Temperature control method and system, electronic equipment and storage medium

Abstract

The invention discloses a temperature control method and system, electronic equipment and a storage medium, and the method comprises the steps: responding to a to-be-enabled service request received by a cloud server, and determining a plurality of target power consumption functions corresponding to the to-be-enabled service request; acquiring target power consumption required for operating a plurality of target power consumption functions; and adjusting a heat dissipation speed parameter of a heat dissipation device of the cloud server based on the target power consumption. According to the scheme, the precision of temperature adjustment can be improved.

Description

Technical Field

[0001] The present application relates to the field of cloud server operation and maintenance technology, and in particular to a temperature control method and system, electronic equipment, and storage medium. Background Art

[0002] At present, in order to solve the heat dissipation problem in cloud servers, the existing technical solutions usually control the heat dissipation speed parameters of the heat dissipation device by obtaining the temperature of the cloud server. However, this solution has hysteresis in reducing the temperature by controlling the heat dissipation speed parameters. The heat dissipation device will not work until the temperature rises to a threshold, and the heat dissipation device will stop working after the temperature drops below the threshold. This makes the judgment accuracy of the entire adjustment process insufficient, and increases the heat dissipation power consumption in vain. Summary of the invention

[0003] The present application at least provides a temperature control method and system, electronic device, and storage medium, which can improve the accuracy of temperature adjustment.

[0004] The first aspect of the present application provides a temperature control method, which includes: in response to a service request to be enabled received by a cloud server, determining several target power consumption functions corresponding to the service request to be enabled; obtaining target power consumption required to run the several target power consumption functions; and adjusting the heat dissipation speed parameters of the heat dissipation device of the cloud server based on the target power consumption.

[0005] Among them, determining several target power consumption functions corresponding to the service request to be enabled includes: obtaining a power consumption function having a mapping relationship with the service request to be enabled from a function warehouse as a target power consumption function, wherein the function warehouse stores different preset service requests and power consumption functions having a mapping relationship with each preset service request.

[0006] Among them, obtaining the target power consumption required for running several target power consumption functions includes: obtaining the initial power consumption corresponding to each target power consumption function from the power consumption mapping information, wherein the power consumption mapping information records the power consumption required when different power consumption functions are running; summing up each initial power consumption to obtain the target power consumption.

[0007] Among them, the determination of several target power consumption functions is executed by the processor of the cloud server, the power consumption mapping information is stored in the baseboard management controller of the cloud server, and the acquisition of target power consumption and the adjustment of the heat dissipation speed parameters of the heat dissipation device are executed by the baseboard management controller; and / or, the power consumption mapping information is calibrated through the following steps: obtaining the temperature rise of the processor under test of the device under test when running different power consumption functions, wherein the temperature rise is determined by using the temperature data detected by the temperature sensor set on the surface of the processor under test; based on the temperature rise corresponding to different power consumption functions, the power consumption mapping information is calibrated to match the type of the processor under test with the type of the processor of the cloud server; or Based on the type of processor of the cloud server, the test obtains the execution times of each core of the processor when executing each power consumption function; for each power consumption function, the total power consumption of the processor corresponding to the power consumption function under the target core voltage and target frequency is calculated, where the total power consumption is equal to the sum of the core power consumption of each core of the processor, and the core power consumption is related to the target core voltage, target frequency, model parameters corresponding to the core, and the execution times of the core power consumption function; the sum of the total power consumption and the additional power consumption of the processor is used as the initial power consumption of the corresponding power consumption function of the processor, where the additional power consumption is independent of the running speed of the processor; based on the initial power consumption corresponding to different power consumption functions, the power consumption mapping information is calibrated.

[0008] Among them, based on the target power consumption, the heat dissipation speed parameter of the heat dissipation device of the cloud server is adjusted, including: obtaining the heat dissipation speed parameter corresponding to the target power consumption from the heat dissipation parameter mapping information as the target heat dissipation speed parameter, wherein the heat dissipation parameter mapping information records the heat dissipation speed parameters corresponding to different power consumptions; and adjusting the heat dissipation speed parameter of the heat dissipation device to the target heat dissipation speed parameter.

[0009] The heat dissipation parameter mapping information is obtained by calibration.

[0010] Among them, the heat dissipation device is a fan, and the heat dissipation speed parameter is the rotation speed of the fan; and / or, after adjusting the heat dissipation speed parameter of the heat dissipation device of the cloud server based on the target power consumption, it includes: obtaining the ambient temperature of the cloud server; when the ambient temperature meets the preset temperature condition, lowering the heat dissipation speed parameter of the heat dissipation device.

[0011] The second aspect of the present application provides a temperature control system, including: a trigger, used to trigger the temperature control operation of a cloud server; a scheduler, used to determine a number of target power consumption functions corresponding to the service requests to be enabled based on the received service requests to be enabled after the trigger is triggered; a baseboard management controller, connected to the scheduler, used to obtain the target power consumption required for the operation of the several target power consumption functions, and adjust the heat dissipation speed parameters of the heat dissipation device of the cloud server based on the target power consumption.

[0012] Among them, the scheduler includes: a function warehouse for storing different preset service requests and power consumption functions having a mapping relationship with each preset service request; and / or, the baseboard management controller includes: power consumption mapping information for recording the power consumption required when different power consumption functions are running.

[0013] A third aspect of the present application provides an electronic device, comprising a memory and a processor coupled to each other, wherein the processor is used to execute program instructions stored in the memory to implement the temperature control method in the first aspect.

[0014] A fourth aspect of the present application provides a computer-readable storage medium having program instructions stored thereon, and when the program instructions are executed by a processor, the temperature control method in the first aspect described above is implemented.

[0015] In the above scheme, after the cloud server receives the service request to be enabled, the service request to be enabled is analyzed to determine several target power consumption functions corresponding to the service request to be enabled, and then the power consumption of the service request to be enabled is obtained by running the target power consumption required by each target power consumption function. Therefore, when the cloud server executes the service request to be enabled, the heat dissipation speed parameters of the heat dissipation device of the cloud server can be adjusted in time according to the power consumption of the service request to be enabled to control the temperature of the cloud server, thereby improving the accuracy of temperature adjustment and avoiding increasing heat dissipation power consumption.

[0016] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into the specification and constitute a part of the specification. These drawings illustrate embodiments consistent with the present application and are used together with the specification to illustrate the technical solution of the present application.

[0018] Figure 1 It is a flow chart of an embodiment of the temperature control method of the present application; Figure 2 It is a flow chart of another embodiment of the temperature control method of the present application; Figure 3 It is a schematic diagram of the framework of an embodiment of the temperature control system of the present application; Figure 4 It is a schematic diagram of the framework of an embodiment of the temperature control device of the present application; Figure 5 It is a schematic diagram of the framework of an embodiment of the electronic device of the present application; Figure 6 It is a schematic diagram of a framework of an embodiment of a computer-readable storage medium of the present application. DETAILED DESCRIPTION

[0019] The scheme of the embodiment of the present application is described in detail below in conjunction with the drawings of the specification.

[0020] In the following description, for the purpose of explanation rather than limitation, specific details such as specific system structures, interfaces, and technologies are provided to facilitate a thorough understanding of the present application.

[0021] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the objects associated before and after are in an "or" relationship. In addition, "many" in this article means two or more than two. In addition, the term "at least one" in this article means any combination of at least two of any one or more of a plurality of, for example, including at least one of A, B, and C, can mean including any one or more elements selected from the set consisting of A, B, and C.

[0022] Existing heat dissipation solutions for cloud servers usually obtain the temperature information of the cloud server first, and then adjust the heat dissipation speed parameters of the heat dissipation device according to the temperature information. However, this solution usually has hysteresis. For example, when the temperature in the cloud server reaches a threshold, the heat dissipation device will be controlled to dissipate heat, so that the temperature of the cloud server will not start to drop until the heat dissipation device has been running for a period of time.

[0023] Therefore, in order to solve the hysteresis problem, this application is based on the serverless computing technology in the cloud computing server, by analyzing the scale of the power consumption function, quantitatively converting it into the corresponding CPU (Central Processing Unit) power consumption, and combining the heat dissipation speed parameters of the existing heat dissipation device to adjust the heat dissipation solution in real time. Compared with the heat dissipation solution that obtains temperature feedback, this solution is more accurate and can effectively solve the hysteresis between the heat dissipation speed parameters of the heat dissipation device and the temperature change.

[0024] See also Figure 1 , Figure 1 This is a flow chart of an embodiment of the temperature control method of the present application. Specifically, it may include the following steps: Step S110: In response to the service request to be activated received by the cloud server, a plurality of target power consumption functions corresponding to the service request to be activated are determined.

[0025] Elastic Compute Service (ECS) is a simple, efficient, secure, reliable, and elastically scalable computing service. Its management is simpler and more efficient than that of physical servers. Cloud servers can provide remote services in a cloud computing environment. The core concept is to virtualize the resources of physical servers (such as processors, memory, storage, etc.) and allocate these virtualized resources to targets. At present, the main cloud services include IaaS (Infrastructure as a Service), PaaS (Platform as a Service), SaaS (Software as a Service), FaaS (Function as a Service), etc. Among them, FaaS has rapidly emerged with its efficient development model and cost advantages. It allows code to run in the form of functions in the FaaS platform. Since its operation is based on functions, it is the basis for the system to be simple, stable, and maintain high performance. Serverless computing technology is also a platform model generated on the basis of FaaS.

[0026] Therefore, in this embodiment, based on the serverless computing technology, the scale of the power consumption function can be analyzed and quantitatively converted into the corresponding CPU power consumption, and the heat dissipation speed parameter of the existing heat dissipation device can be combined to adjust the heat dissipation solution of the cloud server in real time. Among them, the heat dissipation device can be a fan, and the heat dissipation speed parameter can be the speed of the fan. In addition, the heat dissipation device can also be a cooler, and the heat dissipation speed parameter can be the flow speed of the liquid in the cooler. Therefore, no specific limitation is made here regarding the heat dissipation device.

[0027] Furthermore, in order to provide a better experience for the target, the operation and maintenance of the cloud server can be managed through the BMC (Baseboard Management Controller).

[0028] In some embodiments, the target can send different service requests to the cloud server remotely through the smart device to implement different services. After receiving the service request, the cloud server converts the service request into different power consumption functions, and schedules different resources through these power consumption functions to implement the service request, wherein the BMC can be used to schedule different resources based on these power consumption functions.

[0029] Specifically, the cloud server uses the FaaS platform, and the FaaS platform allows the code to run in the form of functions. Therefore, a function warehouse can be set up in the cloud server, and the function warehouse can be used to store different preset service requests and power consumption functions with mapping relationships with each preset service request. After receiving the service request to be enabled sent by the target, the cloud server parses the service request to be enabled to determine which power consumption functions the service request to be enabled can be converted to, and then obtains the power consumption function with mapping relationship with the service request to be enabled from the function warehouse as the target power consumption function. Then, the target power consumption function is run to implement the business corresponding to the service request to be enabled sent by the target.

[0030] Step S120: Obtain target power consumption required for running several target power consumption functions.

[0031] In some embodiments, before running several target power consumption functions, the target power consumption required when running the several target power consumption functions can be determined first. Through the target power consumption, a heat dissipation plan can be formulated in advance to start the heat dissipation device for early heat dissipation, so as to reduce the hysteresis between the adjustment of the heat dissipation device and the temperature of the cloud server.

[0032] Specifically, the initial power consumption corresponding to each target power consumption function can be obtained from the power consumption mapping information, and then the initial power consumption is summed to obtain the target power consumption. The power consumption mapping information records the power consumption required when different power consumption functions are running.

[0033] Regarding power consumption mapping information, the following two calibration methods can be used: 1. Laboratory calibration method 1. Place the device under test in a standard windless and constant temperature thermal design laboratory; 2. The operating object runs different power consumption functions on the device interface of the device under test; 3. Obtaining the temperature rise of the processor under test of the device under test when running different power consumption functions, wherein the temperature rise is determined by using temperature data detected by a temperature sensor disposed on the surface of the processor under test; 4. Based on the temperature rise corresponding to different power consumption functions, the power consumption mapping information is calibrated, and the type of the processor to be tested matches the type of the processor of the cloud server.

[0034] 2. Model Algorithm 1. Based on the type of processor of the cloud server, the number of executions n of each core of the processor when executing each power consumption function is obtained by testing, wherein the number of executions of each power consumption function may be the same or different, which is not specifically limited here; 2. For each power consumption function, calculate the total power consumption of the processor corresponding to the power consumption function at the target core voltage v and target frequency f , where the total power consumption Equal to the core power consumption of each core of the processor The core power consumption is related to the target core voltage v, the target frequency f, the model parameter k corresponding to the core, and the number of executions n of the core power consumption function: , , Among them, core is the number of cores of the processor; 3. The total power consumption of the processor With additional power consumption The sum of the initial power consumption P of the processor corresponding to the power consumption function, where the additional power consumption has nothing to do with the operating speed of the processor: ; 4. Based on the initial power consumption corresponding to different power consumption functions, the power consumption mapping information is calibrated.

[0035] It is understandable that due to the difference in processors, the power consumption required for each power consumption function in the power consumption mapping information is also different when running. Therefore, the initial power consumption corresponding to the power consumption function under different platforms needs to be recalibrated. Generally, the calibration of the power consumption mapping information can be performed before the cloud server leaves the factory.

[0036] In some other embodiments, a plurality of target power consumption functions may be sent to a virtual machine for execution, and the power consumption generated when the plurality of target power consumption functions are executed in the virtual machine is used as the target power consumption.

[0037] In other embodiments, an AI (Artificial Intelligence) big model may be used to calculate the power consumption required for the target power consumption function to obtain the target power consumption. Specifically, the AI ​​big model has been trained before use. During the training process, a preset power consumption function is used as the input of the AI ​​big model, and the preset power consumption is used as the output result of the AI ​​big model. The difference between the preset power consumption and the actual power consumption is used as the basis for adjusting the parameters of the AI ​​big model, so that the trained AI big model meets the actual usage expectations.

[0038] It is understandable that the method for obtaining the target power consumption is not specifically limited here.

[0039] In some embodiments, the determination of several target power consumption functions is performed by a processor of the cloud server, the power consumption mapping information is stored in a baseboard management controller of the cloud server, and the acquisition of target power consumption and the adjustment of heat dissipation speed parameters of the heat dissipation device are both performed by the baseboard management controller.

[0040] In addition, the power consumption mapping information may also be stored in the processor of the cloud server.

[0041] Step S130: Based on the target power consumption, adjust the heat dissipation speed parameters of the heat dissipation device of the cloud server.

[0042] In some embodiments, the target power consumption may be analyzed to determine the speed at which the temperature of the cloud server rises when it is running certain target power consumption functions compared to the current temperature of the cloud server. If the analysis result shows that the temperature of the cloud server will rise rapidly in a short period of time when it is running certain target power consumption functions, then the heat dissipation speed parameter of the heat dissipation device needs to be adjusted to the maximum; if the analysis result shows that the temperature of the cloud server will rise slowly when it is running certain target power consumption functions, then the heat dissipation speed parameter of the heat dissipation device only needs to be slightly increased.

[0043] Furthermore, in order to make the adjustment of the heat dissipation speed parameter of the heat dissipation device more in line with the actual operating conditions, the heat dissipation speed parameter of the heat dissipation device can be set to levels, and different levels correspond to different heat dissipation solutions. For example, when the heat dissipation device is a fan and the heat dissipation speed parameter is the speed of the fan, three levels can be set: Level 1: The fan speed is set to 1000 rpm, which corresponds to the situation where the temperature of the cloud server rises slowly and the target power consumption is low; Level 2: The fan speed is set to 1500 rpm, which corresponds to the situation where the temperature of the cloud server rises quickly and the target power consumption is moderate; Level 3: The fan speed is set to 2000 rpm, which corresponds to the situation where the temperature of the cloud server rises quickly and the target power consumption is high.

[0044] Through the above method, the adjustment accuracy of the heat dissipation speed parameters of the heat dissipation device is higher, which can effectively solve the hysteresis between the heat dissipation speed parameters and the temperature change of the cloud server. Compared with the existing technology, the heat dissipation device does not need to start running after the temperature of the cloud server reaches the threshold.

[0045] It is understandable that the specific setting of the heat dissipation speed parameter setting level of the heat dissipation device can be adjusted according to the actual usage situation and is not specifically limited here.

[0046] In other embodiments, in order to timely adjust the heat dissipation speed parameter of the heat dissipation device of the cloud server, the heat dissipation speed parameter corresponding to the target power consumption can be obtained from the heat dissipation parameter mapping information as the target heat dissipation speed parameter, wherein the heat dissipation parameter mapping information records the heat dissipation speed parameters corresponding to different power consumptions. Then, the heat dissipation speed parameter of the heat dissipation device is adjusted to the target heat dissipation speed parameter.

[0047] The heat dissipation parameter mapping information is obtained by calibration, and the calibration method used for the heat dissipation parameter mapping information may be the same as or different from the calibration method used for the power consumption mapping information, which is not specifically limited here.

[0048] In some embodiments, after the service request to be enabled is completed, the baseboard management controller may also obtain the ambient temperature of the cloud server, and when the ambient temperature meets the preset temperature condition, reduce the heat dissipation speed parameter of the heat dissipation device. The preset temperature condition may be when the ambient temperature is lower than a certain temperature threshold.

[0049] This application uses serverless computing technology to calibrate the different initial power consumptions required for different CPUs to run different power consumption functions, obtain the relationship between the power consumption function and the initial power consumption, and then adjust the heat dissipation speed parameters in advance based on this power consumption, reduce the total power consumption of the heat dissipation device and the cloud server, and make the heat dissipation speed parameters change more reasonably. In addition, the power consumption mapping information has been calibrated when the cloud server leaves the factory and stored in the BMC, which does not require excessive operation and maintenance, and is simple and convenient.

[0050] See also Figure 2 , Figure 2 This is a flow chart of another embodiment of the temperature control method of the present application. Specifically, it may include the following steps: Step S210: Obtain a service request to be activated.

[0051] In some embodiments, a long link may be established between the cloud server and the smart device used by the target. When the target operates on the smart device and sends a request for a service to be enabled, the cloud server may receive the request for a service to be enabled in a timely manner. In addition, to avoid wasting resources, a short link may also be used between the cloud server and the smart device used by the target, which is not specifically limited here.

[0052] Step S220: matching the received service requests to be activated to obtain several target power consumption functions.

[0053] In some embodiments, a function repository is established in the cloud server. After receiving the service request to be enabled, the cloud server matches the received service request to be enabled with the preset service request in the function repository. If the match is successful, the power consumption function in the function repository that has a mapping relationship with the preset service request is used as the target power consumption function of the service request to be enabled; if the match is unsuccessful, an error prompt is given.

[0054] Step S230: Determine the target power consumption required during operation based on a number of target power consumption functions.

[0055] In some embodiments, the target power consumption function may be matched with the power consumption function in the power consumption mapping information. If the match is successful, the initial power consumption corresponding to the power consumption function in the power consumption mapping information may be used as the initial power consumption of the target power consumption function. The above method is repeated to obtain the initial power consumptions corresponding to several target power consumption functions, and all the initial power consumptions are added together to obtain the target power consumption.

[0056] Step S240: Based on the target power consumption, adjust the heat dissipation speed parameters of the heat dissipation device of the cloud server.

[0057] This step is the same as the above step S130 and will not be described again here.

[0058] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0059] See also Figure 3 , Figure 3 It is a framework diagram of an embodiment of the temperature control system 300 of the present application. In combination with the above content, this embodiment is based on serverless computing technology to analyze the scale of the power consumption function. Therefore, the cloud server also includes a temperature control system 300 based on serverless computing technology. The temperature control system 300 includes: a trigger 310, a scheduler 320 and a baseboard management controller 330. The trigger 310 is used to trigger the temperature control operation of the cloud server. The scheduler 320 is used to determine several target power consumption functions corresponding to the service request to be enabled based on the received service request to be enabled after the trigger 310 is triggered. The baseboard management controller 330 is connected to the scheduler 320, and is used to obtain the target power consumption required for the operation of several target power consumption functions, and adjust the heat dissipation speed parameters of the heat dissipation device of the cloud server based on the target power consumption.

[0060] In some embodiments, the scheduler 320 includes: a function warehouse 321 for storing different preset service requests and power consumption functions having a mapping relationship with each preset service request; In some embodiments, the baseboard management controller 330 includes: power consumption mapping information 331, which is used to record the power consumption required when different power consumption functions are running.

[0061] See also Figure 4 , Figure 4 It is a schematic diagram of a framework of an embodiment of a temperature control device 400 of the present application. The temperature control device 400 includes a function search module 410, an acquisition module 420 and an adjustment module 430. The function search module 410 executes in response to the service request to be enabled received by the cloud server, and determines a number of target power consumption functions corresponding to the service request to be enabled. The acquisition module 420 executes to obtain the target power consumption required to run the number of target power consumption functions. The adjustment module 430 executes to adjust the heat dissipation speed parameter of the heat dissipation device of the cloud server based on the target power consumption.

[0062] In some embodiments, the function search module 410 executes to determine several target power consumption functions corresponding to the service request to be enabled, including: obtaining a power consumption function having a mapping relationship with the service request to be enabled from a function repository as a target power consumption function, wherein the function repository stores different preset service requests and power consumption functions having a mapping relationship with each preset service request.

[0063] In some embodiments, the acquisition module 420 executes to obtain the target power consumption required to run several target power consumption functions, including: obtaining the initial power consumption corresponding to each target power consumption function from the power consumption mapping information, wherein the power consumption mapping information records the power consumption required when different power consumption functions are running; summing up each initial power consumption to obtain the target power consumption.

[0064] In some embodiments, the acquisition module 420 performs the determination of several target power consumption functions by the processor of the cloud server, the power consumption mapping information is stored in the baseboard management controller of the cloud server, the acquisition of the target power consumption and the adjustment of the heat dissipation speed parameters of the heat dissipation device are performed by the baseboard management controller; and / or, the power consumption mapping information is calibrated through the following steps: obtaining the temperature rise of the processor under test of the device under test when running different power consumption functions, wherein the temperature rise is determined by the temperature data detected by the temperature sensor set on the surface of the processor under test; based on the temperature rise corresponding to different power consumption functions, the power consumption mapping information is calibrated, and the type of the processor under test is consistent with the processor of the cloud server. Type matching; or, based on the type of processor of the cloud server, test and obtain the number of executions of each core of the processor when executing each power consumption function; for each power consumption function, calculate and obtain the total power consumption of the processor corresponding to the power consumption function at the target core voltage and target frequency, wherein the total power consumption is equal to the sum of the core power consumptions of each core of the processor, and the core power consumption is related to the target core voltage, target frequency, model parameters corresponding to the core, and the number of executions of the core power consumption function; take the sum of the total power consumption of the processor and the additional power consumption as the initial power consumption of the corresponding power consumption function of the processor, wherein the additional power consumption is independent of the operating speed of the processor; based on the initial power consumption corresponding to different power consumption functions, calibrate and obtain the power consumption mapping information.

[0065] In some embodiments, the adjustment module 430 adjusts the cooling speed parameters of the cooling device of the cloud server based on the target power consumption, including: obtaining the cooling speed parameters corresponding to the target power consumption from the cooling parameter mapping information as the target cooling speed parameters, wherein the cooling parameter mapping information records the cooling speed parameters corresponding to different power consumptions; and adjusting the cooling speed parameters of the cooling device to the target cooling speed parameters.

[0066] In some embodiments, the heat dissipation parameter mapping information executed by the adjustment module 430 is obtained by calibration.

[0067] In some embodiments, the adjustment module 430 executes the heat dissipation device as a fan, and the heat dissipation speed parameter is the fan speed; and / or, after adjusting the heat dissipation speed parameter of the heat dissipation device of the cloud server based on the target power consumption, it includes: obtaining the ambient temperature of the cloud server; when the ambient temperature meets the preset temperature condition, lowering the heat dissipation speed parameter of the heat dissipation device.

[0068] See also Figure 5 , Figure 5 : is a schematic diagram of a framework of an embodiment of an electronic device 50 of the present application. The electronic device 50 includes a memory 51 and a processor 52 coupled to each other, and the processor 52 is used to execute program instructions stored in the memory 51 to implement the steps in any of the above-mentioned temperature control method embodiments. In a specific implementation scenario, the electronic device 50 may include but is not limited to: a microcomputer, a server, and in addition, the electronic device 50 may also include a mobile device such as a laptop computer and a tablet computer, which is not limited here.

[0069] Specifically, the processor 52 is used to control itself and the memory 51 to implement the steps in any of the above-mentioned temperature control method embodiments. The processor 52 can also be called a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip with signal processing capabilities. The processor 52 can also be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In addition, the processor 52 can be implemented by an integrated circuit chip.

[0070] See also Figure 6 , Figure 6 Schematic diagram of a computer-readable storage medium 60 of the present application. The computer-readable storage medium 60 stores program instructions 601 that can be executed by a processor, and the program instructions 601 are used to implement the steps in any of the above temperature control method embodiments.

[0071] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the method described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0072] The above description of various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced to each other, and for the sake of brevity, they will not be repeated herein.

[0073] In the several embodiments provided in the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device implementation described above is only schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation, such as units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0074] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0075] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially 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. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of each implementation method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

Claims

1. A temperature control method, characterized in that: include: In response to the service request to be activated received by the cloud server, determining a number of target power consumption functions corresponding to the service request to be activated; Obtaining target power consumption required for running the plurality of target power consumption functions; Based on the target power consumption, a heat dissipation speed parameter of the heat dissipation device of the cloud server is adjusted.

2. The method according to claim 1, characterized in that: The determining of a plurality of target power consumption functions corresponding to the service request to be enabled includes: A power consumption function having a mapping relationship with the service request to be enabled is obtained from a function warehouse as the target power consumption function, wherein the function warehouse stores different preset service requests and power consumption functions having a mapping relationship with each of the preset service requests.

3. The method according to claim 1, characterized in that The obtaining target power consumption required for running the plurality of target power consumption functions includes: Acquire the initial power consumption corresponding to each of the target power consumption functions from the power consumption mapping information, wherein the power consumption mapping information records the power consumption required when different power consumption functions are running; The initial power consumptions are summed to obtain the target power consumption.

4. The method according to claim 3, characterized in that: The determination of the target power consumption functions is performed by a processor of the cloud server, the power consumption mapping information is stored in a baseboard management controller of the cloud server, and the acquisition of the target power consumption and the adjustment of the heat dissipation speed parameter of the heat dissipation device are performed by the baseboard management controller; And / or, the power consumption mapping information is calibrated by the following steps: Obtaining the temperature rise of the processor under test of the device under test when running different power consumption functions, wherein the temperature rise is determined by using temperature data detected by a temperature sensor arranged on the surface of the processor under test; based on the temperature rise corresponding to different power consumption functions, calibrating the power consumption mapping information, the type of the processor under test matches the type of the processor of the cloud server; or, Based on the type of processor of the cloud server, the number of executions of each power consumption function by each core of the processor is obtained by testing; for each power consumption function, the total power consumption of the processor corresponding to the power consumption function at the target core voltage and target frequency is calculated, wherein the total power consumption is equal to the sum of the core power consumptions of the cores of the processor, and the core power consumption is related to the target core voltage, target frequency, model parameters corresponding to the core, and the number of executions of the power consumption function by the core; the sum of the total power consumption and additional power consumption of the processor is used as the initial power consumption of the processor corresponding to the power consumption function, wherein the additional power consumption is independent of the operating speed of the processor; based on the initial power consumption corresponding to different power consumption functions, the power consumption mapping information is calibrated.

5. The method according to claim 1, characterized in that The adjusting the heat dissipation speed parameter of the heat dissipation device of the cloud server based on the target power consumption includes: Acquire, from the heat dissipation parameter mapping information, a heat dissipation speed parameter corresponding to the target power consumption as a target heat dissipation speed parameter, wherein the heat dissipation parameter mapping information records heat dissipation speed parameters corresponding to different power consumptions; The heat dissipation speed parameter of the heat dissipation device is adjusted to the target heat dissipation speed parameter.

6. The method according to claim 5, characterized in that The heat dissipation parameter mapping information is obtained by calibration.

7. The method according to claim 1, characterized in that The heat dissipation device is a fan, and the heat dissipation speed parameter is the rotation speed of the fan; And / or, after adjusting the heat dissipation speed parameter of the heat dissipation device of the cloud server based on the target power consumption, the method further comprises: Obtaining the ambient temperature of the cloud server; When the ambient temperature meets the preset temperature condition, the heat dissipation speed parameter of the heat dissipation device is lowered.

8. A temperature control system, characterized in that: include: Trigger, used to trigger the temperature control operation of the cloud server; A scheduler, configured to determine, after the trigger is triggered, a number of target power consumption functions corresponding to the service request to be enabled based on the received service request to be enabled; The baseboard management controller is connected to the scheduler and is used to obtain the target power consumption required for the operation of the plurality of target power consumption functions, and adjust the heat dissipation speed parameter of the heat dissipation device of the cloud server based on the target power consumption.

9. The system according to claim 8, characterized in that The scheduler comprises: A function warehouse, used to store different preset service requests and power consumption functions having a mapping relationship with each of the preset service requests; And / or, the baseboard management controller includes: The power consumption mapping information is used to record the power consumption required when different power consumption functions are running.

10. An electronic device, characterized in that: It comprises a memory and a processor coupled to each other, wherein the processor is used to execute program instructions stored in the memory to implement the temperature control method according to any one of claims 1 to 7.

11. A computer-readable storage medium having program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the temperature control method according to any one of claims 1 to 7 is implemented.

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