8 results about "Computer performance" patented technology

The application belongs to the technical field of computer hardware testing, and discloses a multi-sensor integrated detection dock system for notebook computer performance testing, which comprises a multi-sensor module, a data acquisition and interface module, a main control module and a hardware component. The application has the following remarkable advantages: high integration and improved efficiency; data synchronization precision and improved analysis value; high automation degree and reduction of human error; consistent test conditions and strong result comparability.

This invention discloses a computer performance data acquisition method and system, relating to the field of computer data processing technology. Based on the load prediction value Ldp, the system automatically adjusts its operating rhythm. When the device is under high pressure, the sampling adjustment coefficient Frs is suppressed due to the increase in the acquisition overhead value Coi, thereby dynamically lengthening the sampling interval Del, thus preventing the acquisition behavior from exacerbating congestion. When the device is idle, the processing utilization Cpuu, memory utilization Memu, and thread switching rate Ths remain at low values, and the load prediction value Ldp derived from the trend base value Tbs and the acquisition overhead value Coi is low, causing the sampling interval Del to be actively shortened. This allows for early capture even when the user is not operating but background programs are gradually increasing. Traditional fixed-frequency acquisition methods often fail to identify performance degradation inflection points in a timely manner, while the continuous accumulation of the trend base value Tbs triggers an increase in the sampling frequency at an early stage.

The utility model discloses a double -deck formula HDD module support structure, including assembly frame, the inside fixed mounting of assembly frame has a plurality of transverse arrangement's lower support board, each lower support board all is provided with upper support board, each lower support board with upper support board inside all movably inserts and is provided with HDD module, and the lower support board includes a primary support plate, and the top of primary support plate is provided with front baffle, and the lower surface one side of primary support plate is provided with primary fixed hole for installing assembly frame, and the upper surface fixed mounting of front baffle is provided with the frame plate assembly hole for with upper support board assembly, the support structure of the utility model has double -deck formula's HDD module support installation effect, can carry out up -and -down stacked frame body assembly work, and in this way can when HDD module assembly, through the structural design of double -deck support, can effectively promote the assembly number of HDD module, promote computer performance, and simultaneously will not occupy too much cabinet transverse space, reduces the space occupation effect when module assembly.

The present application belongs to the technical field of computer performance detection, and discloses a computer performance degradation prediction and anomaly detection method based on multi-source data fusion, and the specific steps are as follows: S1. Multi-source data acquisition: collect hardware sensor data, software performance counter data, and user behavior and system log data of the computer. By fusing hardware, software and system log multi-source data, the one-sidedness of a single data source is avoided, the computer performance is accurately and comprehensively reflected, the detection accuracy is improved, and the false alarm and missed alarm rates are reduced; based on the historical data of the health state, a personalized model is trained to build a health region, which is adapted to different user habits, solves the drawbacks of fixed threshold one-size-fits-all, and enhances adaptability; the health degree trend is predicted through the LSTM model, the change from "post-detection" to "pre-prediction" is realized, and the user is helped to carry out preventive maintenance in advance; with the help of the SHAP method, the abnormal root cause is located, the fault diagnosis and repair time is shortened, and the operation and maintenance efficiency is improved.

A method improves performance of a computer that provides binaural sound to a listener. A memory stores coordinate locations that follow a path of how the head of the listener moves. This path is retrieved in anticipation of subsequent head movements of the listener to improve computer performance of executing binaural sound.

The present application belongs to the technical field of computer performance detection, and discloses a computer adaptive testing method based on POMDP and dynamic confidence state updating, and the specific steps are as follows: step one: build a hardware platform and a sensor network, the hardware platform is composed of a host control unit, a multi-type sensor array and a U disk test starting device. Through the confidence state dynamic adjustment mechanism, the test cases corresponding to the low probability state can be automatically trimmed, the test time is greatly shortened, and the problem of low efficiency of the traditional method is solved; combined with Kalman filter multi-sensor fusion and POMDP model, the system uncertainty is accurately modeled, the state estimation is corrected in real time, the performance inflection point is captured in advance, the warning accuracy and the adaptability to the system state change are improved, and the pain points of poor prediction and poor adaptability are solved; with the help of AHP-TOPSIS dynamic weight multi-dimensional evaluation and visual output, quantitative scoring and multi-dimensional comparison are realized, and misjudgment is reduced.

The application discloses a parallel optimization method and system for a high-performance computer and relates to the technical field of computer performance optimization. The method constructs a local task inheritance tree for each parallel process and labels inheritance cost. Each process only exchanges root node inheritance cost with adjacent processes and updates a global load baseline, and triggers pre-splitting when the local cost exceeds the baseline dynamic threshold. Subnode division schemes are enumerated, load balancing benefits and communication costs are quantified through a split benefit formula, the optimal scheme is selected to divide the calculation unit, task meta information is written into the target process through a remote direct memory access one-way write operation, the target process writes back the result after completion, the current process polls the completion flag and recycles, and the timeout task can be re-delegated. The application realizes the pre-perception and dynamic balancing of load and improves parallel computing efficiency.