Heat dissipation method of processor, computer equipment, storage medium and program product

Abstract

The invention discloses a heat dissipation method of a processor, computer equipment, a storage medium and a program product, and relates to the technical field of processor heat dissipation, and the method comprises the following steps: when a target processor power consumption mode is a high power consumption mode, obtaining a target temperature difference and a target processor utilization rate, mapping the target temperature difference and the target processor utilization rate to a corresponding fuzzy set by utilizing a Gaussian function, determining and determining a target value of a heat dissipation parameter combination based on a target temperature difference membership degree and a target processor utilization rate membership degree, and further adjusting the rotating speed of a fan corresponding to a target processor; when the power consumption mode of the target processor is a low-power-consumption mode, a first value of a current temperature set point of the target processor and a second value of an expected temperature set point of the target processor are obtained, and the wind direction of a fan corresponding to the target processor is adjusted based on the first value and the second value. The technical problem that a single heat dissipation strategy is difficult to meet the heat dissipation requirements of different processors is solved, and the technical effect of improving the heat dissipation reliability of the processors is achieved.

Description

Technical Field

[0001] This application relates to the technical field of processor cooling, and particularly to a cooling method for a processor, a computer device, a storage medium, and a program product. Background Art

[0002] During the high-speed read and write process, a graphics processing unit (GPU) generates a large amount of heat. Especially in a server environment with high-density deployment, when multiple GPUs work simultaneously, the heat dissipation problem becomes more prominent. If the GPU temperature is too high, it will not only affect the performance and lifespan of the GPU, but may also lead to data loss or hardware failures. Therefore, effective heat dissipation control is crucial for ensuring the stable operation of the GPU.

[0003] Traditional cooling systems usually adopt a unified cooling strategy, making it difficult to perform refined management according to the cooling requirements of different GPUs, and easily resulting in problems such as insufficient or excessive heat dissipation for some GPUs. Summary of the Invention

[0004] This application provides a cooling method for a processor, a computer device, a storage medium, and a program product to solve the technical problem that a single cooling strategy in related technologies is difficult to meet the cooling requirements of different processors.

[0005] This application provides a cooling method for a processor, including: Obtain the power consumption mode of the target processor; In response to the power consumption mode of the target processor being the high-power mode, obtain the target temperature difference and the target processor utilization rate, where the target temperature difference is the difference between the actual temperature and the desired temperature of the target processor; map the target temperature difference to the target temperature difference fuzzy set using a Gaussian function to determine the target temperature difference membership degree; map the target processor utilization rate to the target processor utilization rate fuzzy set using a Gaussian function to determine the target processor utilization rate membership degree; determine the target value of the cooling parameter combination based on the target temperature difference membership degree and the target processor utilization rate membership degree; adjust the rotational speed of the fan corresponding to the target processor based on the target value of the cooling parameter combination; In response to the power consumption mode of the target processor being the low-power mode, obtain the first value of the current temperature set point of the target processor and the second value of the desired temperature set point of the target processor, and adjust the wind direction of the fan corresponding to the target processor based on the first value and the second value.

[0006] This application also provides a computer device, including: a memory for storing a computer program; a processor for implementing the steps of the data processing method in the following embodiments when executing the computer program.

[0007] Obtain the power consumption mode of the target processor; In response to the target processor power consumption mode being the high-power consumption mode, obtain the target temperature difference and the target processor utilization rate. The target temperature difference is the difference between the actual temperature and the desired temperature of the target processor; use the Gaussian function to map the target temperature difference to the target temperature difference fuzzy set to determine the target temperature difference membership degree; use the Gaussian function to map the target processor utilization rate to the target processor utilization rate fuzzy set to determine the target processor utilization rate membership degree; determine the target value of the heat dissipation parameter combination based on the target temperature difference membership degree and the target processor utilization rate membership degree; adjust the rotation speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination; In response to the target processor power consumption mode being the low-power consumption mode, obtain the first value of the current temperature set point of the target processor and the second value of the desired temperature set point of the target processor, and adjust the wind direction of the fan corresponding to the target processor based on the first value and the second value.

[0008] This application also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the steps of the data processing method in the following embodiments are implemented.

[0009] Obtain the target processor power consumption mode; In response to the target processor power consumption mode being the high-power consumption mode, obtain the target temperature difference and the target processor utilization rate. The target temperature difference is the difference between the actual temperature and the desired temperature of the target processor; use the Gaussian function to map the target temperature difference to the target temperature difference fuzzy set to determine the target temperature difference membership degree; use the Gaussian function to map the target processor utilization rate to the target processor utilization rate fuzzy set to determine the target processor utilization rate membership degree; determine the target value of the heat dissipation parameter combination based on the target temperature difference membership degree and the target processor utilization rate membership degree; adjust the rotation speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination; In response to the target processor power consumption mode being the low-power consumption mode, obtain the first value of the current temperature set point of the target processor and the second value of the desired temperature set point of the target processor, and adjust the wind direction of the fan corresponding to the target processor based on the first value and the second value.

[0010] This application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the data processing method in the following embodiments are implemented.

[0011] Obtain the target processor power consumption mode; In response to the target processor power consumption mode being the high-power consumption mode, obtain the target temperature difference and the target processor utilization rate. The target temperature difference is the difference between the actual temperature and the desired temperature of the target processor; map the target temperature difference to the target temperature difference fuzzy set using the Gaussian function to determine the target temperature difference membership degree; map the target processor utilization rate to the target processor utilization rate fuzzy set using the Gaussian function to determine the target processor utilization rate membership degree; determine the target value of the heat dissipation parameter combination based on the target temperature difference membership degree and the target processor utilization rate membership degree; adjust the rotational speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination; In response to the target processor power consumption mode being the low-power consumption mode, obtain the first value of the current temperature set point of the target processor and the second value of the desired temperature set point of the target processor, and adjust the wind direction of the fan corresponding to the target processor based on the first value and the second value.

[0012] Through the processor heat dissipation method provided in this application, by distinguishing different target processor power consumption modes and setting different processor heat dissipation strategies, In response to the target processor power consumption mode being the high-power consumption mode, obtain the target temperature difference and the target processor utilization rate. The target temperature difference is the difference between the actual temperature and the desired temperature of the target processor; map the target temperature difference to the target temperature difference fuzzy set using the Gaussian function to determine the target temperature difference membership degree; map the target processor utilization rate to the target processor utilization rate fuzzy set using the Gaussian function to determine the target processor utilization rate membership degree; determine the target value of the heat dissipation parameter combination based on the target temperature difference membership degree and the target processor utilization rate membership degree; adjust the rotational speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination; in response to the target processor power consumption mode being the low-power consumption mode, obtain the first value of the current temperature set point of the target processor and the second value of the desired temperature set point of the target processor, and adjust the wind direction of the fan corresponding to the target processor based on the first value and the second value. Therefore, it is possible to selectively adjust the rotational speed or the wind direction of the fan corresponding to the processor according to the heat dissipation requirements of the processor in different power consumption modes, and it is possible to achieve refined control of the processor heat dissipation while taking into account energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0014] Figure 1 It is a flowchart showing the process of the processor heat dissipation method provided in an embodiment of the present application; Figure 2 Schematic diagram of the structure of the heat dissipation system of a processor provided by an embodiment of the present application; Figure 3 Schematic diagram of the structure of the heat dissipation system of a processor provided by another embodiment of the present application; Figure 4 Schematic diagram of the structure of the heat dissipation device of a processor provided by an embodiment of the present application; Figure 5 Internal structure diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners

[0015] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present application.

[0016] It should be noted that in the description of the present application, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. The terms "first", "second", etc. in the present application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0017] In order to enable those skilled in the art in the technical field to better understand the solutions of the present application, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0018] As Figure 1 shown, an embodiment of the present application provides a heat dissipation method for a processor, and the method specifically includes the following steps: Step 101: Obtain the power consumption mode of the target processor.

[0019] Step 102: In response to the power consumption mode of the target processor being the high power consumption mode, obtain the target temperature difference and the target processor utilization rate, where the target temperature difference is the difference between the actual temperature of the target processor and the desired temperature of the target processor; map the target temperature difference to the target temperature difference fuzzy set by using the Gaussian function, and determine the target temperature difference membership degree; map the target processor utilization rate to the target processor utilization rate fuzzy set by using the Gaussian function, and determine the target processor utilization rate membership degree; determine the target value of the heat dissipation parameter combination based on the target temperature difference membership degree and the target processor utilization rate membership degree; adjust the rotation speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination.

[0020] The target processor of this application can specifically be a graphics processing unit (GPU). It is a hardware chip specifically designed for efficiently processing graphics rendering, parallel computing, and machine learning tasks.

[0021] The power consumption status of the target processor can be queried by directly reading the processor MSR register, obtaining it through the IPMI command of the baseboard management controller, reading it through the Windows WMI interface, etc. The power consumption status of the target processor obtained through different methods is classified into a high-power consumption mode or a low-power consumption mode according to a unified standard.

[0022] In one embodiment, in the high-power consumption mode, the target temperature difference and the utilization rate of the target processor can be obtained. The target temperature difference is the difference between the actual temperature and the desired temperature of the target processor. The utilization rate of the target processor can be obtained by statistically calculating the proportion of the time when the GPU executes non-idle tasks. For example, if the GPU has executed calculations for 800 milliseconds in the past 1 second, the utilization rate is 80%.

[0023] In this application, multiple temperature difference fuzzy sets can be preset in advance. Each temperature difference fuzzy set corresponds to a temperature difference range, and there may be intersections between the temperature difference ranges of different temperature difference fuzzy sets in this application. That is, a target temperature difference can belong to two temperature difference fuzzy sets at the same time. After obtaining the target temperature difference, the Gaussian function can be used to map the target temperature difference to the target temperature difference fuzzy set, and then the membership degree of the target temperature difference can be determined.

[0024] Specifically, obtain multiple temperature difference fuzzy sets and the temperature difference ranges corresponding to the multiple temperature difference fuzzy sets; select the temperature difference fuzzy set corresponding to the temperature difference range that matches the target temperature difference as the target temperature difference fuzzy set; obtain the target temperature difference range corresponding to the target temperature difference fuzzy set, determine the central point value of the target temperature difference range, and the standard deviation of the target temperature differences of multiple temperature differences in the target temperature difference range; calculate the membership degree of the target temperature difference based on the central point value of the target temperature difference range, the standard deviation of the target temperature difference, and the membership degree calculation formula of the target temperature difference.

[0025] The central point value of the target temperature difference range refers to the average value of all temperature differences belonging to the target temperature difference range. Calculate the square of the difference between every two temperature differences in the target temperature difference range, find the average value of these squared differences to obtain the variance, and take the square root of the variance to obtain the standard deviation of the target temperature difference. The standard deviation of the target temperature difference can measure the degree of dispersion of the temperature difference values around the mean value. Input the central point value of the target temperature difference range and the standard deviation of the target temperature difference into the membership degree calculation formula of the target temperature difference to calculate the membership degree of the target temperature difference.

[0026] Exemplarily, multiple temperature difference fuzzy sets of the present application may include a first temperature difference fuzzy set, a second temperature difference fuzzy set, a third temperature difference fuzzy set, a fourth temperature difference fuzzy set, and a fifth temperature difference fuzzy set, and the target temperature difference fuzzy set is at least one of the multiple temperature difference fuzzy sets.

[0027] The formula for calculating the membership degree of the target temperature difference set in the present application can be shown as follows: ; Where, μ represents the membership degree of the target temperature difference, X1 represents the target temperature difference belonging to the first temperature difference fuzzy set, Y1 represents the central point value of the first temperature difference range corresponding to the first temperature difference fuzzy set, Z1 represents the first temperature difference standard deviation of multiple temperature differences in the first temperature difference range; X2 represents the target temperature difference belonging to the second temperature difference fuzzy set, Y2 represents the central point value of the second temperature difference range corresponding to the second temperature difference fuzzy set, Z2 represents the second temperature difference standard deviation of multiple temperature differences in the second temperature difference range; X3 represents the target temperature difference belonging to the third temperature difference fuzzy set, Y3 represents the central point value of the third temperature difference range corresponding to the third temperature difference fuzzy set, Z3 represents the third temperature difference standard deviation of multiple temperature differences in the third temperature difference range; X4 represents the target temperature difference belonging to the fourth temperature difference fuzzy set, Y4 represents the central point value of the fourth temperature difference range corresponding to the fourth temperature difference fuzzy set, Z4 represents the fourth temperature difference standard deviation of multiple temperature differences in the fourth temperature difference range; X5 represents the target temperature difference belonging to the fifth temperature difference fuzzy set, Y5 represents the central point value of the fifth temperature difference range corresponding to the fifth temperature difference fuzzy set, Z5 represents the fifth temperature difference standard deviation of multiple temperature differences in the fifth temperature difference range.

[0028] Further, mapping the target processor utilization rate to the target processor utilization rate fuzzy set by using the Gaussian function, and determining the membership degree of the target processor utilization rate includes: obtaining multiple processor utilization rate fuzzy sets and the utilization rate ranges corresponding to the multiple processor utilization rate fuzzy sets; selecting the processor utilization rate fuzzy set corresponding to the utilization rate range matching the target processor utilization rate as the target processor utilization rate fuzzy set; obtaining the target utilization rate range corresponding to the target processor utilization rate fuzzy set, determining the central point value of the target utilization rate range, and the target utilization rate standard deviation of multiple utilization rates in the target utilization rate range; calculating the membership degree of the target processor utilization rate based on the central point value of the target utilization rate range, the target utilization rate standard deviation, and the formula for calculating the membership degree of the target utilization rate.

[0029] In this application, multiple processor utilization fuzzy sets are also preset in advance. Each processor utilization fuzzy set corresponds to a processor utilization range, and there may be an intersection in the temperature difference ranges of different processor utilization sets in this application. The central point value of the target utilization range refers to the average value of all utilizations belonging to the target utilization range. Calculate the square of the difference between every two utilizations in the target utilization range, find the average value of these squared differences to obtain the variance, and take the square root of the variance to obtain the target utilization standard deviation. The target utilization standard deviation can measure the degree of dispersion of utilization values around the mean. Input the central point value of the target utilization range and the target utilization standard deviation into the target utilization membership calculation formula to calculate the target processor utilization membership degree.

[0030] Exemplarily, the multiple processor utilization fuzzy sets of this application may include a first processor utilization fuzzy set, a second processor utilization fuzzy set, and a third processor utilization fuzzy set. The target processor utilization fuzzy set may be at least one of the multiple processor utilization fuzzy sets. The target utilization membership calculation formula set in this application may be as follows: ; Where, β represents the target processor utilization membership degree, A1 represents the target processor utilization belonging to the first processor utilization fuzzy set, B1 represents the central point value of the first utilization range corresponding to the first processor utilization fuzzy set, and C1 represents the first utilization standard deviation of multiple utilizations in the first utilization range; A2 represents the target processor utilization belonging to the second processor utilization fuzzy set, B2 represents the central point value of the second utilization range corresponding to the second processor utilization fuzzy set, and C2 represents the second utilization standard deviation of multiple utilizations in the second target processor utilization range; A3 represents the target processor utilization belonging to the third processor utilization fuzzy set, B3 represents the central point value of the third utilization range corresponding to the third processor utilization fuzzy set, and C3 represents the third utilization standard deviation of multiple utilizations in the third utilization range.

[0031] In this application, the target temperature difference and the target processor utilization are respectively mapped to the target temperature difference fuzzy set and the target processor utilization fuzzy set through the Gaussian function, which can analyze the potential attributes of the target temperature difference and the target processor utilization, and provide support for accurately adjusting the rotation speed of the fan corresponding to the target controller in the subsequent process.

[0032] After obtaining the target temperature difference membership degree and the target processor utilization rate membership degree through the above steps, the target value of the heat dissipation parameter combination can be determined based on the target temperature difference membership degree and the target processor utilization rate membership degree, which specifically includes: obtaining a pre-defined fuzzy rule table, where the pre-defined fuzzy rule table defines the initial heat dissipation parameter combinations corresponding to different temperature difference fuzzy sets and different processor utilization rate sets; selecting from the pre-defined fuzzy rule table the target initial heat dissipation parameter combination that matches the target temperature difference fuzzy set and matches the target processor utilization rate fuzzy set; using the target temperature difference membership degree and the target processor utilization rate membership degree as the weights of multiple heat dissipation parameters in the target heat dissipation parameter combination, and calculating the target values of multiple heat dissipation parameters in the heat dissipation parameter combination.

[0033] The heat dissipation parameters refer to parameters including the setpoint (temperature setpoint), alarm threshold (used to determine whether the temperature is too high and an alarm is needed), and PID parameters. The PID parameters specifically include: ki (integral parameter), kp (proportional parameter), kd (derivative parameter), and other heat dissipation-related parameters. The PID parameters can be used to adjust the fan speed. The proportional parameter kp determines the magnitude of the control action proportional to the current temperature error. If the current temperature is much higher than the setpoint, according to the value of kp, the fan speed will be increased significantly to lower the temperature. The integral parameter ki is used to consider the accumulation of past temperature errors and adjust the long-term temperature deviation. For example, if the temperature remains slightly higher than the setpoint, ki will gradually increase the control action to further adjust the fan speed. The derivative parameter kd is sensitive to the rate of change of temperature. If the temperature changes rapidly, kd will adjust the fan speed according to the rate of change to quickly respond to the temperature change and prevent the temperature from being too high or too low.

[0034] The pre-defined fuzzy rule table can exist in the form of a PID parameter reference value matrix. For example, different columns in the first row of the rule table represent different processor utilization rate fuzzy sets. Different rows in the first column of the rule table represent different temperature difference fuzzy sets, and the intersections of other columns and rows in the table represent the initial heat dissipation parameter combinations composed of the integral parameter and its initial value, the proportional parameter and its initial value, and the derivative parameter and its initial value under the temperature difference fuzzy set corresponding to the row and the processor utilization rate fuzzy set corresponding to the column. Therefore, through the pre-defined fuzzy rule table, the initial heat dissipation parameter combination that simultaneously considers both factors of processor utilization rate and temperature difference can be found.

[0035] Since the target temperature difference and the target processor utilization rate of the target processor in this application can respectively and simultaneously belong to different temperature difference fuzzy sets and different processor utilization rate fuzzy sets, in a specific implementation, the target temperature difference fuzzy set may include a first target temperature difference fuzzy set and a second target temperature difference fuzzy set; the target processor utilization rate fuzzy set may include a first target processor utilization rate fuzzy set and a second target processor utilization rate fuzzy set; in this case, using the target temperature difference membership degree and the target processor utilization rate membership degree as the weights of multiple heat dissipation parameters in the target heat dissipation parameter combination, calculating the target values of multiple heat dissipation parameters in the heat dissipation parameter combination may include: S1: Obtain the first target temperature difference membership degree corresponding to the target temperature difference belonging to the first target temperature difference fuzzy set and the second target temperature difference membership degree corresponding to the target temperature difference belonging to the second target temperature difference fuzzy set.

[0036] S2: Obtain the first target processor utilization rate membership degree corresponding to the target processor utilization rate belonging to the first target processor utilization rate fuzzy set and the second target processor utilization rate membership degree corresponding to the target processor utilization rate belonging to the second target processor utilization rate fuzzy set.

[0037] S3: Compare the first target temperature difference membership degree and the second target temperature difference membership degree. In response to the first target temperature difference membership degree being greater than the second target temperature difference membership degree, use the first target temperature difference membership degree as the main temperature difference weight and the second target temperature difference membership degree as the auxiliary temperature difference weight.

[0038] Here, by using the Gaussian function to simultaneously capture the characteristics of the target temperature difference in the first target temperature difference fuzzy set and the characteristics of the target temperature difference in the second target temperature difference fuzzy set, the characteristics of the target temperature difference in different temperature difference fuzzy sets can be perceived in a multi-modal manner, avoiding the control blind area caused by a single membership degree, and improving the temperature detection sensitivity. Take the target temperature difference membership degree with a larger membership degree value, that is, a larger proportion, as the main temperature difference weight. Conversely, take the target temperature difference membership degree with a smaller membership degree value, that is, a smaller proportion, as the auxiliary temperature difference weight, which can prioritize responding to the control requirements of the target temperature difference with a larger membership degree to promptly cope with sudden large-scale cooling requirements, and at the same time retain the auxiliary temperature difference weight to prevent overshoot.

[0039] S4: Set the first target processor utilization rate weight and the second target processor utilization rate weight respectively according to the influence of the first target processor utilization rate on processor heat dissipation and the influence of the second target processor utilization rate on processor heat dissipation, where the target processor utilization rate weight is proportional to the influence of the target processor utilization rate on processor heat dissipation.

[0040] Here, by using the Gaussian function to capture the characteristics of the target processor utilization rate in the first target processor utilization rate fuzzy set and the heat generation characteristics of the target processor utilization rate in the first target processor utilization rate fuzzy set, the control blind area caused by a single membership degree can be avoided, and the detection sensitivity of the processor utilization rate can be improved. The target processor utilization rate with a higher impact on processor heat dissipation, that is, a higher load, is set with a higher weight.

[0041] S5: Perform an addition operation on the product of the first target processor utilization rate weight and the first target processor utilization rate membership degree and the product of the second target processor utilization rate weight and the second target processor utilization rate membership degree to obtain the processor utilization rate rule weight.

[0042] By using a weighted method, a smooth transition of the load state can be achieved, the impact of instantaneous load fluctuations can be reduced, and the fan speed fluctuation can be decreased.

[0043] S6: Compare the main temperature difference weight and the processor utilization rate rule weight. In response to the main temperature difference weight being greater than the processor utilization rate rule weight, use the processor utilization rate rule weight as the main rule weight.

[0044] S7: Compare the auxiliary temperature difference weight and the processor utilization rate rule weight. In response to the processor utilization rate rule weight being greater than the auxiliary temperature difference weight, use the auxiliary temperature difference weight as the auxiliary rule weight.

[0045] Here, by comparing the main temperature difference weight and the auxiliary temperature difference weight with the processor utilization rate rule weight respectively, and selecting the smaller rule weight in the comparison process as the main rule weight and the auxiliary rule weight, it can be ensured that the regulation intensity does not exceed the credibility of any input condition.

[0046] S8: Sequentially select any type of heat dissipation parameter as the target heat dissipation parameter, and obtain the initial heat dissipation parameter value corresponding to the target heat dissipation parameter.

[0047] S9: Add the product of the main rule weight and the initial heat dissipation parameter value corresponding to the target heat dissipation parameter and the product of the auxiliary rule weight and the initial heat dissipation parameter value corresponding to the target heat dissipation parameter to obtain the target value corresponding to the target heat dissipation parameter.

[0048] Finally, through weighted synthesis of each heat dissipation parameter by the main rule weight and the auxiliary rule weight, the target value corresponding to the heat dissipation parameter is obtained. Combine the target values corresponding to each type of heat dissipation parameter, and finally obtain the target value corresponding to the target heat dissipation parameter.

[0049] For example, assume that the target initial heat dissipation parameter combination is L = [kp = 3.0, ki = 0.1, kd = 1.0], the calculated main rule weight is 0.6, and the calculated secondary rule weight is 0.5. Then the target value corresponding to the kp type heat dissipation parameter = initial kp value (3.0) * main rule weight 0.6 + initial kp value (3.0) * secondary rule weight (0.5) = 3.3. And so on, the target value of the finally obtained heat dissipation parameter combination is L(final) = [kp = 3.3, ki = 0.11, kd = 1.1].

[0050] In this application, the rotation speed of the fan is mainly adjusted by heat dissipation parameters such as proportional parameters, integral parameters, and differential parameters. In one embodiment, adjusting the rotation speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination includes: obtaining the proportional target value of the proportional parameter, the integral target value of the integral parameter, and the differential target value of the differential parameter; inputting the proportional target value, the integral target value, and the differential target value into the target value calculation formula of the heat dissipation parameter combination to obtain the target value of the heat dissipation parameter combination; converting the target value of the heat dissipation parameter combination into the duty cycle of the target pulse width modulation signal; obtaining the maximum rated rotation speed of the fan corresponding to the target processor, and calculating the target fan rotation speed according to the maximum rated rotation speed and the duty cycle of the target pulse width modulation signal; and adjusting the rotation speed of the fan corresponding to the target processor based on the target fan rotation speed.

[0051] Among them, the target value calculation formula of the heat dissipation parameter combination includes: ; The constraint condition is: ; Among them, u(t) is the target value of the heat dissipation parameter combination, λ is the performance gain coefficient of the target processor, k u is the utilization gain coefficient of the target processor, U(t) is the utilization of the target processor, kp is the proportional target value, ki is the integral target value, kd is the differential target value, e(t) is the target temperature difference, is the error change rate, P fan (u(t)) is the power of the fan corresponding to the target processor, P max is the maximum fan power, e max is the maximum temperature difference.

[0052] The target processor performance gain factor can be set according to the performance mode of the processor. The processor performance mode can include a high-performance mode, a normal mode, and a power-saving mode. The performance mode of the processor can be determined based on the power consumption level of the processor and the load size of the processor. The performance mode gain factor is proportional to the level of the performance mode. For example, in the high-performance mode, the target processor performance gain factor is higher, and in the power-saving mode, the target processor performance gain factor is lower. Thus, by differentiating different performance modes and setting gain factors for the target values of the heat dissipation parameter combinations, rapid response to heat dissipation can be achieved in the high-performance mode. The specific value of the target processor performance gain factor can be set based on actual experience. The target processor utilization gain factor is determined based on the magnitude of the target processor utilization. Generally, the larger the target processor utilization, the larger the target processor utilization gain factor. The specific value of the target processor utilization gain factor can be set based on actual experience.

[0053] In this application, by introducing the maximum temperature difference to constrain the target temperature difference, introducing the maximum fan power to constrain the power of the fan corresponding to the target processor, and simultaneously using the target processor performance gain factor and the target processor utilization gain factor, the size of the target value of the heat dissipation parameter combination is adjusted in real time according to the processor utilization and the processor performance scenario, thereby controlling the heat dissipation intensity of the fan, while limiting the fan power and the maximum temperature difference to avoid overheating or excessive power consumption of the fan.

[0054] The proportional target value, the integral target value, and the derivative target value are input into the calculation formula for the target value of the heat dissipation parameter combination to output the target value of the heat dissipation parameter combination, that is, the PID control value. The PID control value is converted into the duty cycle of the target pulse width modulation signal. The finally obtained target value of the heat dissipation parameter combination is a percentage. The finally obtained target value of the heat dissipation parameter combination is converted into a PWM value (pulse width modulation signal duty cycle) using an 8-bit register (0 - 255), obtaining a PWM value, specifically a number between 0 and 255. The relationship between the fan speed and the PWM is usually non-linear. The finally obtained target fan speed can be obtained by looking up the corresponding relationship between the fan speed and the PWM, or the maximum rated speed of the fan corresponding to the target processor can be used to calculate the product of the maximum rated speed and the duty cycle of the target pulse width modulation signal, thereby obtaining the target fan speed.

[0055] In practical applications, the server may form a mixed GPU configuration or skip insertion (less insertion) or the customer may modify the configuration by themselves. Due to the differences in power consumption, heat generation characteristics, etc. among different types of GPUs, this makes the heat dissipation management in a mixed insertion environment more complex. Therefore, in this application, the heat dissipation parameters of multiple target processors can be integrated, and the heat dissipation parameters of the target processor with the highest heat dissipation requirement can be selected as the heat dissipation standard for the entire system. The purpose of doing this is to ensure that all processors can be within a suitable working temperature range even under the most stringent heat dissipation requirements, thereby ensuring the stability and reliability of the system. For example, assume that there are two GPUs, A and B, in a GPU mixed insertion environment. The maximum allowable temperature of GPU A during high-load operation is 60 °C, and the warning temperature is 70 °C, while the thresholds for GPU B are 55 °C and 65 °C. At this time, the system will take the heat dissipation requirements of GPU B as the benchmark and formulate corresponding heat dissipation strategies to ensure that the GPU temperature will not exceed 65 °C and cause damage to the GPU under any circumstances.

[0056] In one embodiment, when the target value of the heat dissipation parameter combination is used as the heat dissipation requirement consideration standard, multiple target pulse width modulation signal duty cycles corresponding to multiple target processors can be obtained, and the target pulse width modulation signal duty cycle with the largest value can be selected from the multiple target pulse width modulation signal duty cycles as the reference target pulse width modulation signal duty cycle; based on the reference target pulse width modulation signal duty cycle and the maximum rated speed, the target fan speed is calculated, and the speeds of multiple fans corresponding to multiple target processors are adjusted based on the target fan speed.

[0057] This application controls the PID speed regulation of the fan based on the heat dissipation parameters of the GPU with the highest heat dissipation requirement determined by speed regulation according to heat dissipation parameters, especially parameters such as the setpoint, ki, kp, kd, etc. Continuously monitor the temperature of the GPU, and dynamically adjust the fan speed according to the target temperature difference corresponding to the target processor, combined with heat dissipation parameters such as ki, kp, kd, etc., to ensure that the GPU operates within a suitable temperature range. At the same time, always pay attention to the warning threshold, and once the temperature exceeds the warning threshold, promptly send a warning message.

[0058] In one embodiment, the heat dissipation method further includes: S10: Obtain the key parameters of the target processor and the initial physical address of the target processor, and determine whether the target processor has been replaced based on the key parameters of the target processor and the initial physical address.

[0059] Specifically, the processor into which the current initial physical address is inserted is used as the verification processor; obtain the key parameters of the verification processor and the key parameters of the target processor, where the key parameters include the processor manufacturer ID, processor ID, processor sub - manufacturer ID, and sub - processor ID; determine whether the key parameters of the verification processor are consistent with the key parameters of the target processor; in response to the key parameters of the verification processor being consistent with the key parameters of the target processor, determine that the target processor has not been replaced; in response to the key parameters of the verification processor being inconsistent with the key parameters of the target processor, determine that the target processor has been replaced.

[0060] In the actual use process, the replacement of the GPU is inevitable. In this application, the baseboard management controller (BMC) is used to interact with the GPU to read the key parameters such as the GPU's vender ID (processor manufacturer ID), device ID (processor ID), sub vender ID (processor sub - manufacturer ID), and sub device ID (sub - processor ID) in real - time. By analyzing these parameters, the model of the currently connected GPU and whether the GPU has been replaced can be accurately judged.

[0061] S20: In response to the target processor having been replaced, determine the type of the replacement processor inserted at the current initial physical address.

[0062] Specifically, determine the access link of the replacement processor based on the current initial physical address; obtain the correspondence between the preset processor protocol address and the processor type; sequentially select any processor protocol address from the correspondence between the preset processor protocol address and the processor type as the replacement processor protocol address; access the replacement processor through the replacement processor access link and the replacement processor protocol address, and obtain the access status of the replacement processor; in response to the access status of the replacement processor being access successful, use the processor type matching the replacement processor protocol address as the type of the replacement processor.

[0063] If it is determined that the target processor originally inserted at the initial physical address has been replaced, at this time, it is necessary to first determine which type of processor the replacement processor is. Given the current initial physical address, the access link to the replacement processor inserted at the current processing physical address can be determined according to the initial physical address.

[0064] Please refer to Figure 2, in this application, the I2C interface of the BMC is connected to the I2C switch (expander) on the motherboard. After the BMC is powered on, it first initializes and configures the I2C interface, setting parameters such as appropriate communication rates and data formats to ensure its normal communication with the I2C switch on the motherboard. The reason for choosing the I2C switch is that it can implement the expansion function of the I2C bus, enabling the BMC I2C to connect more devices. This connection method constructs the basic physical link for data transmission in the entire system, ensuring that the BMC can communicate with the subsequently attached devices. Different channels (multiple Channels shown in the figure) of the I2C switch on the motherboard are respectively connected to each GPU. Each GPU backplane serves as an independent branch, obtaining I2C communication capabilities from the motherboard I2C switch. This design enables the system to flexibly manage multiple GPUs and, when the number of GPUs needs to be expanded, new GPU connections can be added conveniently.

[0065] The BMC (Baseboard Management Controller) baseboard controller is a management controller designed specifically for servers and other hardware devices. It is part of the Intelligent Platform Management Interface (IPMI), allowing system administrators to monitor and control the hardware status of the server through an independent management network. The BMC is usually integrated on the server motherboard, has its own processor, memory, and storage space, and runs an independent management software system. In a server environment, the BMC (Baseboard Management Controller) plays a key role in effectively monitoring the operating status of GPUs.

[0066] I2C (Inter-Integrated Circuit) is a two-wire bidirectional serial bus standard used to connect microcontrollers to other integrated circuits (ICs) on the same circuit board.

[0067] In this application, the BMC accesses the I2C (Inter-Integrated Circuit) bus system sequentially according to the pre-set hardware link logic. During this process, special attention should be paid to the riser card under I2C because an I2C switch is integrated on the riser card, and this switch is responsible for managing multiple channels. The BMC will sequentially traverse each channel, aiming to establish communication with the GPU devices connected to the I2C link through these channels. During the access process of each I2C link, the BMC needs to determine the type of the connected GPU. For this purpose, the BMC will utilize the addresses and access protocols of multiple types of GPUs that have been pre-adapted. These protocols are specifically customized for different types of GPUs (such as type A, type B, type C, etc.). The BMC will attempt to access each possible combination of address and protocol. Specifically, it will start from the first address and sequentially send request signals to the device according to the protocols of various types of GPUs. If, under a certain I2C link, communication can be successfully established with the device according to the type A GPU protocol and the response signal of the device is received, then the BMC can determine that the GPU inserted under this link is a type A GPU.

[0068] In a feasible implementation manner, the GPU protocol addresses of two manufacturers may conflict. At this time, an error may occur in judging whether the GPU is present. When the protocol addresses conflict, key parameters such as the vender ID (processor manufacturer ID), device ID (processor ID), sub vender ID (processor sub-manufacturer ID), and sub device ID (sub-processor ID) of the GPU can be obtained according to the protocol addresses to distinguish GPUs of different manufacturers. In this way, the type of the GPU can be identified more accurately.

[0069] In this application, the GPU adaptation conf file can be loaded into the memory to facilitate subsequent rapid search for relevant information of GPUs from different manufacturers. The GPU-related information here can include the temperature storage location and calculation method. The temperature storage location here refers to different register addresses. Each GPU has a different location for reading temperature or power, so the temperature storage location corresponding to the GPU needs to be recorded to facilitate rapid search for relevant information of the GPU. According to the instructions in the adaptation file, a command to obtain temperature information is sent to the GPU, the original temperature data is read, and it is converted into the actual temperature value according to the calculation method. For the basic information of the GPU, such as key parameter information like the vender ID, etc., and the physical location information are written into the assert.json file (a kind of transfer file) for subsequent acquisition.

[0070] The BMC of this application supports importing and exporting the scattered conf file through the Redfish interface and the web. By exporting this file, the administrator can conveniently modify the heat dissipation parameters in the external environment. These parameters cover key information such as the fan speed adjustment strategy and the temperature threshold setting to adapt to different hardware configurations and heat dissipation requirements. The modified parameters can be easily imported into the BMC through the web interface. Once the import is successful, the BMC will adjust the heat dissipation strategy power of the system according to the new heat dissipation parameters. This method greatly improves the flexibility and convenience of heat dissipation management. Without entering the complex underlying system settings, the administrator can quickly respond to hardware changes or optimize the heat dissipation effect.

[0071] S30: Determine the expected temperature of the replaced processor based on the type of the replaced processor.

[0072] S40: Adjust the speed of the fan corresponding to the replaced processor based on the expected temperature of the replaced processor.

[0073] Once the BMC determines the type of GPU under the access link, for example, after identifying it as GPU type A, it will register the device type information of this type A GPU into a dedicated GPU monitoring thread. This monitoring thread plays a role in continuously monitoring the running status of the GPU in the entire server system. Subsequently, this monitoring thread will regularly send requests to the GPU to obtain information according to the protocol corresponding to type A GPU. For example, obtain the temperature information of the GPU through this protocol to determine whether the GPU is operating within the normal temperature range, and also obtain key information such as the usage rate and power consumption of the GPU, so as to achieve all-round and real-time monitoring of the running status of the GPU and ensure the stable operation of the GPU in the server system. Set relevant energy-saving strategy parameters such as the proportion of the fan speed reduction when the GPU is not in place in the heat dissipation conf file configuration of the BMC. The system administrator can adjust these parameters according to actual needs. For example, in some environments with high heat dissipation requirements, the proportion of the fan speed reduction can be appropriately reduced.

[0074] In a specific example, the BMC continuously monitors the system hardware status, including detecting the presence of the GPU. In the motherboard design, the GPU slot has specific pins for feeding back its presence information to the BMC. When the GPU is properly inserted into the slot, these pins form a specific electrical signal connection, and the BMC can recognize this signal to confirm the presence of the GPU. When the GPU is not present, the pin connection status changes, and the BMC detects the signal change, thus determining that the GPU is not present. Once the BMC detects that the GPU is not present, it will perform corresponding operations according to the pre-set energy-saving strategy. Since the GPU is a high-heat-generating component in the system, when it is not present, the heat dissipation requirement at the corresponding position is greatly reduced. Therefore, the BMC sends an instruction to the circuit controlling the fan speed, and the fan control circuit controls the fan speed through a PWM (Pulse Width Modulation) signal to reduce the fan speed at this position, thereby reducing the power consumption of the fan motor and achieving the purpose of energy saving.

[0075] Write a GPU presence detection program in the BMC firmware. This program periodically reads the status of the pins for detecting the presence of the GPU in the slot. It reads the pin level status every 3 seconds. If the pin level indicating that the GPU is not present is detected continuously for multiple times (3 times), it confirms the status that the GPU is not present. When the BMC detects that the GPU is not present, the program calculates the PWM signal parameters corresponding to the new fan speed according to the pre-set energy-saving strategy. It is preset that when the GPU is not present, the fan speed is reduced by 50%. Then the program calculates the PWM duty cycle corresponding to 50% speed and sends this PWM signal to the fan control circuit.

[0076] In one embodiment, if the processor inserted at the initial physical address at the current sampling moment is a replacement processor, and the processor inserted at the initial physical address at the previous sampling moment is the target processor to be replaced, determine the expected temperature of the replacement processor based on the type of the replacement processor; adjusting the speed of the fan corresponding to the replacement processor based on the expected temperature of the replacement processor includes: S100: Obtain the proportional target value, integral target value, derivative target value, and target pulse width modulation signal duty cycle corresponding to the target processor to be replaced at the previous sampling moment from the system file.

[0077] S110: Collect the temperature of the replacement processor at the current sampling moment and the temperature of the target processor to be replaced at the previous sampling moment. Use the temperature of the replacement processor at the current sampling moment as the minuend and the temperature of the target processor to be replaced at the previous sampling moment as the subtrahend for subtraction operation to obtain the first temperature change amount.

[0078] S120: Multiply the first temperature change amount by the proportional target value corresponding to the target processor to be replaced at the previous sampling moment to obtain the proportional change amount.

[0079] Exemplarily, kp_part (proportional change) = the proportional target value corresponding to the target processor replaced at the previous sampling moment * (the temperature of the replaced processor at the current sampling moment - the temperature of the target processor replaced at the previous sampling moment). The proportional adjustment part is calculated by combining the difference between the temperature of the replaced processor at the current sampling moment and the temperature of the target processor replaced at the previous sampling moment with the proportional target value corresponding to the target processor replaced at the previous sampling moment.

[0080] S130: Obtain the expected temperature of the replaced processor. Use the temperature of the replaced processor at the current sampling moment as the minuend and the expected temperature of the replaced processor as the subtrahend for subtraction operation to obtain the second temperature change.

[0081] S140: Multiply the second temperature change by the integral target value corresponding to the target processor replaced at the previous sampling moment to obtain the integral change.

[0082] ki_part (integral change) = the integral target value corresponding to the target processor replaced at the previous sampling moment * (the temperature of the replaced processor at the current sampling moment - the expected temperature of the replaced processor). The integral adjustment part is calculated by combining the deviation between the temperature of the replaced processor at the current sampling moment and the expected temperature of the replaced processor with the integral target value corresponding to the target processor replaced at the previous sampling moment, and is used to eliminate the static error.

[0083] S150: Collect the temperature of the target processor replaced at the previous sampling moment before the previous sampling moment (the previous sampling moment of the previous sampling moment). Use the sum of the temperature of the replaced processor at the current sampling moment and the temperature of the target processor replaced at the previous sampling moment before the previous sampling moment as the minuend and twice the temperature of the target processor replaced at the previous sampling moment as the subtrahend for subtraction operation to obtain the third temperature change.

[0084] S160: Multiply the third temperature change by the differential target value corresponding to the target processor replaced at the previous sampling moment to obtain the differential change.

[0085] Exemplarily, kd_part (differential change) = the proportional target value corresponding to the replaced target processor * (the temperature of the replaced processor at the current sampling moment - 2 * the temperature of the target processor replaced at the previous sampling moment + the temperature of the target processor replaced at the previous sampling moment before the previous sampling moment). The differential adjustment part is calculated based on the temperature changes at the current, previous, and previous sampling moments before the previous sampling moment, and combines the proportional target value corresponding to the replaced target processor to reflect the rate of temperature change.

[0086] S170: Calculate the sum of the duty cycle, proportional change amount, integral change amount, and differential change amount of the target pulse width modulation signal corresponding to the target processor replaced at the previous sampling moment, to obtain the duty cycle of the target pulse width modulation signal corresponding to the replaced processor.

[0087] S180: Adjust the rotational speed of the fan corresponding to the replaced processor based on the duty cycle of the target pulse width modulation signal corresponding to the replaced processor.

[0088] Finally, combine the sum of the duty cycle, proportional change amount, integral change amount, and differential change amount of the target pulse width modulation signal corresponding to the target processor replaced at the previous sampling moment, to obtain the current PWM output for control. In this way, precise dynamic adjustment of the rotational speed of the fan corresponding to the processor can be achieved.

[0089] In one embodiment, in response to obtaining a heat dissipation update instruction or when the system is in the startup phase, obtain the current system environment temperature; search for the duty cycle of the pulse width modulation signal that matches the current system environment temperature from the preset correspondence between the system environment temperature and the duty cycle of the pulse width modulation signal; and adjust the rotational speed of the fan corresponding to the target processor based on the duty cycle of the pulse width modulation signal that matches the current system environment temperature.

[0090] This application takes into account that in some special cases, such as when the heat dissipation process restarts or the BMC is not fully started, additional safeguard mechanisms are required for the system's heat dissipation control. For this reason, RTOS (Real-Time Operating System) is introduced to assist in heat dissipation control. RTOS has the capabilities of fast response and precise control, and it can read the inlet temperature (system environment temperature) in real time. Based on this temperature data, RTOS can directly control the rotational speed of the fan, ensuring that the system can still maintain the basic heat dissipation function when the BMC cannot function properly. For example, in the initial stage of system startup, the BMC takes a certain amount of time to complete initialization and load various driver programs. During this period, RTOS monitors the inlet temperature and adjusts the rotational speed of the fan to prevent the GPU from overheating due to insufficient heat dissipation. Similarly, when the heat dissipation process restarts due to certain reasons, RTOS can continue to provide stable heat dissipation support during the transition stage until the BMC takes over the heat dissipation control again.

[0091] When the GPU is plugged in or out or replaced, the file named assert.json will change. The BMC can determine whether the GPU has been replaced by comparing the differences in the file before and after the GPU is plugged in or out or replaced. If the BMC detects that the GPU has been replaced, it will recalculate the required cooling parameters according to the new situation and restart the cooling process. The significance of this operation is to ensure that the cooling is always in the optimal state without affecting the customer's business. Within two seconds after the cooling process is restarted, the Real-Time Operating System (RTOS) will take over the cooling work. The RTOS will adjust the fan speed according to the server inlet temperature to ensure that the cooling can proceed normally. In this way, the cooling can be ensured to be always in the optimal state without affecting the business.

[0092] Step 103: In response to the target processor power consumption mode being the low power consumption mode, obtain the first value of the current temperature setpoint of the target processor and the second value of the desired temperature setpoint of the target processor, and adjust the air direction of the fan corresponding to the target processor based on the first value and the second value.

[0093] Specifically, adjusting the air direction of the fan corresponding to the target processor based on the first value and the second value includes: performing a subtraction operation with the second value as the minuend and the first value as the subtrahend to obtain the temperature difference of the temperature setpoint; calculating the target proportion of the temperature difference of the temperature setpoint to the second value; multiplying the target proportion by the maximum air direction adjustment angle to obtain the target adjustment direction of the fan corresponding to the target processor; and adjusting the angle of the fan board of the fan corresponding to the target processor based on the target adjustment direction.

[0094] The current temperature setpoint of the target processor here refers to the current setpoint of the target processor. The desired temperature setpoint of the target processor here refers to the setpoint that the target processor needs to reach. Assume that the first value of the current temperature setpoint is 70 degrees and the second value of the desired temperature setpoint of the target processor is 80 degrees. At this time, the target adjustment direction angle of the fan corresponding to the target processor should be (80 - 70) divided by 80, and then multiplied by 90 degrees (multiplied by the maximum air direction adjustment angle). The target adjustment direction angle here refers to adjusting the angle of the fan board corresponding to each fan, so as to adjust the air direction of the fan.

[0095] In one embodiment, adjusting the wind direction of the fan corresponding to the target processor includes: determining the physical positions of multiple processors to be adjusted in the system whose wind directions are to be adjusted; obtaining the heat dissipation requirements of the multiple processors to be adjusted, where the heat dissipation requirement is the difference between the current temperature and the desired temperature of the processor to be adjusted; grouping the multiple processors to be adjusted based on the heat dissipation requirements and physical positions of the multiple processors to be adjusted to obtain at least one heat concentration area group; adjusting the wind directions of the fans corresponding to the processors to be adjusted in the heat concentration area group and the wind directions of the fans corresponding to the processors to be adjusted adjacent to the heat concentration area group to achieve heat dissipation for the processors to be adjusted in the heat concentration area group.

[0096] The multiple processors to be adjusted refer to the processors whose wind directions are about to be adjusted. Obtain the physical positions of the multiple processors to be adjusted, and add the processors to be adjusted with high heat dissipation requirements and close physical positions to the heat concentration area group. Priority is given to adjusting the wind direction in the high-temperature area or the area with high heat dissipation requirements. In addition to adjusting the wind direction of the fan corresponding to the processor to be adjusted in the heat concentration area group, the wind direction of the fan corresponding to the processor to be adjusted adjacent to the heat concentration area group can also be made to face the heat concentration area group. In this way, the wind direction adjustment resources can be concentrated to preferentially process the areas with high requirements, and local processor heat dissipation can be optimized while considering energy consumption.

[0097] In one embodiment, for the fan board of the fan corresponding to the processor to be adjusted in the heat concentration area group, its expansion can also be set to form an independent air duct to force cold air to pass through the heat dissipation fins intensively. The fan board of the fan corresponding to the processor to be adjusted in the non-heat concentration area group can be kept close to the upper cover of the chassis to avoid excessive flow disturbance causing wind pressure loss. In this way, in the case of mixed insertion of different types of GPUs, local heat dissipation can be carried out as needed for the processors to be adjusted with high heat dissipation requirements and close physical positions. Separately setting the fan board corresponding to the GPU can also achieve isolation of the CPU / GPU air duct. At the same time, each fan board is smaller in volume and can be compatible with 1U / 2U server chassis.

[0098] In one embodiment, the processor heat dissipation method provided in this application is applied to a processor heat dissipation system. The processor heat dissipation system is as Figure 3As shown in the figure, it includes a server chassis, multiple processors, a baseboard management controller (BMC), multiple fans, and multiple fan boards. Each processor corresponds to a fan, and each fan has a fan board. The fan board is attached to the upper cover of the server chassis. All fan boards can be connected to the BMC through a control bus (such as I2C / PWM). The BMC dynamically adjusts the angle of the heat dissipation baffle of each fan board, and thus adjusts the wind direction of the fan corresponding to the processor. The fan board can adopt a hinge-type blade design. In the default state, it adheres to the upper cover of the chassis (reducing wind resistance). In one embodiment, when triggering the adjustment of the turning direction of the fan board, a micro stepping motor can be unfolded at a specific angle (adjustable from 30° to 90°) to form a physical air guide plate.

[0099] An embodiment of the present application provides a heat dissipation device for a processor. The heat dissipation device for the processor is specifically as Figure 4 shown. The heat dissipation device for the processor includes: an acquisition module 20 and an adjustment module 21.

[0100] The acquisition module 20 is configured to acquire the power consumption mode of the target processor.

[0101] The adjustment module 21 is configured to, in response to the power consumption mode of the target processor being the high power consumption mode, acquire the target temperature difference and the utilization rate of the target processor. The target temperature difference is the difference between the actual temperature of the target processor and the desired temperature of the target processor; map the target temperature difference to the target temperature difference fuzzy set by using the Gaussian function to determine the membership degree of the target temperature difference; map the utilization rate of the target processor to the target processor utilization rate fuzzy set by using the Gaussian function to determine the membership degree of the target processor utilization rate; determine the target value of the heat dissipation parameter combination based on the membership degree of the target temperature difference and the membership degree of the target processor utilization rate; adjust the rotational speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination; in response to the power consumption mode of the target processor being the low power consumption mode, acquire the first value of the current temperature set point of the target processor and the second value of the desired temperature set point of the target processor, and adjust the wind direction of the fan corresponding to the target processor based on the first value and the second value.

[0102] As Figure 5 shown, an embodiment of the present application further provides a computer device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above embodiments of the heat dissipation method for the processor.

[0103] An embodiment of the present application further provides a computer-readable storage medium. A computer program is stored in the computer-readable storage medium. The computer program is configured to execute the steps in any one of the above embodiments of the heat dissipation method for the processor when running.

[0104] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to: various media such as USB flash drives, read-only memory (ROM), random access memory (RAM), external hard drives, magnetic disks, or optical discs that can store computer programs.

[0105] Those skilled in the art can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Skilled professionals can use different methods to implement the described functions for each specific application, but such implementation should not be determined to exceed the scope of this application.

[0106] The above has introduced in detail a heat dissipation method for a processor provided in this application. Specific examples have been used herein to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method of this application and its core idea. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and modifications can be made to this application, and these improvements and modifications also fall within the protection scope of this application.

Claims

1. A heat dissipation method for a processor, characterized in that: The heat dissipation method comprises: Get the target processor power consumption mode; In response to a target processor power consumption mode being a high power consumption mode, a target temperature difference and a target processor utilization are obtained, wherein the target temperature difference is a difference between an actual temperature of the target processor and an expected temperature of the target processor; the target temperature difference is mapped to a target temperature difference fuzzy set using a Gaussian function to determine a target temperature difference membership; the target processor utilization is mapped to a target processor utilization fuzzy set using a Gaussian function to determine a target processor utilization membership; a target value of a heat dissipation parameter combination is determined based on the target temperature difference membership and the target processor utilization membership; and a speed of a fan corresponding to the target processor is adjusted based on the target value of the heat dissipation parameter combination; In response to the target processor power consumption mode being the low power consumption mode, a first value of the target processor current temperature setting point and a second value of the target processor desired temperature setting point are obtained, and the wind direction of the fan corresponding to the target processor is adjusted based on the first value and the second value.

2. The heat dissipation method for a processor according to claim 1, wherein: Mapping the target temperature difference to the target temperature difference fuzzy set using a Gaussian function and determining the target temperature difference membership comprises: Obtain multiple temperature difference fuzzy sets and temperature difference ranges corresponding to the multiple temperature difference fuzzy sets; Select the temperature difference fuzzy set corresponding to the temperature difference range matching the target temperature difference as the target temperature difference fuzzy set; Obtaining a target temperature difference range corresponding to the target temperature difference fuzzy set, determining a center point value of the target temperature difference range, and target temperature difference standard deviations of multiple temperature differences in the target temperature difference range; The target temperature difference membership is calculated based on the center point value of the target temperature difference range, the target temperature difference standard deviation, and a target temperature difference membership calculation formula.

3. The heat dissipation method for a processor according to claim 2, wherein: The target temperature difference fuzzy set includes at least one of the first temperature difference fuzzy set, the second temperature difference fuzzy set, the third temperature difference fuzzy set, the fourth temperature difference fuzzy set, and the fifth temperature difference fuzzy set. The target temperature difference membership calculation formula include: ； Wherein, μ represents the target temperature difference membership, X1 represents the target temperature difference belonging to the first temperature difference fuzzy set, Y1 represents the center point value of the first temperature difference range corresponding to the first temperature difference fuzzy set, and Z1 represents the first temperature difference standard deviation of multiple temperature differences in the first temperature difference range; X2 represents the target temperature difference belonging to the second temperature difference fuzzy set, Y2 represents the center point value of the second temperature difference range corresponding to the second temperature difference fuzzy set, and Z2 represents the second temperature difference standard deviation of multiple temperature differences in the second temperature difference range; X3 represents the target temperature difference belonging to the third temperature difference fuzzy set, Y3 represents the center point value of the third temperature difference range corresponding to the third temperature difference fuzzy set, and Z3 represents the third temperature difference standard deviation of the multiple temperature differences in the third temperature difference range; X4 represents the target temperature difference belonging to the fourth temperature difference fuzzy set, Y4 represents the center point value of the fourth temperature difference range corresponding to the fourth temperature difference fuzzy set, and Z4 represents the fourth temperature difference standard deviation of the multiple temperature differences in the fourth temperature difference range; X5 represents the target temperature difference belonging to the fifth temperature difference fuzzy set, Y5 represents the center point value of the fifth temperature difference range corresponding to the fifth temperature difference fuzzy set, and Z5 represents the fifth temperature difference standard deviation of multiple temperature differences in the fifth temperature difference range.

4. The heat dissipation method for a processor according to claim 1, wherein: Mapping the target processor utilization to the target processor utilization fuzzy set by using a Gaussian function and determining the target processor utilization membership comprises: Obtaining multiple processor utilization fuzzy sets and utilization ranges corresponding to the multiple processor utilization fuzzy sets; Selecting a processor utilization fuzzy set corresponding to a utilization range matching the target processor utilization as the target processor utilization fuzzy set; Obtaining a target utilization range corresponding to the target processor utilization fuzzy set, determining a center point value of the target utilization range, and target utilization standard deviations of multiple utilizations in the target utilization range; The target processor utilization membership is calculated based on the center point value of the target utilization range, the target utilization standard deviation, and a target utilization membership calculation formula.

5. The heat dissipation method for a processor according to claim 4, wherein: The target processor utilization fuzzy set is at least one of the first processor utilization fuzzy set, the second processor utilization fuzzy set, and the third processor utilization fuzzy set. The target utilization membership calculation formula is: include: ； in, β represents the target processor utilization membership, A1 represents the target processor utilization belonging to the first processor utilization fuzzy set, B1 represents the center point value of the first utilization range corresponding to the first processor utilization fuzzy set, and C1 represents the first utilization standard deviation of multiple utilizations in the first utilization range; A2 represents the target processor utilization that belongs to the second processor utilization fuzzy set, B2 represents the center point value of the second utilization range corresponding to the second processor utilization fuzzy set, and C2 represents the second utilization standard deviation of multiple utilizations in the second target processor utilization range; A3 represents the target processor utilization belonging to the third processor utilization fuzzy set, B3 represents the center point value of the third utilization range corresponding to the third processor utilization fuzzy set, and C3 represents the third utilization standard deviation of multiple utilizations in the third utilization range.

6. The heat dissipation method for a processor according to claim 1, wherein: Determining the target value of the heat dissipation parameter combination based on the target temperature difference membership and the target processor utilization membership includes: Obtaining a predefined fuzzy rule table, wherein the predefined fuzzy rule table defines initial heat dissipation parameter combinations corresponding to different temperature difference fuzzy sets and different processor utilization sets; Selecting a target initial cooling parameter combination that matches the target temperature difference fuzzy set and the target processor utilization fuzzy set from a predefined fuzzy rule table; The target temperature difference membership and the target processor utilization membership are used as weights of multiple heat dissipation parameters in the target heat dissipation parameter combination, and target values of the multiple heat dissipation parameters in the heat dissipation parameter combination are calculated.

7. The heat dissipation method for a processor according to claim 6, wherein: The target temperature difference fuzzy set includes a first target temperature difference fuzzy set and a second target temperature difference fuzzy set; the target processor utilization fuzzy set includes a first target processor utilization fuzzy set and a second target processor utilization fuzzy set; The step of calculating target values of the plurality of heat dissipation parameters in the heat dissipation parameter combination by using the target temperature difference membership and the target processor utilization membership as weights of the plurality of heat dissipation parameters in the target heat dissipation parameter combination includes: Obtaining a first target temperature difference membership corresponding to a target temperature difference belonging to the first target temperature difference fuzzy set and a second target temperature difference membership corresponding to a target temperature difference belonging to the second target temperature difference fuzzy set; Obtaining a first target processor utilization membership corresponding to a target processor utilization belonging to a first target processor utilization fuzzy set and a second target processor utilization membership corresponding to a target processor utilization belonging to a second target processor utilization fuzzy set; comparing a first target temperature difference membership and a second target temperature difference membership, and in response to the first target temperature difference membership being greater than the second target temperature difference membership, using the first target temperature difference membership as a primary temperature difference weight and using the second target temperature difference membership as a secondary temperature difference weight; According to the influence of the first target processor utilization on the processor heat dissipation and the influence of the second target processor utilization on the processor heat dissipation, respectively setting a first target processor utilization weight and a second target processor utilization weight, wherein the target processor utilization weight is proportional to the influence of the target processor utilization on the processor heat dissipation; Adding the product of the first target processor utilization weight and the first target processor utilization membership and the product of the second target processor utilization weight and the second target processor utilization membership to obtain a processor utilization rule weight; comparing the main temperature difference weight and the processor utilization rule weight, and in response to the main temperature difference weight being greater than the processor utilization rule weight, using the processor utilization rule weight as the main rule weight; comparing the auxiliary temperature difference weight and the processor utilization rule weight, and in response to the processor utilization rule weight being greater than the auxiliary temperature difference weight, using the auxiliary temperature difference weight as the auxiliary rule weight; Selecting any type of heat dissipation parameter in turn as a target heat dissipation parameter, and obtaining an initial heat dissipation parameter value corresponding to the target heat dissipation parameter; The product of the main rule weight and the initial heat dissipation parameter value corresponding to the target heat dissipation parameter and the product of the auxiliary rule weight and the initial heat dissipation parameter value corresponding to the target heat dissipation parameter are added together to obtain a target value corresponding to the target heat dissipation parameter.

8. The heat dissipation method for a processor according to claim 1, wherein: The heat dissipation parameter combination includes a plurality of heat dissipation parameters, wherein the plurality of heat dissipation parameters include a proportional parameter, an integral parameter, and a differential parameter. Adjusting the rotation speed of the fan corresponding to the target processor based on the target value of the heat dissipation parameter combination includes: Obtaining the proportional target value of the proportional parameter, the integral target value of the integral parameter, and the differential target value of the differential parameter; Inputting the proportional target value, the integral target value, and the differential target value into a target value calculation formula of a heat dissipation parameter combination to obtain a target value of the heat dissipation parameter combination; Converting the target value of the heat dissipation parameter combination into a target pulse width modulation signal duty cycle; Obtaining a maximum rated speed of a fan corresponding to a target processor, and calculating a target fan speed based on the maximum rated speed and a target pulse width modulation signal duty cycle; The rotation speed of the fan corresponding to the target processor is adjusted based on the target fan rotation speed.

9. The heat dissipation method for a processor according to claim 8, wherein: The target value calculation formula of the heat dissipation parameter combination includes: ； The constraints are: ； Where u(t) is the target value of the heat dissipation parameter combination, λ is the target processor performance gain coefficient, and k u is the target processor utilization gain coefficient, U(t) is the target processor utilization, kp is the proportional target value, ki is the integral target value, kd is the differential target value, e(t) is the target temperature difference, is the error change rate, P fan (u(t)) is the power of the fan corresponding to the target processor, P max is the maximum power of the fan, e max is the maximum temperature difference.

10. The heat dissipation method for a processor according to claim 8, wherein: There are multiple target processors, and obtaining the maximum rated speed of the fan corresponding to the target processor, and calculating the target fan speed according to the maximum rated speed and the target pulse width modulation signal duty cycle further includes: Acquire multiple target pulse width modulation signal duty cycles corresponding to multiple target processors, and select a target pulse width modulation signal duty cycle with the largest value from the multiple target pulse width modulation signal duty cycles as a reference target pulse width modulation signal duty cycle; A target fan speed is calculated based on the reference target pulse width modulation signal duty cycle and the maximum rated speed, and the speeds of multiple fans corresponding to multiple target processors are adjusted based on the target fan speed.

11. The heat dissipation method for a processor according to claim 1, wherein: The heat dissipation method further includes: Acquiring key parameters of a target processor and an initial physical address of the target processor, and determining whether the target processor has been replaced based on the key parameters of the target processor and the initial physical address; In response to the target processor having undergone a replacement operation, determining a type of replacement processor inserted at the current initial physical address; determining a replacement processor expected temperature for the replacement processor based on the replacement processor type; The rotation speed of the fan corresponding to the replaced processor is adjusted based on the expected temperature of the replaced processor.

12. The heat dissipation method for a processor according to claim 11, wherein: The acquiring key parameters of the target processor and the initial physical address of the target processor, and determining whether the target processor has been replaced based on the key parameters of the target processor and the initial physical address includes: The processor at the current initial physical address is inserted as a check processor; Obtain key parameters of the verification processor and the target processor, wherein the key parameters include processor manufacturer ID, processor ID, processor sub-manufacturer ID, and sub-processor ID; Determining whether the verification processor key parameters are consistent with the target processor key parameters; In response to the verification processor key parameter being consistent with the target processor key parameter, determining that the target processor has not been replaced; In response to the verification processor key parameter being inconsistent with the target processor key parameter, it is determined that the target processor has been replaced.

13. The heat dissipation method for a processor according to claim 11, wherein: Determining the replacement processor type inserted at the current initial physical address includes: determining a replacement processor access link based on the current initial physical address; Obtain the correspondence between the preset processor protocol address and the processor type; Selecting any processor protocol address from the preset correspondence between the processor protocol address and the processor type in sequence as the replacement processor protocol address; Accessing the replacement processor via the replacement processor access link and the replacement processor protocol address, Get the replacement processor access status; In response to the replacement processor access status being access success, a processor type matching the replacement processor protocol address is used as the type of the replacement processor.

14. The heat dissipation method for a processor according to claim 11, wherein: If the processor initially physically inserted at the current sampling moment is a replacement processor and the processor initially physically inserted at the previous sampling moment is a target processor to be replaced, determining the replacement processor expected temperature of the replacement processor based on the type of the replacement processor; Adjusting the rotation speed of the fan corresponding to the replacement processor based on the expected temperature of the replacement processor includes: Obtain from the system file the proportional target value, integral target value, differential target value, and target pulse width modulation signal duty cycle corresponding to the target processor replaced at the previous sampling moment; collecting the temperature of the processor being replaced at the current sampling moment and the temperature of the target processor being replaced at the previous sampling moment, performing a subtraction operation using the temperature of the processor being replaced at the current sampling moment as a minuend and the temperature of the target processor being replaced at the previous sampling moment as a subtrahend to obtain a first temperature change; Multiplying the first temperature change by the proportional target value corresponding to the target processor replaced at the previous sampling moment to obtain a proportional change; Obtaining an expected temperature of the replacement processor, performing a subtraction operation with the temperature of the replacement processor at the current sampling moment as the minuend and the expected temperature of the replacement processor as the subtrahend to obtain a second temperature change; Multiplying the second temperature change by the integral target value corresponding to the target processor replaced at the previous sampling moment to obtain an integral change; collecting the temperature of the target processor that was replaced at a previous sampling moment, where the previous sampling moment is the sampling moment before the previous sampling moment, performing a subtraction operation using the sum of the temperature of the replaced processor at the current sampling moment and the temperature of the target processor that was replaced at the previous sampling moment as a minuend, and using double the temperature of the target processor that was replaced at the previous sampling moment as a subtrahend to obtain a third temperature change; Multiplying the third temperature change by the differential target value corresponding to the target processor replaced at the previous sampling moment to obtain a differential change; Calculating the sum of the target pulse width modulation signal duty cycle, proportional change, integral change, and differential change corresponding to the target processor replaced at the previous sampling moment to obtain the target pulse width modulation signal duty cycle corresponding to the replaced processor; The rotation speed of the fan corresponding to the replaced processor is adjusted based on the target pulse width modulation signal duty cycle corresponding to the replaced processor.

15. The heat dissipation method for a processor according to claim 1, wherein: The heat dissipation method further includes: In response to obtaining a heat dissipation update instruction or the system being in a startup phase, obtaining a current system ambient temperature; From the preset correspondence between the system ambient temperature and the pulse width modulation signal duty cycle, searching for the pulse width modulation signal duty cycle that matches the current system ambient temperature; The rotation speed of the fan corresponding to the target processor is adjusted based on the duty cycle of the pulse width modulation signal that matches the current system ambient temperature.

16. The heat dissipation method for a processor according to claim 1, wherein: The adjusting the wind direction of the fan corresponding to the target processor based on the first value and the second value includes: performing a subtraction operation using the second value as the minuend and the first value as the subtrahend to obtain a temperature difference between the temperature set points; Calculating a target ratio of a temperature difference between a temperature set point and a second value; Multiplying the target ratio by the maximum wind direction adjustment angle to obtain a target adjustment direction of the fan corresponding to the target processor; The angle of the fan plate of the fan corresponding to the target processor is adjusted based on the target adjustment direction.

17. The heat dissipation method for a processor according to claim 1, wherein: The adjusting the wind direction of the fan corresponding to the target processor includes: Determining the physical locations of multiple processors to be adjusted in the system for adjusting wind directions; Obtaining heat dissipation requirements of multiple processors to be adjusted, where the heat dissipation requirement is a difference between a current temperature of the processor to be adjusted and an expected temperature of the processor to be adjusted; Grouping the plurality of processors to be adjusted based on the heat dissipation requirements of the plurality of processors to be adjusted and the physical locations of the plurality of processors to be adjusted to obtain at least one heat concentration area group; The wind directions of the fans corresponding to the processors to be adjusted in the heat concentration area group and the wind directions of the fans corresponding to the processors to be adjusted adjacent to the heat concentration area group are adjusted to achieve heat dissipation for the processors to be adjusted in the heat concentration area group.

18. A computer device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the heat dissipation method for a processor as claimed in any one of claims 1 to 17 when executing the computer program.

19. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the heat dissipation method for a processor according to any one of claims 1 to 17 are implemented.

20. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the heat dissipation method for a processor according to any one of claims 1 to 17 are implemented.

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