311 results about "System hardware" patented technology

The invention discloses a mapping prediction method and system based on a hardware resource load and system operation relationship. The method comprises the following steps: collecting hardware index data in real time when an operating system operates; the method comprises the following steps: preprocessing hardware index data, performing association analysis on each index data by adopting an association rule mining algorithm, generating association rules, evaluating the association rules, screening out the association rules meeting conditions, and constructing a multivariable association model; based on a correlation analysis result, a load prediction model is constructed and trained, and the trained model is deployed in the system for load prediction; and dynamically adjusting a system hardware resource allocation strategy according to a prediction result, carrying out task migration and load balancing according to a predicted load condition, and automatically adjusting hardware resources through an automatic script or a scheduling tool. Through real-time monitoring and deep correlation analysis of indexes such as the CPU, the memory, the storage I / O and the network bandwidth, the resource utilization rate and the operation efficiency of the system are improved, and the stability and the reliability of the system are improved.

The invention discloses a large language model reasoning method based on an unloading pipeline, and the method comprises the steps: obtaining an optimal unloading reasoning strategy through calculation according to the obtained model structure information and model configuration information of a large language model, and the hardware specification information and system operation load information of reasoning equipment; and then tasks in the optimal unloading reasoning strategy are scheduled through a fine-grained pipeline to output an unloading reasoning result of the large language model. According to the method, reasoning tasks are automatically configured according to input large language model information and a system hardware environment, and hardware resource use and reasoning performance are optimized. For deployment of a large language model on local equipment, transmission optimization is carried out for unloading using a solid state disk, so that the data transmission speed is increased. Meanwhile, fine-grained assembly line task scheduling is carried out for unloading reasoning, and the reasoning concurrency and the model throughput can be remarkably improved through unloading reasoning of an assembly line model.

According to the model lightweight deployment method and device based on the hardware performance of the end system, parameters such as the maximum computing power and the batch processing amount are obtained through a static hardware performance evaluation query database, and the actual computing power and the memory are calculated in real time through dynamic operation state monitoring to serve as compression targets; when the hardware resource change exceeds a threshold value, light weight is triggered, and dynamic adjustment of a compression strategy is achieved; in the lightweight process, hardware parameters and model features are fused into a low-dimensional state vector, collaborative compression parameters of a reinforcement learning strategy network output pruning rate, quantization bit width and distillation temperature are input, and finally a lightweight model adaptive to the hardware dynamic environment is generated. The automatic compression process reduces the labor cost, ensures that the lightweight model is accurately matched with the end side hardware constraint, improves the reasoning speed and reduces the energy consumption.

The invention provides a full-autonomous cell operation system based on body intelligence, and relates to the field of cell operation, the system comprises a system hardware architecture and a system software architecture; the system hardware architecture comprises a micromanipulation execution system, a precision positioning system, a multi-mode sensing system and an intelligent calculation and control center. The micromanipulation execution system is used for cell environment interaction, the precision positioning system is used for sample bearing and environment control, the multi-modal sensing system is used for providing key information, and the intelligent calculation and control center is used for operation decision making; the system software architecture comprises a sensing layer, a planning layer, an execution layer and an interaction layer. According to the application, cell recognition, tool selection, path planning, operation execution and result feedback can be automatically completed without manual intervention; through tool autonomous switching and strategy dynamic adjustment, various operations such as cell clamping, injection, controllable deformation and micro-assembly can be completed, and the problems that traditional cell operation depends on manual work, efficiency is low, and consistency is poor are solved.

The invention provides a large-model-oriented heterogeneous computing power adaptive compiling method, which comprises the following steps that: a user inputs a trained large model through a system interface, and a system front-end conversion module analyzes a computational graph of the model and converts the computational graph into an intermediate representation based on a unified operator description language (UDL); the system hardware sensing module automatically detects and extracts hardware feature fingerprints of at least one piece of target hardware; based on the unified operator description language UDL intermediate representation and the hardware feature fingerprint, automatically generating an optimization adaptation rule oriented to at least one piece of target hardware; wherein the basis of parameterized filling comprises specific parameters of hardware feature fingerprints and optimized attribute tags carried in an intermediate representation of a unified operator description language (UDL); and generating and deploying multiple back-end codes. The method has the beneficial effects that intelligent compiling based on hardware features can be realized, and the deployment efficiency and the operation performance of a large model in a complex heterogeneous computing power cluster are remarkably improved.

The embodiment of the invention provides a memory testing system and method, and relates to the technical field of embedded system hardware manufacturing. According to the memory test system disclosed by the invention, the physical layer interface of the memory controller is calibrated, the input / output interface of the memory bus is trained, and the optimized parameters are generated, so that the memory data of the memory unit (including memory particles) can be collected under the optimal condition corresponding to the optimized parameters. And then, carrying out a pressure test on the storage unit based on the optimized parameters, and recording fault information and abnormal information of the storage unit according to a pressure test result. Therefore, the memory test system provided by the invention not only can cover the test of the memory particles, but also can cover the test of the memory controller, and can ensure the stability and reliability of the whole memory unit.

According to the heterogeneous multi-core chip power consumption state control system and the heterogeneous multi-core chip provided by the invention, the power consumption state request of each sub power supply domain is received through the set system hardware power consumption management module, and the driving signal is sent to the corresponding sub power supply domain according to the preset hardware time sequence, so that the corresponding sub power supply domain enters the target state; generating a PMU control signal; and the power management module drives an internal voltage regulator to execute corresponding regulation operation according to the PMU control signal. A special control processor (SCP) is not needed, the system hardware power consumption management module realized by pure hardware is adopted to directly control the power consumption state of each sub power supply domain in the heterogeneous multi-core SoC, the software processing delay is eliminated, the response speed is high, the static power consumption of the power consumption management module is remarkably reduced, and the system is particularly suitable for an ultra-low power consumption scene and has a wide application prospect. And hardware-level surge current protection is realized in a multi-core power-on process.

The invention discloses a crack width measurement method and system based on dynamic topological structure analysis. A system hardware basis comprises an image acquisition module, an image processing unit, a data storage module and a result display module. According to the method, the working process of an image processing unit is divided into two stages according to a time sequence: the first stage is used for realizing data processing and crack segmentation, and the second stage is used for completing dynamic topology analysis and width measurement of cracks. In the second stage, the steps of form closed operation, skeleton extraction and enhancement, end point bridging, topological statistics and segment width measurement are executed in sequence, and finally a visual result and quantized data are output. The method comprises the following steps: processing an initial skeleton image by adopting an independently researched and developed topology enhancement algorithm; the method is especially good at processing complex net-shaped cracks, and the defect that measurement is inaccurate at crossed and bent cracks in a traditional method is effectively overcome through a dynamic topology analysis method.

Methods, apparatuses, and systems related to securing memory data are described. A hardware circuit is configured to encrypt and decrypt memory data using a scrambling key unique to a computing process processing the memory data. In writing the memory data, the hardware circuit generates scrambled memory data based on encrypting the memory data according to the security key. The scrambled memory data is stored for the write operation instead of the memory data. When the same process reads back the scrambled data, the same security key can be used to decrypt the scrambled data and recover the initial unscrambled memory data.

The invention relates to the technical field of industrial automation control, and particularly discloses a rotating speed detection and closed-loop control system based on photoelectric sensing and a PLC, and the system comprises at least one rotating body which is a rotating speed controlled object, and the surface of the rotating body is provided with a configurable number of reflection mark areas or speed measurement holes; the proximity photoelectric switches are in one-to-one correspondence with the rotating bodies, are aligned with the reflection mark areas or the speed measurement holes, and are used for detecting rotation information of the rotating bodies and generating original pulse signals; a high-speed counter input port of the PLC is electrically connected with signal output ends of the proximity photoelectric switches, and a pulse preprocessing module, a rotating speed calculation module, a deviation processing module, a control algorithm module and a signal adaptation module are arranged in the PLC. The PLC and the proximity photoelectric switch which are widely applied in the industrial field and high in popularity rate are adopted as core technical components, and expensive special servo controllers, encoders and other devices are not needed, so that the hardware purchase cost of the system is greatly reduced.

The invention discloses a wearable emotion regulation system and method integrated with an artificial intelligence algorithm, and belongs to the technical field of intelligent wearing, system hardware comprises an Arduino microcontroller, a biosensor array, an audio output module, a man-machine interaction module and a communication module; software comprises a multi-mode emotion recognition model, a self-adaptive music recommendation engine and a self-healing logic controller, implementation steps include data acquisition and preprocessing, emotion state recognition, music interaction strategies and closed-loop feedback adjustment, the system is integrated to clothes, and the system has specific sensor layout and a safety mechanism. The method can be used in the fields of depression adjuvant therapy, motion monitoring and the like.

The invention discloses a distributed crane safety monitoring and early warning device which comprises a crane main body used for hoisting materials, the crane main body comprises hardware equipment and a software system, and the hardware equipment is used for forming the crane main body and comprises a cart operation assembly, a trolley operation assembly, a main beam, a hoisting assembly and a sensor assembly. The software system comprises a data acquisition unit, a data transmission unit, a data analysis and processing unit, an early warning unit, a control unit, a man-machine interaction unit and a data storage and query unit. According to the invention, various types of sensors are reasonably arranged on each key component of the crane, and multi-source data acquisition and adaptive sampling frequency adjustment technologies are combined, so that the spatial motion state, the load state, the self-structure state and the working environment of the crane are comprehensively and accurately monitored, diversified early warning modes and graded early warning mechanisms are provided, and the safety and reliability of the crane are improved. And the pertinence and effectiveness of early warning are improved by combining context awareness and intelligent voice early warning.

The invention relates to the technical field of space optical communication and distance measurement, in particular to a distance measurement method and device based on a non-equal sampling digital phase discriminator and a storage medium. A non-equal sampling method is used for carrying out sampling and phase discrimination on data bit clocks on two asynchronous clock domains for sending and receiving GTX, and hardware resources required for processing all use an FPGA internal digital logic block; the clock processing rate and the GTX sending and receiving clock rate are kept in a non-integer multiple relationship, so that the measurement precision of the phase difference between the two clock rates is improved, and the purpose of improving the laser ranging precision on the basis of simplifying the hardware design of a ranging system is achieved.

The invention is suitable for the technical field of processors, and particularly relates to a hardware prefetching system. The hardware prefetching system comprises a processor, a first-level cache, a second-level cache, a third-level cache, a prefetching module and a memory. The prefetching module comprises a prefetching management unit, a stride prefetching unit, an optimal deviation value prefetching unit and a Markov prefetching unit; the prefetching management unit is used for dynamically selecting the stride prefetching unit, the optimal deviation value prefetching unit and the Markov prefetching unit; the stride prefetching unit is used for sending a prefetching request according to the stride between the current access address of the processor and the historical access address of the processor; the optimal deviation value prefetching unit is used for sending a prefetching request according to the optimal deviation value between the current access address and the historical access address. Compared with the prior art, different prefetching units can be selected according to the current access address of the processor through the prefetching device management module, so that the prefetching precision is improved.

The invention discloses a self-checking router network communication system, which belongs to the technical field of router network communication, and comprises a hardware module and a software module, the hardware module comprises a central processing unit used for executing system instructions and processing data, a storage unit used for storing temporary data, basic starting programs and key configuration files, and a network interface used for being connected with an external network. The software module comprises a self-checking program used for carrying out comprehensive self-checking on system hardware and software, a communication protocol stack used for realizing encapsulation, de-encapsulation and transmission of network data, and a network management module used for configuring, monitoring and managing the system; the self-checking items of the self-checking program comprise network card detection, power supply detection, connectivity detection of network connection and accuracy detection of a routing table; the system can discover and process network communication faults in time and guarantee stable operation of the network.

The invention relates to the field of oil pumping unit fault diagnosis, in particular to a multi-parameter oil pumping unit fault diagnosis method, system and device based on edge calculation and a storage medium. Multi-dimensional parameters of the operation state of the target oil pumping unit are obtained in real time; performing preprocessing and feature extraction on the multi-dimensional parameters to generate standard feature data; based on the standard feature data, performing parallel reasoning by using a machine learning model deployed in an edge computing device to obtain a fault type probability output by each model; performing weighted fusion on the fault type probability output by each model to generate a comprehensive fault diagnosis result; comparing the comprehensive fault diagnosis result with a preset threshold value to determine a fault level; and generating a corresponding control instruction according to the fault level. According to the invention, the operation state of the oil pumping unit can be comprehensively monitored, the hardware and operation and maintenance cost of the system is obviously reduced, and the requirements of an industrial field on real-time performance and high efficiency are met.

The invention relates to the field of data processing, and provides an intelligent operation and maintenance method and system for a photovoltaic inspection robot and electronic equipment, which can avoid the relevance failure among data by carrying out differentiated extraction on data of different sensors, only retaining local key information, reducing the transmission of invalid information and carrying out protocol unification and timestamp alignment. Then, on the basis of analysis and recognition, a polling path is generated through a dynamic polling priority queue and a dual-mode path planning algorithm, and finally, polling and operation and maintenance are conducted in sequence according to the path and an operation and maintenance task queue. According to the invention, the transmission and association of invalid information can be reduced, the calculation pressure and communication occupation of system hardware can be reduced, the response speed of the system can be improved, and on the basis, the system can utilize the dynamic inspection priority queue and dual-mode path planning to realize instant response aiming at different conditions, and the inspection efficiency, accuracy and effectiveness can be improved.

The invention discloses a user interrupt event callback mechanism implementation method, which adopts an implementation method of combining user interrupt event callback caused by hardware interrupt and conventional task scheduling, after system hardware interrupt occurs, kernel interrupt processing codes construct a user mode code running environment, and a user mode is switched to run a user event callback function, so that the user interrupt event callback is realized. After the execution of the user event callback function is finished, the system environment before the execution of the user event callback function is recovered through an undefined instruction falling into a kernel; and when all the user callback event functions are executed, falling into the kernel through the undefined instruction again, and recovering an instruction execution stream before the interruption event occurs by utilizing the stack frame information reserved when the interruption is entered. According to the method, an emergency processing mechanism with determined delay is realized, the constructed interrupt event callback function runs in a user space, and the method has the functions of shielding low-priority interrupt and protecting a memory, is low in overhead, simple to implement and easy to adapt to various processors, and has a good application prospect.

The invention discloses an activity identification method based on conditional antagonism data enhancement, which comprises three parts of a conditional generative adversarial network, a kinematic feature constraint module and a prototype sample generator, a system hardware structure is designed based on an embedded heterogeneous computing platform, a main processor adopts an ARM Cortex-A72 core operation condition generative adversarial network, and the model sample generator is designed based on an embedded heterogeneous computing platform. The coprocessor adopts NPU to accelerate kinematics parameter calculation, and the sensor interface module is connected with a six-axis IMU sensor through an SPI bus to collect data of an accelerometer and a gyroscope in real time. According to the activity recognition method based on conditional antagonism data enhancement, enhancement data with diversity, authenticity and semantic accuracy can be provided for a human body activity recognition model in a scene of insufficient training data, so that the overall recognition accuracy of the model on a UCI HAR data set is improved by 14.7%, the F1 value on the aspect of few sample categories is averagely improved by 21.3%, and the recognition accuracy of the model on the UCI HAR data set is greatly improved. And an effective technical solution is provided for data scarce scenes such as medical monitoring and motion analysis.

The invention discloses a positioning method for generating a pseudo LiDAR descriptor for cross-modal matching based on visual depth estimation, and the method comprises the following stages: in an offline training stage, obtaining synchronous multi-modal data, inputting a camera image into a pre-trained monocular depth estimation network, generating a dense depth map, and carrying out the alignment; training a global descriptor generation network with weight sharing; a laser LiDAR global descriptor database is constructed; an on-line positioning stage: acquiring a surrounding environment image; inputting the image into a pre-trained monocular depth estimation network to generate dense depth map alignment; inputting a global descriptor generation network, and generating a visual global descriptor; and performing cross-modal descriptor retrieval and matching. Generating a geometrically aligned pseudo LiDAR depth map through monocular depth estimation, and realizing cross-modal matching with a real LiDAR map; the system hardware threshold is obviously reduced; introducing a triple supervision mechanism based on geometric overlapping degree and a yaw angle invariant descriptor network of weight sharing; and a modal gap between the vision and the LiDAR is bridged.

The invention discloses a system problem analysis method and device based on a Linux system. The method comprises the following steps: starting a data collection service, and collecting the following system data: system software data, system hardware data, kernel operation data and system security data; storing the collected system data in a database; analyzing the system data of the specified time period in the database through a preset rule, determining abnormal data, and generating an analysis result; and displaying the analysis result in a visual data chart form. According to the scheme, the data information existing in the system can be quickly and visually checked, and the time consumed by data arrangement and collection is shortened; when system operation and maintenance work is carried out, possible problems can be found in advance, so that the time consumed for continuously carrying out problem analysis and positioning in the operation and maintenance process is shortened; a visual analysis report can be output, the granularity of data is improved, and operation and maintenance personnel are helped to carry out problem positioning and system maintenance more quickly.

Embodiments of the present application provide a data access method and system, a hardware offloading device, an electronic device, and a medium. In the embodiments of the present application, on one hand, a data access task for an object-based storage system is transferred from an electronic device to a hardware offloading device for execution, which can reduce processing pressure on the electronic device, improve processing performance of the electronic device, and enhance data access performance. On the other hand, after every time receiving a to-be-written file from an application, the hardware offloading device does not directly write the to-be-written file into the object-based storage system, but first caches it locally, and after a plurality of to-be-written files are cached, the hardware offloading device merges the plurality of to-be-written files into a new object file to write it into the object-based storage system.

A system and method for facilitating various forms of cyber training. In some embodiments, the system and method enable the creation and deployment of cyber ranges. Such a cyber range can simulate one or more network environment(s) of one or more real or hypothetical organizations for various network, software, and system / hardware components, as well as simulations of various network traffic.

The invention relates to the technical field of computer system security, in particular to a method and a system for constructing an endogenous trusted container of a Kylin system of a cryptographic chip. Comprising the following steps: integrating a domestic cryptographic chip to a hardware platform of a kylin system, establishing a high-speed secure communication channel between the domestic cryptographic chip and a CPU memory, and performing initialization configuration on the cryptographic chip when the system is started, including loading a key, setting a national cryptographic algorithm and configuring a security strategy; according to the method, the domestic cryptographic chip is deeply integrated on the hardware platform of the Kylin system, a hardware-level secure communication channel is established, initialization configuration is carried out, a hardware trust root based on the cryptographic chip is provided for trusted container construction, and the trusted reference of the system is improved from the bottom-layer architecture level.

The invention discloses a 1-bit DAC precoding optimization design method suitable for a large-scale MU-MIMO system, and the method comprises the steps: setting base station data configuration, and modulating an input symbol vector; quantizing the modulated input signal by using a 1-bit DAC (Digital-to-Analog Converter); generating a complex cyclic symmetric Gaussian random channel matrix H by adopting Rayleigh distribution; designing a signal of a receiver end; establishing a 1-bit DAC precoding optimization problem based on a minimum mean square error according to the average transmitting power of the base station and a 1-bit DAC character set constraint; a mean square error between a recovery signal and an input signal is minimized by utilizing a designed ADMM-HB method under the constraint of the average transmitting power of a base station and a 1-bit DAC character set. According to the method, the ADMM-HB method is used in the optimization process, the signal mean square error of the receiving end and the transmitting end can be minimized with low calculation complexity, the system efficiency is improved, the system hardware cost and power consumption are reduced, and the method better conforms to engineering practical application.

The invention relates to the technical field of automobile infotainment, and discloses an automobile infotainment theme production binding method, system and device and a storage medium, and the method comprises the steps: obtaining an original data flow of a vehicle multi-mode sensor; analyzing the original data stream to generate a standardized feature vector; outputting a scene label corresponding to the current vehicle by analyzing the feature vector; dividing the to-be-started application process into different grades according to a preset scene grading mapping table; allocating corresponding hardware resources to different levels of application processes, and dynamically adjusting an allocation scheme of the hardware resources of the vehicle-mounted system; according to the adjusted resource allocation scheme, the application processes of the corresponding levels are started in sequence; and when it is detected that the feature vector has a change exceeding a preset threshold, re-outputting the scene label, and synchronously updating the application process grading and resource allocation scheme according to the re-output scene label. Therefore, quick starting of the application process, reasonable distribution of system resources and optimization of user experience are realized.

The invention discloses a commercial vehicle air suspension system hardware-in-the-loop test device and method, the device comprises an ECAS test bench and an HIL test system, the ECAS test bench comprises a bench body, an external pressure sensor and an external displacement sensor, the external pressure sensor is arranged at an air bag air inlet of the bench body, and the external displacement sensor is arranged at an air bag air outlet of the bench body. The external displacement sensors are arranged at detection points in all directions of the rack body; the HIL test system comprises a fault injection module, an acquisition module and an upper computer. According to the invention, after fault injection of the ECAS system to be tested, the external pressure sensor and the external displacement sensor are used to replace a sensor of the ECAS system to be tested to carry out data acquisition so as to realize normal data acquisition when a fault environment is simulated. The system is complete in function, can simulate a simulation environment through the change of the test bench, and also can collect data and test the suspension function under the condition that the ECAS system to be tested has a fault.

The invention relates to the technical field of energy storage system data information, and discloses an energy storage system data acquisition method and an energy storage system. In the application, after the acquisition configuration information is issued to the intermediate service layer, the acquisition configuration information is analyzed through the intermediate service layer to obtain the acquisition equipment and the acquisition protocol, so that decoupling between the acquisition task and the acquisition equipment is realized; furthermore, corresponding library files are matched in an equipment library and a protocol library according to the analyzed collection equipment and the collection protocol and are loaded, so that the dynamic loading of the collection task is realized, and finally, the current collection task is generated and operated, and the association between the collection task and the hardware equipment of the energy storage system is reduced; therefore, the expandability and reusability of the acquisition system are improved, and the operation of the acquisition task can be realized without reconstructing the whole acquisition system under the conditions of large data acquisition demand quantity and multiple types.

The invention relates to the technical field of mine safety and intelligent management, and provides a goaf grouting resource multi-modal scheduling method and system, which realize multi-dimensional perception of goaf fire through multi-modal data fusion, and improve comprehensiveness and accuracy of anomaly recognition. A Transform model and an improved evidence theory are introduced, so that the correlation analysis capability of cross-modal data is enhanced, and the false alarm rate is effectively reduced; dynamic deduction is combined with a physical model and deep reinforcement learning, so that the dynamic adaptability of fire development prediction is improved; path planning is fused with a heuristic algorithm and an AR visualization technology, and intelligent dynamic optimization of an escape path is achieved; a four-level response mechanism and an intelligent resource scheduling strategy are adopted, so that the emergency disposal period is shortened, and the grouting material matching and equipment scheduling efficiency is improved; the anti-interference capability and the self-diagnosis function are enhanced by the hardware design of the system, and the stability of data acquisition in a complex environment is guaranteed; the lightweight model and parallel computing technology improve the efficiency of real-time analysis and multi-fire-zone deduction.

The application discloses a card display method, and belongs to the technical field of visualization. The method comprises the following steps: in response to a dynamic card display request under a target scene, loading a target container corresponding to the dynamic card, and simultaneously acquiring a resource package associated with the dynamic card; under the condition that the target container is loaded and the resource package is acquired, processing the resource package; and rendering the processed resource package through the loaded target container, so as to display the dynamic card under the target scene. The core of the application is to process the time-consuming container loading and resource package acquisition processes in parallel, break the performance bottleneck of traditional serial loading, significantly shorten the total loading time, improve the loading efficiency, reduce the user perception delay, optimize the user experience, and improve the parallel utilization rate of system hardware resources.