767 results about "Processing Instruction" patented technology

The invention discloses a machine tool control method and system based on mechatronics, and the method comprises the steps: outputting an optimal cutting track sequence according to the three-dimensional model features and material attribute parameters of a machined workpiece; based on the optimal cutting track sequence, motion interference among shafts of the machine tool is eliminated through dynamic weight distribution, and an anti-interference optimization machining instruction is generated; constructing a nonlinear vibration wave propagation model according to the coupling relation between the spindle rotating speed and the feeding speed, and generating a steady speed regulation and control signal; generating an energy efficiency optimal parameter set including motor torque, cooling power and lubricating frequency based on the energy consumption efficiency constraint condition and the steady speed regulation and control signal; and outputting a closed-loop control signal and synchronously updating the three-dimensional machining precision thermodynamic diagram according to the real-time data in the machining process and the predicted deviation of the digital twin model. According to the embodiment of the invention, global optimization, dynamic adaptation and efficient operation of the machine tool can be realized, and technical support is provided for intelligent upgrading of the modern manufacturing industry.

According to the instruction processing system, method and device provided by the invention, the instructions can be efficiently and smoothly distributed and run through the at least one processing module of the processor, and different instruction distribution logics are adopted based on different types of business processing instructions through two-stage instruction distribution, so that the service processing efficiency is improved. The business processing instructions are stored in the target storage area and then scheduled to the instruction execution module, so that quick distribution and hardware support of different types of business processing instructions are realized, the instruction distribution efficiency is greatly improved, complex calculation tasks can be flexibly and efficiently processed, instruction scheduling can be performed according to the priorities of the business processing instructions, and the service processing efficiency is improved. The key business operation is ensured to be responded and processed in time, and the overall performance and the operation efficiency of the database processor are effectively improved. The technical effect of flexibly and efficiently processing the database acceleration task is achieved.

The invention discloses a spacecraft intelligent design method and system capable of autonomously learning, and belongs to the technical field of spacecraft design and simulation. The problems that in spacecraft design, natural language requirements are fuzzy and difficult to process, instruction generation is prone to ambiguity, linkage between simulation and design is not smooth, a design scheme lacks an effective iterative optimization mechanism, and traditional design is low in efficiency are solved. The method comprises the following steps: firstly, receiving a natural language demand, extracting key parameters to generate prompt words, inputting the prompt words into Design.AI, and generating a simulation instruction sequence; simulation is started through MCP Server conversion, if the result does not reach the standard, feedback correction is carried out, and iterative optimization is carried out. And repeating the steps until a design target is met, and generating a design report containing multiple items of content. Through natural language processing, real-time simulation, iterative optimization, knowledge accumulation and other technologies, the spacecraft design efficiency is greatly improved, the accuracy is enhanced, the threshold is lowered, and the flexibility is improved.

The invention discloses a private network data security detection method based on big data, and belongs to the field of security detection, and the method comprises the steps: obtaining a real-time data packet from private network traffic, encoding the data packet through a forward error correction code technology, generating redundancy check information, and obtaining an encoded data packet; if a bit error is detected in the transmission process of the coded data packet, requesting a sending end to retransmit a damaged data packet through an automatic retransmission request mechanism to obtain a retransmitted data packet; adjusting the redundancy of a forward error correction code and a trigger threshold of an automatic retransmission request according to the adaptive error correction parameter, generating an optimized error correction scheme, and obtaining a repaired data packet; and aiming at the alarm processing instruction, automatically adjusting a network flow control strategy, limiting the transmission bandwidth of an abnormal destination, updating the sensitive data fingerprint database, and obtaining optimized protection configuration.

The invention relates to the technical field of network communication, and discloses an intelligent control method and system of a switch. The method comprises the following steps: receiving a heterogeneous data stream in a target network domain; performing data processing by using a preset flow feature aggregation model, and generating a flow dynamic pressure field distribution diagram and a protocol priority mapping matrix; constructing an adaptive scheduling threshold model, and generating a multi-target flow control instruction set; a cascade effect is simulated based on a network congestion chained conduction model, and collaborative routing parameters are optimized; and iteratively optimizing through a mixed integer programming framework, and outputting a network scheduling action sequence to a switch control engine. The system correspondingly comprises a data receiving module, a data processing module, an instruction generation module, a simulation optimization module and an instruction output module. According to the method, heterogeneous data can be effectively processed, congestion can be accurately predicted, flow control can be optimized, the overall performance of the network can be improved, and communication requirements in a complex network environment can be met.

One aspect of the instant disclosure may provide a system and method for processing scatter-gather direct memory access (S-G DMA) instructions. During operation, the system may receive an S-G DMA instruction associated with a message and gather instruction context for the S-G DMA instruction. An S-G DMA processor may process the S-G DMA instruction based on the gathered instruction context and determine whether there exists a pending S-G DMA instruction associated with the message. In response to the presence of the pending S-G DMA instruction, the system stores the instruction context in a hot context cache at an address corresponding to the pending S-G DMA instruction. In response to the absence of the pending S-G DMA instruction, the system stores the instruction context in a cold context cache.

A computer-implemented system for automated document generation receives user input and processes it through artificial intelligence models to create professional documents. The system combines user-provided information with specialized knowledge databases containing domain-specific requirements and formatting standards to generate enhanced processing instructions. Trained machine learning models process these instructions to produce contextually appropriate content that addresses specific technical and legal requirements. The generated content is formatted using configurable templates to create completed documents that meet professional standards. The system provides adaptive user interfaces that adjust functionality based on user expertise levels, supports multiple operational modes including guided and automated generation, learns from example documents to improve output quality, and enables comprehensive workflow management through network-accessible services. Applications include patent applications, legal responses, technical documentation, and other specialized professional documents requiring domain expertise and regulatory compliance.

The invention relates to a synchronous processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a to-be-processed task, splitting the to-be-processed task into at least one to-be-processed instruction, and distributing the to-be-processed instructions to different thread processing units; obtaining an access sequence barrier corresponding to the to-be-processed task, and sending the access sequence barrier to each thread processing unit; when the execution of the at least one to-be-processed instruction is completed, generating access sequence barrier execution completion feedback information, and storing the access sequence barrier execution completion feedback information to a target barrier cache region corresponding to the thread processing unit; if the corresponding access sequence barrier execution completion feedback information is stored in each target barrier cache region, it is determined that the to-be-processed task is completed, and the target barrier cache regions correspond to the thread processing units. By adopting the method, the processing efficiency can be improved.

The invention provides a multi-source network equipment fault mode identification and positioning method and system, and relates to the technical field of computer fault diagnosis, and the method comprises the steps: collecting equipment hardware data and software data, generating a fault feature vector, collecting adjacent equipment information, and constructing a communication relation graph and a link abnormity probability distribution graph; determining fault source equipment and probability through correlation analysis; according to the method, the processing instruction is generated, and the baseline data is updated, so that the computer network fault can be accurately identified and quickly positioned, the fault processing efficiency is improved, and the network maintenance cost is reduced.

The invention relates to the technical field of data processing, in particular to a customized packaging design management system for household appliances, which comprises a dynamic feature genetic coding module, a cross-domain parameter coupling optimization engine, a double-level genetic optimization architecture, a dynamic case feature reconstruction module, a coevolution verification interface and a self-adaptive processing instruction generator. Converting the geometric features of the household appliance into a hybrid coded chromosome data stream; the cross-domain parameter coupling optimization engine integrates the logistics vibration spectrum and the material shock resistance parameters, constructs a dynamic constraint matrix and generates a multi-target non-dominated solution set; the coevolution verification interface corrects and optimizes the weight coefficient through physical simulation feedback to form a closed loop verification link; according to the method, the problems of static template adaptation lag, insufficient multi-constraint coupling and historical case feedback deficiency are solved, and the packaging design efficiency and the structural reliability are improved.

The invention provides a quadrant switching smooth control method, device and equipment for an electro-hydrostatic system, and relates to the technical field of electro-hydraulic compound drive control. According to the method, sensor state information is acquired, a discretization state-space equation is established, a cost function is designed, improved sequential quadratic programming is called to solve the optimal control quantity, instructions are smoothly processed through a linear tracking differentiator, a reference value is calculated through a current distribution strategy and pressure feed-forward compensation, and cooperative impact resistance control is achieved through a PI controller and SVPWM. The response speed and stability of the electro-hydraulic compound system in the quadrant switching process can be remarkably improved, the problems of impact and torque overshoot are effectively restrained, the service life of equipment is prolonged, and the electro-hydraulic compound system is suitable for high-performance requirement scenes under complex working conditions such as electric loaders, excavators and winches.

The invention relates to the technical field of factory intelligent inspection, and discloses a distributed factory intelligent inspection path dynamic planning and fault linkage processing system. The system comprises four core modules, namely a partition monitoring module, a path planning module, a fault analysis module and a linkage execution module. The subarea monitoring module obtains current operation data of each production area and provides basic data for a subsequent process; the path planning module generates an initial inspection path, breaks through the limitation of a traditional fixed path, and optimizes the distribution of inspection resources. The fault analysis module calculates a path deviation value according to the real-time operation state data of the path nodes, and captures node state changes to identify fault risks; and the linkage execution module triggers the linkage processing instruction of the corresponding area according to the deviation value, thereby reducing information transmission links and realizing rapid fault response. The system forms a complete closed loop of data monitoring, path planning, deviation analysis and linkage processing, and ensures the production stability and safety of distributed factories.

The invention relates to the technical field of system-on-chip service interrupt processing, in particular to a hardware Sequence-based SoC interrupt processing method, which comprises the following steps of: pre-programming an interrupt processing instruction sequence into an instruction random access memory (RAM), and configuring an instruction set, a sequence processor and an interrupt priority strategy of a task scheduler Sequence; receiving the interrupt signal by a task scheduler, and selecting a corresponding sequence processor according to an interrupt type; for the interrupt with low priority, the Sequencer directly executes the pre-stored instruction sequence to complete the interrupt response; and for high-priority interruption, the Sequencer caches the state of the register and sends a message packet to notify the CPU to perform cooperative processing. According to the method, interrupt autonomous response is achieved through hardware Sequence, zero CPU intervention is achieved in low-priority interrupt, a lightweight message mechanism is adopted in high-priority interrupt, and bandwidth occupation and power consumption are reduced while efficiency is improved.

A facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, comprising a server comprising communications module configured to receive data and to transmit load management instructions; plurality of electrical charging stations; plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

The invention provides a spindle constant-temperature AI closed-loop heat engine system, and relates to the technical field of numerical control machine tool control and heat management. The invention aims to solve the problems of response lag, uncontrollable thermal stress, single heating strategy and the like of the traditional spindle heat engine method. The system comprises a multi-dimensional thermal state sensing module used for constructing a multi-node discrete temperature field representing the overall thermal distribution of the main shaft; the real-time heat balance feedback module is used for judging the cold / hot starting state of the main shaft according to the initial temperature difference and executing a differentiated feedback control strategy; and an AI prediction forward compensation module that predicts a future cutting thermal load by pre-reading a machining instruction and generates a feedforward thermal compensation instruction. According to the method, the thermal stress is controlled by introducing the radial thermal gradient index as the safety constraint, negative precooling or positive preheating is achieved in combination with the AI predictive capacity, a feedback and feedforward composite control mode is formed, and the dynamic thermal stability and the machining precision of the main shaft under the complex working condition are improved.

The invention discloses a collaborative response method and device for large and small models, equipment, a medium and a program. The method comprises the steps of calling a low-rank adaptation small model to generate an initial response through an edge node when an input instruction of a user is received; calculating the whole sentence confidence coefficient in the initial response; if the whole sentence confidence coefficient is smaller than a sentence-level confidence coefficient threshold value, a collaborative response instruction is sent to the cloud server cluster; selecting a specified number of target large models from the plurality of large models, and correcting at least one lexical element based on a lexical element level confidence coefficient threshold to obtain a plurality of collaborative responses; and selecting the target collaborative response with the highest confidence as a real response, and returning the real response to the user. According to the embodiment of the invention, the large model and the small model are utilized to cooperatively work to quickly give a preliminary reply to a simple question, the large model intervenes in optimization when a complex question is encountered, a satisfactory answer is provided for a user, the user experience is improved, and the instruction processing capability is enhanced by performing fine tuning optimization on the low-rank adaptive small model.

The invention relates to a data processing device and method, a processor and a chip, and relates to the technical field of computers, the data processing device comprises a processing module and a driving module; the processing module obtains address information of each thread in a first instruction when judging that the instruction to be processed is the first instruction, the first instruction is a multi-thread parallel loading instruction, and the address information of different threads is mutually independent; the driving module determines a parallel loading result according to address information of each thread in the first instruction, the address information is used for determining an off-chip address and an on-chip address of each thread, and the thread is used for loading data at a position indicated by the off-chip address to a position indicated by the on-chip address. According to the embodiment of the invention, multi-thread parallel execution of different data accesses can be realized, and the calculation efficiency is remarkably improved.

The invention provides an instruction pipeline processing method of a processor and the processor. A processor includes: a control module; the control module is set to execute the branch instruction speculatively according to the branch prediction direction when detecting that the first instruction subjected to initial decoding is the branch instruction, and execute the branch instruction if detecting that the second instruction subjected to initial decoding is the function call instruction or the function return instruction before the speculation execution result of the first instruction is generated. If yes, pausing all operations after the instruction processing assembly line performs initial decoding on the second instruction, and blocking the instruction fetching operation of the instruction processing assembly line on the next instruction until a speculation execution result of the first instruction is obtained; wherein the operation after the initial decoding comprises the step of carrying out a push-in or push-out operation of a return address stack (RAS) according to the second instruction. According to the technical scheme, the pollution risk caused by speculative execution of the branch instruction to the return address stack can be shielded, so that the hardware implementation logic of the return address stack is simplified, and the circuit area and power consumption are saved.

The invention relates to the technical field of CAM intelligent programming, and discloses a CAM programming algorithm and system based on a generative artificial intelligence large model. The algorithm comprises the steps of analyzing a CAD document, fusing geometric features, tolerances and material information through a generative artificial intelligence large model, and generating a structured semantic skeleton. Then, the semantic skeleton is matched with a process knowledge base, a preliminary processing instruction cluster is generated, and a dynamic processing graph with a node dependency relationship is constructed; secondly, receiving an editing intention of a user for the graph, analyzing the intention by using a generative artificial intelligence model, and automatically reconstructing node logic and connection of the graph to form a corrected processing logic network; and finally, before execution, simulating a network execution process by using a generative artificial intelligence model, and identifying potential logic and resource conflict nodes. According to the invention, intelligent conversion from design to processing instructions, and intent-driven process chain dynamic optimization and conflict pre-verification are realized.

The invention provides a software development system management method and system based on big data. A code review data set in remote collaboration software development is collected, a review knowledge graph is constructed based on time-space correlation characteristics of the data set, and graph nodes comprise review behavior modes correlated with geographical and time characteristics. Syntactic structure features of current code change are synchronously extracted, the syntactic structure features and historical review tracks in the knowledge graph are jointly coded, and a processing instruction containing version difference analysis priorities is generated. And determining an allocation strategy of the cross-regional review task by dynamically matching the processing instruction and the domain knowledge coverage range. And finally, according to a mapping relationship among the distribution strategy, the version priority and the quality evaluation node, generating an examination management regulation and control strategy adaptive to the software development system. According to the technical scheme provided by the invention, the management efficiency and precision of the software development system can be improved.

The embodiment of the invention discloses a multi-engine task processing system and method, electronic equipment and a readable storage medium, and relates to the technical field of computers. According to the multi-engine task processing system provided by the embodiment of the invention, a plurality of service clusters can be configured to execute the task processing instructions corresponding to different instance identifiers, so that a task allocation process and a task execution process can be decoupled, and the same task processing instruction is executed by the same target service cluster as far as possible; and the same instruction is prevented from being processed across multiple databases. Due to the fact that the dependency relationship does not exist between the service clusters and the process engines in the service clusters, a user can randomly increase or reduce the service clusters and the process engines in the multi-engine task processing system, the problems that the bearing capacity of the system is insufficient, the transformation cost is high, and capacity expansion is difficult are solved, and the user experience is improved. And meanwhile, the system has the capabilities of high concurrency, large capacity, high stability and high expandability.

An accelerator offload device (100) includes: a data processing amount acquisition part (110) that acquires a data processing amount that is a data processing amount at the current time of offload target processing being performed and / or a predicted data processing amount; an operation destination determination part (120) that determines whether to perform an operation by a CPU (11) or offload the operation to an ACC (12) based on the data processing amount of an APL (1), and when a change is necessary, changes an offload destination of an operation processing offload part (130); and an operation processing offload part (130) that receives a request of operation processing from the APL (1), stores data to be processed and a processing instruction in a shared memory, and causes the CPU (11) or the ACC (12) to execute pertinent processing.

A system for automating information technology software actions using advanced AI techniques including a processing system, storage medium, a communications interface, a user interface, a natural language processing model or neural network, operable to interface with at least one of an embedded prompt or chatbot prompt and hosted on a control node which communicates with one or more nodes comprised by a node network via the communications interface, and program instructions on storage medium that direct the processing system to receive an instruction from the user interface, process the instruction using the one or more natural language processing model or neural network, along with one or more AI agents, and execute the instruction one of locally or on a node of the node network via the communications interface.

The invention discloses a processing device, an instruction processing method, a chip device and electronic equipment, and belongs to the technical field of electronics. The processing device comprises a physical register file, a physical register cache unit and an execution unit, the physical register file comprises a first read port and a first number of physical registers, the physical register cache unit comprises a second read port and a second number of cache lines used for caching data of the second number of physical registers, and the second number is smaller than the first number; the execution unit is used for responding to all the source data of the first instruction and executing the first instruction based on all the source data of the first instruction, and any source data in all the source data of the first instruction is read from the first number of physical registers through the first read port or read from the second number of cache lines through the second read port. The instruction execution efficiency can be improved on the basis that the occupied area is not greatly increased, and the instruction processing performance of the processing device is improved.

The invention provides a secure execution environment construction method and system, a chip and a storage medium. The method comprises the following steps: creating an encrypted memory area; distributing an independent security data space in the encrypted memory area for each thread; storing the key encryption key and the security parameter in a locking register, and setting an access control strategy of the locking register by using a flag bit register; and monitoring illegal access to the locked register in real time by using an exception handling instruction. According to the secure execution environment construction method and system, the chip and the storage medium provided by the embodiment of the invention, a reliable hardware-level security mechanism is realized through physical isolation, thread-level encryption container, register locking and the like, and the capability of preventing side channel attacks is improved by introducing random elements of power disturbance according to the security level of the locked register.

The invention discloses a dangerous scene linkage disposal method based on causal reasoning. The method comprises the following steps: collecting and preprocessing multi-source heterogeneous dangerous scene data; executing causal structure learning to generate a dangerous event causal structure skeleton; introducing an improved LiNGAM model to obtain a dangerous event causal directed acyclic graph; forming a dangerous event causal reasoning model; executing causal reasoning calculation to generate a causal influence path; performing risk assessment to generate a risk level label; issuing to a target linkage subsystem to form a linkage processing instruction set; obtaining linkage processing execution feedback data; and outputting the optimized causal reasoning model, realizing accurate identification and dynamic updating of the causal relationship of the dangerous event, and improving the response speed and the disposal precision of the system in a complex environment.

The invention discloses a data processing method based on a vector matrix processor and the vector matrix processor, and the method comprises the steps: transmitting vector data stored in a vector matrix memory to a vector register based on a business processing instruction packet; if the business processing instruction packet belongs to the vector matrix cascade mode, performing vector operation on the vector data based on a vector processing component to obtain a vector operation result, and writing the vector operation result into a vector register; and transmitting the matrix data stored in the vector matrix memory to the matrix register, transmitting the vector operation result stored in the vector register and the matrix data stored in the matrix register to the matrix processing component, and performing matrix operation on the matrix data and the vector operation result based on the matrix processing component to obtain a cascade operation result. By adopting the application, the calculation performance of the vector processing component and the matrix processing component can be improved, and the power consumption is reduced.

The embodiment of the invention provides a threat intelligence data processing method and related equipment. The method comprises the following steps: acquiring an associated knowledge graph constructed based on multi-source threat intelligence data and network asset data; acquiring a real-time operation data flow in the monitoring network, determining asset data associated with the real-time operation data flow based on the associated knowledge graph, and performing priority matching based on the corresponding comprehensive risk value to obtain a priority corresponding to the real-time operation data flow; generating context associated data corresponding to the real-time operation data flow based on the associated asset data, and obtaining standard event data based on the corresponding priority, the real-time operation data flow and the context associated data; and matching the standard event data based on the at least one detection research and judgment rule corresponding to the research and judgment label to obtain the target research and judgment label, and generating the target processing instruction based on the processing strategy corresponding to the target research and judgment label, thereby improving the threat response efficiency and the closed-loop processing accuracy.

A method for emulating a distributed computing scenario using a graph-based representation of AI / ML workload execution with an expanded collective communication operation includes receiving a graph-based representation of AI / ML workload execution comprising a collective communication node and expanding the collective communication node by replacing a collective communication operation of the collective communication node with low-level processing instructions. A modified graph-based representation of AI / ML workload execution comprising the low-level processing instructions is generated. The modified graph-based representation of AI / ML workload execution is implemented in an emulated test case using an emulation engine.

The invention provides a return address backup method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a return address stack (RAS) corresponding to a first pipeline processing unit, and configuring RASs corresponding to at least one second pipeline processing unit; obtaining a to-be-processed instruction sequence, and performing pipeline processing on the to-be-processed instruction sequence; in the process of performing assembly line processing on the instruction sequence to be processed, responding to assembly line flushing operation initiated by a target assembly line processing unit, copying an RAS corresponding to the target assembly line processing unit into an RAS corresponding to the first assembly line processing unit, the target assembly line processing unit is one of the at least one second assembly line processing unit. Based on the scheme of the invention, the RAS backup can be realized by setting the RAS in the second assembly line processing unit, so that the influence of assembly line scouring on the RAS is eliminated, and the accuracy of the RAS for predicting the return address is improved.