., the second heat dissipation strategy) to control the second heat dissipation device, and obtains multiple target benefit values. These target benefit values ​​reflect a comprehensive consideration of the first server's heat dissipation effect and power consumption. Then, based on the evaluation results, a heat dissipation strategy is selected from the candidate heat dissipation strategies as the heat dissipation strategy of the first server in the next iteration (i.e., the (i+1)th iteration process).

[0052] Through the above operations and the dynamic update mechanism, the first server can continuously adjust its own heat dissipation strategy based on the heat dissipation strategy of the second server, thus completing self-adjustment. This helps the server respond quickly to complex scenarios such as sudden load changes, promotes overall system thermal balance, reduces the possibility of local overheating, improves the server's operational stability and lifespan, and provides the server with a higher level of thermal management and performance protection.

[0053] As an optional implementation, the target benefit of the first server is determined separately when the second server controls the second heat dissipation device according to the second heat dissipation strategy, and when the first server controls the first heat dissipation device according to each candidate heat dissipation strategy. Multiple target benefit values ​​are obtained, including: performing the following operations for any candidate heat dissipation strategy among the multiple candidate heat dissipation strategies to obtain multiple target benefit values: obtaining the temperature change of N temperature points in the first server to obtain N first temperature change values, where the j-th first temperature change value is the change in temperature value of the j-th temperature point before and after the first server executes the first candidate heat dissipation strategy, the first candidate heat dissipation strategy is any candidate heat dissipation strategy, N is an integer greater than or equal to 1, and j is an integer greater than 0 and less than N; obtaining the second temperature change value of the second server, where the second temperature change value is the change in temperature value of the second server before and after the second heat dissipation strategy is executed; determining the first target benefit value corresponding to the first candidate heat dissipation strategy based on the N first temperature change values ​​and the second temperature change value, where the multiple target benefit values ​​include the first target benefit value.

[0054] In this embodiment of the application, the temperature point mentioned above can be a temperature acquisition point set in the server to monitor the internal thermal state. The temperature point can be a temperature acquisition point set on heat-generating devices such as the central processing unit (CPU), memory, and hard disk, or it can be multiple temperature acquisition points set inside the server according to actual needs.

[0055] In this embodiment, the aforementioned temperature change can be the magnitude of temperature change, used to measure the temperature change, such as increase, decrease, or no change. Specifically, the first temperature change can be the change in temperature value at each temperature point within the first server before and after implementing any candidate heat dissipation strategy; the second temperature change can be the change in the overall temperature value of the second server before and after implementing the second heat dissipation strategy. Multiple different temperature points can also be set within the second server.

[0056] In this embodiment of the application, the first target benefit value can be the target benefit value calculated for any candidate heat dissipation strategy during the decision-making process.

[0057] For example, the first controller determines the first temperature change at each temperature point inside the first server before and after the first server executes a certain candidate heat dissipation strategy, and the second temperature change of the second server as a whole before and after the second server executes the second heat dissipation strategy. Then, based on the first temperature change and the second temperature change, the first target benefit value corresponding to the candidate heat dissipation strategy is calculated and determined, thereby obtaining multiple target benefit values ​​corresponding to multiple candidate heat dissipation strategies.

[0058] Through the above operations, a dynamic target benefit calculation mechanism is introduced, enabling the first controller to evaluate the effectiveness of cooling strategies not only based on the temperature changes of its own nodes but also considering the feedback from the second server's cooling strategy on its temperature. This achieves a more comprehensive evaluation of cooling performance. By accurately assessing the overall benefit to the server under each candidate cooling strategy, the optimal cooling strategy can be selected, achieving efficient and low-power dual-node server cooling management.

[0059] As an optional implementation, determining a first target benefit value corresponding to a first candidate heat dissipation strategy based on N first temperature change quantities and second temperature change quantities includes: determining a first energy consumption cost of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy, wherein the first energy consumption cost is used to indicate the heat dissipation power consumption of the first server; determining a first temperature suppression benefit of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy based on N first temperature change quantities and second temperature change quantities, wherein the first temperature suppression benefit is used to indicate the heat dissipation effect of the first server; and determining the difference between the first temperature suppression benefit and the first energy consumption cost as the first target benefit value.

[0060] In this embodiment of the application, the first energy consumption cost may be the cost caused by the energy consumption of the first heat dissipation device when the first heat dissipation device is controlled according to the first candidate heat dissipation strategy, and is used to indicate the heat dissipation power consumption of the first server.

[0061] In this embodiment of the application, the first temperature suppression benefit may be the benefit brought about by the temperature drop when the first heat dissipation device is controlled according to the first candidate heat dissipation strategy, which is used to indicate the heat dissipation effect of the first server, wherein the first temperature suppression benefit is positively correlated with the temperature drop magnitude (i.e. the first temperature change amount).

[0062] For example, the first target return value can be determined using the following formula:

[0063]

[0064] In the formula, It is the first target return value. The first temperature suppression benefit, The primary energy cost is... It is the first candidate heat dissipation strategy. This is the second heat dissipation strategy.

[0065] Through the above steps, the controller can quickly converge to the optimal combination of heat dissipation strategies based on real-time shared heat dissipation data. This not only effectively responds to heat dissipation requirements under high loads, but also tends to save energy under low loads, reducing unnecessary heat dissipation power consumption and achieving a dynamic balance between system performance and energy consumption.

[0066] As an optional implementation, determining the first energy consumption cost of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy includes: determining the first rotation speed of the first heat dissipation device in the first candidate heat dissipation strategy; and determining the first energy consumption cost as the product of the first weighting factor and the m-th power of the first rotation speed.

[0067] For example, the first energy cost can be determined using the following formula:

[0068]

[0069] In the formula, The primary energy cost is... It is the first weighting factor. It is the first rotational speed. It is an arbitrary constant that can be set according to actual needs. Usually, m is taken as 3.

[0070] As an optional implementation, determining the first temperature suppression benefit of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy based on N first temperature change amounts and second temperature change amounts includes: obtaining the target temperatures of N pre-configured temperature points to obtain N target temperature values; determining the predicted temperatures of the N temperature points based on the N first temperature change amounts and second temperature change amounts to obtain N predicted temperature values; and obtaining the first temperature suppression benefit based on the N target temperature values ​​and the N predicted temperature values.

[0071] In this embodiment of the application, the target temperature value can be the desired temperature value set for each temperature point, which can be the ideal temperature of each temperature point under different load conditions of the simulation server.

[0072] In this embodiment of the application, the predicted temperature value can be the temperature value of each temperature point predicted based on the first candidate heat dissipation strategy and the thermal coupling effect, which is used to evaluate the effectiveness of the first candidate heat dissipation strategy.

[0073] Optionally, the first temperature suppression benefit is obtained based on N target temperature values ​​and N predicted temperature values, including: determining a second weighting factor for each temperature point based on the temperature of each temperature point before controlling the first heat dissipation device according to the first heat dissipation strategy; determining the difference between the target temperature value and the predicted temperature value of each temperature point as the first difference of each temperature point; determining the product of the second weighting factor of each temperature point and the first difference of each temperature point as the second parameter of each temperature point; and determining the sum of the second parameters of the N temperature points as the first temperature suppression benefit.

[0074] For example, the first temperature suppression benefit can be determined using the following formula:

[0075]

[0076] In the formula, The first temperature suppression benefit, This is the second weighting factor for the j-th temperature point. The second weighting factor for each temperature point can be determined based on the temperature at each temperature point before the first heat dissipation device is controlled according to the first heat dissipation strategy. For example, each temperature point can be set with three threshold levels: high, medium, and low. Three values—high, medium, and low—are also set. When the temperature point is at the high, medium, or low threshold temperature, the weighting factor... Then adjust them to high, medium, and low values ​​respectively. It is the target temperature value at the j-th temperature point. It is the predicted temperature value of the j-th temperature point.

[0077] Through the above operations, a method of comparing and analyzing the target temperature values ​​and predicted temperature values ​​of N pre-configured temperature points is used to determine the first temperature suppression benefit of the first server. This allows the first controller to quantitatively evaluate the cooling effect of the first candidate heat dissipation strategy on the first server, i.e., the first temperature suppression benefit. This ensures that the heat dissipation strategy is formulated not only considering the current temperature state but also predicting future temperature trends, thereby achieving more accurate and forward-looking heat dissipation management. Simultaneously, to more accurately calculate the first temperature suppression benefit, a second weighting factor is introduced, and the corresponding second weighting factor is dynamically selected based on the actual load of the server. This enables dynamic adjustment of the strategy according to the actual load conditions. Under high load conditions, the heat dissipation effect of the system is effectively considered to ensure system performance, while under low load conditions, the energy-saving effect of the system is prioritized. This makes the selection of the heat dissipation strategy more refined, improves heat dissipation efficiency, reduces unnecessary energy consumption, and ensures that the system maintains optimal operating conditions under various load conditions.

[0078] As an optional implementation, the predicted temperatures of N temperature points are determined based on N first temperature changes and N second temperature changes to obtain N predicted temperature values. This includes: obtaining the temperature of the j-th temperature point before controlling the first heat dissipation device according to the first heat dissipation strategy to obtain the j-th temperature value; determining the thermal coupling coefficient of the second server to the j-th temperature point to obtain the j-th thermal coupling coefficient; determining the product of the j-th thermal coupling coefficient and the second temperature change as a first parameter; and determining the sum of the j-th temperature value, the first temperature change of the j-th temperature point, and the first parameter as the predicted temperature value of the j-th temperature point, wherein the N predicted temperature values ​​include the predicted temperature value of the j-th temperature point.

[0079] For example, the predicted temperature value of the j-th temperature point can be determined using the following formula:

[0080]

[0081] In the formula, It is the predicted temperature value at the j-th temperature point. It is the j-th temperature value. It is the first temperature change at the j-th temperature point. It is the j-th thermal coupling coefficient. It is the second temperature change.

[0082] Through the above steps, the thermal coupling effect between the two nodes is fully considered in the temperature prediction of the temperature point, thereby ensuring that the optimization of the heat dissipation strategy is not limited to a single node, but focuses on the thermal balance and efficiency of the entire system. It can more realistically reflect the heat conduction characteristics inside the multi-node system, help the decision module to predict the temperature change trend in advance, and effectively solve the problem that local optimization may lead to an increase in the global temperature difference, thereby achieving more accurate heat management and heat dissipation control.

[0083] It should be noted that the thermal coupling coefficient can be a preset value, or it can be dynamically updated by monitoring the heat flow distribution in real time, thereby further improving the accuracy of the predicted temperature value and ensuring that the system can achieve the ideal heat dissipation effect under various load conditions.

[0084] As an optional implementation, during server operation, the thermal coupling coefficient can be updated and corrected online using a dynamic estimation method, specifically including:

[0085] First, a discrete-time state-space model is established, and the thermal coupling coefficient k is defined. AB The parameter to be identified is embedded within this model, specifically the change in the current temperature of the first server, which stems from the combined effects of its own heat dissipation devices, the interference caused by the temperature change of the second server, and its own thermal load. A simplified temperature prediction model can be expressed as the following formula:

[0086]

[0087] In the formula, It is the actual temperature measured at the (x+1)th temperature point of the first server. It is the actual temperature measured at the j-th temperature point on the first server in the x-th measurement. This is the heat dissipation efficiency coefficient of the primary server, which can be calibrated through experiments in the early stages. It is the change in fan speed of the first server in the x-th measurement relative to the (x-1)-th measurement. The thermal coupling coefficient to be estimated is... It is the second server's number The temperature change at temperature point x relative to the (x-1)th measurement It is a constant.

[0088] Optionally, the heat dissipation efficiency coefficient of the first server can be determined by running only one server in a constant temperature environment in an experiment, with the fan speed remaining constant until a steady state is reached. In this case, the thermal coupling effect can be ignored, and the temperature at the temperature point and the fan speed should satisfy the following:

[0089]

[0090] By changing the fan speed and measuring it multiple times, and then substituting the measured data into the formula, the heat dissipation efficiency coefficient of the first server can be calculated.

[0091] Secondly, the above temperature prediction model is rewritten in linear form:

[0092]

[0093] in, This represents the change in observed temperature. , is a data vector Let be the parameter vector to be estimated, where only . The parameter to be estimated is 1; all others are known values.

[0094] Then, an iterative operation is performed. After obtaining new observation data after each iteration period x, the following calculations are performed to stop the iteration when the iterative operation converges, thus obtaining the thermal coupling coefficient k. AB :

[0095] (1) Calculate the gain vector:

[0096]

[0097] In the formula, It is the gain vector obtained in the (x+1)th iteration. It is the covariance obtained in the x-th iteration. It is the data vector obtained in the (x+1)th iteration. This is the forgetting factor, among which, This is used to reduce the impact of old data and enable the algorithm to track time-varying parameters. The closer to 1, the smoother the estimation but the slower the tracking speed; the closer to 0, the faster the tracking speed but the larger the estimation fluctuation.

[0098] (2) Update parameter estimates:

[0099]

[0100] In the formula, It is the parameter vector obtained in the (x+1)th iteration. It is the parameter vector obtained in the x-th iteration. It is the gain vector obtained in the (x+1)th iteration. It is the change in temperature of the observed value obtained in the (x+1)th iteration. It is the data vector obtained in the (x+1)th iteration.

[0101] (3) Update covariance:

[0102]

[0103] In the formula, It is the covariance obtained in the (x+1)th iteration. This is the forgetting factor. It is the covariance obtained in the x-th iteration. It is the gain vector obtained in the (x+1)th iteration. It is the data vector obtained in the (x+1)th iteration.

[0104] It should be noted that the initial value of the covariance is set as a diagonal matrix, which can be obtained by multiplying an identity matrix by a preset coefficient. During the initial operation, the forgetting factor can be empirically selected with a trial value of 0.98, and then adjusted according to the system's operating status in subsequent runs. If the server operating environment is stable, the thermal coupling coefficient may change slowly; in this case, the forgetting factor can be appropriately increased to obtain a smoother and more stable estimate. If the server load fluctuates frequently or the environment changes drastically, the thermal coupling coefficient is expected to change rapidly; in this case, the forgetting factor should be appropriately decreased to ensure tracking speed.

[0105] As an optional implementation, the heat dissipation strategy of the first server is updated according to multiple target benefit values ​​to obtain the heat dissipation strategy determined by the first server in the (i+1)th iteration, including: determining the benefit value with the largest value among multiple target benefit values ​​as the maximum benefit value; and updating the candidate heat dissipation strategy corresponding to the maximum benefit value to the heat dissipation strategy determined by the first server in the (i+1)th iteration.

[0106] For example, the heat dissipation strategy determined by the first server during the (i+1)th iteration can be determined by the following formula:

[0107]

[0108] In the formula, It is the heat dissipation strategy determined by the first server during the (i+1)th iteration. It is the target return value. It is a function used to determine the candidate heat dissipation strategy corresponding to the maximum profit value.

[0109] Through the above operations, based on the target benefit values ​​corresponding to each candidate heat dissipation strategy, the candidate heat dissipation strategy corresponding to the largest target benefit value (i.e., the maximum benefit value) is updated to the heat dissipation strategy determined by the first server in the (i+1)th iteration. This update guides the determination of subsequent heat dissipation strategies and heat dissipation control operations. This ensures that the selection of heat dissipation strategies always favors those that provide the most significant heat dissipation effect or optimize energy consumption, thereby achieving a balance between heat dissipation performance and energy efficiency under different server operating states, such as high-load or low-load scenarios. By systematically comparing and selecting the optimal strategy, the heat dissipation management efficiency of the dual-node server is effectively improved, ensuring that while meeting heat dissipation requirements, the goals of reducing energy consumption and noise are also considered.

[0110] As an optional implementation, the above method further includes: receiving a notification message sent by a second server, wherein the notification message is used to indicate that the third heat dissipation strategy has reached the convergence condition, and the second server determines that the third heat dissipation strategy has reached the convergence condition by: determining a second rotation speed and a first airflow direction of the second heat dissipation device in the third heat dissipation strategy; determining a third rotation speed and a second airflow direction of the second heat dissipation device in the second heat dissipation strategy; and determining that the third heat dissipation strategy has reached the convergence condition when the difference between the second rotation speed and the third rotation speed is less than the convergence error and the first airflow direction is in the same direction as the second airflow direction.

[0111] In this embodiment of the application, the aforementioned message may be data sent by the second server to the first server. This data may include the third heat dissipation strategy determined by the second controller of the second server during the (i+1)th iteration, as well as the second server's judgment result on whether the third heat dissipation strategy has reached the convergence condition, etc.

[0112] In this embodiment, the second rotation speed and the first airflow direction can be control parameters of the heat dissipation device included in the third heat dissipation strategy.

[0113] In the embodiments of this application, the aforementioned third rotation speed and second airflow direction may be control parameters of the heat dissipation device included in the second heat dissipation strategy.

[0114] For example, the third heat dissipation strategy is considered to have reached convergence if it simultaneously meets the following conditions:

[0115]

[0116]

[0117] In the formula, It's the second rotation speed. It is the third rotation speed. It is the convergence error. It is the first wind direction. It's the second wind direction.

[0118] Through the above operations, by adding a communication mechanism to ensure efficient collaboration between strategies, the consistency and stability of heat dissipation control of the dual-node server are ensured. At the same time, the convergence speed of heat dissipation strategies can be significantly improved, the system performance loss caused by uncoordinated heat dissipation regulation can be reduced, and more precise temperature control and energy efficiency optimization can be achieved.

[0119] Example 2:

[0120] In practical applications, the two node servers exchange heat dissipation data and communicate with each other, while also periodically exchanging heartbeat signals. If one node server fails to respond to the heartbeat signal within a preset period (i.e., a preset time), the other node server can take over the heat dissipation control of the faulty server based on historical data.

[0121] As an optional implementation, the method further includes: if no heartbeat signal is received from the second server within a preset time period, acquiring multiple historical heat dissipation strategies determined by the second server within a historical time range; performing a weighted average operation on the multiple historical heat dissipation strategies to obtain a fourth heat dissipation strategy; using the fourth heat dissipation strategy as the heat dissipation strategy of the second server; and controlling the second heat dissipation device according to the fourth heat dissipation strategy.

[0122] In this embodiment of the application, the aforementioned preset time can be a pre-set duration used to determine whether the server has malfunctioned. For example, if the first server does not receive the heartbeat signal from the second server within the preset time, it is determined that the second server has malfunctioned.

[0123] In the application embodiment, the aforementioned historical heat dissipation strategy can be the heat dissipation strategy adopted by the second server over a past period (i.e., within a historical time frame), including the rotation speed of the heat dissipation device and the airflow direction, etc., for subsequent strategy adjustments and data analysis, such as the heat dissipation strategies of the second server in the most recent 5 times within the historical time frame. This historical heat dissipation strategy can be obtained from the local storage of the first server, wherein the local storage of the first server and the local storage of the second server mutually store the heat dissipation strategies determined by each other within the historical time frame.

[0124] In the application embodiment, the above-mentioned fourth heat dissipation strategy may be the heat dissipation strategy of the second server determined by the first controller based on historical heat dissipation strategies, such as the heat dissipation strategy generated by performing a weighted average operation based on historical heat dissipation strategies, which is used to predict the behavior of the other party node based on historical data when the other party node fails, so as to ensure the stable operation of the heat dissipation system.

[0125] For example, when the first server does not receive a heartbeat signal from the second server within a preset time range, it determines that the second server has failed. At this time, the first server automatically triggers a takeover process: it acquires multiple historical cooling strategies determined by the second server within a historical time range, and performs a weighted average operation on these historical cooling strategies, with the most recent strategy having the highest weight, gradually decreasing until a fourth cooling strategy is obtained. This fourth cooling strategy is then used as the cooling strategy for the second server, and the first server controls the operation of the second server's cooling devices according to this strategy. This ensures that even if the second server (or the second controller of the second server) fails, the cooling system can still maintain a basic operating state and cooling effect, avoiding the risk of system overheating, while reducing system downtime caused by single point of failure, and improving the overall stability and reliability of the system. In addition, by using historical cooling strategies for weighted averaging, the first server can simulate the cooling behavior of the second server during normal operation, providing the decision-making module with near-realistic input, making the adjustment of the cooling strategy smoother, avoiding drastic changes in fan speed caused by sudden takeover, and reducing the impact on the system. This enhances the robustness of the dual-node server, optimizes the continuity and intelligence of cooling control, and improves the efficiency and experience of server operation and maintenance.

[0126] As an optional implementation, after using the fourth heat dissipation strategy as the heat dissipation strategy of the second server, the above method further includes: determining a fifth heat dissipation strategy for the first server according to the fourth heat dissipation strategy; controlling a first heat dissipation device configured in the first server according to the fifth heat dissipation strategy; and controlling a second heat dissipation device configured in the second server according to the fourth heat dissipation strategy.

[0127] For example, the first server calculates its own optimal control strategy (i.e., the fifth heat dissipation strategy) based on the predictive control strategy of the second server (i.e., the fourth heat dissipation strategy), and uses it to control the heat dissipation devices of this node. At this time, the first server no longer considers the real-time temperature of the second server, but only performs calculations based on the temperature data of the first server and the historical data of the second server to ensure the minimum operation of the system.

[0128] It should be noted that the above embodiments one and two are only described using a two-node server as a preferred embodiment. In practical applications, the above method steps can also be adapted to use in multi-node servers.

[0129] As an optional implementation method, Figure 3 This is a schematic diagram of the structure of the dual-node heat dissipation system provided in the embodiments of this application, as shown below. Figure 3 As shown, the system mainly includes:

[0130] The monitoring module is responsible for monitoring the temperature of the node (i.e., the server, such as the first server or the second server, where node A can be the first server and node B can be the second server), including the temperature of each temperature sensor (i.e., the temperature sensor set at the temperature point) within the node, the fan speed (i.e. the heat dissipation device) of the current node and the airflow direction, and transmitting this data to the decision module in real time.

[0131] The communication module is responsible for exchanging heat dissipation data in real time with the communication module of the other node, including the temperature of each temperature sensor in the node, the current fan speed and airflow direction of the node, and historical control strategies (such as the heat dissipation strategies of the last 5 times), and transmitting them to the decision module.

[0132] The decision-making module solves the control strategy (i.e. heat dissipation strategy) of the local node based on the data of the local node and the other node. After multiple iterations, it reaches Nash equilibrium and obtains the optimal control strategy.

[0133] The control module generates control commands based on the optimal control strategy obtained from the solution, and controls the operation of the fan in this node.

[0134] As an optional implementation method, Figure 4 A flowchart for determining the heat dissipation strategy for the controller provided in the embodiments of this application is shown below. Figure 4 As shown, this is applied to node A (i.e., the first server), and the specific process is as follows:

[0135] Step S401: Begin executing the iteration operation;

[0136] Step S402: Initialize the strategies (i.e., heat dissipation strategies) for node A (i.e., the first server) and node B (i.e., the second server). A 0 and S B 0 Set the convergence error and the maximum number of iterations K for the iteration operation. max ;

[0137] Step S403, according to the current strategy S of node B B (i) (i.e., the second heat dissipation strategy) Solve for the optimal response S of node A. A (i +1) (That is, the heat dissipation strategy determined by the first server during the (i+1)th iteration).

[0138] Step S404, Node B, based on Node A's optimal response S A (i+1) Solve for the optimal response S of node B. B (i+1)(i.e., the third heat dissipation strategy), Node A receives Node B's optimal response S sent by Node B. B (i+1) ;

[0139] Step S405, node B determines the optimal response S B (i+1) Whether the convergence condition has been met, node A receives the judgment result sent by node B;

[0140] Step S406, at node B, the optimal response S B (i+1) In the case of convergence, the optimal response S of output node A. A (i+1) The optimal heat dissipation strategy (i.e., the first heat dissipation strategy) is used as the first heat dissipation device, and step S410 is executed directly.

[0141] Step S407, at node B, the optimal response S B (i+1) If the circuit does not converge, determine whether the next iteration count is greater than the maximum iteration count (i.e., the value of i+1 reaches the preset maximum value).

[0142] Step S408: If the next iteration number is greater than the maximum iteration number, then output the optimal response S of node A. A (i +1) The optimal heat dissipation strategy (i.e., the first heat dissipation strategy) is used as the first heat dissipation device, and step S410 is executed directly.

[0143] Step S409: If the next iteration number is less than or equal to the maximum iteration number, then execute the next iteration operation;

[0144] Step S410: End the loop operation.

[0145] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0146] Embodiments of this application also provide a first controller. Figure 5 A structural block diagram of the first controller provided in the embodiments of this application is shown below. Figure 5As shown, the first controller includes: an iteration module 502, used to repeatedly perform the following iteration operations until a preset condition is met, to obtain a first heat dissipation strategy for the first server: obtaining a second heat dissipation strategy for the second server determined by the second controller of the second server in the i-th iteration, where i is a natural number greater than or equal to 0, the first server and the second server are thermally coupled, and the second heat dissipation strategy is used to control the second heat dissipation device configured in the second server; updating the obtained heat dissipation strategy of the first server based on the second heat dissipation strategy to obtain the heat dissipation strategy determined by the first server in the (i+1)-th iteration; and a control module 504, used to control the first heat dissipation device configured in the first server according to the first heat dissipation strategy.

[0147] In an exemplary embodiment, the first controller is further configured to acquire multiple candidate heat dissipation strategies for the first server; determine the target benefit values ​​of the first server when the second server controls the second heat dissipation device according to the second heat dissipation strategy, and when the first server controls the first heat dissipation device according to each candidate heat dissipation strategy, thereby obtaining multiple target benefit values, wherein the target benefit values ​​are determined based on the heat dissipation effect and heat dissipation power consumption of the first server; and update the obtained heat dissipation strategy of the first server according to the multiple target benefit values ​​to obtain the heat dissipation strategy determined by the first server in the (i+1)th iteration.

[0148] In an exemplary embodiment, the first controller is further configured to perform the following operations for any one of the candidate heat dissipation strategies included in the plurality of candidate heat dissipation strategies, to obtain a plurality of target benefit values: obtaining the temperature change of N temperature points in the first server to obtain N first temperature change values, wherein the j-th first temperature change value is the change in temperature value of the j-th temperature point before and after the first server executes the first candidate heat dissipation strategy, the first candidate heat dissipation strategy is any candidate heat dissipation strategy, N is an integer greater than or equal to 1, and j is an integer greater than 0 and less than N; obtaining the second temperature change value of the second server, wherein the second temperature change value is the change in temperature value of the second server before and after the second heat dissipation strategy is executed; determining the first target benefit value corresponding to the first candidate heat dissipation strategy based on the N first temperature change values ​​and the second temperature change value, wherein the plurality of target benefit values ​​includes the first target benefit value.

[0149] In an exemplary embodiment, the first controller is further configured to determine a first energy consumption cost of the first server when controlling the first heat dissipation device according to a first candidate heat dissipation strategy, wherein the first energy consumption cost is used to indicate the heat dissipation power consumption of the first server; determine a first temperature suppression benefit of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy based on N first temperature change amounts and second temperature change amounts, wherein the first temperature suppression benefit is used to indicate the heat dissipation effect of the first server; and determine the difference between the first temperature suppression benefit and the first energy consumption cost as a first target benefit value.

[0150] In an exemplary embodiment, the first controller is further configured to determine the first rotational speed of the first heat dissipation device in the first candidate heat dissipation strategy; and to determine the first energy consumption cost by multiplying the first weighting factor by the m-th power of the first rotational speed.

[0151] In an exemplary embodiment, the first controller is further configured to acquire the target temperatures of N pre-configured temperature points to obtain N target temperature values; determine the predicted temperatures of the N temperature points based on the N first temperature changes and the second temperature changes to obtain N predicted temperature values; and obtain a first temperature suppression benefit based on the N target temperature values ​​and the N predicted temperature values.

[0152] In an exemplary embodiment, the first controller is further configured to acquire the temperature of the j-th temperature point before controlling the first heat dissipation device according to the first heat dissipation strategy, and obtain the j-th temperature value; determine the thermal coupling coefficient of the second server to the j-th temperature point, and obtain the j-th thermal coupling coefficient; determine the product of the j-th thermal coupling coefficient and the second temperature change as a first parameter; and determine the sum of the j-th temperature value, the first temperature change of the j-th temperature point, and the first parameter as the predicted temperature value of the j-th temperature point, wherein the N predicted temperature values ​​include the predicted temperature value of the j-th temperature point.

[0153] In an exemplary embodiment, the first controller is further configured to determine a second weighting factor for each temperature point based on the temperature of each temperature point before controlling the first heat dissipation device according to the first heat dissipation strategy; determine the difference between the target temperature value and the predicted temperature value of each temperature point as a first difference for each temperature point; determine the product of the second weighting factor of each temperature point and the first difference for each temperature point as a second parameter for each temperature point; and determine the sum of the second parameters of N temperature points as a first temperature suppression benefit.

[0154] In one exemplary embodiment, the first controller is further configured to determine the maximum value among multiple target profit values ​​as the maximum profit value; and update the candidate heat dissipation strategy corresponding to the maximum profit value to the heat dissipation strategy determined by the first server in the (i+1)th iteration.

[0155] In an exemplary embodiment, the aforementioned preset conditions include at least one of the following: the third heat dissipation strategy determined by the second controller during the (i+1)th iteration reaches the convergence condition; the value of i+1 reaches the preset maximum value.

[0156] In an exemplary embodiment, the first controller is further configured to receive a notification message sent by the second server, wherein the notification message is used to indicate that the third heat dissipation strategy has reached the convergence condition, and the second server determines that the third heat dissipation strategy has reached the convergence condition by: determining a second rotational speed and a first airflow direction of the second heat dissipation device in the third heat dissipation strategy; determining a third rotational speed and a second airflow direction of the second heat dissipation device in the second heat dissipation strategy; and determining that the third heat dissipation strategy has reached the convergence condition when the difference between the second rotational speed and the third rotational speed is less than the convergence error and the first airflow direction is in the same direction as the second airflow direction.

[0157] In an exemplary embodiment, the first controller is further configured to, if it does not receive a heartbeat signal from the second server within a preset time period, acquire multiple historical heat dissipation strategies determined by the second server within a historical time range; perform a weighted average operation on the multiple historical heat dissipation strategies to obtain a fourth heat dissipation strategy; use the fourth heat dissipation strategy as the heat dissipation strategy of the second server; and control the second heat dissipation device according to the fourth heat dissipation strategy.

[0158] For a description of the features in the embodiment corresponding to the first controller, please refer to the relevant description of the embodiment corresponding to the control method of the heat dissipation device, which will not be repeated here.

[0159] Embodiments of this application also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above-described embodiments of the control method for a heat dissipation device.

[0160] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above-described embodiments of the control method for a heat dissipation device when running.

[0161] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0162] The embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above-described control method embodiments for heat dissipation devices.

[0163] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above-described control method embodiments for a heat dissipation device.

[0164] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0165] The control method, controller, storage medium, and electronic device for a heat dissipation device provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. It should be noted that those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A control method for a heat dissipation device, characterized in that, Applied to a first controller, which is a control device within a first server, including: Repeat the following iterative operation until a preset condition is met to obtain the first heat dissipation strategy of the first server: Obtain the second heat dissipation strategy of the second server determined by the second controller of the second server in the i-th iteration, where i is a natural number greater than or equal to 0, the first server and the second server are thermally coupled, and the second heat dissipation strategy is used to control the second heat dissipation device configured in the second server; Update the obtained heat dissipation strategy of the first server based on the second heat dissipation strategy to obtain the heat dissipation strategy of the first server determined in the (i+1)-th iteration. The first heat dissipation device configured in the first server is controlled according to the first heat dissipation strategy. Specifically, the heat dissipation strategy of the first server is updated based on the second heat dissipation strategy to obtain the heat dissipation strategy determined by the first server in the (i+1)th iteration, including: Obtain multiple candidate heat dissipation strategies for the first server; The target benefit of the first server is determined when the second server controls the second heat dissipation device according to the second heat dissipation strategy, and when the first server controls the first heat dissipation device according to each of the candidate heat dissipation strategies. Multiple target benefit values ​​are obtained, wherein the target benefit value is determined based on the heat dissipation effect and heat dissipation power consumption of the first server. The heat dissipation effect of the first server is indicated by the first temperature suppression benefit. The first temperature suppression benefit is obtained based on N target temperature values ​​and N predicted temperature values. The N target temperature values ​​are the target temperatures of N temperature points in the first server that are pre-configured, and the N predicted temperature values ​​are the predicted temperatures of N temperature points. N is an integer greater than or equal to 1. The heat dissipation strategy of the first server is updated based on multiple target benefit values ​​to obtain the heat dissipation strategy of the first server determined in the (i+1)th iteration. The method for obtaining the first temperature suppression benefit based on N target temperature values ​​and N predicted temperature values ​​includes: determining a second weighting factor for each temperature point based on the temperature of each temperature point before controlling the first heat dissipation device according to the first heat dissipation strategy; determining the difference between the target temperature value and the predicted temperature value for each temperature point as a first difference for each temperature point; determining the product of the second weighting factor and the first difference for each temperature point as a second parameter for each temperature point; and determining the sum of the second parameters of the N temperature points as the first temperature suppression benefit.

2. The control method for the heat dissipation device according to claim 1, characterized in that, The target benefit of the first server is determined when the second server controls the second heat dissipation device according to the second heat dissipation strategy, and when the first server controls the first heat dissipation device according to each of the candidate heat dissipation strategies. Multiple target benefit values ​​are obtained, including: For any one of the multiple candidate heat dissipation strategies, the following operations are performed to obtain multiple target benefit values: Obtain the temperature change of N temperature points in the first server to obtain N first temperature change values, wherein the j-th first temperature change value is the change in temperature value of the j-th temperature point before and after the first server executes the first candidate heat dissipation strategy, and the first candidate heat dissipation strategy is any candidate heat dissipation strategy, and j is an integer greater than 0 and less than N. Obtain the second temperature change of the second server, wherein the second temperature change is the change in the temperature value of the second server before and after the second heat dissipation strategy is implemented; A first target benefit value corresponding to the first candidate heat dissipation strategy is determined based on N first temperature change values ​​and second temperature change values, wherein the plurality of target benefit values ​​include the first target benefit value.

3. The control method for the heat dissipation device according to claim 2, characterized in that, The first target benefit value corresponding to the first candidate heat dissipation strategy is determined based on N first temperature change quantities and second temperature change quantities, including: When the first heat dissipation device is controlled according to the first candidate heat dissipation strategy, the first energy consumption cost of the first server is determined, wherein the first energy consumption cost is used to indicate the heat dissipation power consumption of the first server. The first temperature suppression benefit of the first server is determined based on N first temperature change values ​​and second temperature change values ​​when the first heat dissipation device is controlled according to the first candidate heat dissipation strategy. The difference between the first temperature suppression benefit and the first energy consumption cost is determined as the first target benefit value.

4. The control method for the heat dissipation device according to claim 3, characterized in that, The first energy consumption cost of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy includes: In the first candidate heat dissipation strategy, determine the first rotational speed of the first heat dissipation device; The product of the first weighting factor and the m-th power of the first rotational speed is determined as the first energy consumption cost.

5. The control method for the heat dissipation device according to claim 3, characterized in that, The first temperature suppression benefit of the first server when controlling the first heat dissipation device according to the first candidate heat dissipation strategy, determined based on N first temperature change quantities and second temperature change quantities, includes: The target temperatures of the N pre-configured temperature points are obtained respectively, resulting in N target temperature values; Based on N first temperature changes and N second temperature changes, the predicted temperatures of N temperature points are determined, resulting in N predicted temperature values; The first temperature suppression benefit is obtained based on N target temperature values ​​and N predicted temperature values.

6. The control method for the heat dissipation device according to claim 5, characterized in that, Based on N first temperature changes and N second temperature changes, the predicted temperatures of N temperature points are determined, resulting in N predicted temperature values, including: The temperature of the j-th temperature point before the first heat dissipation device is controlled according to the first heat dissipation strategy is obtained to obtain the j-th temperature value; Determine the thermal coupling coefficient of the second server to the j-th temperature point to obtain the j-th thermal coupling coefficient; The product of the j-th thermal coupling coefficient and the second temperature change is determined as the first parameter; The sum of the j-th temperature value, the first temperature change at the j-th temperature point, and the first parameter is determined as the predicted temperature value at the j-th temperature point, wherein the N predicted temperature values ​​include the predicted temperature value at the j-th temperature point.

7. The control method for the heat dissipation device according to claim 1, characterized in that, The heat dissipation strategy of the first server is updated based on multiple target benefit values ​​to obtain the heat dissipation strategy determined by the first server in the (i+1)th iteration, including: The largest value among the multiple target profit values ​​is determined as the maximum profit value; The candidate heat dissipation strategy corresponding to the maximum profit value is updated to the heat dissipation strategy determined by the first server in the (i+1)th iteration.

8. The control method for the heat dissipation device according to claim 1, characterized in that, The preset conditions include at least one of the following: The third heat dissipation strategy determined by the second controller during the (i+1)th iteration meets the convergence condition; The value of i+1 reaches the preset maximum value.

9. The control method for the heat dissipation device according to claim 8, characterized in that, The method further includes: The second server receives a notification message from the second server, wherein the notification message indicates that the third heat dissipation strategy has reached the convergence condition. The second server determines that the third heat dissipation strategy has reached the convergence condition in the following manner: In the third heat dissipation strategy, the second rotation speed and the first airflow direction of the second heat dissipation device are determined; In the second heat dissipation strategy, the third rotation speed and the second airflow direction of the second heat dissipation device are determined; If the difference between the second rotation speed and the third rotation speed is less than the convergence error, and the first wind direction is in the same direction as the second wind direction, then the third heat dissipation strategy is determined to have met the convergence condition.

10. The control method for the heat dissipation device according to claim 1, characterized in that, The method further includes: If no heartbeat signal is received from the second server within a preset time, obtain multiple historical heat dissipation strategies determined by the second server within a historical time range; A weighted average operation is performed on multiple historical heat dissipation strategies to obtain a fourth heat dissipation strategy; The fourth heat dissipation strategy is used as the heat dissipation strategy for the second server; The second heat dissipation device is controlled according to the fourth heat dissipation strategy.

11. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the control method for the heat dissipation device as described in any one of claims 1 to 10 when executing the computer program.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, it implements the steps of the control method for the heat dissipation device as described in any one of claims 1 to 10.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the control method for the heat dissipation device as described in any one of claims 1 to 10.

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