Notebook computer hardware adaptation optimization method and system

Abstract

The invention discloses a notebook computer hardware adaptation optimization method and system, and relates to the technical field of notebook computer hardware adaptation optimization, and the method comprises the following steps: S1, the hardware operation parameters of a notebook computer are monitored in real time, and the hardware operation parameters at least comprise a CPU usage rate, a memory occupancy rate, a hard disk read-write rate and a graphics card load; s2, identifying a current application scene of the notebook computer, wherein the application scene comprises a multi-office software concurrent scene and a multimedia webpage browsing scene; and S3, according to a matching result of the application scene and the hardware operation parameters. According to the notebook computer hardware adaptation optimization method and system, the problem of jamming of a notebook computer during multi-task processing can be effectively solved, the working efficiency is greatly improved, and the system can intelligently allocate hardware resources and quickly respond to various operation instructions when multiple pieces of office software are operated at the same time for complex document processing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of notebook computer hardware adaptation optimization, in particular to a notebook computer hardware adaptation optimization method and system. BACKGROUND

[0002] With the digitalization of office scenarios and the multimediaization of web page content, the use of notebook computers is becoming increasingly complex: users often need to run Word, Excel, and PPT simultaneously for complex document processing, at which time the computer is prone to have a CPU load that is too high and a memory occupancy that is saturated, resulting in a delay of 3-10 seconds when clicking to save and a lag when switching pages; when browsing web pages containing a large number of high-definition pictures, short videos, or dynamic JavaScript scripts (such as e-commerce platform product pages and news information pages), the hard disk read-write rate is insufficient and the graphics card decoding capability is not fully called upon, which can cause the web page to load to a halt and the video to drop frames, seriously affecting user experience.

[0003] The existing notebook computer hardware optimization scheme has obvious deficiencies: the traditional method mostly adopts a "one-size-fits-all" performance adjustment mode, which cannot dynamically adapt hardware resources according to specific application scenarios; for example, in a multi-office software concurrent scenario, the preset "high performance" mode can cause the CPU to run at full core and high frequency, resulting in unnecessary energy waste; and the "balance" mode cannot meet the needs of memory-intensive operations, in addition, the existing scheme lacks a closed-loop feedback mechanism for the lag indicator, cannot real-time correct the hardware adjustment strategy, and is difficult to completely eliminate the lag problem. SUMMARY

[0004] The present application aims to provide a notebook computer hardware adaptation optimization method and system to solve the problems raised in the background.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solution: a notebook computer hardware adaptation optimization method, comprising the following steps:

[0006] S1: Real-time monitoring of notebook computer hardware running parameters, the hardware running parameters at least including CPU usage, memory occupancy, hard disk read-write rate, and graphics card load;

[0007] S2: Identifying the current application scenario of the notebook computer, the application scenario including a multi-office software concurrent scenario and a multimedia web browsing scenario;

[0008] S3: Dynamically adjusting the hardware resource allocation strategy according to the matching results of the application scenario and the hardware running parameters:

[0009] When identified as a multi-office software concurrent scenario and CPU usage ≥ 70% or memory occupancy ≥ 80%, increase the CPU single-core working frequency to 1.1-1.3 times of the base frequency, and at the same time, close unnecessary background memory processes;

[0010] When identified as a multimedia web browsing scenario and hard disk read-write speed ≤ 50MB / s or GPU load ≥ 60%, enable the hard disk cache acceleration module, and raise the priority of video decoding on the GPU to the highest level;

[0011] S4: Continuously monitor the adjusted hardware operating parameters. If the notebook computer lag indicators have not been eliminated, repeat step S3 to optimize the resource allocation strategy until the lag indicators are eliminated.

[0012] Further, the multi-office software concurrent scenario is running Word, Excel, and PPT simultaneously and performing complex document processing.

[0013] Further, the multimedia web browsing scenario is loading ≥ 3 web pages containing pictures, videos, and JavaScript scripts.

[0014] Further, the monitoring frequency of the hardware operating parameters in step S1 is 1 time / 0.5 seconds, and the data is collected in real time by the notebook computer's built-in hardware monitoring chip.

[0015] Further, when "increasing the CPU single-core working frequency" in step S3, the CPU voltage is controlled within the range of 1.05-1.2V to avoid hardware overheating.

[0016] Further, "enabling the hard disk cache acceleration module" in step S3 specifically refers to dividing 5%-8% of the total hard disk capacity as a dedicated cache area for temporarily storing web multimedia data.

[0017] Further, a notebook computer hardware adaptation optimization system applies the notebook computer hardware adaptation optimization method, which includes:

[0018] Monitoring module: for real-time collection of notebook computer hardware operating parameters such as CPU usage, memory occupancy, hard disk read-write speed, and GPU load, with a collection frequency of 1 time / 0.5 seconds;

[0019] Scenario identification module: for identifying multi-office software concurrent scenarios and multimedia web browsing scenarios through process detection;

[0020] Optimization control module: electrically connected with the monitoring module and the scenario identification module, and according to the scenario type and hardware parameter matching result, executes the hardware resource allocation strategy adjustment described in step S3 of claim 1;

[0021] Feedback regulation module: for monitoring the adjusted lag index, if not up to standard, triggering the optimization control module to readjust the resource allocation strategy.

[0022] Further, the monitoring module is integrated into the hardware monitoring chip of the notebook computer mainboard, and the hardware bottom layer running data is directly read.

[0023] Further, the optimization control module further comprises a temperature protection unit: when the CPU temperature is greater than or equal to 90 DEG C, the CPU working frequency is automatically reduced to 0.9 times of the reference frequency, and the cooling fan is started to run at full speed.

[0024] The application provides a notebook computer hardware adaptation optimization method and system, which has the following beneficial effects: the application can effectively solve the lag problem of the notebook computer in multitasking processing, greatly improve the work efficiency, and intelligently allocate hardware resources when multiple office software are simultaneously run for complex document processing, quickly respond to various operation instructions, shorten the waiting time for clicking saving or switching pages from several seconds or even tens of seconds, enable the user to smoothly work, reduce the time wasted due to lag, and improve the continuity and efficiency of work. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 It is a three-dimensional structure schematic view of the application of a notebook computer hardware adaptation optimization method and system. DETAILED DESCRIPTION

[0026] The embodiments of the application will be further described in detail below in combination with the drawings and examples. The following examples are used to illustrate the application, but cannot be used to limit the scope of the application.

[0027] As shown in the drawings, Figure 1 A notebook computer hardware adaptation optimization method comprises the following steps:

[0028] S1: Real-time monitoring of the hardware running parameters of the notebook computer, the hardware running parameters at least including CPU usage, memory occupancy, hard disk read-write speed and graphics card load, the monitoring frequency of the hardware running parameters in step S1 being 1 time / 0.5 seconds, and the data being collected in real time through the hardware monitoring chip built-in the notebook computer;

[0029] S2: Identifying the current application scenario of the notebook computer, the application scenario including a multiple office software concurrent scenario and a multimedia web browsing scenario, the multiple office software concurrent scenario being that Word, Excel and PPT are simultaneously run and complex document processing is performed, and the multimedia web browsing scenario being that more than three web pages containing pictures, videos and JavaScript scripts are loaded;

[0030] S3: dynamically adjust the hardware resource allocation strategy according to the matching result of the application scenario and the hardware running parameter:

[0031] When it is identified as a multi-office software concurrent scenario and the CPU usage is ≥ 70% or the memory occupancy is ≥ 80%, the CPU single-core working frequency is increased to 1.1-1.3 times of the benchmark frequency, and the unnecessary background process of memory is closed;

[0032] When it is identified as a multimedia web browsing scenario and the hard disk read-write rate is ≤ 50MB / s or the graphics card load is ≥ 60%, the hard disk cache acceleration module is enabled, the priority of video decoding of the graphics card is raised to the highest level, and when the CPU single-core working frequency is increased in step S3, the CPU voltage is controlled within the range of 1.05-1.2V to avoid hardware overheating, and the "enable hard disk cache acceleration module" in step S3 is specifically: dividing 5%-8% of the total capacity of the hard disk as a dedicated cache area for temporarily storing web multimedia data;

[0033] S4: continuously monitor the adjusted hardware running parameters, and if the notebook computer lag index is not eliminated, repeat step S3 to optimize the resource allocation strategy until the lag index is eliminated.

[0034] A notebook computer hardware adaptation optimization system, a notebook computer hardware adaptation optimization method, comprising:

[0035] The monitoring module is used for real-time acquisition of the CPU usage, memory occupancy, hard disk read-write rate, and graphics card load of the notebook computer, and the acquisition frequency is 1 time / 0.5 second. The monitoring module is integrated in the hardware monitoring chip of the notebook computer motherboard, and directly reads the hardware bottom layer running data;

[0036] The scene recognition module is used for identifying multi-office software concurrent scenarios and multimedia web browsing scenarios through process detection;

[0037] The optimization control module is electrically connected with the monitoring module and the scene recognition module, and adjusts the hardware resource allocation strategy according to the matching result of the scene type and the hardware parameter, and executes the hardware resource allocation strategy adjustment of step S3 of claim 1. The optimization control module further comprises a temperature protection unit: when the CPU temperature is ≥ 90℃, the CPU working frequency is automatically reduced to 0.9 times of the benchmark frequency, and the cooling fan is started to run at full speed;

[0038] The feedback adjustment module is used for monitoring the adjusted lag index, and if it does not meet the standard, the optimization control module is triggered to readjust the resource allocation strategy.

[0039] The system integrates the monitoring module in the hardware monitoring chip of the notebook computer mainboard, establishes data interaction with CPU, memory, hard disk and display card through the LPC bus; the scene recognition module, the optimization control module and the feedback adjustment module are integrated in the operating system kernel through software, process data and hardware parameters are acquired through the system call interface, and real-time communication between the modules is realized.

[0040] Embodiments of the application are presented for the purpose of illustration and description and are not intended to limit the application to the forms disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. Embodiments were chosen and described in order to best explain the principles of the application and its practical application, and to thereby enable others skilled in the art to best utilize the application with various modifications as are suited to the particular use contemplated.

Claims

1. A method for optimizing laptop hardware compatibility, characterized in that: Includes the following steps: S1: Real-time monitoring of the laptop's hardware operating parameters, including at least CPU utilization, memory usage, hard disk read / write speed, and graphics card load; S2: Identify the current application scenario of the laptop, including scenarios of multiple office software running concurrently and multimedia web browsing. S3: Based on the matching results between the application scenario and the hardware operating parameters, dynamically adjust the hardware resource allocation strategy: When the scenario is identified as a concurrent scenario involving multiple office software applications and the CPU utilization rate is ≥70% or the memory utilization rate is ≥80%, the CPU single-core operating frequency is increased to 1.1-1.3 times the base frequency, while unnecessary background processes that occupy memory are closed. When the scenario is identified as a multimedia web browsing scenario and the hard disk read / write speed is ≤50MB / s or the graphics card load is ≥60%, the hard disk cache acceleration module is enabled, and the graphics card video decoding priority is raised to the highest level. S4: Continuously monitor the adjusted hardware operating parameters. If the laptop lag issue persists, repeat step S3 to optimize the resource allocation strategy until the lag issue is resolved.

2. The method for optimizing laptop hardware according to claim 1, characterized in that, The scenario involving concurrent use of multiple office software programs refers to running Word, Excel, and PowerPoint simultaneously while performing complex document processing.

3. The method for optimizing laptop hardware according to claim 2, characterized in that, The multimedia webpage browsing scenario involves loading ≥3 webpages containing images, videos, and JavaScript scripts.

4. The method for optimizing laptop hardware according to claim 3, characterized in that, The monitoring frequency of the hardware operating parameters mentioned in step S1 is once every 0.5 seconds, and the data is collected in real time through the hardware monitoring chip built into the laptop.

5. A method for optimizing laptop hardware according to claim 4, characterized in that, In step S3, when "increasing the CPU single-core operating frequency", the CPU voltage is simultaneously controlled within the range of 1.05-1.2V to avoid hardware overheating.

6. The method for optimizing laptop hardware according to claim 5, characterized in that, In step S3, "enabling the hard disk cache acceleration module" specifically means: allocating 5%-8% of the total hard disk capacity as a dedicated cache area for temporarily storing web page multimedia data.

7. A laptop hardware adaptation and optimization system, employing the laptop hardware adaptation and optimization method according to any one of claims 1-6, characterized in that, include: Monitoring module: Used to collect real-time hardware operating parameters of the laptop, such as CPU usage, memory usage, hard drive read / write speed, and graphics card load, at a frequency of once every 0.5 seconds; Scene recognition module: used to identify concurrent scenarios of multiple office software applications and multimedia web browsing scenarios through process detection; Optimization control module: electrically connected to the monitoring module and scene recognition module, and performs hardware resource allocation strategy adjustment as described in step S3 of claim 1 based on the scene type and hardware parameter matching results; Feedback adjustment module: Used to monitor the adjusted lag indicators. If the indicators are not met, the optimization control module is triggered to readjust the resource allocation strategy.

8. A laptop hardware adaptation and optimization system according to claim 7, characterized in that, The monitoring module is integrated into the hardware monitoring chip on the laptop motherboard and directly reads the underlying hardware operating data.

9. A laptop hardware adaptation and optimization system according to claim 8, characterized in that, The optimization control module also includes a temperature protection unit: when the CPU temperature is ≥90℃, it automatically reduces the CPU operating frequency to 0.9 times the base frequency and starts the cooling fan to run at full speed.

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