96 results about "Networking hardware" patented technology

The invention provides a system and a method for generating CAN (Controller Area Network) mailbox configuration and data routing configuration based on a communication matrix table. The method comprises the following steps of: reading a predefined finished automobile CAN communication network signal routing information table; analyzing the whole vehicle CAN communication network signal routing information table to obtain CAN communication configuration parameters of each CAN channel; the number of receiving mailboxes and the number of sending mailboxes of each CAN channel are distributed according to the maximum number of receiving mailboxes and the maximum number of sending mailboxes supported by the whole vehicle CAN communication network hardware for each CAN channel and CAN communication configuration parameters of each CAN channel; and when the number of the messages to be processed of a certain CAN channel exceeds the allocated mailbox number, classifying the messages, and multiplexing the same mailbox by the messages belonging to the same class. According to the method, CAN mailbox resources are used to the greatest extent, and the reliability of data routing is ensured; when the whole vehicle communication network signal routing table is frequently changed, the reliability of the routing function is ensured, and meanwhile, the development efficiency is improved.

The invention provides a large-scale constellation network semi-physical simulation test system and method, the system comprises a constellation simulator, a satellite-borne router, ground detection equipment and a protocol conversion network bridge, a Mininet simulation platform is deployed, and dynamic topology adjustment, an OSPF dynamic routing protocol and a multi-scene test function are supported; a user can observe network topology change, route updating time and key performance indexes in real time. A semi-physical simulation architecture is realized through unified IP subnet interconnection and the same routing protocol, a space-time synchronization engine ensures that virtual and real node routing tables take effect at an appointed moment, and in combination with a protocol consistency sandbox, hidden faults caused by inconsistent behaviors of hardware and software protocol stacks are solved, and the service life of the virtual and real node routing tables is prolonged. A plurality of real nodes are accessed in a large-scale network environment, and end-to-end data transmission test, security policy verification and protocol compatibility analysis are carried out; the invention provides an efficient, flexible and reliable solution for the design, verification and optimization of the satellite network, and has a wide application prospect.

The application discloses a medical image transmission method based on a 5G network, and specifically comprises the following steps: step one, hardware architecture; step two, image acquisition and encapsulation; step three, decapsulation and restoration; and step four, fault-tolerant processing, and relates to the technical field of medical communication. The medical image transmission method based on the 5G network constructs a 5G network hardware framework system, utilizes the low-latency and high-speed characteristics of the 5G network for information transmission, and cooperates with a client, a slice information unit, a state information monitoring unit, a fault-tolerant information unit and an identification unit to form a client message system, utilizes a server, a transmission data record module, a slice image information module, a data information module and a data integration module to form a server end heat preservation system, and after encapsulation and decapsulation, the medical image with a large amount of data can be completely and quickly transmitted and saved to a remote secure server while ensuring the high-speed stability of the transmission environment.

One or more computing devices, systems, and / or methods for visual troubleshooting a network device setup. Images of the network device setup are provided to the system. A GenAI component processes the images to generate one or more device identifying features. The features are further processed to identify the device. The system utilizes hardware-specific information to prompt the GenAI component to answer troubleshooting-related questions concerning the device setup. The images may be pre-processed to include one or more visual guides to assist the GenAI component.

The present invention proposes a method for realizing in-memory computing based on a small-signal ferroelectric capacitor with non-destructive readout, belonging to the field of novel computing architectures. The present invention realizes the linearly inseparable comparison operation of a content-addressable memory (CAM) unit and the local multiplication operation of a signed synaptic unit on a ferroelectric capacitor, reducing the hardware cost. Compared with the method of distance measurement based on the traditional CAM architecture, it has higher computational linearity and detection range, as well as lower search power consumption; at the same time, compared with the resistive synaptic array, it has no DC power consumption and no potential DC conduction path, avoiding the "IR drop" problem of large-scale arrays, and has lower computational power consumption, showing significant advantages in edge machine learning tasks based on feature retrieval and neural network hardware acceleration.

A system and method is provided for designing and optimizing hardware accelerators for neural networks. During a pre-design phase, rules are extracted from compilation patterns that describe conversion between neural network operators, coarse-grained operators, and fine-grained dataflow. A fast mapper for converting neural network models to coarse-grained operator descriptions and a dataflow mapper are generated. A coarse-grained design phase employs an architecture optimizer to generate plural provisional hardware accelerator designs The coarse-grained operator descriptions are simulated using a coarse-grained simulator to obtain performance metrics of each provisional accelerator design. A fine-grained design phase employs a dataflow mapper and fine-grained simulator to finalize provisional hardware accelerator designs. A hardware accelerator is generated from a finalized hardware accelerator design and a corresponding software toolchain is created including a compiler and software development kit (SDK) for programming, debugging, and deploying the hardware accelerator design.

The invention discloses a network configuration method and device, electronic equipment and a storage medium, relates to the technical field of container cluster management, realizes network multiple models of a distributed cluster by constructing a multi-network model plug-in integrated with multiple functions, and solves the technical problem that the cluster needs multiple network plug-ins, so that the multi-network plug-ins cannot be used in the distributed cluster. The complexity of cluster deployment and maintenance is high; multiple network plug-ins work cooperatively, the network problem boundary is not clear, and the problem checking complexity is high; the multi-network plug-in lacks a unified IPAM management mechanism; only the setting of a workload granularity network model is supported, the implementation scheme of Namespace granularity is lacked, and the usability is poor; due to different network hardware resources required by service applications, a user needs to customize scheduling nodes and the like of a workload; the application performance of the distributed cluster is improved, through configuration of the network resources, the network configuration process is simplified, the network configuration efficiency is improved, and the application performance of the distributed cluster is further improved.

Systems and methods are provided for generating libraries for hardware realization of neural networks. The method includes obtaining a plurality of neural network topologies. Each neural network topology corresponds to a respective neural network. The method also includes transforming each neural network topology to a respective equivalent analog network of analog components. The method also includes generating a plurality of lithographic masks for fabricating a plurality of circuits. Each circuit implements a respective equivalent analog network of analog components.

A machine learning-based proxy model may generate measurements of quality of user experience in a vehicle-based communication network in the absence of direct feedback from the users regarding the user experience. Once generated, the proxy model may be applied to observed operational parameters of the on-board network to quantify the user experience for any user in any given instance. User experience measurements (e.g., trends identified therein) may be utilized to identify and implement adjustments to hardware, firmware, software, and / or service procedures associated with implementation of the on-board network. These adjustments may be implemented between transits of the vehicle, or in some cases, during transit of the vehicle to improve the user experience over the duration of use of the vehicle-based communication network.

Systems and methods herein are for at least one circuit that can determine that a network reference associated with a first network hardware is subject to a network performance degradation in a network, can cause suspension of traffic flow associated with the network reference, can save configuration for at least the network reference at a node associated with the first network hardware, and can cause the configuration to be deployed in a second network hardware so that the network reference that was previously in the first network hardware is provided from the second network hardware to resume the traffic flow.

A cluster configuration request to form a hyperconverged computing infrastructure (HCI) cluster in a cloud computing environment is processed. Based on the cluster configuration request and any other cluster specifications, a plurality of bare metal computing nodes of the cloud computing environment are configured to operate as an HCI cluster. First, a tenant-specific secure network overlay is formed on a first set of tenant-specific networking hardware resources. Then, the tenant-specific secure network overlay is used by an orchestrator to provision a second set of tenant-specific networking hardware resources. The second set of tenant-specific networking hardware resources are configured to interconnect node-local storage devices into a shared storage pool having a contiguous address space. Top-of-rack switches are configured to form a network overlay on the first set of tenant-specific networking hardware resources. Then, top-of-rack switches are configured to form a layer-2 subnet on the second set of tenant-specific networking hardware resources.

System and method that enable a userspace compartmented IP Stack and network interfaces between a user device and communications devices associated with the user device, including mobile devices. The system and method include userspace bridging of data to / from external communications devices and applications onboard the user device. The system and method include userspace control of the network interfaces, routing between disparate IP networks, and routing of external IP network interfaces into user device interfaces. The system and method includes incorporating userspace device drivers required for external network hardware interface.

The application discloses a transconductance variable field effect transistor array suitable for a dendritic network hardware and application, and belongs to the technical field of semiconductor integrated circuits.The application realizes three-element multiplication of a storage variable and two input variables based on a single transconductance variable field effect transistor, and realizes mapping of a dendritic network core algorithm based on a complementary device array.Compared with a traditional neural network hardware which realizes nonlinear transformation by using a neuron activation circuit, the application realizes nonlinear transformation by using intrinsic nonlinearity of a device, effectively reduces design complexity, optimizes area and power consumption of a system peripheral circuit, and has important significance for design of a high-performance artificial intelligence computing system.

The utility model discloses a computer network hardware equipment installation device which comprises a case, case seats are installed on the upper side and the lower side of the case, a cushion seat is installed below the case seats, a lower seat is installed below the cushion seat, a heat removal groove is formed in the surface of the lower seat, special-shaped grooves are formed in the two sides of the heat removal groove, and the heat removal groove and the special-shaped grooves are communicated with each other. A base plate is embedded in the special-shaped groove, and a supporting plate is arranged on one side of the base plate. The pedestal is installed at the bottom of the case and divided into an upper part and a lower part, the lower part is a lower seat, and the lower seat and the pedestal are movably connected through sleeving connection between the hollow sleeve and the sleeve rod, so that the pedestal and the lower seat are conveniently separated, the space of the bottom of the pedestal is enlarged, the heat dissipation space is increased, and better heat dissipation is facilitated; a special-shaped groove of a T-shaped structure is formed in the surface of the cushion seat, the cushion plate and the supporting plate are moved, and the cushion plate is used for increasing the height of the cushion seat, so that the space between the cushion seat and the lower seat is increased.

A black screen control system for nitric acid production, comprising network hardware nodes deployed in a local area network and control units running on the network hardware nodes, the control units are independently deployed at each operation station and adopt a multi-thread isolation architecture. The invention allocates time-consuming bottom layer data collection, processing and front-end UI interaction to independent threads for asynchronous execution, ensuring the ultimate smoothness and stability of the system under high concurrency; the state control and abnormal response are separated, the system enters the energy-saving black screen state under normal conditions to reduce power consumption, and when an abnormal signal occurs, the system is instantly awakened across threads and a safety alarm is triggered, realizing true safe unattended operation; the control units are independently deployed and run at each operation station, and are uniformly scheduled by a master control module, avoiding the whole line paralysis caused by single point failure or network fluctuation, and ensuring the absolute independence and reliability of a single device.

Respective network addresses are assigned to a networking hardware device and a network function accelerator incorporated within an offloading card of a virtualization server by a control plane server of a virtualized computing service. A compute instance is launched at the virtualization server using a virtualization controller of the offloading card. The compute instance executes a network function of a radio-based application in response to a request received using the network address assigned to the hardware device, and requests execution of a second network function at the accelerator. The result of the second network function is sent to a radio unit of the application using the address assigned to the accelerator.

The invention provides an optimal phase shift parameter design method based on a switch multiplexing type multi-resonant switched capacitor, and the method comprises the steps: determining a control parameter combination according to the value interval of a preset phase shift ratio and a preset frequency ratio; determining resonance network hardware parameters according to the preset target equalization power and the preset resonance frequency; according to a preset soft switching constraint condition, verifying a parameter set composed of all control parameter combinations and resonance network hardware parameters; if the parameter set meets the preset soft switching constraint condition, taking the parameter set as an element of a feasible solution set; screening a parameter set with the minimum root mean square value of the resonance current according to the feasible solution set; and according to the parameter set with the minimum root-mean-square value of the resonance current, screening the parameter set with the minimum peak value of the resonance current as an optimal working point. According to the invention, through collaborative optimization of multiple performance indexes, on the premise of following the soft switching constraint, the switching loss and the operation loss of the switching tube are reduced, and the overall efficiency and the reliability of the equalizer are improved.

Systems and methods for Kubernetes-cluster-driven modification of network hardware configuration. A Kubernetes event is detected in received network traffic and the corresponding packet is examined to identify a pod of a Kubernetes cluster, then the packet is forwarded to the pod for processing. The pod determines a configuration modification of a network hardware element (e.g., a load balancing switch) based on the processing of the event. The pod sends the modification to a controller, which then generates a command (e.g., an API call or CLI command) and sends this command to the network hardware element to implement the desired modification. The configuration of the network element is then updated according to the command received from the controller.

The application discloses a 2-group signed tensor calculation circuit structure based on a 6-bit approximate full adder, relates to the field of neural network hardware acceleration, and comprises a 6-bit approximate full adder module, a signed 8*8 approximate multiplier circuit structure based on the 6-bit approximate full adder and the 2-group signed tensor calculation circuit structure based on the 6-bit approximate full adder. Since the neural network accelerator can sacrifice part of the accuracy of data in exchange for the optimization of delay, area and power consumption of a circuit structure, the 6-bit approximate full adder module ignores part of the carry, thereby reducing the circuit area and lowering the circuit power consumption, the signed 8*8 multiplier calculation process and the 2-group signed tensor calculation process are optimized by using the 6-bit approximate full adder module, approximate calculation is introduced at some positions, and in exchange for the improvement of area and power consumption of the circuit structure, part of the accuracy is lost.

The technology is directed to methods and systems in which network hardware components and their associated functionality are incorporated into servers, the network hardware components functioning to couple the servers to one or more networks. The network hardware components include virtual routers and are configured to form a ring network that includes their respective servers and an aggregation switch. The routing capability provided via the network hardware components function within the network to advertise routes to each other and provide the aggregation switch access to pathways that can be used to deliver data packets to their destination without using other switches, e.g., a top of rack switch.

A computing device includes a memory and a processing device. The memory enters an uninitialized state in response to power being applied to the memory. The processing device is coupled to the memory, and is configured to select a portion of the memory in the uninitialized state to seed a random number generator process. The processing device may alternatively select an uninitialized state of the network hardware that is coupled to the processing device to seed a random number generator process. In one embodiment, the computing device is a compute node in a multi-node processing system, and the memory is a High-Bandwidth Memory.

This application discloses a method, apparatus, device, storage medium, and program for adjusting the number of virtual machine connections, relating to the field of cloud platform technology. The method includes: determining the maximum preset number of tracking connections supported by the host machine in a cloud environment based on the network hardware information corresponding to the host machine and the expected load of establishing the virtual machine; sending status detection commands to each of the multiple target virtual machines when multiple target virtual machines already exist in the cloud environment; determining the actual tracking connection data corresponding to multiple connection tracking domains associated with the multiple target virtual machines based on the feedback results of the status detection commands; and adjusting the upper limit of the number of tracking connections supported by each target virtual machine based on the maximum preset number of tracking connections and the actual tracking connection data. This solves the problem in related technologies where the dynamic control of the number of virtual machine tracking connections in a cloud environment is insufficient, thus affecting the communication performance of the host machine.

Various aspects of the subject technology relate to systems, methods, and machine-readable media for cross-platform programmable network communication. The method includes receiving, via a conversational user interface (UI), a request from a user for a radio access network (RAN), the request including a description of a set of requirements for the RAN made in a conversation format. The method also includes generating a set of constraints for network hardware of the RAN based on the request. The method also includes providing, via the conversational UI, a description of the set of constraints to the user. The method also includes generating, based on an approval of the set of constraints from the user, a solution to a deployment for the network hardware of the RAN according to the set of constraints. The method also includes outputting a description of the solution including attributes of the solution.

The invention discloses a data processing method, device and equipment for a long short-term memory network and a medium, relates to the technical field of computers, and is applied to a preset long short-term memory network hardware implementation circuit, and the circuit comprises a plurality of static random access memories used for storing different types of network input data. The method comprises the steps of determining an initialization result based on a data processing task; based on a preset slicing strategy and a preset three-dimensional cyclic data processing strategy, splitting and loading various data in the initialization result, and triggering a storage operation of a corresponding static random access memory; after all storage operations are completed, data processing corresponding to four gates in the long and short-term memory network is completed in sequence based on the data in each static random access memory; and when it is judged that the cyclic data processing of the three dimensions is completed currently, obtaining a task result based on a corresponding data processing result. Through efficient and reasonable hardware circuit design, the hardware acceleration efficiency during data processing can be improved.

This invention relates to the field of network hardware security technology, specifically disclosing a device authentication and key derivation method and electronic device based on FPGA physical binding. The method includes: in response to device power-on, blocking the protected data path; calling the underlying hardware primitives of the FPGA to read the chip's unique physical identifier sequence; comparing the unique physical identifier sequence with preset authentication information to generate an authentication result; and generating a working key based on the unique physical identifier sequence and an external input key when authentication is successful. This invention restricts the protected data path at the initial power-on stage of the device and combines the chip-bound physical identifier sequence with the external input key to dynamically generate the working key, reducing reliance on static key storage mechanisms and mitigating the risk of configuration data being copied to unauthorized chips and continuing to operate.

The invention provides a partial product decoupling-based dynamic precision approximate multiplication implementation method and a multiplier, and the multiplier comprises a significance evaluation unit which splits a first operand and a second operand into high digits and low digits, and correspondingly generates a first amplitude and a second amplitude; different precision instructions are generated based on the amplitudes and the threshold values; the dynamic precision unit performs zero setting processing on the second low digit based on the precision instruction to form an approximate number, and calculates a partial product of the first high digit and the approximate number; the accurate calculation unit accurately calculates products of the other three parts; and the final addition unit sums the products of the four parts according to the weight. The calculation unit can be used for constructing or optimizing a multiplication calculation array in a neural network hardware accelerator, is particularly suitable for scenes with dense fixed-point number operation such as convolution, and performs efficient approximate operation on the input fixed-point number through a data driving mechanism by utilizing the common sparsity and amplitude difference characteristics of neural network data, so that the calculation efficiency is improved. And self-adaptive management of power consumption is realized.

1. Name of the Design Product: Computer Network Equipment Storage Cabinet. 2. Use of the Design Product: The design product is used for storing computer network hardware equipment. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Stereogram.

The invention discloses an artificial intelligence-oriented neural network method. The method comprises the following steps of S1, constructing related contents on an FPGA (Field Programmable Gate Array) device by using an RISC-V instruction set; s2, designing an assembly line and a bus based on the specific structure of the Xuanting E902 processor of the RISC-V architecture; s3, determining neural network parameters according to verification; s4, the FPGA implementation and digital identification verification process of the E902 kernel is divided into an ov5640 camera image acquisition and data processing part and a neural network hardware implementation part and is integrated into an IP core on the whole; s5, verifying the database minst through the artificial neural network, and achieving the recognition of the handwritten characters on the FPGA. The flexibility of a kernel is improved, the language compiled by itself is strictly matched between the two platforms, the incompatibility situation is avoided, the system stability is improved, the effect in the aspect of gesture recognition is more prominent, and the method is suitable for popularization and application. The method has a wide application prospect and is beneficial to popularization and application.

The application provides a dynamic adjustment method, a management device and a system of a vehicle network. The dynamic adjustment method comprises: acquiring data transmission requests of each first function module and each second function module respectively; acquiring network state data of a vehicle-mounted network and external networks corresponding to each first function module respectively; determining network working modes of each first function module according to the network state data and the data transmission requests; determining network use permissions of each first function module and each second function module according to function attributes of each first function module and each second function module; and controlling each first function module to work in a corresponding network working mode, and controlling each first function module and each second function module to transmit data based on the vehicle-mounted network and / or each external network according to the corresponding network use permissions. According to the application, the defects of network hardware can be solved through software, and the real-time performance of the function of the vehicle network is improved.