1316 results about "Data channel" patented technology

The invention discloses a big language model reasoning optimization method and system based on dynamic video memory compression and memory isomerism, and intelligent management of video memory resources is realized by integrating a dynamic compression strategy of KV Cache and a memory parallel architecture. The method comprises the following steps: 1) analyzing the spatial-temporal characteristics of the KV Cache in real time, adaptively selecting a quantization compression algorithm, a rarefaction algorithm or a low-rank decomposition algorithm, performing hierarchical storage based on attention head importance scores, keeping high precision of a core head, and implementing low-bit quantization on a secondary head; (2) the compressed inactive data are divided into a plurality of data blocks to be stored in a system memory, a parallel data channel group is established according to the number of physical channels, the compressed blocks are concurrently read through multiple channels during loading, and parallel decompression of a sparse matrix is accelerated through a GPU tensor core; and 3) constructing a KV Cache multiplexing mechanism and a parallel channel, and parallelizing a compression / decompression process and model calculation by adopting a hardware acceleration compression and asynchronous pipeline mechanism.

The invention relates to the technical field of data asset sharing, in particular to a data asset sharing method and system based on square and circular clouds, and the method comprises the following steps: obtaining data structure information and establishing a standardized list, counting field matching and jumping conditions to construct a remapping list, extracting an idle path aggregation path group to generate a candidate list, and judging priority conflicts to generate a shunting mapping result, and performing sharing operation on the combined fields and the paths in a butt joint manner. According to the invention, through combination of field name coding and type expression, the unified field identification capability is enhanced, coding difference and type vector difference are adopted to synthesize a score and screen a remapping field pair, the field matching precision is improved, and a path state, service attribution and priority elements are fused to construct a path group; the alternative number and the distribution identifier are configured under the path conflict, and the field and the path number are combined and butted, so that the granularity collaborative sharing is realized, the correspondence between the data channel structure and the access control is enhanced, and the stability of data sharing under multiple environments is improved.

The invention relates to the technical field of fault prediction, in particular to a centrifuge fault prediction system based on machine learning, which comprises a data channel synchronization module, a multi-dimensional feature extraction module, a state evolution index construction module, a trend aggregation trajectory recognition module and a fault section recognition module. According to the method, different types of data are synchronously aligned by a multi-channel signal segmentation processing mechanism based on a periodic state, a state evolution sequence is constructed in combination with a unified sampling structure based on a time scale, a state characteristic track is established through a multi-dimensional parameter set, a trend change index is constructed by means of a difference root-mean-square between adjacent states, and the state evolution sequence is analyzed. According to the method, the aggregation section is recognized and the trajectory deviation frequency is counted by utilizing continuous trend mutation, so that dynamic migration of the trajectory boundary and intelligent recognition of the fault section are realized, the boundary failure problem caused by static preset conditions is avoided, and the continuous prediction stability of long-period equipment and the application range under a non-standard working condition are effectively enhanced.

The invention discloses a retrieval generation method and system based on multi-agent collaboration, a terminal and a medium, and relates to the field of artificial intelligence. Performing semantic analysis on the input word embedding converted by the natural language query instruction through a query analysis agent, and determining a semantic intention vector; performing reinforcement learning and meta learning on the semantic intention vector through a strategy construction agent, and determining a retrieval strategy; performing semantic enhancement on the semantic intention vector according to knowledge graph node embedding to obtain a semantic enhancement vector; determining a data channel according to the semantic enhancement vector, a retrieval strategy and a real-time system load, and calling the data channel for retrieval to obtain candidate documents; and generating a target answer according to each candidate document based on an adaptive reflection feedback mechanism in combination with an auto-encoder and a generative adversarial network. The problems that the prior art depends on a fixed retrieval strategy, has limitation when facing complex query, multi-round interaction and cross-modal data fusion, is easily interfered by noise and is not accurate enough in semantic matching are effectively solved.

The invention discloses a multi-agent collaborative data authorization operation management method and system, and the method comprises the steps: carrying out the edge grading, edge verification and desensitization of scientific research data, obtaining desensitized shared data, encrypting and transmitting the desensitized shared data to a cloud sharing platform, carrying out the layering encryption, and generating an uploading log, the method comprises the following steps: generating an encrypted request packet, screening data, providing the data for a research and development institution, generating an intelligent contract, carrying out dynamic authorization to generate an authorization instruction and an authorization log, verifying the authorization instruction, opening a data channel permission to determine visited data, carrying out hierarchical decryption on the visited data to obtain collaborative authorization data, and sending the collaborative authorization data to the research and development institution. And carrying out weight sorting on the collaborative authorization data, accessing and downloading the collaborative authorization data, and updating an access log. The method not only can improve the efficiency and accuracy of scientific research data authorization operation management, but also has good interpretability, and can be directly applied to a scientific research data authorization operation management system.

The invention discloses an information security management method and system based on sensitive data, relates to the technical field of data management, and comprises the following steps: realizing quantum encryption transmission of remote high-sensitive data by combining a quantum key distribution link and a dynamic chaotic key stream; the partitioning and synchronization priority is dynamically adjusted according to the node load, the data integrity is verified through CRC, the distributed storage disaster recovery system with extremely high safety and usability is achieved, it is ensured that data can still be recovered even under extreme disasters, a zero-trust data channel based on an IPSec tunnel is constructed in the data transmission process, and the reliability of data transmission is improved. The tamper-proof, anti-counterfeiting and anti-leakage capabilities of a data access link are greatly improved, the access frequency abnormity is detected through the isolated forest model, the behavior trend is detected through the LSTM time sequence prediction model, the baseline deviation analysis is performed through user behavior portrait comparison, and the real-time, multi-modal and chained security monitoring of the user data operation behavior is realized.

The invention provides a GNSS (Global Navigation Satellite System) anti-interference receiver system based on radio frequency front end-INS (Inertial Navigation System) combined assistance, which adopts a dual-core ARM Cortex-A9 and a programmable logic unit for layered decoupling, and realizes real-time receiving and processing of a high-bandwidth data stream, closed-loop control of an interference suppression link and quick response of a navigation path and a strategy decision. All the modules efficiently cooperate through AXI-Lite register mapping, interrupt signals, a shared state buffer area and a timer synchronization mechanism. By controlling bus and state buffer mapping to keep consistency and supporting a module-level independent debugging and system-level soft reset mechanism under hot start, the expandability of subsystem cascade debugging, fault module positioning and online updating is realized. In the aspects of module architecture, data channels and cooperation mechanisms, the structure order, efficient communication and control closed loop are realized, and an embedded multi-module cooperation anti-interference platform which is suitable for a high-interference environment, multi-channel fusion processing and navigation task real-time response is constructed.

A system for recovering information lost during genomic data compression employs a quality-driven approach using neural networks. The system evaluates the importance of genomic regions through a quality analysis engine that assigns quality scores, while a rate control engine determines optimal compression rates based on these scores. A specialized neural network recovers lost information from correlated genomic datasets that have undergone lossy compression, utilizing recurrent layers for feature extraction and a channel-wise transformer with attention to capture complex relationships between data channels. The neural network architecture incorporates a deblocking network that combines these components to effectively reconstruct compressed data. A decoder receives and decompresses the data, then processes it through the neural network to recover information lost during compression. This adaptive system ensures critical genomic information is preserved while maximizing compression efficiency.

The invention discloses a Hall sensor combination system and method for magnetic imaging stability optimization. The system comprises a three-dimensional orthogonal Hall sensor array; the embedded encoder module is used for converting the analog magnetic field signals acquired by the sensor array into digital encoding signals with timestamps; the control module constructs an electromagnetic feature extraction model and is used for carrying out time-frequency domain conjoint analysis on the digital coding signals to obtain magnetic environment disturbance feature parameters; generating a compensation magnetic field parameter opposite to the magnetic environment disturbance characteristic parameter by adopting a closed-loop feedback mechanism; establishing a real-time data channel with a preset electromagnetic imaging module and a preset magnetic field generation module through a preset communication protocol; and constructing a magnetic environment state space model corresponding to the three-dimensional orthogonal Hall sensor array, and obtaining magnetic field distribution data to dynamically adjust and compensate magnetic field parameters so as to realize active magnetic interference cancellation in a three-dimensional space. Problems in the prior art can be effectively solved, and the precision and stability of magnetic imaging are improved.

The embodiment of the invention provides a read-write request processing method, a protocol conversion module, electronic equipment and a storage medium, and relates to the technical field of chips. The method comprises the steps that a protocol conversion module is arranged in a processor cluster, an original read-write request is converted into a first read-write request conforming to a CHI protocol through a first conversion module in the protocol conversion module, and a corresponding transmission channel is distributed to the first read-write request; and the request queue module orderly sends the received first read-write request, and the second conversion module recombines the first read-write request information to a second read-write request conforming to the CHI protocol, and allocates a corresponding channel for the second read-write request. According to the embodiment of the invention, the internal data channel (AXI or similar AXI) is directly converted into the CHI interface in the processor cluster, the internal circuit resources of the processor cluster are reused, the circuit area is saved, and the access path time delay is reduced.

The invention discloses a cross-platform virtual-real fusion scene construction method and system based on AI space calculation, and relates to the technical field of artificial intelligence and space calculation, and the method comprises the steps: carrying out the multi-scale feature fusion based on a received cross-modal conversion instruction set, and generating an initial image sequence; carrying out implicit field coding on a target object by combining a three-dimensional reconstruction algorithm to obtain an initial parameterized model; performing space-time alignment on the multi-view video stream, loading a digital scene asset package in combination with physical sensing data and a preset spatial index structure, and establishing a bidirectional data channel between a virtual scene and a physical sensor; performing rendering and illumination parameter adjustment on the initial parameterized model to obtain an optimized parameter model; performing differential coding processing on the optimization parameter model to obtain a target virtual-real scene fusion model; and distributing the target virtual-real scene fusion model to a preset terminal. The invention provides a virtual-real fusion construction method for end-to-end collaborative optimization, which is suitable for cross-platform live broadcast or dynamic interaction scenes.

Disclosed in the present invention is a soft tissue photoacoustic / ultrasonic multi-modal image fusion method based on deep learning. The method comprises the following steps: an ultrasonic-photoacoustic imaging device collecting a human body soft tissue photoacoustic image and ultrasonic image, and performing size normalization processing; inputting the images into a spatial conversion module to convert same into a YCbCr space; inputting the images into a pre-convolutional module to change the number of data channels; inputting the images into a multi-scale feature extraction module to extract salient features of the source images; inputting the features into a filter prediction module to obtain a multi-scale filter; and inputting the filter into a filtering fusion and adaptive enhancement module and combining same with the input source images, so as to obtain a final fusion result. Compared with several traditional fusion methods and deep-learning-based fusion methods, the method provided in the present invention has a greater fusion effect, and more importantly, has an excellent real-time performance. Moreover, multiple modes of photoacoustic / ultrasonic fusion extension experiments are performed on a photoacoustic / ultrasonic multi-modal imaging system, verifying the effectiveness of the method in the present invention.

The invention relates to the technical field of edge computing, and discloses an intelligent edge computing co-processing system based on an integrated circuit, which comprises a heterogeneous computing cluster module, a hardware computing unit set, a multi-core control processor based on RISC-V, a programmable pulse tensor computing array and a reconfigurable engine oriented to streaming processing, according to the intelligent edge computing cooperative processing system based on the integrated circuit, zero-delay data exchange is realized through silicon intermediate layer integration of the heterogeneous computing cluster module and a snakelike data channel, and traditional bus arbitration delay is eliminated through real-time operation code analysis and optimal optical communication path mapping of the hardware task routing matrix (TRF) module; the priority path distribution of the task scheduling subsystem is synchronously coordinated with the time-sensitive task, so that the collaborative efficiency of the computing unit is improved in multiple dimensions, the non-blocking transmission of the high-priority task is ensured, and the effect of enhancing the overall processing capability and response speed of the intelligent edge computing is achieved.

Disclosed are systems and methods for maintaining data integrity (e.g., of a database, a data lake, etc.). In some embodiments, one or more processing circuits identify an update, insertion, or deletion of unstructured data stored in an upstream source. The processing circuits determine a new schema of the unstructured data using an inferring function and further determine a divergence between the new schema and a previous schema of the unstructured data based on comparing the new schema to the previous schema of the unstructured data. In an example, the processing circuits store the structured data in a database. The database includes an established data channel between the database and a downstream source, and the structured data is a unique representation within the database of the update, insertion, or deletion of the unstructured data.

The invention relates to the technical field of service robot navigation and motion control, in particular to a service robot dynamic obstacle pre-judgment obstacle avoidance system, which comprises an environment sensing unit for outputting sensing data; the target state estimation unit outputs a target state sequence; the future evolution prediction unit is used for outputting a target future evolution result; the risk quantification unit outputs the current collision risk degree; operating the strategy management unit, and outputting strategy parameters; the evasion decision and path generation unit is used for outputting candidate evasion tracks and speed curves; the execution and control interface unit is used for outputting a chassis control instruction and implementing trajectory tracking; and the device communication and calculation platform is used for outputting a time sequence synchronization and data channel management result according to operation requirements and providing fault monitoring. According to the method, target state estimation, future evolution prediction, collision risk quantification and strategy linkage are completed within real-time constraints, consistent input and constraints are provided for planning and execution on a unified data channel, and safety and traceability are improved.

The invention discloses a multi-brand AGV same-field mixed operation management and control method and device, electronic equipment and a storage medium, and the method comprises the steps: building a standardized data channel with an original scheduling system of each brand AGV, so as to obtain the real-time operation state data and planning path data of each AGV; based on the real-time operation state data and the planned path data, carrying out space intersection judgment on planned paths of all AGVs, and carrying out collision risk initial judgment on AGV pairs with space intersection based on preset limit operation parameters; motion simulation is carried out on the AGV pair with the collision risk through preliminary judgment in the virtual environment based on the actual operation parameters so as to output a quantized collision risk result; and based on the quantized collision risk result, generating an avoidance strategy for the AGV with the low priority in the AGV pair with the collision risk in combination with a preset dynamic priority rule, and issuing and executing a standardized scheduling instruction generated based on the avoidance strategy. According to the invention, safe and efficient cooperative operation of multiple brands of AGVs in a same-field mixed operation environment can be realized.

The invention relates to the technical field of medical information, in particular to a method and a system for processing medical record documents by utilizing artificial intelligence, and particularly relates to a method and a system which can receive and process multi-modal input information including images, videos and voices, can work cooperatively through a multi-agent system and can process the medical record documents. The invention discloses a system for automatically generating, controlling quality and safely inputting medical records in combination with a medical knowledge base and an implementation method thereof. The invention relates to an automatic medical record writing system based on multi-modal input and multi-agent driving. The automatic medical record writing system comprises a multi-modal input module, a multi-agent processing platform and a safety intranet input module. According to the method, establishment of the data channel between the medical intranet and the external AI system is proposed for the first time, the problem of medical intranet isolation is solved, industrial pain points are solved in a breakthrough mode, and a new medical AI landing path is developed.

The invention relates to the field of new energy automobile power supply, and provides an electric automobile interconnection sharing charging operation method and device and a storage medium, the method comprises the following steps: realizing heterogeneous system interconnection of a multi-source charging platform and a supervision platform through a standardized interface protocol, and establishing a cross-platform data channel; a dynamic user authentication system is constructed based on a cross-platform data channel, user registration and authority distribution of the electric vehicle are completed in a multi-mode identity authentication mode to obtain a user authority level, and an authentication result is fed back to the supervision platform; performing intelligent charging pile matching based on the real-time multi-dimensional charging resource atlas according to the user permission level, and generating a dynamic service instruction containing a navigation path and charging parameters; and in a charging service execution process, a bidirectional supervision data flow is created through a cross-platform data channel, full-life-cycle supervision of the charging process is executed in real time, and a service strategy is dynamically adjusted based on a feedback instruction of a supervision platform. According to the technical scheme, the electric vehicle can be cooperatively charged.

The invention discloses a data assimilation method for infrared hyperspectral data of a clear sky channel. The data assimilation method comprises the following steps: acquiring the infrared hyperspectral data of the clear sky channel; a linear or non-linear relationship to convert variables from a mode space to an observation space using a fast radiation transfer mode; satellite infrared hyperspectral atmospheric vertical detection data channel screening is carried out in combination with a principal component method; a channel which is not influenced by cloud pollution is searched by observing the difference between the brightness temperature observed by the infrared and the brightness temperature simulated by the background field; eliminating the statistical deviation between the radiation value observed by the satellite instrument and the radiation value simulated and calculated according to the background field profile; eliminating observation data with errors exceeding a preset threshold value on the mixed earth surface type; and outputting a data assimilation result of the infrared hyperspectral data of the clear sky channel. Analysis fields of all layers of the global atmosphere are improved, the numerical forecasting level is effectively improved, typhoon forecasting intensity errors are remarkably improved, and path errors before landing are superior to conventional observation data tests.

The invention discloses a real estate registration information real-time query system based on graphic data, and relates to the technical field of information real-time query, and the system comprises a knowledge graph generation unit which is used for processing an established multi-modal data set, generating a joint vector, coding the joint vector, and storing the coded joint vector in a preset graph database, synchronously constructing a dual dynamic index mechanism to generate a real estate knowledge graph; the knowledge graph updating unit is used for capturing change events in the multi-modal data set in real time, identifying graph structure differences of a change area and generating a topology correction strategy by positioning the change area and a neighborhood range, and updating a real estate topology knowledge graph in combination with transaction characteristics of a graph database; a query result display unit; and a data synchronization unit. According to the method, the real-time data channel is constructed, capturing and incremental processing of the real estate business change event are achieved, and it is ensured that the real estate knowledge graph and graphic data are dynamically consistent in topological structure and attribute information.

The invention provides an intelligent contract driven workflow engine automatic execution method and system based on a block chain. The method comprises the following steps: constructing a knowledge graph through a historical workflow task, and identifying an association rule between a task type and a resource demand; deploying a monitoring agent at an edge computing node, collecting node load data, and interacting with the block chain smart contract through an encrypted data channel; when a workflow trigger event is detected, a resource pre-allocation strategy is generated in combination with the knowledge graph and the node load data; the block chain intelligent contract verifies the matching degree of the strategy and the current node resource, and after verification is passed, an encryption allocation voucher is generated and written into a block chain account book; the intelligent contract triggers the workflow engine to start the container instance group at the target node according to the voucher, and the task is automatically executed. According to the technical scheme, efficient and safe edge computing resource allocation and workflow automatic execution are achieved, and the resource utilization rate and the task execution efficiency are improved.

The invention provides a coordinated control method and device for flexible interaction of an optical storage and charging micro-grid and a power distribution network, and belongs to the technical field of intelligent power grids and distributed energy management. According to the method, through a day-ahead, intra-day and real-time three-layer coordination control architecture, the system operation cost is optimized, and the power grid stability is improved. The day-ahead layer generates a 24-hour scheduling plan based on photovoltaic output prediction, electric vehicle charging requirements and time-of-use electricity price; the intra-day layer performs rolling optimization in combination with real-time photovoltaic / load fluctuation, and dynamically allocates V2G and energy storage adjustment tasks; the real-time layer adopts adaptive droop control, monitors power grid abnormity and triggers cross-layer cooperation, and also sets photovoltaic fluctuation compensation and island mode switching conditions. Collaborative optimization is realized among the layers through bidirectional data channels. According to the method, the defect of interactive control of the optical storage and charging micro-grid and the power distribution network in the prior art is overcome, the adaptability of the system to distributed energy fluctuation is enhanced, the V2G resource potential is fully played, and the coping capacity under the abnormal condition of the power grid is improved.

The invention discloses a deep learning-based multimodal image fusion method for soft tissue photoacoustic / ultrasound imaging. Steps: an ultrasound-photoacoustic imaging device acquires photoacoustic and ultrasound images of human soft tissue and performs size normalization processing; an input spatial transformation module converts the images to the YCbCr space; an input pre-convolution module modifies the number of data channels; an input multi-scale feature extraction module extracts salient features from the source images; an input filter prediction module derives multi-scale filters; and an input filter fusion and adaptive enhancement module combines the input source images to obtain the final fused result. The invention has superior fusion performance compared to several traditional fusion methods and deep learning-based fusion methods, and more importantly, it exhibits excellent real-time performance. Furthermore, various modes of photoacoustic / ultrasound fusion extension experiments have verified the effectiveness of the method proposed in the invention.

The invention discloses a method for reducing line loss and improving power supply reliability based on the Internet of Things, and the method comprises the steps: carrying out the full-dimension load and line state monitoring: deploying an Internet of Things sensor, constructing an end-to-end monitoring network, and collecting key parameters in real time; a low-delay and wide-coverage data channel is constructed; a layered communication architecture is adopted, and efficient data transmission is realized; the real-time analysis and intelligent decision engine is used for constructing a load-line-equipment three-dimensional data model based on a cloud end and an edge platform, and realizing line loss real-time diagnosis, load prediction, situation awareness and rapid fault positioning; dynamic optimization and self-healing control: based on a data layer analysis result, source-network-load coordinated regulation and control are realized through an Internet of Things terminal, line loss is reduced, and stable power supply is guaranteed; user interaction and global optimization: realizing power grid-user interaction and peak load shifting through a user-side Internet of Things terminal to reduce the pressure of a power system; the system has the advantages of being capable of reducing line loss, guaranteeing power supply reliability, having various functions and being good in comprehensive application effect.

The invention relates to the technical field of computers, and discloses a data transmission method and electronic equipment, the method is suitable for a host, a plurality of data channels are arranged between the host and a graphics processor, and the host is deployed with buffer areas corresponding to the data channels. The method comprises the following steps: determining scheduling priorities of a plurality of data channels based on first communication data of the plurality of data channels and a target scheduling model; determining a target data channel in the plurality of data channels based on the scheduling priority; writing to-be-sent data in the shared cache space to obtain a target address of the to-be-sent data in the shared cache space; writing the target address into a target buffer area corresponding to the target data channel; wherein the graphics processor is used for reading the target address in the target buffer area through the target data channel, and reading and processing the to-be-sent data in the shared cache space according to the target address. The problem of data loss in a data interaction scene of the host and the graphics processor can be solved.

Disclosed is an LED driver circuit, a multi-wire communication device and a method for an LED display system. The device comprises a controller providing at least one of a configuration data packet, a brightness data packet, and a display data packet; the LED driver circuits, wherein the LED driver circuits are cascaded to provide a first data channel using first data ports and second data ports, the LED driver circuits are connected in parallel to provide a second data channel using third data ports. The device relays an enable signal or an address data packet stage by stage using the first data channel, transmit at least one of the configuration data packet, the brightness data packet and the display data packet in parallel using the second data channel. The number of the cascaded LED driver circuits can be infinite, the number of data wires is reduced, data rate is increased.

The invention relates to the technical field of automatic operation and maintenance of a power system, in particular to an automatic operation and maintenance method and system for plant-station equipment based on a knowledge graph, and the method comprises the steps: collecting static ledger data, real-time operation data and historical operation and maintenance data of the plant-station equipment, constructing a multi-dimensional association knowledge graph, creating a digital twinborn body for target equipment in a plant station, and carrying out the operation and maintenance of the plant-station equipment. Establishing a bidirectional data channel between the digital twin and a corresponding equipment entity node in the knowledge graph; and based on a state evaluation rule and a fault propagation path model preset in the knowledge graph, performing real-time health state evaluation on the target equipment by using the state evaluation rule and the fault propagation path model to generate a health index, and when an abnormality is monitored, tracing along the topological relation between the electrical connection and the equipment in the knowledge graph, the fault source is positioned, the confidence probability is calculated, risk level evaluation and processing priority ranking are carried out according to the confidence probability, an operation and maintenance diagnosis work order containing an execution time sequence is obtained, and the fault reason can be quickly traced and positioned.

The invention provides an equipment management method and system based on an industrial internet identification analysis system, which are applied to the technical field of industrial internet, and are used for receiving a data packet using a proprietary protocol from heterogeneous industrial equipment, and analyzing and converting the proprietary protocol data packet through a protocol conversion gateway deployed in a local private cloud environment. The standard format data is transmitted to the device identification management module through the security data channel, and data encryption is carried out, so that the security of the data in the transmission process is ensured. And carrying out equipment identity verification based on the extracted equipment identification information by utilizing an equipment identification management module, and carrying out equipment state management according to the equipment state information, thereby realizing unified management of the heterogeneous equipment. Therefore, the scheme has the advantages that under the local private cloud environment, enterprise special protocols are compatible, the confidentiality of protocol details is guaranteed, and unified management and secure data exchange of heterogeneous equipment are realized.

The invention belongs to the technical field of artificial intelligence chip and robot control, and relates to a heterogeneous calculation and control fusion chip control system and method, a robot and a storage medium. A GPU, an NPU, a BPU and an MCU are integrated in a central large core cluster, a communication network subunit and a memory control subunit are matched, and a low-delay data channel is constructed in a chip, so that perception, cognition and control instructions can be directly interacted, the cross-chip communication delay is reduced, and the real-time performance is improved. The three-level cache module is accessed through the memory control subunit, high-bandwidth sharing and centralized scheduling are achieved, data migration is reduced, the bandwidth bottleneck is relieved, and the complex task processing efficiency is improved. A trust root subunit is arranged in each unit, chip-level trusted verification and access isolation are provided, and the reliability under key action control and security sensitive scenes is enhanced.

The invention discloses an LVDS (Low Voltage Differential Signaling) receiving circuit and an LVDS transmitting circuit for cross-BANK transmission. The LVDS receiving circuit for cross-BANK transmission comprises a clock channel and a plurality of data channels, the clock channel and the data channels are distributed in at least two BANKs, and the clock channel and at least one of the data channels are located in the same BANK; the programmable phase-locked loop is used for receiving a single-ended clock signal generated by the clock channel, and the first global clock buffer and the second global clock buffer are respectively used for buffering a first clock and a second clock and then outputting the first clock and the second clock; each of the clock channel and the data channel comprises a differential-to-single-ended module, a delay module and a serial-to-parallel conversion module. The programmable phase-locked loop and the global clock buffer are introduced, the clock channels and the data channels are distributed in the at least two BANKs, it is guaranteed that part of the data channels and the clock channels are located in the same BANK, and a flexible and efficient LVDS transmission architecture for cross-BANK transmission is achieved.