Server heat dissipation method and device, computer equipment and storage medium

Abstract

The invention discloses a server heat dissipation method and device, computer equipment and a storage medium, and relates to the technical field of heat dissipation, and the method comprises the steps: collecting the temperature data of each function module of a server; determining the heat dissipation weight of each functional module based on the temperature data of each functional module; determining a heat dissipation resource proportion required by each functional module based on the heat dissipation weight of each functional module; and allocating corresponding heat dissipation resources to the functional modules based on the heat dissipation resource proportions of the functional modules. According to the method, the heat dissipation resources can be dynamically allocated to the functional modules according to the functional modules of the server, so that the heat dissipation efficiency is improved, and the waste of the heat dissipation resources is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of heat dissipation technology, and particularly relates to a server heat dissipation method and device, computer equipment and a storage medium. BACKGROUND

[0002] In recent years, the state has continuously promoted the energy-saving and emission-reducing and green development strategy, and has successively introduced a number of policies to guide various industries to optimize the energy utilization structure, improve energy efficiency and reduce carbon emission intensity. This policy orientation puts forward higher requirements for the server industry, and also creates new opportunities for technological upgrading. The server industry needs to respond to the call of high-quality development, and actively explore innovative technical solutions to realize the fundamental optimization of energy consumption structure.

[0003] With the acceleration of social digital transformation process, the demand for data processing presents exponential growth, and the power consumption problem of servers as the core carrier of computing power is increasingly prominent. Under this background, reducing the overall energy consumption needs to deeply analyze the energy efficiency performance of each module from the system level. It is particularly worth noting that the heat dissipation subsystem as a key component of server energy consumption still has significant room for improvement in efficiency optimization.

[0004] The current server field generally adopts air cooling heat dissipation scheme, which relies on synchronous high-speed rotation to generate directional airflow through multiple fixed-position fans deployed inside the case, and the airflow flows through the heat sinks of CPU, memory and other main modules to realize heat exchange. However, this scheme has a fundamental defect: the thermal load of each module inside the server presents a dynamic and uneven characteristic. For example, in a high computing load scenario, the CPU area may generate intensive heat, while the thermal load of other modules is relatively low. At this time, the traditional heat dissipation strategy still forces all fans to run at high speed synchronously, resulting in two core contradictions: first, the number of effective fans actually bearing the CPU heat dissipation task may be less than half, and the airflow generated by the remaining fans forms excessive heat dissipation due to limited heat source demand; second, the fixed-position fans cannot dynamically adjust the air supply angle and wind concentration for high-heat areas, resulting in structural mismatch of heat dissipation resources. The mismatch between this static heat dissipation deployment mode and the dynamic heat load distribution not only causes up to 30%-50% of invalid air circulation (industry test data), but also directly pushes up the overall power consumption and noise level of the system.

[0005] In summary, the key bottleneck of the prior art is that the fixed fan heat dissipation system cannot dynamically adjust the spatial allocation of heat dissipation resources according to the real-time heat distribution inside the server, resulting in the coexistence of excessive heat dissipation in low-heat areas and insufficient heat dissipation in high-heat areas, causing significant energy waste. SUMMARY

[0006] This invention provides a server heat dissipation method, apparatus, computer equipment, and storage medium, aiming to solve the problem that fixed fan cooling systems cannot dynamically adjust the allocation of heat dissipation resources according to the real-time heat distribution inside the server, resulting in both excessive heat dissipation in low-heat areas and insufficient heat dissipation in high-heat areas, causing significant energy waste.

[0007] In a first aspect, embodiments of the present invention provide a server heat dissipation method, comprising:

[0008] Collect temperature data from various functional modules of the server;

[0009] The heat dissipation weight of each functional module is determined based on the temperature data of each functional module.

[0010] The proportion of heat dissipation resources required by each functional module is determined based on the heat dissipation weight of each functional module.

[0011] Based on the proportion of heat dissipation resources for each functional module, corresponding heat dissipation resources are allocated to each functional module.

[0012] A further technical solution is that each functional module of the server is equipped with a temperature sensor, and the collection of temperature data of each functional module of the server includes: distributing the temperature data of each functional module to the temperature sensor of each functional module.

[0013] A further technical solution is that determining the heat dissipation weight of each functional module based on the temperature data of each functional module includes:

[0014] Obtain the preset temperature-heat dissipation weight mapping relationship;

[0015] Based on the temperature data of each functional module, the heat dissipation weight of each functional module is determined by querying the temperature-heat dissipation weight mapping relationship.

[0016] A further technical solution is that determining the proportion of heat dissipation resources required by each functional module based on the heat dissipation weight of each functional module includes:

[0017] Calculate the quotient of the heat dissipation weight of the functional module and the sum of the heat dissipation weights of all functional modules to obtain the proportion of heat dissipation resources required by the functional module.

[0018] A further technical solution is that the heat dissipation resources include multiple fans; the proportion of heat dissipation resources based on each functional module is the allocation of corresponding heat dissipation resources to each functional module, including:

[0019] Based on the proportion of heat dissipation resources of each functional module, determine the target number of fans allocated to each functional module;

[0020] Assign a target number of fans to each of the aforementioned functional modules.

[0021] A further technical solution is that the fan is mounted on a slide rail and can be driven to move on the slide rail by a drive device. The functional modules of the server are sequentially arranged on one side of the slide rail. The step of allocating a corresponding target number of fans to each functional module includes:

[0022] The target number of fans corresponding to the functional module are moved to one side of the functional module to dissipate heat from the functional module.

[0023] A further technical solution is that the method further includes:

[0024] The target operating parameters of the fan corresponding to each functional module are determined based on the temperature data of each functional module.

[0025] Adjust the operating parameters of the fan corresponding to the functional module to the target operating parameters.

[0026] Secondly, embodiments of the present invention also provide a server heat dissipation device, which includes a unit for performing the above-described method.

[0027] Thirdly, embodiments of the present invention also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0028] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0029] This invention provides a server heat dissipation method, apparatus, computer device, and storage medium. The method includes: collecting temperature data of each functional module of the server; determining a heat dissipation weight for each functional module based on the temperature data; determining the required proportion of heat dissipation resources for each functional module based on its heat dissipation weight; and allocating corresponding heat dissipation resources to each functional module based on its required proportion of heat dissipation resources. This invention can dynamically allocate heat dissipation resources to each functional module according to its specific function, thereby improving heat dissipation efficiency and avoiding waste of heat dissipation resources. Attached Figure Description

[0030] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating a server heat dissipation method according to an embodiment of the present invention.

[0032] Figure 2 This is a schematic diagram of a fan on a slide rail provided in an embodiment of the present invention;

[0033] Figure 3 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0036] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0037] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0038] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0039] Please see Figure 1 This invention provides a server heat dissipation method, which includes the following steps:

[0040] S1 collects temperature data from various functional modules of the server.

[0041] In specific implementation, the functional modules include CPU, memory, etc., which are not specifically limited in this invention. In this invention, temperature data of each functional module of the server are collected separately.

[0042] For example, in some preferred embodiments, each functional module of the server is equipped with a temperature sensor. The above step of "collecting temperature data of each functional module of the server" specifically includes the following steps: collecting temperature data of each functional module through the temperature sensor of each functional module.

[0043] In practice, the server's BMC receives temperature data collected by the temperature sensors of each of the functional modules.

[0044] This invention achieves a refined upgrade in temperature monitoring granularity by integrating dedicated temperature sensors into each functional module (including CPU, GPU, memory, etc.). The distributed sensor network can capture transient temperature fluctuations in local hotspot areas. For example, when a memory module experiences a sudden surge in data throughput and generates a high temperature, its dedicated temperature sensor can quickly collect and report the abnormal data. This design, through physical-level sensing optimization, provides a high spatiotemporal resolution data foundation for heat dissipation weight calculation, avoiding delays in heat dissipation response caused by lag in temperature monitoring. Technically, the physically tight coupling design between the temperature sensor and the functional module shortens the heat conduction path, and the time-sharing acquisition mechanism eliminates signal crosstalk, ensuring the authenticity and real-time nature of the temperature data. In practical applications, this solution improves the accuracy of hotspot identification to the module level (e.g., precisely locating a specific CPU core), making subsequent resource allocation more targeted and fundamentally eliminating the heat dissipation blind spots or resource waste problems caused by fuzzy monitoring in traditional solutions.

[0045] S2, determine the heat dissipation weight of each functional module based on the temperature data of each functional module.

[0046] In practice, after collecting temperature data from each functional module, the heat dissipation weight of each functional module is determined based on the temperature data. Specifically, the higher the temperature of a functional module, the greater its corresponding heat dissipation weight.

[0047] For example, in some preferred embodiments, the above step "determine the heat dissipation weight of each functional module based on the temperature data of each functional module" specifically includes the following steps: obtaining a preset temperature-heat dissipation weight mapping relationship; and querying the temperature-heat dissipation weight mapping relationship to determine the heat dissipation weight of each functional module based on the temperature data of each functional module.

[0048] In practical implementation, a pre-defined temperature-heat dissipation weight mapping relationship is adopted (e.g., 80℃ corresponds to a weight of 0.9, and 40℃ corresponds to a weight of 0.1), simplifying the weight calculation process into an efficient table lookup operation. This scheme significantly reduces the system's computational load, shortening the heat dissipation decision response time to the microsecond level. For example, when the CPU temperature rises from 60℃ to 85℃, the system directly retrieves the weight value of 0.95 corresponding to 85℃ from the mapping table, generating control commands without iterative calculations. The technical principle is that the mapping relationship is essentially a pre-stored thermodynamic optimization solution set. The optimal heat dissipation intensity (weight) at different temperatures is calibrated experimentally, and discretized data replaces online calculations. This not only avoids the convergence oscillation problem that may occur in dynamic algorithms, but also improves system stability by solidifying expert experience. The practical benefits are reflected in two aspects: first, it reduces the computing power requirement of the BMC controller, enabling it to operate in low-power mode; second, it ensures the determinism of strategy generation under extreme conditions (such as sudden temperature changes), preventing temperature control failure caused by convergence delays in traditional adaptive algorithms.

[0049] S3, determine the proportion of heat dissipation resources required by each functional module based on the heat dissipation weight of each functional module.

[0050] In practice, the server is equipped with heat dissipation resources, such as multiple fans. In this invention, the required proportion of heat dissipation resources for each functional module is determined based on its heat dissipation weight. Specifically, the higher the heat dissipation weight of a functional module, the higher its corresponding proportion of heat dissipation resources.

[0051] For example, in some preferred embodiments, the above step "determining the proportion of heat dissipation resources required by each functional module based on the heat dissipation weight of each functional module" specifically includes the following steps: calculating the quotient of the heat dissipation weight of the functional module and the sum of the heat dissipation weights of all functional modules to obtain the proportion of heat dissipation resources required by the functional module.

[0052] In practical implementation, the global normalized allocation of heat dissipation resources is achieved through the quotient calculation of the mathematical formula "Heat dissipation resource ratio = heat dissipation weight of functional module / total weight of all functional modules" (e.g., CPU weight 0.7 ÷ total weight 1.0 = 70%). This algorithm ensures two core principles: the total amount of resources is conserved (the sum of the proportions of each module is always 100%) and the allocation ratio is strictly proportional to the weight requirement. For example, when the total system weight is 1.0, a CPU weight of 0.7 corresponds to 70% of the resources, a memory weight of 0.1 corresponds to 10% of the resources, and the remaining 20% ​​of the resources can be allocated to other modules or stored in energy-saving reserves. Its technical principle lies in converting absolute weights into relative proportional coefficients, eliminating the risk of allocation imbalance caused by fluctuations in the absolute value of weights. The practical effects are reflected in three aspects: First, it prevents resource over-allocation (such as the total exceeding 100%, which leads to fan overload); second, it ensures that low-weight modules receive basic heat dissipation (even if the weight is only 0.05, it can still obtain 5% of the resources); and third, it simplifies the control logic through normalization, so that the system only needs to adjust the total airflow to synchronously scale the supply of each module, which greatly improves the efficiency of strategy execution.

[0053] S4. Allocate corresponding heat dissipation resources to each functional module based on the proportion of heat dissipation resources of each functional module.

[0054] In practice, heat dissipation resources are allocated to each functional module based on its heat dissipation resource ratio. For example, if a functional module's heat dissipation resource ratio is 50%, then the allocated heat dissipation resources for it are 50% of the server's total heat dissipation resources. Therefore, the higher the heat dissipation resource ratio of a functional module, the more heat dissipation resources it receives.

[0055] For example, in some preferred embodiments, the above step "allocating corresponding heat dissipation resources to each functional module based on the heat dissipation resource ratio of each functional module" specifically includes the following steps: determining the target number of fans allocated to each functional module based on the heat dissipation resource ratio of each functional module; and allocating the corresponding target number of fans to each functional module.

[0056] In practical implementation, abstract heat dissipation resources are concretized into physical fan entities, and the number of fans is directly mapped to the proportion of heat dissipation resources (e.g., 70% CPU usage corresponds to 5 out of 7 fans), achieving discrete and precise scheduling of heat dissipation resources. When the system detects that the GPU module's heat dissipation resource usage reaches 60%, it automatically allocates 4 out of 6 fans (rounded down) to serve the GPU area, while the remaining modules share the remaining fan resources. The technical principle lies in establishing a "proportion-quantity" conversion relationship (quantity = total number of fans × proportion), replacing the traditional single-dimensional control of airflow adjustment through spatial reconfiguration of physical resources. The core benefit is breaking through the rigid limitations of fixed fan deployment: on the one hand, concentrating more fans on high-heat modules can create a superimposed airflow effect, improving the local heat transfer coefficient (e.g., multiple fans in parallel on a single module increase air pressure by 30%); on the other hand, reducing the number of fans for low-heat modules can avoid eddy current losses caused by airflow redundancy.

[0057] Furthermore, in some preferred embodiments, see [link to previous document]. Figure 2 The fan 10 is mounted on the slide rail 20 and can be driven by a drive device to move on the slide rail 20. The functional modules of the server are arranged sequentially on one side of the slide rail 20.

[0058] The above step of "assigning a target number of fans to each of the functional modules" specifically includes the following steps: controlling the target number of fans corresponding to the functional module to move to one side of the functional module to dissipate heat from the functional module.

[0059] In practical implementation, the mechanical design of the slide rail mechanism and drive device allows the fan cluster to have spatial freedom. After assigning a target number of fans to a functional module, the system controls the fans to move along the slide rail to the position directly opposite the module (e.g., moving three fans from the memory area to the CPU area), achieving spatial coupling between heat dissipation resources and heat sources. Taking CPU overheating as an example, traditional solutions can only increase the fan speed but are limited by the fixed position, leading to air resistance losses; while this solution moves the fan cluster to 5cm to the side of the CPU heatsink, shortening the airflow path by 60% and perpendicularly incident on the heatsink fins. Technically, physical displacement eliminates the "ineffective flow channel effect" in aerodynamics, allowing airflow energy to be directly converted into heat transfer efficiency. After the fans move, the heat transfer in the target area is effectively improved. Furthermore, this design naturally avoids the airflow interference problem caused by the fixed fan position in traditional solutions.

[0060] Furthermore, after determining the fan corresponding to the functional module, the moving distance of the fan is determined based on the distance between the fan and the functional module. For example, when the driving device is a stepper motor, the number of steps of the stepper motor is determined.

[0061] Furthermore, in some preferred embodiments, the method further includes the following steps: determining the target operating parameters of the fan corresponding to each functional module based on the temperature data of each functional module; and adjusting the operating parameters of the fan corresponding to the functional module to the target operating parameters.

[0062] In practice, a preset temperature-operating parameter mapping relationship is obtained, and the target operating parameters of the fan are determined by querying the temperature-operating parameter mapping relationship based on the temperature data of the functional module.

[0063] This invention adds dynamic adjustment of operating parameters (such as target rotation speed) to the spatial positioning to achieve multi-dimensional collaborative optimization of heat dissipation intensity. Once the fan moves to the target position, the system further sets the optimal operating parameters based on the module temperature: for example, configuring a 6000rpm speed for a 90℃ CPU module, while setting only 2000rpm for a 50℃ memory module. The technical principle is that position adjustment solves the problem of "whether the airflow can effectively reach the target location," while operating parameters solve the problem of "how the airflow efficiently exchanges heat." Speed ​​adjustment precisely matches the heat load intensity (avoiding over / under-heat dissipation). This collaborative control effectively improves the temperature drop rate of a single module.

[0064] This invention proposes a server heat dissipation method, comprising: collecting temperature data of each functional module of the server; determining the heat dissipation weight of each functional module based on the temperature data; determining the required proportion of heat dissipation resources for each functional module based on the heat dissipation weight; and allocating corresponding heat dissipation resources to each functional module based on the required proportion of heat dissipation resources. This invention can dynamically allocate heat dissipation resources to each functional module according to the server's functional modules, thereby improving heat dissipation efficiency and avoiding waste of heat dissipation resources.

[0065] This invention fundamentally solves the problem of heat dissipation resource misallocation caused by the dynamic imbalance of heat distribution in the server field by constructing a four-level linkage control mechanism of "temperature acquisition - weight calculation - proportion determination - resource allocation". Because the various functional modules within a server (such as CPU, GPU, and memory array) exhibit significant differences in heat load during actual operation, traditional heat dissipation solutions using a fixed fan group synchronous speed adjustment strategy inevitably result in both overheating of low-heat modules and underheating of high-heat modules. This solution creatively introduces a quantitative mediator variable of heat dissipation weight, transforming temperature monitoring data into a module-level heat dissipation demand intensity index. For example, when the CPU temperature rises sharply, its heat dissipation weight will be much higher than that of the memory module, which is at a low temperature, thus accurately reflecting the actual heat urgency of each area. Based on the weight value, the proportion of heat dissipation resources is further calculated, ensuring that the allocation of limited heat dissipation resources strictly follows the principle of supply on demand, completely changing the extensive management model of "average allocation" in traditional solutions.

[0066] In its implementation, this technical solution demonstrates three core benefits: First, by using a weighted calculation model, it achieves precise quantification of heat dissipation needs, enabling the system to identify key areas that truly require enhanced heat dissipation (such as computing units experiencing sudden high loads), and then concentrate airflow resources towards these high-heat areas. For example, when CPU heat dissipation resources account for 70% of total resources, the system can selectively increase airflow to that area, avoiding the energy waste of traditional solutions that force an increase in overall fan speed to meet local hotspots. Second, the dynamic allocation mechanism of heat dissipation resources significantly improves system adaptability. In scenarios with fluctuating server loads (such as switching from standby to full-speed operation), the system can quickly adjust resource layout based on real-time weight ratios, ensuring that heat dissipation intensity always remains synchronized with the thermal load curve. Finally, by eliminating redundant heat dissipation behaviors, this solution significantly reduces wind resistance losses and high-frequency noise caused by ineffective airflow circulation, while also reducing overall mechanical wear of the fan array.

[0067] Corresponding to the above server heat dissipation methods, the present invention also provides a server heat dissipation device. This server heat dissipation device includes a unit for performing the above server heat dissipation methods, and can be configured in a desktop computer, tablet computer, laptop computer, or other terminal. Specifically, the server heat dissipation device includes:

[0068] The data acquisition unit is used to collect temperature data from various functional modules of the server.

[0069] The first determining unit is used to determine the heat dissipation weight of each functional module based on the temperature data of each functional module;

[0070] The second determining unit is used to determine the proportion of heat dissipation resources required by each of the functional modules based on the heat dissipation weight of each functional module;

[0071] The allocation unit is used to allocate corresponding heat dissipation resources to each of the functional modules based on the proportion of heat dissipation resources of each functional module.

[0072] In some preferred embodiments, each functional module of the server is equipped with a temperature sensor, and the collection of temperature data from each functional module of the server includes: distributing the temperature data of each functional module to the temperature sensor of each functional module.

[0073] In some preferred embodiments, determining the heat dissipation weight of each functional module based on the temperature data of each functional module includes:

[0074] Obtain the preset temperature-heat dissipation weight mapping relationship;

[0075] Based on the temperature data of each functional module, the heat dissipation weight of each functional module is determined by querying the temperature-heat dissipation weight mapping relationship.

[0076] In some preferred embodiments, determining the proportion of heat dissipation resources required by each functional module based on the heat dissipation weight of each functional module includes:

[0077] Calculate the quotient of the heat dissipation weight of the functional module and the sum of the heat dissipation weights of all functional modules to obtain the proportion of heat dissipation resources required by the functional module.

[0078] In some preferred embodiments, the heat dissipation resources include multiple fans; the heat dissipation resource ratio based on each functional module is the allocation of corresponding heat dissipation resources to each functional module, including:

[0079] Based on the proportion of heat dissipation resources of each functional module, determine the target number of fans allocated to each functional module;

[0080] Assign a target number of fans to each of the aforementioned functional modules.

[0081] In some preferred embodiments, the fan is mounted on a slide rail and can be driven to move on the slide rail by a drive device. The functional modules of the server are sequentially arranged on one side of the slide rail. The step of allocating a target number of fans to each functional module includes:

[0082] The target number of fans corresponding to the functional module are moved to one side of the functional module to dissipate heat from the functional module.

[0083] In some preferred embodiments, the server heat dissipation device further includes:

[0084] The third determining unit is used to determine the target operating parameters of the fan corresponding to each functional module based on the temperature data of each functional module.

[0085] The adjustment unit is used to adjust the operating parameters of the fan corresponding to the functional module to the target operating parameters.

[0086] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned server heat dissipation device and each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0087] The aforementioned server cooling device can be implemented as a computer program, which can, for example... Figure 3 It runs on the computer device shown.

[0088] Please seeFigure 3 , Figure 3 This is a schematic block diagram of a computer device provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The server can be a standalone server or a server cluster composed of multiple servers.

[0089] The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0090] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. When the computer program 5032 is executed, it causes the processor 502 to perform a server cooling method.

[0091] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0092] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can perform a server heat dissipation method.

[0093] The network interface 505 is used for network communication with other devices. Those skilled in the art will understand that the above structure is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. A specific computer device 500 may include more or fewer components than shown in the figures, or combine certain components, or have different component arrangements.

[0094] The processor 502 is used to run a computer program 5032 stored in the memory to perform the following steps:

[0095] Collect temperature data from various functional modules of the server;

[0096] The heat dissipation weight of each functional module is determined based on the temperature data of each functional module.

[0097] The proportion of heat dissipation resources required by each functional module is determined based on the heat dissipation weight of each functional module.

[0098] Based on the proportion of heat dissipation resources for each functional module, corresponding heat dissipation resources are allocated to each functional module.

[0099] In some preferred embodiments, each functional module of the server is equipped with a temperature sensor, and the collection of temperature data from each functional module of the server includes: distributing the temperature data of each functional module to the temperature sensor of each functional module.

[0100] In some preferred embodiments, determining the heat dissipation weight of each functional module based on the temperature data of each functional module includes:

[0101] Obtain the preset temperature-heat dissipation weight mapping relationship;

[0102] Based on the temperature data of each functional module, the heat dissipation weight of each functional module is determined by querying the temperature-heat dissipation weight mapping relationship.

[0103] In some preferred embodiments, determining the proportion of heat dissipation resources required by each functional module based on the heat dissipation weight of each functional module includes:

[0104] Calculate the quotient of the heat dissipation weight of the functional module and the sum of the heat dissipation weights of all functional modules to obtain the proportion of heat dissipation resources required by the functional module.

[0105] In some preferred embodiments, the heat dissipation resources include multiple fans; the heat dissipation resource ratio based on each functional module is the allocation of corresponding heat dissipation resources to each functional module, including:

[0106] Based on the proportion of heat dissipation resources of each functional module, determine the target number of fans allocated to each functional module;

[0107] Assign a target number of fans to each of the aforementioned functional modules.

[0108] In some preferred embodiments, the fan is mounted on a slide rail and can be driven to move on the slide rail by a drive device. The functional modules of the server are sequentially arranged on one side of the slide rail. The step of allocating a target number of fans to each functional module includes:

[0109] The target number of fans corresponding to the functional module are moved to one side of the functional module to dissipate heat from the functional module.

[0110] In some preferred embodiments, the method further includes:

[0111] The target operating parameters of the fan corresponding to each functional module are determined based on the temperature data of each functional module.

[0112] Adjust the operating parameters of the fan corresponding to the functional module to the target operating parameters.

[0113] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0114] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0115] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program. When executed by a processor, the computer program causes the processor to perform the following steps:

[0116] Collect temperature data from various functional modules of the server;

[0117] The heat dissipation weight of each functional module is determined based on the temperature data of each functional module.

[0118] The proportion of heat dissipation resources required by each functional module is determined based on the heat dissipation weight of each functional module.

[0119] Based on the proportion of heat dissipation resources for each functional module, corresponding heat dissipation resources are allocated to each functional module.

[0120] In some preferred embodiments, each functional module of the server is equipped with a temperature sensor, and the collection of temperature data from each functional module of the server includes: distributing the temperature data of each functional module to the temperature sensor of each functional module.

[0121] In some preferred embodiments, determining the heat dissipation weight of each functional module based on the temperature data of each functional module includes:

[0122] Obtain the preset temperature-heat dissipation weight mapping relationship;

[0123] Based on the temperature data of each functional module, the heat dissipation weight of each functional module is determined by querying the temperature-heat dissipation weight mapping relationship.

[0124] In some preferred embodiments, determining the proportion of heat dissipation resources required by each functional module based on the heat dissipation weight of each functional module includes:

[0125] Calculate the quotient of the heat dissipation weight of the functional module and the sum of the heat dissipation weights of all functional modules to obtain the proportion of heat dissipation resources required by the functional module.

[0126] In some preferred embodiments, the heat dissipation resources include multiple fans; the heat dissipation resource ratio based on each functional module is the allocation of corresponding heat dissipation resources to each functional module, including:

[0127] Based on the proportion of heat dissipation resources of each functional module, determine the target number of fans allocated to each functional module;

[0128] Assign a target number of fans to each of the aforementioned functional modules.

[0129] In some preferred embodiments, the fan is mounted on a slide rail and can be driven to move on the slide rail by a drive device. The functional modules of the server are sequentially arranged on one side of the slide rail. The step of allocating a target number of fans to each functional module includes:

[0130] The target number of fans corresponding to the functional module are moved to one side of the functional module to dissipate heat from the functional module.

[0131] In some preferred embodiments, the method further includes:

[0132] The target operating parameters of the fan corresponding to each functional module are determined based on the temperature data of each functional module.

[0133] Adjust the operating parameters of the fan corresponding to the functional module to the target operating parameters.

[0134] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0135] Those skilled in the art will 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 implementations should not be considered beyond the scope of this invention.

[0136] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0137] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0138] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0139] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0140] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Since these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0141] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A server heat dissipation method, characterized in that, include: Collect temperature data from various functional modules of the server; The heat dissipation weight of each functional module is determined based on the temperature data of each functional module. The proportion of heat dissipation resources required by each functional module is determined based on the heat dissipation weight of each functional module. Based on the proportion of heat dissipation resources for each functional module, corresponding heat dissipation resources are allocated to each functional module.

2. The server heat dissipation method according to claim 1, characterized in that, Each functional module of the server is equipped with a temperature sensor. The process of collecting temperature data from each functional module of the server includes: distributing the temperature data of each functional module to the temperature sensor of each functional module.

3. The server heat dissipation method according to claim 1, characterized in that, The determination of the heat dissipation weight of each functional module based on the temperature data of each functional module includes: Obtain the preset temperature-heat dissipation weight mapping relationship; Based on the temperature data of each functional module, the heat dissipation weight of each functional module is determined by querying the temperature-heat dissipation weight mapping relationship.

4. The server heat dissipation method according to claim 1, characterized in that, The determination of the required heat dissipation resource ratio for each functional module based on the heat dissipation weight of each functional module includes: Calculate the quotient of the heat dissipation weight of the functional module and the sum of the heat dissipation weights of all functional modules to obtain the proportion of heat dissipation resources required by the functional module.

5. The server heat dissipation method according to claim 1, characterized in that, The heat dissipation resources include multiple fans; the heat dissipation resource ratio based on each functional module is the allocation of corresponding heat dissipation resources to each functional module, including: Based on the proportion of heat dissipation resources of each functional module, determine the target number of fans allocated to each functional module; Assign a target number of fans to each of the aforementioned functional modules.

6. The server heat dissipation method according to claim 5, characterized in that, The fan is mounted on a slide rail and can be driven to move along the slide rail. The functional modules of the server are arranged sequentially on one side of the slide rail. The process of allocating a target number of fans to each functional module includes: The target number of fans corresponding to the functional module are moved to one side of the functional module to dissipate heat from the functional module.

7. The server heat dissipation method according to claim 6, characterized in that, The method further includes: The target operating parameters of the fan corresponding to each functional module are determined based on the temperature data of each functional module. Adjust the operating parameters of the fan corresponding to the functional module to the target operating parameters.

8. A server heat dissipation device, characterized in that, Includes a unit for performing the method as described in any one of claims 1-7.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-7.

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