A method and system for automatically testing performance of a graphics card
By constructing graphics card performance testing methods under normal and anti-cheat modes, the deviation problem of graphics card performance testing in real game environment simulation is solved, providing a more accurate performance evaluation and revealing the actual impact of anti-cheat services on game performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN SHIXING TECH CO LTD
- Filing Date
- 2026-03-20
- Publication Date
- 2026-06-26
AI Technical Summary
Existing graphics card performance testing methods have biases when simulating real game environments, especially due to the inaccuracy of test results caused by the system resources consumed by anti-cheat detection mechanisms.
Two controlled environments, normal mode and anti-cheat mode, are constructed. Synthetic benchmark tests are performed in both environments to collect hardware and system activity data. By comparing and analyzing the differences in performance indicators, accurate graphics card performance evaluation is provided.
It improves the accuracy of graphics card performance evaluation, enhances the practical reference value of test results, and can clearly reveal the impact of background services such as anti-cheat on game performance.
Smart Images
Figure CN122285402A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of testing, and in particular relates to an automatic testing method and system for graphics card performance. Background Technology
[0002] In the current graphics card performance evaluation system, synthetic benchmarks are one of the most commonly used testing methods. These tests aim to maximize the performance potential of graphics cards under specific tasks by running specially written demo programs or high-intensity scenarios that are independent of real-world applications.
[0003] Typical testing tools include:
[0004] 3DMark: Considered the gold standard of industry benchmarking, it offers professional test items covering a variety of graphics APIs and different hardware levels.
[0005] FurMark: Known for its extreme load, it is often used as a "graphics card stress test" tool, which puts enormous pressure on the graphics card through a complex hair rendering algorithm.
[0006] Unigine Heaven / Superposition: Developed based on the Unigine engine, it features beautiful visual effects in the test scenes, but also places high demands on graphics card performance.
[0007] The main advantage of synthetic benchmarks lies in their standardization and repeatability. The test scenarios and settings are completely fixed, making the benchmark results of different graphics cards highly comparable. Furthermore, these tests can quickly push graphics cards to their power consumption and temperature limits, making them ideal for verifying overclocking stability and cooling system performance. Finally, they provide clear, quantifiable scores, facilitating rapid performance ranking among different models.
[0008] However, this type of testing also has certain limitations, especially in simulating real-world gaming environments where deviations may occur. For example, some games employ anti-cheat detection mechanisms during runtime, scanning running programs or hard drive content to identify cheating behavior. These background operations consume system resources, causing the graphics card testing environment to differ from the actual gaming environment, thus affecting the accuracy and representativeness of the test results, and requiring improvement. Summary of the Invention
[0009] Therefore, it is necessary to provide an automatic testing method and system for graphics card performance to address the above-mentioned problems.
[0010] This invention is implemented as follows: an automatic graphics card performance testing method includes the following steps:
[0011] Clearly define and configure normal mode and anti-cheat mode. In normal mode, disable all unnecessary background services and anti-cheat functions to build a clean test environment and measure the theoretical maximum performance of the graphics card. In anti-cheat mode, control the anti-cheat process to run in the background and simulate the scanning behavior of the anti-cheat process to build an anti-cheat working environment and measure the performance of the graphics card under the anti-cheat process.
[0012] Run the same synthetic benchmark suite in both normal and anti-cheat modes. Perform graphics card performance tests (such as various 3DMark items) in normal mode. After completion, restart the computer system or use a script to clean up the environment to ensure that the environment is reset. Switch to anti-cheat mode. After the anti-cheat system is correctly loaded and running in the background, run the exact same test suite as in normal mode again to perform graphics card performance tests (that is, except for the anti-cheat process, all environmental factors such as hardware configuration, driver version, and system service status that the two tests depend on are kept completely consistent. Throughout the process, not only should the startup of the test software be controlled, but it is also necessary to verify whether the target mode has been correctly loaded, such as confirming the specific anti-cheat service process).
[0013] During graphics card performance testing, hardware performance data and computer system activity data are collected. Hardware performance data includes the final score given by the testing software and real-time hardware indicators (frame rate, power consumption, temperature, etc.) monitored in real time. Computer system activity data includes CPU utilization, memory usage, and disk activity time. Data collected in different modes is labeled with different mode tags (such as "normal mode" or "anti-cheat mode") and stored in the database.
[0014] By comparing and analyzing data labeled with different modes, the system provides various performance indicators of the graphics card under different modes and automatically calculates the differences or percentage changes of various performance indicators under different modes.
[0015] In one embodiment, the present invention provides an automatic graphics card performance testing method, which further includes:
[0016] Establish an anti-cheat scenario library, which is categorized according to game type (such as FPS, MOBA, MMORPG) and anti-cheat technology principles (such as client scanning, behavior analysis, driver-level protection) for different game types. The library also includes representative games and corresponding anti-cheat processes. In anti-cheat mode, it can call a single anti-cheat process or a combination of different anti-cheat processes from the anti-cheat scenario library according to preset strategies (such as random selection, specified type, or full coverage).
[0017] In one embodiment, the present invention provides an automatic graphics card performance testing method, which further includes:
[0018] After completing the anti-cheat mode test and performing the environment cleanup operation, the graphics card performance test was performed again in normal mode. By comparing the various performance indicators of the first normal mode test and the current normal mode test, the environment was verified to have been successfully reset, ensuring that the test results were not affected by the previous test.
[0019] In one embodiment, the present invention provides an automatic graphics card performance testing method, which further includes:
[0020] During the synthetic benchmark test run in anti-cheat mode, the critical life cycle of the anti-cheat process is precisely triggered or waited for. The instantaneous performance impact of the anti-cheat process during the critical life cycle (such as startup, initialization scan, periodic scan and exit) is captured, and the graphics card performance indicators (frame time fluctuation, frame rate stability and percentile frame rate of the graphics card, etc., are part of the real-time hardware indicators) are recorded.
[0021] In one embodiment, the present invention provides an automatic graphics card performance testing method, which further includes:
[0022] By controlling the enabling and disabling of the computer system's underlying security functions, and performing a synthetic benchmark test of anti-cheat mode in both states, it is determined whether there are any performance deviations in the computer system caused by permission conflicts or hardware virtualization resource contention.
[0023] In one embodiment, the present invention provides an automatic graphics card performance testing system, comprising:
[0024] The mode definition configuration module is used to explicitly define and configure normal mode and anti-cheat mode. In normal mode, all unnecessary background services and anti-cheat functions are disabled to build a clean test environment and measure the theoretical maximum performance of the graphics card. In anti-cheat mode, the anti-cheat process is controlled to run in the background and simulate the scanning behavior of the anti-cheat process to build an anti-cheat working environment and measure the performance of the graphics card under the anti-cheat process.
[0025] The graphics card performance testing module is used to execute the same synthetic benchmark suite in both normal and anti-cheat modes. In normal mode, graphics card performance tests (such as various 3DMark items) are performed. After completion, the computer system is restarted or a script is used to clean up the environment to ensure that the environment is reset. Then, the system switches to anti-cheat mode. After the anti-cheat system is correctly loaded and running in the background, the exact same test suite as in normal mode is run again to perform graphics card performance tests (that is, except for the anti-cheat process, all environmental factors such as hardware configuration, driver version, and system service status are kept completely consistent in the two tests). Throughout the process, not only is the startup of the test software controlled, but it is also necessary to verify whether the target mode has been correctly loaded, such as confirming the specific anti-cheat service process.
[0026] The data acquisition module is used to collect hardware performance data and computer system activity data during graphics card performance testing. Hardware performance data includes the final score given by the testing software and real-time hardware indicators (frame rate, power consumption, temperature, etc.) under real-time monitoring. Computer system activity data includes CPU utilization, memory usage, and disk activity time. Data collected in different modes is labeled with different mode tags (such as "normal mode" or "anti-cheat mode") and stored in the database.
[0027] The performance index output module is used to compare and analyze data labeled with different modes, provide various performance indicators of the graphics card in different modes, and automatically calculate the difference or percentage change of various performance indicators in different modes.
[0028] In one embodiment, the present invention provides an automatic graphics card performance testing system, further comprising:
[0029] The anti-cheat scenario library creation module is used to establish an anti-cheat scenario library. The anti-cheat scenario library is categorized according to game type (such as FPS, MOBA, MMORPG) and the anti-cheat technology principles of different game types (such as client scanning, behavior analysis, driver-level protection). The anti-cheat scenario library includes corresponding representative games and corresponding anti-cheat processes. In anti-cheat mode, it can call a single anti-cheat process or a combination of different anti-cheat processes from the anti-cheat scenario library according to preset strategies (such as random selection, specified type, or full coverage).
[0030] In one embodiment, the present invention provides an automatic graphics card performance testing system, further comprising:
[0031] The environment reset verification module is used to perform graphics card performance testing again in normal mode after completing the anti-cheat mode test and performing the environment cleanup operation. By comparing the various performance indicators of the first normal mode and the current normal mode, it verifies whether the environment has been successfully reset and ensures that the test results are not affected by the previous test.
[0032] In one embodiment, the present invention provides an automatic graphics card performance testing system, further comprising:
[0033] The instantaneous performance verification module is used to precisely trigger or wait for the critical life cycle of the anti-cheat process during the synthetic benchmark test run in anti-cheat mode, capture the instantaneous performance impact of the anti-cheat process in the critical life cycle (such as startup, initialization scan, periodic scan and exit), and record the graphics card performance indicators (frame time fluctuation, frame rate stability and percentile frame rate of the graphics card, etc., which are part of the real-time hardware indicators).
[0034] In one embodiment, the present invention provides an automatic graphics card performance testing system, further comprising:
[0035] The conflict detection module is used to determine whether there are any performance deviations in the computer system caused by permission conflicts or hardware virtualization resource contention by controlling the enabling and disabling of the computer system's underlying security functions and performing a synthetic benchmark test in anti-cheat mode in both states.
[0036] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention constructs two controlled environments: a normal mode and an anti-cheat mode. The former provides a performance benchmark, while the latter actively simulates the real environment brought about by the game's anti-cheat process scanning in the background. Identical synthetic benchmark tests are performed in both modes, and hardware performance data and computer system activity data are accurately collected. By comparing and analyzing the performance index differences between the two modes, the invention provides graphics card performance in both normal and anti-cheat modes, improving the accuracy of graphics card performance evaluation and enhancing the practical reference value of the test results. Attached Figure Description
[0037] Figure 1 This is a schematic diagram of the first part of an automatic graphics card performance testing method provided in an embodiment of the present invention.
[0038] Figure 2 This is a schematic diagram of the second part of an automatic graphics card performance testing method provided in an embodiment of the present invention.
[0039] Figure 3 This is a flowchart illustrating the third part of an automatic graphics card performance testing method provided in an embodiment of the present invention.
[0040] Figure 4 This is a flowchart illustrating the fourth part of an automatic graphics card performance testing method provided in an embodiment of the present invention.
[0041] Figure 5 This is a flowchart of the fifth part of an automatic graphics card performance testing method provided in an embodiment of the present invention.
[0042] Figure 6 This is a schematic diagram of the first part of an automatic graphics card performance testing system provided in an embodiment of the present invention.
[0043] Figure 7 This is a schematic diagram of the second part of an automatic graphics card performance testing system provided in an embodiment of the present invention.
[0044] Figure 8 This is a schematic diagram of the third part of an automatic graphics card performance testing system provided in an embodiment of the present invention.
[0045] Figure 9This is a schematic diagram of the fourth part of an automatic graphics card performance testing system provided in an embodiment of the present invention.
[0046] Figure 10 This is a schematic diagram of the fifth part of an automatic graphics card performance testing system provided in an embodiment of the present invention. Detailed Implementation
[0047] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.
[0048] In one embodiment, such as Figure 1 As shown, an automatic graphics card performance testing method includes the following steps:
[0049] Step S1: Clearly define and configure normal mode and anti-cheat mode. In normal mode, disable all unnecessary background services and anti-cheat functions to build a clean test environment and measure the theoretical maximum performance of the graphics card. In anti-cheat mode, control the anti-cheat process to run in the background and simulate the scanning behavior of the anti-cheat process to build an anti-cheat working environment and measure the performance of the graphics card under the anti-cheat process.
[0050] Step S2: Execute the same synthetic benchmark suite in both normal mode and anti-cheat mode. Perform graphics card performance tests (such as various 3DMark items) in normal mode. After completion, restart the computer system or use a script to clean up the environment to ensure that the environment is reset. Switch to anti-cheat mode. After the anti-cheat system has been correctly loaded and running in the background, run the exact same test suite as in normal mode again to perform graphics card performance tests (that is, except for the anti-cheat process, all environmental factors such as hardware configuration, driver version, and system service status that the two tests depend on are kept completely consistent. Throughout the process, not only should the startup of the test software be controlled, but it is also necessary to verify whether the target mode has been correctly loaded, such as confirming the specific anti-cheat service process).
[0051] Step S3: During the graphics card performance test, collect hardware performance data and computer system activity data. Hardware performance data includes the final score given by the test software and real-time hardware indicators (frame rate, power consumption, temperature, etc.) under real-time monitoring. Computer system activity data includes CPU utilization, memory usage, and disk activity time. Data collected in different modes is labeled with different mode tags (such as "normal mode" or "anti-cheat mode") and stored in the database.
[0052] Step S4 involves comparing and analyzing the data labeled with different modes to provide various performance indicators of the graphics card under different modes, and automatically calculating the differences or percentage changes of various performance indicators under different modes.
[0053] Common and representative anti-cheat processes:
[0054] Easy Anti-Cheat (EAC) is a widely adopted third-party anti-cheat solution, known for its lightweight design and ease of integration. It primarily prevents common cheating behaviors by monitoring system processes and memory during game runtime.
[0055] BattlEye is known for its proactive and powerful detection capabilities, especially in multiplayer competitive games. BattlEye employs deep kernel-level monitoring and dynamic response mechanisms, which can significantly increase system resource consumption, making it an ideal high-load testing scenario.
[0056] Riot Vanguard is a typical driver-level anti-cheat system. Its core component, as a kernel driver, loads when the computer boots up and has extremely high system privileges to achieve deep monitoring. Due to its unique run level and access to low-level system resources, it is extremely valuable in testing for assessing permission conflicts and kernel resource contention.
[0057] In one embodiment, such as Figure 2 As shown, an automatic graphics card performance testing method also includes:
[0058] Step S5: Establish an anti-cheat scenario library. In the anti-cheat scenario library, classify games according to game type (such as FPS, MOBA, MMORPG) and anti-cheat technology principles of different game types (such as client scanning, behavior analysis, driver-level protection). Include representative games and corresponding anti-cheat processes in the anti-cheat scenario library. In anti-cheat mode, a single anti-cheat process or a combination of different anti-cheat processes can be called from the anti-cheat scenario library according to preset strategies (such as random selection, specified type, or full coverage).
[0059] The practical application of setting up different anti-cheat process combinations is to simulate a user's multitasking scenario, such as launching game B without ending game A. In this case, the anti-cheat processes for both games will reside and run concurrently in the system, competing for system resources.
[0060] In one embodiment, such as Figure 3 As shown, an automatic graphics card performance testing method also includes:
[0061] Step S6: After completing the anti-cheat mode test and performing the environment cleanup operation, perform the graphics card performance test again in normal mode. By comparing the various performance indicators of the first normal mode and the current normal mode, verify whether the environment has been successfully reset and ensure that the test results are not affected by the previous test.
[0062] If the difference in core performance metrics (such as average frame rate and total test score) between two normal modes is less than ±3%, this is usually within the normal fluctuation range of the test system itself. The environment reset can be considered successful, and the test data is valid. A difference between ±3% and ±5% indicates that the environment may not have been completely reset, suggesting slight contamination. A warning should be triggered, and manual review based on system logs is recommended. A difference > ±5% indicates a significant performance drop, strongly suggesting an environment reset failure. There may be driver-level or kernel-level anti-cheat components residing in memory that have not been cleaned up, continuously consuming system resources.
[0063] In one embodiment, such as Figure 4 As shown, an automatic graphics card performance testing method also includes:
[0064] Step S7: During the benchmark test run in anti-cheat mode, precisely trigger or wait for the critical life cycle of the anti-cheat process, capture the instantaneous performance impact of the anti-cheat process in the critical life cycle (such as startup, initialization scan, periodic scan and exit), and record the graphics card performance indicators (frame time fluctuation, frame rate stability and percentile frame rate of the graphics card, etc., which are part of the real-time hardware indicators).
[0065] The specific methods for accurately triggering or waiting for critical lifecycle events of the anti-cheat process are as follows: First, process monitoring tools are used to track the creation and exit events of the target anti-cheat process in real time. For behaviors such as initialization scanning and periodic scanning, they are actively triggered by intercepting specific system calls, monitoring file access patterns, or directly sending simulated detection signals. Simultaneously, a high-precision performance probe is used to initiate high-frequency data acquisition the instant the aforementioned critical events are predicted or detected, in order to capture the subsequent frame time fluctuations and performance jitters, thereby accurately correlating lifecycle events with instantaneous performance impacts.
[0066] In one embodiment, such as Figure 5 As shown, an automatic graphics card performance testing method also includes:
[0067] Step S8 involves controlling the computer system's underlying security functions to be enabled or disabled, and performing a synthetic benchmark test of the anti-cheat mode in both states to determine whether there are any performance deviations in the computer system caused by permission conflicts or hardware virtualization resource contention.
[0068] A computer system performance deviation can be identified when any of the following conditions are met:
[0069] Significantly low key performance indicators: The final score or average frame rate given by the testing software drops by more than 3%, or the percentile frame rate drops by more than 5%, and this result can be reproduced in multiple tests;
[0070] Abnormal system resource indicators: Under similar graphics card load conditions, CPU core utilization is abnormally high, interrupt handling latency is significantly increased, or hard disk activity time remains high.
[0071] Functional or stability issues may occur: During testing, abnormal phenomena such as driver timeouts and screen freezes may occur that did not occur when security features are disabled.
[0072] In one embodiment, such as Figure 6 As shown, an automatic graphics card performance testing system includes:
[0073] The mode definition configuration module 1 is used to explicitly define and configure the normal mode and anti-cheat mode. In normal mode, all unnecessary background services and anti-cheat functions are disabled to build a clean test environment and measure the theoretical maximum performance of the graphics card. In anti-cheat mode, the anti-cheat process is controlled to run in the background and simulate the scanning behavior of the anti-cheat process to build an anti-cheat working environment and measure the performance of the graphics card under the anti-cheat process.
[0074] Graphics card performance test module 2 is used to execute the same synthetic benchmark suite in both normal mode and anti-cheat mode. In normal mode, graphics card performance tests (such as various 3DMark items) are performed. After completion, the computer system is restarted or a script is used to clean up the environment to ensure that the environment is reset. Then, the system is switched to anti-cheat mode. After the anti-cheat system is correctly loaded and running in the background, the same test suite as in normal mode is run again to perform graphics card performance tests (that is, except for the anti-cheat process, all environmental factors such as hardware configuration, driver version, and system service status that the two tests depend on are kept completely consistent. Throughout the process, not only is the startup of the test software controlled, but it is also necessary to verify whether the target mode has been correctly loaded, such as confirming the specific anti-cheat service process).
[0075] Data acquisition module 3 is used to collect hardware performance data and computer system activity data during graphics card performance testing. Hardware performance data includes the final score given by the testing software and real-time hardware indicators (frame rate, power consumption, temperature, etc.) under real-time monitoring. Computer system activity data includes CPU utilization, memory usage, and disk activity time. Data collected in different modes is labeled with different mode tags (such as "normal mode" or "anti-cheat mode") and stored in the database.
[0076] The performance index output module 4 is used to compare and analyze data labeled with different modes, provide various performance indicators of the graphics card in different modes, and automatically calculate the difference or percentage change of various performance indicators in different modes.
[0077] The report will highlight conclusions in two key areas: first, the absolute performance ranking of graphics cards in normal mode; and second, the performance fluctuations or losses caused by additional system load in simulated real-world gaming environments. This comparative report clearly reveals the actual impact of background services such as anti-cheat measures on game performance, providing a more comprehensive basis for evaluating the real-world gaming performance of graphics cards.
[0078] In anti-cheat mode, two scenarios are simulated: low-intensity monitoring (game lobby state) and high-intensity scanning (during a match or when suspicious behavior is detected). This tests the sensitivity of the graphics card's performance to the dynamic behavior of the anti-cheat process, reveals its performance fluctuation range, and the evaluation results reflect the complexity of real-world situations better than a single static load test.
[0079] In one embodiment, such as Figure 7 As shown, an automatic graphics card performance testing system also includes:
[0080] The anti-cheat scenario library creation module 5 is used to create an anti-cheat scenario library. In the anti-cheat scenario library, the scenarios are categorized according to game type (such as FPS, MOBA, MMORPG) and the anti-cheat technology principles of different game types (such as client scanning, behavior analysis, driver-level protection). The anti-cheat scenario library includes corresponding representative games and corresponding anti-cheat processes. In anti-cheat mode, it can call a single anti-cheat process or a combination of different anti-cheat processes from the anti-cheat scenario library according to preset strategies (such as random selection, specified type, or full coverage).
[0081] A single test cannot cover the diverse anti-cheat technologies. By establishing a structured anti-cheat scenario library and classifying it according to game type and technical principles, this solution can systematically cover anti-cheat processes with different characteristics. This allows testing to expand from case analysis of a single scenario to a comprehensive survey of the impact of various anti-cheat systems, thereby drawing more universal conclusions and accurately assessing the potential cumulative performance impact when multiple anti-cheat processes coexist.
[0082] Data collected under different modes is labeled with different mode tags, and can therefore be further subdivided into "anti-cheat mode - game A, anti-cheat mode - game B".
[0083] In one embodiment, such as Figure 8 As shown, an automatic graphics card performance testing system also includes:
[0084] The environment reset verification module 6 is used to perform a graphics card performance test again in normal mode after completing the anti-cheat mode test and performing the environment cleanup operation. By comparing the various performance indicators of the first normal mode with the current normal mode, it verifies whether the environment has been successfully reset and ensures that the test results are not affected by the previous test.
[0085] Some anti-cheat processes (especially driver-level ones) may still have remnants after the test, thus contaminating subsequent test environments. By performing a cleanup operation and then rerunning the graphics card performance test in normal mode and comparing the results with the initial normal mode test, we can effectively verify whether the test environment has been successfully reset to a clean state. This step is a critical quality assurance step, ensuring that the performance difference between normal mode and anti-cheat mode is entirely due to variables introduced in the current test, rather than interference from historical tests.
[0086] In one embodiment, such as Figure 9 As shown, an automatic graphics card performance testing system also includes:
[0087] The instantaneous performance verification module 7 is used to precisely trigger or wait for the critical life cycle of the anti-cheat process during the synthetic benchmark test run in anti-cheat mode, capture the instantaneous performance impact of the anti-cheat process in the critical life cycle (such as startup, initialization scan, periodic scan and exit), and record the graphics card performance indicators (frame time fluctuation, frame rate stability and percentile frame rate of the graphics card, etc., which are part of the real-time hardware indicators).
[0088] Average frame rate cannot fully reflect the smoothness of a game; momentary stutters are the key factor affecting user experience. The instantaneous performance verification module 7 accurately captures the instantaneous activities of the anti-cheat process during key lifecycle stages such as startup and scanning, and simultaneously records fine-grained indicators such as frame time. This provides crucial data support for evaluating the smoothness of the graphics card in real games.
[0089] In one embodiment, such as Figure 10 As shown, an automatic graphics card performance testing system also includes:
[0090] The conflict detection module 8 is used to determine whether there is a performance deviation of the computer system caused by permission conflicts or hardware virtualization resource contention by controlling the enabling and disabling of the computer system's underlying security functions and performing a synthetic benchmark test of anti-cheat mode in both states.
[0091] Modern computer operating systems have built-in strict security features, such as Windows' Virtualization-based Security (VBS). Resource conflicts may arise between the underlying security features of the computer operating system and the anti-cheat mode that operates with high privileges. The conflict detection module 8, by controlling the on / off state of the computer system's security features and performing comparative tests, is specifically designed to diagnose and identify systemic performance deviations or instability caused by permission conflicts or the preemption of hardware virtualization resources.
[0092] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.
[0093] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0094] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.
[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
[0096] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.
Claims
1. A method for automatically testing performance of a display card, characterized by, The automatic graphics card performance testing method includes the following steps: Clearly define and configure normal mode and anti-cheat mode. In normal mode, disable all unnecessary background services and anti-cheat functions to build a clean test environment and measure the theoretical maximum performance of the graphics card. In anti-cheat mode, control the anti-cheat process to run in the background and simulate the scanning behavior of the anti-cheat process to build an anti-cheat working environment and measure the performance of the graphics card under the anti-cheat process. Run the same synthetic benchmark suite in both normal mode and anti-cheat mode. Perform graphics card performance tests in normal mode. After completion, restart the computer system or use a script to clean up the environment to ensure that the environment is reset. Switch to anti-cheat mode. After the anti-cheat system has been correctly loaded and running in the background, run the exact same test suite as in normal mode again to perform graphics card performance tests. During graphics card performance testing, hardware performance data and computer system activity data are collected. Hardware performance data includes the final score given by the testing software and real-time hardware indicators monitored in real time. Computer system activity data includes CPU utilization, memory usage, and disk activity time. Data collected under different modes is labeled with different mode tags and stored in the database. By comparing and analyzing data labeled with different modes, the system provides various performance indicators of the graphics card under different modes and automatically calculates the differences or percentage changes of various performance indicators under different modes.
2. The method of claim 1, wherein the step of automatically testing the performance of the graphic card is performed by a graphic card driver. Also includes: Establish an anti-cheat scenario library, which is categorized according to game type and the anti-cheat technology principles of different game types. The library also includes representative games and corresponding anti-cheat processes. In anti-cheat mode, a single anti-cheat process or a combination of different anti-cheat processes can be called from the anti-cheat scenario library according to a preset strategy.
3. The automatic test method of graphic card performance according to claim 1 or 2, characterized in that, Also includes: After completing the anti-cheat mode test and performing the environment cleanup operation, the graphics card performance test was performed again in normal mode. By comparing the various performance indicators of the first normal mode test and the current normal mode test, the environment was verified to have been successfully reset, ensuring that the test results were not affected by the previous test.
4. The method of claim 3, wherein the step of automatically testing the performance of the graphic card is performed by a graphic card performance test program. Also includes: During the benchmark test run in anti-cheat mode, the critical life cycle of the anti-cheat process is precisely triggered or waited for, capturing the instantaneous performance impact of the anti-cheat process during the critical life cycle and recording the graphics card performance indicators.
5. The method of claim 1, wherein the method further comprises: Also includes: By controlling the enabling and disabling of the computer system's underlying security functions, and performing a synthetic benchmark test of anti-cheat mode in both states, it is determined whether there are any performance deviations in the computer system caused by permission conflicts or hardware virtualization resource contention.
6. An automatic testing system for performance of a display card, characterized by, include: The mode definition configuration module is used to explicitly define and configure normal mode and anti-cheat mode. In normal mode, all unnecessary background services and anti-cheat functions are disabled to build a clean test environment and measure the theoretical maximum performance of the graphics card. In anti-cheat mode, the anti-cheat process is controlled to run in the background and simulate the scanning behavior of the anti-cheat process to build an anti-cheat working environment and measure the performance of the graphics card under the anti-cheat process. The graphics card performance testing module is used to execute the same synthetic benchmark suite in normal mode and anti-cheat mode, respectively. Perform graphics card performance testing in normal mode. After completion, restart the computer system or use a script to clean up the environment to ensure that the environment is reset. Switch to anti-cheat mode. After the anti-cheat system has been correctly loaded and running in the background, run the same test suite as in normal mode again to perform graphics card performance testing. The data acquisition module is used to collect hardware performance data and computer system activity data during graphics card performance testing. Hardware performance data includes the final score given by the testing software and real-time hardware indicators monitored in real time; computer system activity data includes CPU utilization, memory usage, and disk activity time; data collected in different modes is labeled with different mode tags and stored in the database. The performance index output module is used to compare and analyze data labeled with different modes, provide various performance indicators of the graphics card in different modes, and automatically calculate the difference or percentage change of various performance indicators in different modes.
7. The automatic video card performance testing system of claim 6, wherein, Also includes: The anti-cheat scenario library creation module is used to establish an anti-cheat scenario library. The anti-cheat scenario library is categorized according to game type and the anti-cheat technology principles of different game types. The library includes corresponding representative games and corresponding anti-cheat processes. In anti-cheat mode, it can call a single anti-cheat process or a combination of different anti-cheat processes from the anti-cheat scenario library according to preset strategies.
8. The automatic test system for video card performance according to claim 6 or 7, wherein, Also includes: The environment reset verification module is used to perform graphics card performance testing again in normal mode after completing the anti-cheat mode test and performing the environment cleanup operation. By comparing the various performance indicators of the first normal mode and the current normal mode, it verifies whether the environment has been successfully reset and ensures that the test results are not affected by the previous test.
9. The automatic video card performance testing system of claim 8, wherein, Also includes: The instantaneous performance verification module is used to precisely trigger or wait for the critical life cycle of the anti-cheat process during the synthetic benchmark test run in anti-cheat mode, capture the instantaneous performance impact of the anti-cheat process during the critical life cycle, and record the graphics card performance indicators.
10. The automatic video card performance testing system of claim 6, wherein, Also includes: The conflict detection module is used to determine whether there are any performance deviations in the computer system caused by permission conflicts or hardware virtualization resource contention by controlling the enabling and disabling of the computer system's underlying security functions and performing a synthetic benchmark test in anti-cheat mode in both states.