149 results about "Adapter (computing)" patented technology

The invention discloses a computing system and a control method, device, equipment, medium and product thereof, and relates to the technical field of computers.A host device, a first switch and an acceleration computing device are divided, the first switch comprises a plurality of interconnected switching controllers, and uplink ports of the switching controllers are connected with the host device; the downlink port is connected with the acceleration computing device, the binding relation of the physical link layer between the mainboard and the acceleration card is removed, the port configuration and the resource allocation path of the exchange controller can be flexibly adjusted, and the acceleration computing resources can be allocated according to needs. The first board card provided with the first slot and the cable adapter plate are arranged in the acceleration computing device, so that the acceleration computing device with high-density deployment is realized. Therefore, the method solves the problem that the expansion capability of acceleration computing resources of a multi-card system reaches a bottleneck, and lays a foundation for expanding large-scale computing power by a single host and constructing a multi-host shared large-scale computing resource pool.

The invention provides a multi-LoRA large language model deployment system based on a cloud computing platform. A cloud computing AI platform layer trains a LoRA adapter matched with a basic large language model for a reasoning process; the multi-LoRA dynamic loading layer dynamically switches LoRA adapters needing to be mounted according to the request parameters, GPU optimization configuration is carried out according to service priorities in the request parameters, a basic large language model is loaded, and a plurality of LoRA adapters stacked in a sparse matrix form are mounted; and the resource scheduling optimization layer responds to the resource scheduling application, and outputs the request parameters subjected to priority management and hardware sensing optimization to the LoRA dynamic loading layer based on the container arrangement platform. According to the method, LoRA and container arrangement are deeply fused, and an automatic assembly line of training and reasoning is achieved. A video memory sharing mechanism enables a plurality of service scenes to share the same basic large language model, a LoRA adapter is loaded as required, and video memory occupation is greatly reduced. Full-life-cycle management from data preparation to model service is supported, and the large model deployment cost is remarkably reduced.

A non-transitory storage system is constructed based on the converged architecture system and includes: a plurality computing nodes in a computing resource pool, an adapter board, and a plurality of solid-state drives configured to establish a communication connection with the plurality of computing nodes through the adapter board to expand a storage resource pool. Through the foregoing design, the storage resource pool is expanded based on the third-generation converged architecture system and a bus interconnection technology, to achieve remote expansion of storage. In addition, the plurality of computing nodes share decoupled storage resources, thereby solving the problems that a storage capacity of conventional Just a Bunch of Flash (JBOF) may only be expanded to a limited extent and remote decoupled access to storage resources by a plurality of hosts is not capable to be achieved.

The embodiment of the invention relates to the field of computing power scheduling, and discloses an intelligent inference system and method, equipment and a medium. The system includes a base model for performing an inference process of shared parameters; a plurality of adapter models, each of which is used for performing an inference process of an inference task; the base model and the adapter model are separately and independently deployed, and parallel inference of the multiple adapter models on one base model is supported; and the intelligent router is used for receiving and analyzing the inference task, selecting the corresponding adapter model according to a preset rule, and loading the adapter model to the corresponding inference node. By introducing the adapter design of the LoRA model and the intelligent router mechanism, the efficient deployment and inference of the multi-expert model in the low video memory environment are realized, the use of the video memory can be obviously reduced, and the inference response speed is improved at the same time. The technical problem of low expert model inference efficiency can be at least solved.

The invention provides an open accelerator infrastructure server which can be applied to the technical field of servers. The server comprises an acceleration node comprising a universal substrate, a plurality of accelerator modules and at least one switch chip, the plurality of accelerator modules and the at least one switch chip being arranged on the universal substrate; the computing node comprises a server main board and a plurality of computing units arranged on the server main board, each computing unit is provided with a network interface card, and the server main board and the universal substrate are arranged in parallel; the front panel is provided with M structure pluggable modules and N network interface cards, the front panel is used for interconnection between the acceleration node and at least one computing node and interconnection between the acceleration node and an acceleration node outside the open accelerator infrastructure server, and the front panel is perpendicular to the universal substrate.

A misinsertion detection method for an external device, and a computing device, relating to the technical field of servers, for use in ensuring the correct connection between a docking station and a computing device, so that the computing device can normally use a hardware device to be expanded that is inserted on the docking station. The computing device comprises a controller, a plurality of adapter connectors, and at least two docking stations; each docking station comprises at least two expansion connectors; one of the plurality of adapter connectors is connected to one expansion connector; the plurality of adapter connectors are separately connected to the controller; and the controller is configured to: determine a current connection relationship of each docking station, the connection relationship comprising a connection relationship between each expansion connector of the docking station and the corresponding adapter connector; and output alarm information when the current connection relationship of the docking station is different from a preset connection relationship of the docking station, the alarm information being used for indicating that the current connection relationship of the docking station is incorrect.

The invention relates to the technical field of block chain smart contracts, and provides a smart contract automatic execution system and method based on a block chain technology. In order to solve the problems that in the prior art, out-of-chain event verification is fragile, cross-contract atomicity is lacked, and resource management and control are insufficient, the system comprises a multi-mode under-chain event verification module, and a tamper-proof data channel is established through an Internet of Things hardware anchor point and an anti-collusion oracle; the autonomous execution engine is integrated with a resource awareness scheduler and an out-of-chain computing adapter; the transaction atomicity guarantee module is used for realizing cross-contract rollback by adopting a global snapshot tree and an intelligent compensation contract; the governance arbitration interface supports anonymous dispute resolution. The method comprises the steps of out-of-chain event multi-level verification, voucher execution queue management and sandbox resource isolation control. Credible collaboration inside and outside the chain is realized, the execution reliability is improved by more than 90%, and the contract development cost is reduced by 40%.

The invention provides a personalized federated learning method based on personalized enhancement and sharing self-adaption, which comprises the following steps: enabling a sharing module in a Transform model to participate in federated aggregation, promoting knowledge migration of each client, storing a personalized module in a local client, and improving the adaptability to heterogeneous data; a Lora low-rank adapter is introduced into a personalized module, only Lora parameters are uploaded, feature expression homogenization caused by global aggregation is avoided, initial global shared module parameters and local parameters of a shared module are subjected to self-adaptive fusion, semantic offset caused by model decoupling is effectively relieved, and the robustness of the system is improved. Therefore, the generalization performance is improved, and the stability and adaptability of a local model are kept; dynamic incremental clustering is performed on each client based on Lora parameters, and shared feature representation with cross-client migration value is mined in a personalized module, so that the calculation overhead is reduced, and the personalized knowledge sharing and migration capability among similar clients is enhanced.

The invention relates to the technical field of electric power design, and discloses an electric power design agent intelligent processing system based on an AI large model, which comprises an interface interaction module, a professional model module, a dialogue management module and a professional algorithm module. The interface interaction module orderly calls idle modules according to the instruction sequence; the professional model module periodically retrieves multi-source data, constructs a professional data set through dynamic denoising, secondary classification processing and verification, generates a fine tuning data set through various knowledge distillation modes, and optimizes an industry large model by adopting a low-rank adapter; the dialogue management module is connected with input and output and instruction generation; and the professional algorithm module dynamically calls five types of professional models and adapts to computing power resources. According to the system, a traditional tool data island is broken through, the problems of general LLM professional shortages and'illusion 'are solved, automatic closed loop from natural language interaction to professional design tasks is achieved, manual dependence and error risks are reduced, and power design efficiency, quality and system stability are improved.

Systems, methods, and apparatuses disclosed herein can enable a computing system to connect to a network. These systems, methods, and apparatuses can connect the computing system to the network through multiple network connections. These multiple network connections represent distinct, physically separate signal pathways to improve security. This physical separation, or isolation, from one another creates distinct boundaries between these multiple network connections, for example, to minimize shared resources these systems, methods, and apparatuses. These distinct boundaries can reduce the vulnerability of these systems, methods, and apparatuses to, for example, attacks that exploit shared sources among these systems, methods, and apparatuses, data leakage within these systems, methods, and apparatuses, and / or unauthorized access to these systems, methods, and apparatuses. Moreover, these distinct boundaries can additionally enhance security by improving fault isolation, enforcing access control, and / or supporting secure communication protocols, among others, within these systems, methods, and apparatuses.

The invention provides a modular data center machine room system, and belongs to the technical field of intelligent machine rooms, the modular data center machine room system comprises a plurality of stackable functional unit modules, and each functional unit module comprises a composite load-bearing frame, an integrated standardized mechanical interface and an electrical fast-assembly interface; the computing unit supports plug and play of heterogeneous computing equipment; the storage unit supports RAID hot plug of the mixed medium; the network unit provides a programmable switching matrix; the power supply unit is internally provided with a multi-mode adapter and is compatible with AC / DC input and lithium battery / super capacitor hybrid energy storage; and the central intelligent management platform monitors the real-time load rate and the energy efficiency ratio of each module, coordinates the resources of each module, detects the interface attribute of a new module and configures a network address when judging that the new module needs to be accessed, executes a topology reconstruction instruction, carries out topology reconstruction and outputs a prompt. Compared with the prior art, the crossing from a fixed framework to elastic ecology is realized.

The subject technology relates to model compatibility for large language models. An apparatus receives a first trained machine learning model having a first adapter layer and generates a second trained machine learning model having a second adapter layer, in which the second model is a transformed version of the first model and both models share a base model. The apparatus initializes the second adapter layer using parameters derived from the first adapter layer and trains the second adapter layer using parameters of the first adapter layer and initialization parameters of the second adapter layer. The apparatus computes a divergence metric between probability distributions of the two models to assess a difference between them. The second adapter layer may be adjusted based on the divergence metric exceeding a threshold. The apparatus deploys the second trained machine learning model in a computing environment based on the divergence metric not exceeding the threshold.

An instruction executing within a computing environment is used to perform at least one operation on one or more controls of a queue to be used in communications between a control program executing within the computing environment and an adapter module of the computing environment. Execution of the instruction includes obtaining an indication of the queue for which at least one operation is to be performed on the one or more controls of the queue. At least one operation is performed on the one or more controls of the queue and a result of executing the instruction is provided.

A control program executing on a computing device of a computing environment transmits control request information to an adapter module executing within the computing environment. The transmitting uses a control plane transmit queue of a set of queues. The control plane transmit queue identifies a location to store the control request information to be retrieved by the adapter module. The control program receives from the adapter module an indication of another location storing control reply information replying to the control request information. The indication is obtained from a control plane receive queue of the set of queues. The control program retrieves from the another location the control reply information and performs processing based on the control reply information.

The invention relates to the technical field of data security and privacy computing, in particular to an ODRL-based trusted data space data delivery method and system, and the method comprises the following steps: defining data use permission and constraint through an ODRL strategy, verifying a user request by a control plane based on the ODRL strategy, and recording a structured log by a data plane through a protocol adapter factory; the method has the beneficial effects that through layered architecture design, ODRL deep integration, protocol irrelevant adaptation and full-link security auditing, the core problems of an existing data delivery scheme in the aspects of authority management, transmission flexibility, performance and compliance are systematically solved, and a universal and highly reliable technical solution is provided for trusted data space construction; and the data circulation efficiency and security are remarkably improved, and the method has wide industrial application value.

An identifier, such as a worldwide name, corresponding to a host computing device, or corresponding to a host bus adapter corresponding to the host computing device, may be transmitted to a storage array to configure the storage array to be accessed by the host computing device. The host may request a token from the array. The host may embed the token into a token block of a command message that is transmitted to the storage array requesting access to the array. Before performing an action corresponding to the command message, the storage array may verify that the token is a valid token and thus that the host computing device that transmitted the command message is a host computing device that has been authorized to access the storage array. If the storage array determines that the token is valid the storage array may perform an action corresponding to the command message.

Embodiments of the present disclosure implement hardware-based snoop logic streaming timers for input / output (I / O) communications between a host and a shared network adapter in a computing system. The disclosed embodiments describe a hardware-based snoop logic and snoop logic timer function control of input / output (I / O) processor monitoring a defined memory area to detect a completion queue entry being written to a completion queue, and implementing streaming timers and interpacket timers, based on the completion queue entry and predefined configuration information for an associated host interface connection, to provide streaming data status, interpacket arrival times, and streaming timer expiration for the associated host interface connection.

An assembly kit for a computing system is disclosed. The assembly kit includes a mounting ear configured for attachment to a computer chassis, the computer chassis being configured to be received in a cabinet, the mounting ear having an L-shape formed by a first wall and a second wall, the second wall being perpendicular to the first wall, wherein the mounting ear is configured to receive a fastener configured for attaching the assembly kit to the cabinet; and an adapter releasably coupled to the mounting ear, the adapter having a third wall, a fourth wall that is perpendicular to the third wall, and a fifth wall that is perpendicular to the third wall, the fourth wall and the fifth wall being parallel. A space is formed between the fourth wall and the fifth wall, the space being configured to receive the fastener.

This invention discloses a non-embedded UAV information acquisition device and method. The non-embedded UAV information acquisition device includes a shell assembly, a three-mode adapter structure, a standardized physical interface, a main control module, a communication module, a positioning and sensing module, and a power management module. The internal cavity wall of the shell assembly is fitted with an anti-magnetic shielding layer made of permalloy. The three-mode adapter structure is integrated into the bottom of the shell assembly and includes a magnetic suction component, a suspension component, and a screw fixing interface. The standardized physical interface is located on the surface of the shell assembly and uses a gold-plated gold finger contact structure, which is electrically connected to the main control module. This invention enables deployment without disassembly of the UAV through a non-intrusive design while maintaining the UAV's airworthiness. It utilizes edge computing to alleviate cloud scheduling pressure and reduce task latency, and with independent power supply, achieves long endurance and high reliability, making it widely adaptable to various UAV models and harsh operating environments.

The application belongs to the technical field of collaborative learning, and particularly relates to a parameter efficient collaborative learning method and system suitable for intelligent sensing devices. The application is directed to a collaborative application scene of multiple distributed terminal devices with sensing, computing and communication capabilities. Under the premise of freezing backbone parameters, a shared adapter and a personalized adapter are introduced. Personalized parameters are only updated and saved locally to maintain single-device adaptation capability. Shared parameters realize knowledge sharing through interaction and weighted aggregation of neighboring devices. An adaptive weight matrix is used to fuse shared prediction and personalized prediction, so that global collaboration and personalized adaptation are considered in the distributed sensing scene with significant data distribution difference. Meanwhile, only the lightweight trainable part is updated and exchanged, which significantly reduces the end-side computing burden and communication overhead, and maintains the efficiency and convergence stability of collaborative learning under resource-limited conditions.

Techniques discussed herein relate to monitoring and / or detecting destabilization events of a host machine of a cloud computing environment. At least some of these destabilization events can be associated with a converged network adaptor of the host machine. The converged network adaptor may include a combination of functionality of a host network interface card (NIC) and functionality associated with a smart adaptor (e.g., a smart NIC). The smart adaptor may be configured to use at the host machine. A converged infrastructure management service may monitor operational data associated with the host machine to identify destabilization events that may be associated with the converged network adaptor. One or more remedial actions may be identified based at least in part on identifying these destabilizing events.

This application discloses an adapter structure, a board assembly, a quantum computing measurement and control system, and a quantum computer. The adapter structure is used to electrically connect a first signal connector of a functional board to a second signal connector of a measurement and control circuit. The adapter structure includes: a mounting base for detachable installation with the functional board; and a signal adapter connector installed within the mounting base. One end of the signal adapter connector is used to insert and cooperate with the first signal connector under the support of the mounting base to form a first connection interface, and the other end is used to insert and cooperate with the second signal connector to form a second connection interface. The first connection interface provides low insertion and extraction force to extend the insertion and extraction life of the first signal connector, while the second connection interface provides high insertion and extraction force to enhance the connection reliability of the second signal connector. This adapter structure significantly improves the insertion and extraction life of the functional board and reduces maintenance costs while ensuring connection reliability.

Embodiments of the present disclosure implement hardware-based snoop logic streaming timers for input / output (I / O) communications between a host and a shared network adapter in a computing system. The disclosed embodiments describe a hardware-based snoop logic and snoop logic timer function control of input / output (I / O) processor monitoring a defined memory area to detect a completion queue entry being written to a completion queue, and implementing streaming timers and interpacket timers, based on the completion queue entry and predefined configuration information for an associated host interface connection, to provide streaming data status, interpacket arrival times, and streaming timer expiration for the associated host interface connection.

The invention relates to a computer network system, a computer networking method and a computer readable medium. A system is configured to calculate a delay between a first computing device and a second computing device. The system includes a network interface card (NIC) of a first computing device. The NIC includes a set of interfaces configured to receive one or more packets and to transmit the one or more packets. And a processing unit configured to identify information indicative of a forward packet, calculate a delay between the first computing device and the second computing device based on a first time corresponding to the forward packet and a second time corresponding to a reverse packet associated with the forward packet, the second computing device includes a destination of the forward packet and a source of the reverse packet, and outputs information indicative of a delay between the first computing device and the second computing device.

The invention provides a method and device for generating a service execution component through computing power of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructure, the method comprises the following steps: S1, based on the computing power of the intelligent computing center, obtaining coding demand information from static planning information, the static planning information is used for indicating a business processing logic of a target business; and S2, taking the coding demand information as a coding prompt word, and carrying out coding based on the computing power of an intelligent computing center to obtain an adapter function. Under the condition that the basic function cannot meet all the requirements of the target service, the personalized function requirements of the target service are obtained from the static planning information corresponding to the target service by using the computing power of the intelligent computing center to form the coding requirement information, and the coding requirement information is used as the coding prompt word, so that the coding efficiency is improved. And quickly coding to obtain an adapter function for connecting the basic function, so as to guarantee smooth execution of static planning.

The disclosed systems, methods and computer readable media relate to managing Non-Volatile Memory Express (NVMe) over Transmission Control Protocol (TCP) (NVMeOTCP) connections between a smart network interface card (smartNIC) and a block storage data plane (BSDP) of a cloud computing environment. A software agent (“agent”) executing at the smartNIC may manage a number of network paths (active and, in some cases, passive network paths). The agent may monitor the network traffic (e.g., input / output operations (IOPS)) through the paths (e.g., using established NVMeOTCP connections corresponding to the paths). If a condition is met relating to a performance threshold associated with the monitored paths, the agent may increase or decrease the number established NVMeOTCP connections to match real time network conditions.

The application discloses a kind of based on flow perception intelligent network interface card optimization system and method, it belongs to computer network technical field.The optimization system of the application includes flow perception module, flow prediction module, resource scheduling module, priority queue module and load balancing module.The application introduces resource monitoring, flow perception, resource prediction and dynamic scheduling module, real-time monitoring network flow and predicting its change trend, according to flow mode dynamically adjusts resource allocation.The application effectively solves the problem of resource contention, through priority ordering and load balancing, ensure the stable operation of high priority task, improve the throughput and stability of system, reduce resource waste.The application is suitable for resource management of intelligent network interface card in data center and cloud computing environment, improves network processing efficiency and resource utilization, guarantees service quality, reduces resource waste, and enhances the adaptive capacity of system to dynamic load and complex flow mode.

Embodiments of the present disclosure implement hardware-based snoop logic streaming timers for input / output (I / O) communications between a host and a shared network adapter in a computing system. The disclosed embodiments describe a hardware-based snoop logic and snoop logic timer function control of input / output (I / O) processor monitoring a defined memory area to detect a completion queue entry being written to a completion queue, and implementing streaming timers and interpacket timers, based on the completion queue entry and predefined configuration information for an associated host interface connection, to provide streaming data status, interpacket arrival times, and streaming timer expiration for the associated host interface connection.

Systems and methods for supporting heterogeneous and asymmetric dual rail fabric configurations in a high performance computing environment. A method can provide, comprising at one or more computers each including one or more microprocessors, a plurality hosts, each of the plurality of hosts comprising at least one dual port adapter, a private fabric, the private fabric comprising two or more switches, and a public fabric, the public fabric comprising a cloud fabric. A workload can be provisioned at a host of the plurality of hosts. A placement policy can be assigned to the provisioned workload. Then, network traffic between peer nodes of the provisioned workload can be assigned to one or more of the private fabric and the public fabric in accordance with the placement policy.