113 results about "Instruction distribution" patented technology

The invention relates to the technical field of hydraulic engineering monitoring, and discloses a hydraulic engineering operation risk monitoring management system based on multi-sensor fusion. The system comprises a data acquisition module, a data fusion module, an early warning and instruction generation module, and an instruction distribution and verification and correction module. The data acquisition module acquires structural deformation, water flow pressure and environment temperature and humidity data in real time through multiple types of intelligent sensors; the data fusion module inputs the collected data into a dynamic weighted fusion model, and generates a comprehensive monitoring index in combination with a sensor confidence coefficient weight and a historical data deviation rate; the early warning and instruction generation module triggers multi-stage early warning and generates an equipment regulation and control instruction set according to the comprehensive monitoring index and a preset safety threshold value; the instruction distribution module distributes the instruction to an execution terminal through a distributed message queue; and the verification and correction module checks terminal feedback signals by using a back propagation verification mechanism, and corrects the confidence coefficient weight of the model.

The invention relates to the technical field of power system dispatching, in particular to a distributed storage system for source-network-load-storage collaborative dispatching, which comprises a distributed data acquisition module, a regional collaborative sensing module, a distributed energy storage evaluation module, a dispatching instruction generation module and a dispatching instruction distribution module, wherein the distributed data acquisition module is used for acquiring real-time operation data of source, network, load and storage nodes in parallel; the regional collaborative sensing module is used for calculating a real-time power deviation value; the distributed energy storage evaluation module is used for generating an energy storage adjustment instruction set; and the scheduling instruction generation module is used for generating a final refined scheduling instruction. According to the invention, through constructing a cooperative scheduling mechanism of the source network load storage full chain, accurate identification of power deviation and optimal distribution of energy storage resources are realized, and scheduling response efficiency and operation stability of the system are significantly improved.

The invention relates to the technical field of call center control, and discloses an unmanned vehicle formation control and obstacle avoidance reconstruction system based on complex road conditions. The system call data acquisition module is used for acquiring multi-source interaction data in real time; the dynamic feature extraction module is used for performing semantic intention hierarchical analysis on the voice stream text conversion data, performing event fragment segmentation on the user behavior time sequence data, and generating an operation track feature vector; the scene clustering engine module is used for performing space-time alignment on the semantic intention hierarchical analysis result and the event fragment segmentation result to generate a multi-dimensional scene clustering tag; the strategy matching core module is used for retrieving an interaction strategy set matched with the current scene from a distributed strategy library according to the multi-dimensional scene clustering label and generating a dynamic control instruction sequence; and the instruction distribution execution module is used for distributing the dynamic control instruction sequences to corresponding seat terminals and voice routing equipment after sorting the dynamic control instruction sequences according to priorities.

The invention relates to the technical field of industrial internet, in particular to a control system and method for stirrer production. Comprising an edge data preprocessing unit, a flexible production instruction distribution unit and a working condition diagnosis and protection control unit. By constructing an integrated control parameter mapping model, an industrial operation signal is converted into a collaborative sensing digital primitive; the production task is compiled into an intelligent production execution process cluster based on a resource scheduling algorithm, and equipment is driven to execute differentiated production; and performing situation assessment on the digital primitives by using the anomaly detection model, and generating a regulation and control instruction to execute process logic recombination and safety protection. According to the invention, the problems of low production information integration level and tight data in each link of a production control system are solved, and flexible scheduling and active security defense in the production process are realized.

The invention discloses a self-coupling PID (proportion integration differentiation) flight control method of a rudder-controlled transverse-row type rotor unmanned aerial vehicle based on dynamic multi-dimensional heterogeneous fuzzy logic, and belongs to the technical field of flight control of rudder-controlled transverse-row type rotor unmanned aerial vehicles. A flight control system architecture of the self-coupling PID flight control method is composed of three core modules: (1) a dynamic multi-dimensional fuzzy logic coupling PID controller (DMHFL-SCPID); (2) control instruction distribution; and (3) a six-degree-of-freedom dynamical model of the rudder-controlled transverse rotorcraft. According to the control algorithm, input and output dynamic parameters of a system are analyzed in real time, and four-dimensional flight control quantities (roll, pitch, yaw and height instructions) are generated. A control distribution strategy based on the aerodynamic characteristics of the rotor converts the instructions into actuating quantity of an actuating mechanism, and flight attitude adjustment is realized by changing aerodynamic load distribution of a rotor system, so that the unmanned aerial vehicle is guided to realize accurate tracking along a predetermined flight path.

The invention relates to the technical field of mobile communication and Internet of Things, and discloses a heterogeneous network space multi-level mobile Internet of Things cloud system based on artificial intelligence, which comprises a data acquisition module for acquiring real-time state data of a mobile Internet of Things terminal and generating a standardized network-service joint situation vector; the endogenous interference sensing module is used for generating a network interference association diagram based on the vector; the service-network dynamic decoupling module is used for reversely reconstructing terminal service characteristics according to the association diagram and decoupling a key network state sequence; the business intention abstraction module constructs a heterogeneous network cooperation state target according to the sequence; the collaborative scheduling strategy generation module is used for generating a multi-dimensional collaborative scheduling instruction by using a collaborative decision model; the network resource self-growing module is used for performing state sequence evolution after the rehearsal instruction and constructing a compensation network plane; and the instruction distribution and verification module is used for executing the instruction of the fusion compensation logic and updating the association diagram. According to the method, the problems of heterogeneous network interference and scheduling lag of the mobile Internet of Things are effectively solved.

The invention discloses an AI-based multi-device cooperative control method in an Internet of Things environment. By constructing a'perception-decision-control-feedback-self-adaption 'full-closed-loop architecture, terminal components such as an intelligent equipment group and a sensor group of an equipment layer, a multi-source data acquisition and enhancement preprocessing module of a perception layer, a dynamic equipment capability graph of an AI decision layer, an incremental AI decision model and other core units are integrated; and a cross-protocol instruction distribution and closed-loop feedback module of the control layer realizes deep processing of multi-source heterogeneous data, real-time perception of equipment capability, dynamic adjustment of task priority and autonomous optimization of a coordination strategy, thoroughly solves the technical problems of rigid coordination logic, response lag and unreasonable resource allocation of a traditional method, and improves the reliability of the system. And the intelligent level and the operation efficiency of the Internet of Things system are greatly improved.

The invention relates to the technical field of wireless communication synchronization and gate valve action collaboration, in particular to a multichannel audio master-slave sound role intelligent conversion system and method.A master control unit broadcasts a time calibration packet to synchronize unit clocks, and an automatic calibration protocol is executed to generate an inherent processing delay baseline value; the subordinate gate valve unit records an instruction receiving and action completion timestamp through a delay detection module, calculates actual delay containing wireless transmission and local processing delay, and packages the actual delay into a structured feedback data packet for real-time feedback; a dynamic adjustment module of the main control unit filters noise through a weighted moving average algorithm, and calculates individual compensation delay parameters in combination with the dynamic buffer compensation amount of the environment interference monitoring module and delay trend prediction of an adaptive learning engine; and when abnormity occurs, historical data is called for replacement and self-inspection is triggered, an instruction distribution time sequence is adjusted according to compensation parameters, a gate valve action execution confirmation module verifies the displacement precision, and the fluid control precision and stability are improved.

This application relates to the field of smart terminal technology and provides a method, system, apparatus, terminal device, and storage medium for multi-user collaborative editing. The method includes: immediately executing the operation instruction when a user's operation instruction is detected and updating the execution result to a local transient state; sending the operation instruction to a server, where the server performs conflict detection on the operation instruction, assigns a sequence number to the operation instruction, generates a pre-ordered operation instruction set, and updates the global baseline state; receiving the pre-ordered operation instruction set broadcast by the server; comparing the local transient state with the global baseline state based on the pre-ordered operation instruction set, and if there is a state difference, changing the local transient state to make it consistent with the global baseline state, and updating the consistent local transient state to the local baseline state. This application can efficiently and reliably achieve eventual consistency of the states of each client, improving the smoothness and efficiency of multi-user collaborative editing.

The application relates to a session instruction distribution method and device, equipment, a storage medium and a program product. The method comprises the following steps: receiving a current instruction in a current session, the current instruction being an instruction for calling a target object, and the current instruction carrying a current session identifier corresponding to the current session; for each instance identifier in an instance identifier set, determining a target weight corresponding to the instance identifier based on the current session identifier and the instance identifier, the instance identifier representing an instance for running the target object; selecting a target instance identifier from the instance identifier set based on the target weight, and distributing the current instruction to a target instance represented by the target instance identifier for execution. The method can improve the execution effect.

The invention relates to a program analysis method and device, electronic equipment, a storage medium and a computer program product, and the method comprises the steps that before a target program runs, a sampling buffer area is allocated to the target program, and the sampling buffer area comprises sampling buffer partitions allocated for each instruction in the target program; when any sampling moment is reached in the running process of the target program, instruction counter sampling is carried out, a sampling instruction of this time is determined, and a sampling counter in a target sampling buffer partition corresponding to the sampling instruction of this time is updated through atomic operation; after the operation of the target program is finished, determining the total sampling frequency of each instruction in the target program according to the sampling buffer area; and according to the total sampling frequency of each instruction in the target program, performing performance analysis on the target program to obtain a performance analysis result. According to the embodiment of the invention, the operation of the target program is not influenced under the condition that the sampling precision is ensured, and the performance analysis of the target program is effectively realized.

A method for parallel decoding which is applied to a processor including a first decoder cluster and a second decoder cluster, the second decoder cluster being provided with at least one shared decoder shared by the first decoder cluster. In the method, if a quantity of a plurality of instructions is greater than a quantity of decoders in the first decoder cluster, the processor assigns, from the plurality of instructions, first instructions with a quantity corresponding to the quantity decoders of the first decoder cluster to a decoder in the first decoder cluster for decoding, and the processor assigns, from the plurality of instructions, at least one second instruction other than the first instructions to the at least one shared decoder for decoding. The processor then writes micro-ops obtained by decoding the first instructions and micro-ops obtained by decoding the at least one second instruction into a first micro-op queue.

The invention relates to an instruction scheduling method and apparatus, a semiconductor device and a medium. The method comprises the steps of storing a plurality of received service instructions of a service process; distributing a corresponding time slice for each service instruction of the stored service process; and under the condition that the received control instruction indicates that the service process needs to be started, sending the service instruction in the corresponding time slice. According to the method, the efficient execution of the instruction can be realized, the uncertainty caused by communication with the service process in the instruction execution process is eliminated, and the communication reliability is high; and a specific hardware architecture does not need to be adapted, so that the compatibility is good.

This invention provides an access control method, device, and storage medium for a smart grid information system, belonging to the field of smart grid information systems. The method includes: obtaining a time series of current performance indicators; calculating the trust level of intermediate nodes in data transmission using a trust assessment model; allocating transmission paths for each instruction based on its importance and the trust level of the intermediate nodes, thus obtaining a set of instruction paths; determining the access control level of the intermediate nodes based on the path set; and continuously evaluating the trust level of the uploading data source nodes during instruction issuance, and obtaining the transmission path for the uploaded data based on the access control level of the intermediate nodes, and then uploading the data. This invention can capture temporal dependencies, accurately reflect the real-time trust level of nodes, and adapt to changes in the dynamic network environment, effectively responding to sudden failures or attacks.

The embodiment of the invention discloses a processor, a data processing method and computer equipment, and belongs to the technical field of computers. The processor comprises a scalar processing module, a vector processing module and a matrix processing module. The scalar processing module is connected with the vector processing module and the matrix processing module. A scalar processing module in the processor not only has a function of executing a processing instruction for scalar data, but also has an instruction distribution function, so that vector processing instructions in an instruction packet can be distributed to a vector processing module, and matrix processing instructions in the instruction packet can be distributed to a matrix processing module; according to the technical scheme, a module used for distributing instructions does not need to be independently deployed in the processor, the structure of the processor is simplified, the unnecessary data interaction process caused by the fact that the instruction distribution module distributes the scalar processing instructions in the instruction packet to the scalar processing module can be avoided, the data interaction efficiency is guaranteed, and the user experience is improved. Therefore, the processor quickly responds to the received processing instruction, and the data processing efficiency of the processor is ensured.

The invention belongs to the technical field of unmanned aerial vehicles, and discloses a digital twinning enabling global cooperative disturbance and destruction anti-unmanned aerial vehicle system. Comprising the steps of multi-source heterogeneous data acquisition and preprocessing, global scene digital twinning modeling, multi-protocol compatible defense instruction generation, intelligent terminal mainboard function verification and instruction distribution, global defense resource dynamic cooperative control and digital twinning-based disturbance effect evaluation, and dynamic closed loop of sensing, decision making, execution and feedback. According to the method, tactical strategies can be adjusted in real time to cope with emergencies, and particularly, based on digital twinning quantitative effect evaluation, simulation results are compared with actual warfare, and objective defense success rate and resource consumption rate reports are generated, so that each action experience can be converted into nutrients of an optimization algorithm model, and the success rate of defense is improved. And the overall countering capability is promoted to evolve continuously in iteration, and a continuous efficiency improvement mechanism for evaluating and optimizing closed-loop driving is formed.

The application provides a kind of intelligent computing resource scheduling terminal of vehicle cloud cooperation, is deployed in edge cloud node, including full source data sensing and interactive interface, cognitive front-end processing, strategy reasoning decision, computing resource arrangement instruction distribution and performance monitoring and reward calculation module, can realize with scheduling task description generation and receive candidate computing node's node state report and maintain the resource index table of node, node matching feature extraction, target node decision, instruction issuing and execution feedback whole process operation.The application faces intelligent transportation, autonomous driving and other cross-domain collaborative tasks, and for the decision-making uncertainty area formed by the lack of priori discriminability of the execution side selection executed by the vehicle end / cloud end, through the priori matching evaluation of cognitive front-end and strategy reasoning cooperation, the decision-making computing burden of high-dimensional multi-source state can be reduced, and the risk of improper execution side selection can be reduced, so as to improve the computing real-time performance, success rate and system operation safety of vehicle cloud cooperation task.

A graphics processor and resource access method and terminal device, the graphics processor comprises: a stream processor, an adapter, a general-purpose channel and a unified resource memory, wherein: the stream processor comprises N operation execution units divided into M groups; the adapter is adapted to receive a shader resource access instruction and distribute the shader resource access instruction to the M groups; each group comprises at least one operation execution unit; the adapter is adapted to process the shader resource access instruction output by the corresponding group to obtain a unified access instruction and output the unified access instruction to the general-purpose channel corresponding to the corresponding group; the general-purpose channel is adapted to access the unified resource memory based on the received unified access instruction; and the number of general-purpose channels is M. The above scheme can effectively balance different types of shader resources, avoid waste of hardware resources of the graphics processor and improve the performance of the graphics processor.

The invention belongs to the technical field of dog training, and particularly relates to a group behavior regulation and control method and system based on multi-dog cooperative training, and the method comprises the following steps: collecting the spatial position and social behavior data of dogs through an intelligent necklace; on the basis, constructing a group behavior map fusing the physical space relationship and the social influence; dynamically identifying a real-time role of each dog by utilizing a graph theory centrality index; according to the role and the current behavior state, a differential control instruction is generated through a state-role-behavior multi-dimensional instruction mapping model; and finally, executing an instruction and monitoring response data so as to optimize the model and realize closed-loop adaptive adjustment. According to the method, through accurate role identification and differentiated instruction distribution, the problem of group behavior conflict caused by unified instructions is effectively solved, the instruction conflict rate is remarkably reduced, and the efficiency and adaptability of group cooperative training are continuously improved by using a closed-loop learning mechanism.

The embodiment of the invention discloses a flying object control method and device and related equipment, and can be applied to the technical field of data processing. The method comprises the following steps: acquiring a first type control instruction sent by a flight instruction distribution module; the first type control instruction is an instruction generated by the dynamics processing module and sent to the flight instruction distribution module, and the predicted flight path information is determined by the flight auxiliary processing module; acquiring a second type control instruction sent by a flight instruction distribution module; the second type control instruction is an instruction generated by the control operation processing module in response to the control operation for the flying object; determining target control attribute data through the first type control instruction and the second type control instruction; and determining second pose information through the target control attribute data and the first pose information, and controlling the flight object to fly in the flight environment according to the second pose information. According to the embodiment of the invention, the flight control efficiency of the flight object can be improved.

The invention provides a processor transmission queue design method based on data dependence and branch prediction confidence, which comprises the following steps that: a transmission queue in a processor acquires a new enqueue instruction, and allocates an idle transmission queue list item; when the new enqueued instruction enters the transmitting queue, judging whether an instruction on which the new enqueued instruction depends exists in the transmitting queue or not by utilizing a source operand register number of the new enqueued instruction, and if so, adding one to the priority of the instruction on which the new enqueued instruction depends in the transmitting queue; judging whether the correct probability of the branch instruction in the new enqueue instruction is lower than a preset value or not, and if yes, adding one to the priorities of all instructions under the branch where the new enqueue instruction is located in the transmitting queue; the branch prediction confidence is the probability of whether the branch instruction is predicted correctly; and selecting a ready instruction with the highest priority from all idle instructions in the transmission queue list item, and sending the selected instruction to a functional unit in the processor for execution.

The invention provides a database instruction execution method and system for a power system, and relates to the technical field of power system database management, and the method comprises the steps: obtaining a database operation instruction and a target data object; performing semantic analysis on the instruction to construct an access dependency graph; identifying a cascade influence range according to the dependency graph, and determining a data object set needing to be synchronously locked; decomposing the operation instruction into a plurality of sub-instructions and distributing execution priorities; and allocating a resource isolation identifier to the sub-instruction, and limiting and executing a data access permission. According to the method, by identifying the cascade influence range of electrical association, data operation conflicts are effectively avoided, and the concurrency performance and safety of database operation of the power system are improved.

The present disclosure relates to a program analysis method and device, electronic equipment, storage medium and computer program product, the method comprising: allocating a sampling buffer for a target program before the target program runs, the sampling buffer comprising a sampling buffer partition allocated for each instruction in the target program; when reaching any sampling moment during the running of the target program, performing instruction counter sampling, determining the sampling instruction, and updating the sampling counter in the target sampling buffer partition corresponding to the sampling instruction through atomic operation; after the running of the target program ends, determining the total sampling number of each instruction in the target program according to the sampling buffer; and performing performance analysis on the target program according to the total sampling number of each instruction in the target program to obtain a performance analysis result. According to the embodiments of the present disclosure, the performance analysis on the target program can be effectively implemented without affecting the running of the target program under the condition of ensuring sampling accuracy.

A data storage system includes a controller comprising pipelined multiple processors. The controller is configured to: generate plural instructions having dependency based on a command, input from an external device, for controlling at least one storage device to perform an operation corresponding to the command; allocate the plural instructions to the pipelined multiple processors in stages; and reallocate, when a number of second instructions allocated to a second processor of the pipelined multiple processors becomes a first threshold or greater, at least one of the second instructions to a first processor of the multiple processors.

The application discloses a processor, a processing method and related equipment, wherein the processor comprises a processor core, the processor core comprises an instruction scheduling unit, a graph computing flow unit connected with the instruction scheduling unit and at least one general-purpose computing unit; wherein the instruction scheduling unit is configured to distribute general-purpose computing instructions in decoded to-be-executed instructions to the at least one general-purpose computing unit and distribute graph computing control instructions in the decoded to-be-executed instructions to the graph computing unit, the general-purpose computing instructions are used to instruct to execute general-purpose computing tasks, and the graph computing control instructions are used to instruct to execute graph computing tasks; the at least one general-purpose computing unit is configured to execute the general-purpose computing instructions; and the graph computing flow unit is configured to execute the graph computing control instructions. By using the application, the processing efficiency of the processor can be improved.

This invention relates to the field of network security technology, and more specifically to a cloud-edge collaborative security response method that integrates policy self-generation and resource orchestration. It proposes a policy self-generation mechanism that uses AI algorithms such as reinforcement learning to achieve dynamic and adaptive generation of security response policies, rather than relying on preset static rules. It also achieves automated orchestration of security response scripts, transforming high-level self-generated policies into executable atomic operation sequences, thus improving the level of response automation. Furthermore, it constructs a deep cloud-edge collaborative security response system that, through a unified communication and control module, achieves seamless collaboration and instruction distribution and execution of security capabilities between the cloud and the edge.

The application discloses a kind of multi-blowing machine collaborative production and resource optimal scheduling system and method, it is related to industrial manufacturing technical field.The method includes: obtaining global scheduling information including order, resource and environmental parameter;Real-time acquisition of the parison temperature field and material rheological property of each blowing machine and other multivariate working condition information;Based on the above information, integrated decision is made through collaborative scheduling optimization model, and collaborative scheduling instruction set containing production task allocation and process parameter instruction adapted to the real-time working condition of each machine is generated;Finally, it is issued and driven to execute blowing machine.The system corresponds to include global information perception, multivariate working condition acquisition, collaborative scheduling decision and instruction distribution execution and other modules.The application realizes integrated global optimization of task, process and resource by deeply integrating core process state perception into scheduling decision, effectively improves the comprehensive performance, quality consistency and dynamic adaptability of multi-machine collaborative production.

The present invention relates to a vision-language large model-based multi-robot collaborative navigation method and system. The method includes steps of: according to a task instruction input by a user, combined with a semantic map constructed by each robot, allocating subtask instructions to robots after parsing by a large language model; acquiring, by each robot, an environmental image in real time, according to the allocated subtask instruction, parsing and predicting a next action using a vision-language navigation large model, and executing a corresponding action and updating a state by the robot; and monitoring a robot state and checking task progress in real time through a human-machine interface and adjusting a task or handling an exception during execution when needed by an operator, and dynamically adjusting, by the robot, an execution strategy according to feedback information to optimize navigation for task completion.

The invention relates to the technical field of digital employees, and discloses a digital employee-oriented multi-mode office scene perception and data acquisition system. The system comprises a multi-modal data acquisition module, which is used for acquiring text, voice and image data by using a microphone array and the like, and generating an original data queue through framing, semantic segmentation and the like; the multi-modal feature fusion module extracts joint features based on a cross-modal attention mechanism, and generates a semantic association feature matrix; the privacy protection processing module generates desensitization feature data through a sensitive information identification model, a dynamic fuzzy processing strategy and the like; the space-time alignment optimization module constructs a model and an algorithm to carry out space-time alignment on the multi-source data; and the instruction distribution execution module distributes the instruction to the target terminal equipment through the layered architecture. The system can comprehensively sense office scenes, efficiently fuse multi-modal data, guarantee data safety, optimize space-time alignment and accurately execute instructions, improve office efficiency of digital employees and assist enterprises in intelligent office.