3037 results about "Network interface" patented technology

A coherent, intelligent, packet-switched memory fabric enables predictive, cache-coherent access across distributed compute, accelerator, and memory resources using a Memory-Fabric Transaction Layer Protocol (MF-TLP). MF-TLP defines routable packet formats for read, write, vectorized, atomic, reduction, collective, and predictive-prefetch transactions executed by memory-centric network interface controllers (MC-NICs). Each MC-NIC performs packet parsing, address translation, coherence management, and near-memory arithmetic or tensor operations while coordinating with MF-TLP-aware switches providing hierarchical directory control, multi-path routing, and in-network aggregation. Vectorized and multimodal packets encode multiple addresses or tensor offsets to reduce scatter / gather overhead, and programmable caching and quality-of-service modules manage tiered memory and tenant fairness. MF-TLP supports extension headers for predictive prefetch, collective coordination, and tenant governance, operating across hierarchical leaf-spine topologies using Ultra-Ethernet Transport, InfiniBand, or CXL fabrics. The system delivers scalable, low-latency, memory-centric orchestration for large-language-model training, multimodal AI, and data-intensive analytics.

The invention provides an industrial control network security service security guarantee system based on behavior analysis, which belongs to the technical field of industrial control network security, and comprises a multi-source data fusion acquisition module, a dynamic behavior modeling engine, a federal learning analysis cluster, an attack chain prediction module, a self-adaptive protection strategy executor and a model evolution feedback ring, wherein the multi-source data fusion acquisition module synchronously acquires industrial control network flow (including OPC UA / Modbus / DNP3 protocol analysis), equipment operation logs, user operation behavior fingerprints and physical interface state data, and the physical interface state data comprises electrical characteristic fluctuation monitoring of USB / network interfaces. According to the scheme, through multi-technology fusion and closed-loop design, the problems of static performance, single-dimension analysis defects and response lag of a traditional industrial control security scheme are effectively solved, a comprehensive protection system with dynamic modeling, intelligent decision making, privacy protection and continuous optimization is constructed, and the security and service reliability of an industrial control network are remarkably improved.

This disclosure relates to a lending system comprising a processor, a memory, and at least one network interface controller configured to enable data exchange with external systems. The memory includes lending management logic configured to execute a personal loan-lending system wherein one or more loans are generated by collecting and preprocessing borrower data from multiple sources, conducting risk assessment and scoring, generating one or more scores based on the conducted risk assessment, and approving loans based on the generated scores. The system leverages machine learning processes to refine scoring accuracy and dynamically adapt to borrower profiles and external conditions. The system may integrate with third-party data sources for enhanced verification and incorporate compliance logic to ensure adherence to regulatory standards. By employing automated, data-driven processes, the system improves efficiency, accuracy, and security in loan origination, servicing, and compliance while enabling dynamic risk management and tailored loan product offerings.

A system includes a plurality of nodes. Each of the plurality of nodes includes memory; a network interface; and a hardware processor coupled with the memory and the network interface. The system further includes a computing device. The computing device includes memory storing a master key, security keys encrypted using the master key, and associations between the security keys and the nodes. The computing device further includes a network interface and a hardware processor coupled with the memory and the network interface. The processor is configured to receive, from a node of the one or more nodes, a request for a security key of the one or more security keys, identify an association between the node and the security key within the associations, decrypt the security key using the master key to generate a decrypted security key, and communicate the decrypted security key to the node.

A system and method for optimizing automated textual prompts in artificial intelligence (AI) conversational systems is disclosed. The system comprises a network interface, processors, and memory-storing instructions for performing operations to optimize prompts. These operations include receiving and preprocessing input data, tokenizing the data, verifying data authenticity, performing temporal analysis, calculating prompt complexity scores, and selectively expanding or refining prompts based on complexity thresholds. The system further incorporates context-aware optimization, multi-faceted prompt refinement, variation generation, and evaluation using machine learning models. Additional features include a technological hub with advanced processing capabilities, sensor-augmented input apparatus, device-specific prompt optimization, AI model selection, multimodal context integration, and an AI-driven creativity booster. The system provides interactive prompt visualization, certification, and uniqueness verification modules. This comprehensive approach ensures the generation of optimized, contextually relevant, and creative prompts for various AI applications while maintaining data integrity and user engagement.

An apparatus is provided that includes a network interface to transmit and receive data packets over a network; a memory including one or more buffers; an arithmetic logic unit to perform arithmetic operations for organizing and combining the data packets; and a circuitry to receive, via the network interface, data packets from the network; aggregate, via the arithmetic logic unit, the received data packets in the one or more buffers at a network rate; and transmit, via the network interface, the aggregated data packets to one or more compute nodes in the network, thereby optimizing latency incurred in combining the received data packets and transmitting the aggregated data packets, and hence accelerating a bulk data allreduce operation. One embodiment provides a system and method for performing the allreduce operation. During operation, the system performs the allreduce operation by pacing network operations for enhancing performance of the allreduce operation.

The invention provides a production operation dynamic supervision method, which comprises the following key steps: S1, data integration: widely collecting data of different production links, transmitting the data to a database through a network interface, and constructing a comprehensive data basis; s2, establishing a visual monitoring platform to integrate data to drive development, vividly displaying a production state by means of a three-dimensional model, a chart and a report, and helping a manager to intuitively insight; s3, intelligent analysis and early warning: deeply mining a data rule trend by using big data and an artificial intelligence algorithm, accurately setting an early warning threshold value, and giving an alarm in time when the threshold value is exceeded, so as to effectively prevent risks; and S4, collaborative management and decision support are carried out, department information barriers are broken, efficient sharing and collaboration are realized, scientific decision support is provided for managers, and production plans, maintenance strategies and emergency plans are optimized. According to the method, through multi-link collaborative operation, the production operation dynamic management and control capability is comprehensively enhanced, and efficient, safe and robust development of enterprises is powerfully promoted.

A system for predicting system component failures within a computer system that comprises a plurality of hardware components and a plurality of software components. The system may comprise memory storing instructions that, when executed, cause a processor to: obtain performance metrics by monitoring a network interface of the computer system; generate component failure probabilities by processing the performance metrics; determine that a first component failure probability among the component failure probabilities exceeds a risk threshold; determine remedial actions that mitigate a first component failure probability; and mitigate the first component failure probability by initiating an execution of the remedial actions.

The invention relates to the technical field of mobile communication transmission, and discloses a heterogeneous network multilink parallel mobile communication transmission method and system. A dynamic link aggregation module of the system collects link state parameters including signal strength, delay jitter and packet loss rate from a plurality of heterogeneous network interfaces in real time; a flow distribution decision module calculates available bandwidth weight of each link according to the data and generates a dynamic flow distribution strategy; the data fragment packaging module splits to-be-transmitted data into a plurality of data fragments according to the strategy, and adds a sequence identifier and a link identifier to each fragment; the multi-channel concurrent transmission module sends corresponding data fragments in parallel through a specified heterogeneous network link; and the receiving recombination verification module sorts the recombination data fragments according to the sequence identifiers, and detects the data integrity through a verification mechanism. According to the system, a set of complete multi-link parallel transmission solution is formed, and the problems existing in a traditional single link and an existing multi-link transmission technology can be effectively solved.

The invention relates to the technical field of satellite telemetering and remote control, and discloses a port task processing method for a satellite measurement, operation and control system, which comprises the following steps of: 1, detecting all available network interfaces through a port scanner, and establishing a multi-path communication channel comprising a public network, a private network and a satellite link; step 2, acquiring packet loss rate, delay, bandwidth and jitter parameters of each path in the multi-path communication channel in real time, and updating the parameters based on a preset period; and step 3, generating a comprehensive score of each path according to the packet loss rate, the delay, the bandwidth and the jitter parameters. According to the method and the device, the technical scheme of dynamic scoring and switching of the multi-path communication channel is adopted, and the technical effect of automatically selecting the optimal path according to the real-time network performance is achieved; the problems of high transmission delay, large packet loss rate and incapability of adaptive adjustment caused by network fluctuation are solved.

Examples described herein include one or more processors; a network interface; and a direct memory access (DMA) engine communicatively coupled to the one or more processors. In some examples, the DMA engine is to receive a DMA data access request and based on an address in the DMA data access request corresponding to a remote memory device, the DMA engine is to cause the network interface to generate at least one packet for transmission to the remote memory device. In some examples, if the source address corresponds to a local memory device and the destination address corresponds to a remote memory device, the DMA engine is to cause the network interface to generate at least one packet for transmission to the remote memory device.

The present disclosure pertains to an automated system for the identification and resolution of clashes involving reinforcing bars (rebars) in a three-dimensional (3D) model of a building project. The system integrates a computing device that receives and processes 3D models comprised of multiple building areas, each containing detailed rebar designs for beams and columns. A remote server, connected via a network interface, comprises a non-transitory storage device housing executable routines and a building construction history database. The database includes various 3D building templates with beam and column patterns, each marked with unique dimension data to facilitate clash detection. When spatial distances between rebar structures fall beneath certain threshold limits, indicating clashes or disagreements, the processing unit of system initiates an analysis. Utilizing historical data and comparative models, the processing unit formulates resolution strategies, calculates optimized rebar dimensions, and generates updated 3D models devoid of any conflicts. The clash-free models, including optimized beam and column BIMs, are subsequently rendered onto the display of computing device.

The invention relates to the technical field of big data processing, in particular to a data acquisition and analysis system for network big data information analysis, which comprises a data acquisition module, a data preprocessing module, a data storage module, a data analysis module and a data visualization module, wherein the data acquisition module is used for acquiring original data from various data sources in real time through a network interface; the data preprocessing module is used for preprocessing the original data; the data storage module is used for carrying out storage and management by adopting a distributed database; and the data analysis module is used for performing deep analysis by applying a machine learning algorithm and a data mining technology to generate a trend prediction result. According to the method, real-time acquisition, automatic preprocessing, distributed storage and multi-algorithm fusion analysis of the multi-source data are realized, so that the problems of low data quality, poor processing efficiency, model isolation and the like in the prior art are solved, and the precision, efficiency and decision support capability of big data analysis are remarkably improved.

Systems and methods for automated blockchain-based recommendation generation, advertising and promotion in accordance with various embodiments of the invention are described. A user device in accordance with an embodiment of the invention includes: a network interface; memory; and a processor. In addition, the processor is configured to implement an execution environment that enables: initiation of transactions via an immutable ledger; recordation of events; updating a user profile, where the user profile comprises at least one characterization associated with the user profile; encrypting the updated user profile and securely storing the encrypted user profile; receiving a request to access the encrypted user profile from a process; determining access permissions of the process; and when the process has sufficient access permissions, decrypting the user profile and providing user profile data to the process.

Embodiments of the present application provide a network interface card control method and apparatus for a server, a non-volatile readable storage medium, and an electronic device. The method comprises: when a target logic device on a server is powered on and starts, identifying a network interface card type of a target network interface card on the server by means of the target logic device; according to the network interface card type of the target network interface card, controlling a first power supply controller on the server to supply power to the target network interface card in a power supply mode matching the network interface card type of the target network interface card; when it is detected that the the target network interface card has been started, by means of the target logic device, controlling a second power supply controller on the server to supply power to a central processing unit of the server. By means of the present application, the efficiency of identifying a network interface card of a server is improved.

The invention discloses an efficient image transmission method based on multiple channels, and the method comprises the following steps: carrying out the fragmentation of a to-be-transmitted image, and cutting the image into a plurality of data blocks; adjusting the fragment size of the image according to the current network condition; during transmission, data blocks are distributed to different channels by identifying a network interface, and each channel independently transmits a part of fragments; a check code is added to each fragment, and whether the received data fragments are complete or not is verified through the check codes; in the data rendering process, the received complete frame is preferentially rendered, and the recombined complete image data is managed by using the cache pool, so that smooth connection between transmission and rendering is ensured. According to the invention, the image data are fragmented and transmitted concurrently on different network channels, so that the network bandwidth can be fully utilized, and the overall transmission speed is improved. The sizes of the fragments are dynamically adjusted, so that the transmission effect can be optimized under different network conditions, and the transmission delay is reduced.

An example system comprises a plurality of servers comprising respective network interface cards (NICs) connected by physical links in a physical topology, wherein each NIC of the plurality of NICs comprises an embedded switch and a processing unit coupled to the embedded switch; and an edge services controller configured to program the processing unit of a network interface card of the plurality of network interface cards to: receive, at a first network interface of the NIC, a data packet from a physical device; based on the data packet being received at the first network interface, modify the data packet to generate a modified data packet; and output the modified data packet to the physical device via a second network interface of the NIC.

The invention relates to an optical data network (10-1) for connecting a plurality of data network nodes (N1-1, N2-1, N3-1, N4-1). The optical data network (10-1) comprises: i) the plurality of data network nodes (N1-1, N2-1, N3-1, N4-1), the data (99) comprising data packets (99p), wherein each data network node (N1-1, N2-1, N3-1, N4-1) is provided with a network interface (Nl); and ii) a data connection network (100-1) comprising at least one data switch (SW) and a plurality of optical connections (50) for allowing establishment of data links (DL1, DL2) between pairs of said plurality of data network nodes (N1-1, N2-1, N3-1, N4-1). At least one of the at least one data switch (SW) is a smart data switch (SSW) comprising at least one packet switch (PS, EPS) and at least one circuit switch (CS, OCS), At least two network interfaces are smart network interfaces (SN, SNC) comprising a data classifier (25) configured for classifying the data packets (99p) into at least two traffic classes including first traffic class (D1) and a second traffic class (D2) in accordance with a classification scheme. The smart data switch (SSW) and the network interfaces (SN, SNC) are configured to route the data packets (99p) of the first traffic class (D1) to the packet switch (PS, EPS) and to route the data packets (99p) of the second traffic class (D2) to the circuit switch (CS, OCS).

The invention discloses a digital operation management system and method, and relates to the technical field of digital operation management, and the system comprises an operation monitoring module which is used for carrying out the communication with a distributed industrial Internet of Things node through a network interface, collecting production environment parameters and process data, and forming equipment baseline parameters; the knowledge graph engine module is used for constructing an equipment relation network and process flow mapping based on the equipment baseline parameters; the predictive maintenance module is used for carrying out equipment life evaluation and fault early warning according to the relational data of the knowledge graph engine module; the decision support module is used for generating a resource scheduling scheme based on equipment life evaluation and fault early warning in combination with a historical decision effect, and transmitting the resource scheduling scheme to the digital twinning display module; and the digital twinning display module is used for displaying the real-time operation state of the factory by utilizing a three-dimensional visualization technology. The data processing efficiency, the resource utilization rate and the flexibility in the production process are improved, and global monitoring and intelligent optimization of the production process are achieved.

Methods and apparatus for providing L4S support with regard to non-3GPP untrusted / trusted accesses in which a user equipment (UE) is enabled to monitor for uplink and / or downlink congestion with regard to L4S uplink data traffic flows at the UE, detect congestion, and perform explicit congestion notification (ECN) markings or communicate congestion information to perform ECN marking to another device are described. In some embodiments, the UE device indicates detected congestion, at the UE, in an uplink (UL) traffic flow via performing ECN marking of an innermost IP header ECN field. In some other embodiments, the UE device communicates detected congestion information, via a GRE message to a core network interface device, which communicates, via GTP-U, the detected congestion information to a UPF, which then uses the received UE detected congestion information to performs ECN marking in the innermost IP header of an uplink data packet.

The invention belongs to the technical field of semiconductors, and discloses a multi-core GPU interconnection architecture and a self-adaptive cache allocation method thereof.The multi-core GPU interconnection architecture comprises a plurality of GPU clusters and a global cluster, the global cluster comprises a global router, a global scheduler, a directory, a memory and a plurality of GPU clusters, each GPU cluster is composed of a plurality of GPU cores, and the GPU cores are arranged in the global router. Each GPU core grain comprises a plurality of independent primary data caches, secondary data caches, a local router and a network interface, and the network interface judges whether a current request is processed by the GPU core grains in a GPU cluster or not according to whether a target address in a target node belongs to the GPU cluster or not, so that a high-level multi-core grain interconnection architecture supporting cross-cluster communication is formed. According to the method, performance is optimized by adapting to different access modes, private and shared cache modes are switched in real time, single data access delay is reduced, the overall system efficiency is improved, and the method is used for a multi-core-particle heterogeneous system with a plurality of GPUs.

A network interface module for coupling a host device to a switched network as a network node is described. The network interface module comprises a single half-duplex port for communicatively coupling to a shared bus of the switched network, at least one frame queue sized to store one multicast read frame received via the shared bus, and logic circuitry. The logic circuitry is configured to decode a read command for the interface module included in a payload of the multicast read frame that includes multiple read commands for other network nodes of the switched network, and transmit a response frame including read data on the shared bus when detecting the shared bus is available for transmitting.

A decentralized mesh-network platform provides real-time governance, supervision, and audit of large-language-model persona agents in regulated environments such as healthcare. Each computing node hosts processor circuitry, memory, a network interface, and an integrated suite comprising a User-Prompt Interface, Metadata Filter & Enrichment Engine, Persona Role Constructor, Policy Constraint Engine, gating logic module, Supervisor Review Interface, Session Memory Governance Module, Audit Logging Subsystem, cryptographically linked audit ledger, and Fallback Control Module. Devices communicate over a peer-to-peer channel, exchange role-switch tokens, and merge local ledgers into a composite audit graph when connectivity returns. The architecture supports continuous compliance and resilient operation across institutional boundaries, network partitions, and device failures, enabling conversational interaction with heterogeneous medical data while maintaining rigorous credential lineage, policy oversight, and forensic traceability.

Turntable control systems are disclosed. A playback device can include an analog audio source component such as a turntable. The playback device is configured to cause playback of first audio based on analog audio signals generated by the analog audio source component. Based on an indication that analog audio signals are no longer being generated, the playback device requests, via a network interface, audio content from one or more remote computing devices. The request can include identifying related content based on the first audio. The playback device receives, via the network interface, second audio content from, and causes playback of second audio based on the second audio content.

A computing node includes network interface circuitry and processing circuitry. The processing circuitry assigns available computing resources to a plurality of slice contexts. Each slice context of the plurality includes resource allocations of the available computing resources associated with multiple communication networks. A first portion of the resource allocations is designated as dedicated resources and a second, remaining portion is designated as shared resources. A FAFO event associated with a workload is detected. The workload executes on a network slice instance (NSI) associated with a slice context of a subset of slice contexts. The configuration of the NSI is restored to a pre-FAFO event state based on reconfiguring one or both of the dedicated resources or the shared resources of the slice context based on the resource allocations of at least a second slice context in the subset of slice contexts.

The invention relates to a data storage method, system and device, a chip, a network interface card, equipment, a medium and a program product. The method comprises the following steps: receiving a data packet write-in request, wherein the data packet write-in request is triggered by a storage management module on a host through a memory write operation driven by a virtual storage device; triggering PCIE multicast data packet processing based on the data packet write-in request; and under the condition that a PCIE multicast data packet processing result is multicast hit, the data packet is pushed to a plurality of target ports of the PCIE switch, each target port is connected with a virtual storage device located in a data processing unit, and the virtual storage device is used for writing the data packet into a corresponding memory. The method can improve the overall performance of the system.

The disclosure relates to a pre-5th-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4th-Generation (4G) communication system such as Long Term Evolution (LTE). A method performed by an E2 node is provided. The method includes receiving a radio access network (RAN) intelligent controller (RIC) subscription request message from an RIC via an E2 interface, and the RIC subscription request message may include information indicating a network interface type.

An integrated circuit includes a host interface coupled to a host device executing a tenant operating system (OS) on bare metal and hardware accelerator(s) coupled to the host interface and a network interface. The hardware accelerator(s) receive, over the host interface, a snapshot request relating to a snapshot of tenant OS. Snapshot request includes a location, in a physical memory of the host device, of a swap file having contents of random access memory of the host device. The hardware accelerator(s) encrypt the swap file and initiate transfer of the encrypted swap file to a network storage device coupled to a cloud-based server. The hardware accelerator(s) send, over the network interface, to a snapshot manager hosted by the cloud-based server, metadata associated with storing the encrypted swap file in the cloud-based server, to allow the snapshot manager to manage the snapshot of the tenant OS.

A robotic surgical system network includes a plurality of robotic surgical systems. Each system includes robotic arms, sensors, a surgeon console, and a control system with an integrated AI module. A network interface is associated with robotic surgical system and provides secure data communication. A central or distributed data repository securely stores surgical data aggregated from the robotic surgical systems. The surgical data includes at least one of procedural data, sensor readings, imaging data, AI decision logs, surgical outcomes, or user interaction data. A training module utilizes aggregated surgical data to train or update AI models for the robotic surgical systems using unsupervised learning, transfer learning, or federated learning techniques. A cybersecurity module implements security measures for data transmission and system access, the measures comprising at least one of encryption, multi-factor authentication, or real-time threat detection.