242 results about "Virtual computing" patented technology

The invention discloses a computing power resource collaborative scheduling method and device in a multi-cloud scene and a storage medium, and belongs to the field of computing power resource management. Constructing a virtual computing power resource pool based on the multi-cloud cluster; receiving a to-be-processed task, and obtaining a target server identifier and target computing power resource state information; performing task processing capability evaluation on the target cloud processing server, and judging whether the computing power resource requirement of the to-be-processed task is met or not; when the computing power resource requirement of the to-be-processed task is not met, dividing the to-be-processed task into a plurality of sub-tasks; and performing cross-cloud cooperative distribution on the plurality of sub-tasks, so that the loads of the plurality of cloud processing servers tend to be balanced, generating a target scheduling scheme, and executing cross-cloud cooperative processing of the plurality of sub-tasks. The technical problems of low computing power resource scheduling efficiency and unbalanced load in the multi-cloud environment in the prior art are solved, and the technical effects of improving the computing power resource utilization efficiency in the multi-cloud environment, realizing cross-cloud cooperative processing and optimizing load balancing are achieved.

The invention discloses an edge-end-side heterogeneous computing power resource scheduling system and method.The system comprises a computing power virtualization resource pool module, a cross-domain distributed computing power soft bus and a computing power resource scheduling management module, the computing power virtualization resource pool module is based on the heterogeneous computing power virtual computing resource pool technology, and the cross-domain distributed computing power soft bus is used for scheduling the computing power resource scheduling management module; performing unified management and virtualized mapping on various equipment systems on the edge side and the end side according to computing power resources, network resources and storage resources to form a unified virtual computing resource pool; according to the cross-domain distributed computing power soft bus, intermediate routing forwarding nodes of computing power resources are established among different communication domains, the routing forwarding nodes support a power system physical layer protocol, and computing power resource lists among different communication protocol networks are synchronously updated in real time; and the computing power resource scheduling management module is used for realizing dynamic allocation management of computing power resources based on a dynamic computing power scheduling system established by the computing power resource pool, evaluating the computing power demand required by each computing task in real time, and requesting the virtual computing resource pool to allocate an optimal computing power resource combination for algorithm application.

The invention provides a resource unified management method and system based on heterogeneous computing power, and relates to the technical field of resource allocation of heterogeneous computing power. According to the method, operation instructions of different computing units are converted into bidirectional irreversible instruction sequences by constructing a heterogeneous presentation layer, and physical resources are abstracted to generate a virtual computing power unit. A multi-dimensional efficiency baseline is constructed based on parameters such as real-time load and network jitter tolerance, and a time-varying efficiency curve is dynamically generated in combination with a hardware aging rate. A user task is decomposed into sub-task chains, intelligent resource binding is realized by matching hardware sensitivity characteristics with an efficiency curve, and conflicts are solved by adopting reinforcement learning. And monitoring efficiency offset in real time during execution, performing reverse backtracking during abnormality, and generating a recombination strategy based on the alternative resource set. According to the system, efficient management and dynamic optimization of heterogeneous computing power resources are realized, and the computing efficiency and reliability are remarkably improved.

The invention provides an audio and video system data comprehensive analysis and processing method based on a virtual distributed architecture, and the method comprises the steps: collecting a heterogeneous audio and video data set of a target region through a multi-source audio and video collection assembly cluster deployed in a virtual resource pool, and carrying out the distributed task decomposition according to a preset time-space correlation constraint condition; the method comprises the following steps: generating a feature extraction task set, then dynamically allocating tasks to a processing unit group based on real-time resource availability parameters of virtual computing nodes, triggering a parallel feature extraction process, then carrying out fusion operation on an intermediate feature data set through a cross-node communication interface, generating a global state description vector of a target area, and finally, carrying out feature extraction on the global state description vector. And a resource regulation and control instruction set is generated according to a mapping relation between the global state description vector and a preset system configuration strategy, and is transmitted to a scheduling management node of the virtualized resource pool, so that efficient and accurate comprehensive analysis and processing of the audio and video data are realized, and the overall performance and stability of the system are improved.

The invention discloses a computer network experiment environment dynamic construction method based on virtual simulation, which belongs to the field of computer network experiment teaching and virtual simulation technology application, and comprises the following steps: analyzing experiment scene description to generate a modular construction instruction; creating and initializing a virtual machine instance and a basic network; generating a required virtual network device and constructing a corresponding virtual connection; configuration parameters, service scripts and security policies are comprehensively applied to the virtual machine and the network equipment; and integrally outputting the experimental environment to a user interaction interface. According to the method, the demand-driven instruction arrangement, virtual resource pooling scheduling and multi-layer automatic configuration technologies are adopted, so that a diversified and deeply interactive virtual computer network experiment environment can be quickly and flexibly constructed according to specific experiment demands of a user; and the resource utilization rate, the scene construction efficiency and the flexibility of the teaching mode of network experiment teaching are obviously improved.

The present invention provides a fuzz testing system and method based on a virtual computer model. Traditional fuzz testing approaches primarily modify external inputs to detect security vulnerabilities, making it difficult to monitor internal state changes in real-time. This invention constructs a test environment using a virtual computer model and incorporates automatic assertion generation and detection functions, enabling precise analysis of both internal and external signals of the system. After executing fuzz testing, assertion data is analyzed to assess test coverage and identify untested code regions, allowing for an optimized testing strategy. This improves the detection rate of security vulnerabilities, enhances test automation and reliability, and can be applied in various fields such as networks, automotive ECUs, IoT, finance, aerospace, and semiconductors.

Systems and methods are provided for managing computing services for an application comprising a plurality of virtual computing components executing on one or more host computing devices, wherein a service virtual computing component is to perform application functionality, and wherein a system computing component is to perform system functionality including management of the application virtual computing component; determining the service virtual computing component is to execute using a first access credential to provide a first computing service to the application virtual computing component, and the service virtual computing component is to execute using a second access credential to provide a second computing service to the system computing component, wherein the first access credential is assigned a different set of computing resource access permissions than the second access credential.

The invention provides a three-dimensional modeling optimization method and system for a hull fairing, and relates to the technical field of hull fairing three-dimensional modeling, and the method comprises the steps: according to a preliminary hull fairing model, defining a virtual computational domain including the hull fairing and the surrounding environment thereof; setting boundary conditions, dividing the computational domain into a plurality of grid units, and generating boundary layer grids on the surface of the ship body; numerical simulation is carried out, and solving parameters are set and comprise a time step length, a convergence criterion and a discrete format; the resistance performance, including frictional resistance and differential pressure resistance, of the hull fairing in water is calculated through numerical simulation. According to the invention, the design accuracy is improved.

The invention discloses a disk data encryption and decryption method and device, equipment and a storage medium, and relates to the technical field of information security, and the disk data encryption and decryption method comprises the following steps: sending a first key to a volume encryption application component through a virtual computing node controller program by using a virtual encryption volume constructed based on a created virtual machine mirror image; triggering an encryption and decryption thread handle pool creation process by using an encrypted second key obtained based on the first key through the volume encryption application component; when encryption task information is received through the password management component, determining a first target password computing resource chain table based on an encryption and decryption thread handle pool corresponding to the encryption task information, and performing data encryption by using a resource chain table scheduling rule and the first target password computing resource chain table to complete disk data writing; when decryption task information is received through the password management component, the resource chain table scheduling rule and the second target password are used for computing the resource chain table for decryption, and data reading is completed. And the encryption and decryption efficiency is effectively improved.

The invention discloses a bypass laser scanning path planning method for additive manufacturing, and relates to the technical field of additive manufacturing, a printing area and an initial position are determined, the whole printing path is divided into a straight line section and an arc section, an area assistant is distributed for each divided area, a communication link is established, and the communication link is connected with the straight line section and the arc section; the regional assistant is provided with an independent virtual computing resource space; self-adaptive segmentation is executed through each regional assistant, communication with adjacent regional assistants is carried out by using a communication link when local control is executed, and a segmentation state and a result are synchronized; generating a virtual adhesive to carry out smooth transition and error compensation on a splicing gap; and after splicing is completed, submitting the whole path after splicing to a printing control system to execute printing. According to the method, adaptive path planning, multi-region parallel path segmentation task processing and segmented region high-precision splicing according to the local features of the printing region are realized, and efficient and high-quality additive manufacturing printing is achieved.

Systems and methods that enable the efficient and adaptive allocation of resources dedicated to a virtualized resource-based computation (e.g., one or more information processing tasks) are provided. In one embodiment, a reward model is generated based on a set of statistical distributions, for example, in response to receiving a request to launch a set of VCRs. Thereafter, an expected reward is predicting for each configuration of a set of configurations based on the reward model and one or more parameters of the corresponding configuration. The expected reward indicates an efficiency in distribution or allocation of physical computation resources to the set of VCRs. A configuration of the set of configurations is selected based on the predicted expected reward for the configuration. The set of VCRs are then configured with the selected configuration.

The invention discloses a six-degree-of-freedom multi-spacecraft control experiment platform and method based on semi-physics-virtuality, belongs to the technical field of spacecraft system and control system simulation, and constructs a multi-spacecraft system composed of semi-physics spacecrafts and pure virtual spacecrafts. The attitude of the semi-physical spacecraft is simulated by a simulator mounted on a three-dimensional attitude air floating table, is acquired by a sensor and is converted into a rotation matrix form, and a translation part of the semi-physical spacecraft is virtually calculated through a simulation integrator; the pose of the virtual spacecraft is virtually simulated by an SE (3) integrator with high-guarantee geometric characteristics; the system takes the ROS as a communication framework, and realizes state and instruction release by adopting a custom message; and ensuring that the time system of each spacecraft is consistent with the real time through a time synchronization mechanism. The platform supports cooperative operation of a semi-physical spacecraft and a pure virtual spacecraft, and has the characteristics of flexible structure, high simulation precision and good expandability.

The invention discloses a multi-person interaction method based on a large-space computing technology, and relates to the technical field of multi-person interaction. In order to solve the technical problem that in the prior art, most of existing multi-user virtual interaction systems depend on a single interaction area, so that the user experience is poor when multiple users interact at the same time, the technical scheme provided by the invention is as follows: a multi-user interaction method based on a large-space computing technology is provided. Comprising the following steps: dividing a virtual space into a plurality of functional areas; controlling the temperature of the interaction area and the non-interaction area in real time; sharing of virtual roles is realized through the cloud computing platform; a sharing conflict coordination mechanism is introduced, an operation request of a user for a virtual role is managed, and conflicts are coordinated; creating a virtual computing space and dynamically allocating computing resources by combining distributed computing and a cloud platform; a digital co-construction and sharing platform is built through a 5G network and a holographic image technology, and multi-user interaction and co-construction and sharing of virtual articles are achieved. The method is suitable for being applied to virtual reality scene building work of multi-person interaction.

Techniques for executing multiple large language models (LLMs) on a single physical computing device, including receiving a task to be performed by at least a first LLM and a second LLM, creating a plurality of virtual compute nodes on the single physical computing device for processing at least some of first set of sub-tasks to be performed by the first LLM and second set of sub-tasks to be performed by the second LLM, wherein each one of the plurality of virtual compute nodes includes one or more graphics processing unit (GPU) cores allocated for performing a sub-task of the first set of sub-tasks or the second set of sub-tasks, and executing at least some of the first set of sub-tasks and the second set of sub-tasks substantially in parallel across the plurality of virtual compute nodes using shared memory. Inferences between the first and second LLMs may be shared.

The invention discloses a distributed simulation system, a simulation method, electronic equipment and a computer readable storage medium. The distributed simulation system comprises a database and a plurality of simulation nodes, wherein the database is configured to store performance data when multiple tasks are operated in a real distributed system; each simulation node comprises a scheduler, a distributor and a task simulator, and the scheduler is configured to obtain at least one simulation task; the distributor is configured to distribute virtual computing resources for each simulation task; and the task simulator is configured to run at least one simulation task according to a predetermined distributed strategy based on the virtual computing resources allocated for each simulation task and the performance data corresponding to each simulation task acquired from the database to obtain a running result.

The invention discloses a PCIe-based CPU, NPU and GPU interconnection cluster management method, and belongs to the technical field of interconnection cluster management. According to the method, an interconnection link is established through a PCIe switch, and bandwidth is dynamically allocated by means of the link to adapt to task requirements; multi-priority data transmission is supported, and bandwidth resources are distributed in order according to priorities; a multi-element operation mode is configured in advance, and physical and virtual computing power resources are distributed according to needs; and an equipment state monitoring mechanism is established, idle equipment enters a sleep mode, and meanwhile, all transmission links are combed and an optimal path is selected. According to the method, fine scheduling of cluster resources is realized, the bandwidth and computing power resource utilization rate is improved, the adaptation capability to different tasks is enhanced, the orderliness and stability of data transmission are guaranteed, the cluster operation energy consumption is reduced, and efficient and stable operation of the interconnected cluster is facilitated.

In one embodiment, a computer-implemented method comprises using a script automation processor that is hosted using a virtual compute instance and a virtual storage instance associated with one or more second non-transitory computer-readable storage media storing one or more second sequences of instructions defining an API implementation of the API, a graph server, and one or more programming language runtime interpreters, receiving a user pipeline automation script comprising one or more first sequences of instructions specifying one or more API calls to an application programming interface (API), and a user application; using the script automation processor, creating and storing one or more programmatic containers in memory of the script automation processor, the containers corresponding to functions that user pipeline automation script and user application invoke; using the script automation processor, creating and storing a directed acyclic graph (DAG) in the memory of the script processor, the DAG comprising nodes and edges corresponding to dependencies of the containers; using the script automation processor, interpreting the user pipeline automation script using a particular programming language runtime interpreter among the one or more programming language runtime interpreters; using the script automation processor, running the user pipeline automation script to automatically build, test, or deploy the user application in a cloud computing service.

The present application relates to a computing cluster simulation method, system, device, equipment, medium and product. Applied to any target virtual computing unit in each virtual computing node in the computing cluster, the method includes: receiving a read-write access request; the read-write access request includes a read-write access request sent by other virtual computing units in the computing cluster; each virtual computing unit in the computing cluster is configured with a communication port, and each virtual computing unit is connected to each other through the communication port; according to the read-write access request, the corresponding memory read-write operation is performed. A communication port is configured for each virtual computing unit in the computing cluster in advance, so that any virtual computing unit can send a read-write access request to other virtual computing units, and can receive a read-write access request sent from other virtual computing units, which is equivalent to any two virtual computing units in the computing cluster can access each other, realizing the interconnection simulation between the computing nodes in the computing cluster.

The invention relates to a GPU resource scheduling method and device in AI computing, and relates to the technical field of data processing. The method comprises the following steps: acquiring information representing an execution condition of a real AI calculation task and an execution condition of a virtual AI calculation task, determining a target GPU device from a plurality of GPU devices by utilizing the information representing the execution condition of the real AI calculation task and combining an actual condition of the AI calculation task, and executing the target GPU device according to the determined target GPU device. And determining a task execution strategy in combination with the actual condition of the AI calculation task and the execution condition of the virtual AI calculation task of the target GPU equipment, so that the target GPU equipment can execute the AI calculation task. By configuring the real AI calculation task and the virtual AI calculation task in the GPU equipment, the execution condition of the virtual AI calculation task can be used as reference information for scheduling GPU resources, and the GPU resources are also ensured to have a certain task execution margin, so that reasonable scheduling of the GPU resources is realized, and the efficiency and the precision of AI calculation are improved.

Methods and apparatuses for provisioning a database management platform in a cloud computing environment include a server that reserves virtual computing resources in the cloud environment. The server provisions a database management platform using the reserved virtual computing resources. The database management platform includes primary and secondary database instances, a database observer instance, and a platform monitor agent. The server configures a database observer instance to monitor availability of database instances and to route traffic to other database instances. The server integrates the database management platform with an identity authentication service, monitors operational status of the database management platform using a monitoring service, and refreshes the reserved virtual computing resources in the database management platform using a rehydration service.

A system to provision cloud computing-based virtual computing resources within a virtual environment comprising a server computer system including at least one cloud server computer implementing at least one virtual environment, and at least one virtual computer associated with the at least one virtual environment. The at least one virtual computer receives virtual computing resources from the server computer system. The server computer system is configured to provision at least one client device with at least one portion of the available virtual computing resources responsive to the at least one client device accessing the at least one virtual computer.

Techniques are disclosed for processing data packets and implementing policies in a software defined network (SDN) of a virtual computing environment. At least one network device is configured to disaggregate enforcement of policies of the SDN from hosts of the virtual computing environment. Tier-0 devices are communicatively coupled to network interfaces of the network device. The network device comprises a plurality of data processing units that are configured to implement functionality of the network device.

In some examples, a system receives, from a requester, a request to perform a first workload in a virtual computing environment, and determines a type of the requester, the determined type being one of a plurality of different requester types. The system receives metrics relating to resource usage in the virtual computing environment, and determines, using a machine learning model, an allocation of resources to the first workload based on the determined type of the requester and the metrics. The machine learning model adjusts the allocation of resources to the first workload based on further collected metrics relating to resource usage by the workload and based on a detected behavior of the requester while the first workload is performed in the virtual computing environment.

The invention relates to a double-machining-channel machine tool control method and system, a storage medium and a terminal, and relates to the technical field of machine tools, and the method comprises the steps that actual operation parameters and actual machine tool parameters of a double-machining-channel machine tool are obtained; inputting the actual machine tool parameters into a preset virtual computer numerical control module to obtain a virtual machine tool model; inputting the actual operation parameters into the virtual machine tool model to drive the virtual machine tool model to operate and obtain feedback information; and when and only when the collision point exists in the feedback information, controlling the virtual machine tool model and the double-machining-channel machine tool to stop running, and displaying the position displayed by the current actual running parameters of the virtual machine tool model. The double-machining-channel machine tool has the effect of improving the machining efficiency and safety of the double-machining-channel machine tool.

Techniques are described for verifying connectivity in a virtualized computing environment comprising networked computing devices having internal endpoints that are configured with operational connectivity to external endpoints. A connectivity test component is configured to execute as a virtual resource in the virtualized computing environment, execute protocol-aware connectivity tests that enable detection of connectivity errors between the internal endpoints and external endpoints, and instantiate or access network interfaces for establishing connectivity between the internal endpoints and external endpoints. A configuration file defines connectivity types between the internal endpoints and external endpoints. Based on the configuration file, the connectivity test component is executed in the virtualized computing environment. An output is generated by the connectivity test component that is indicative of results of connectivity attempts in accordance with the configuration file.

The invention discloses a heterogeneous AI computing power resource segmentation and scheduling method and system, and the method comprises the steps: recognizing the type of a heterogeneous AI computing power card accessed to a current server and hardware resource parameters of the heterogeneous AI computing power card, and carrying out the abstract modeling to generate a logic resource model; dividing a computing core and a video memory of a single heterogeneous AI computing power card into at least one independent virtual computing power instance through a resource virtualization technology on the basis of the constraint of a logic resource model; and in response to a computing task request, mounting the virtual computing power instance to a computing task in a containerization form, and dynamically scheduling the virtual computing power instance based on the demand of the computing task. Standardized logic resource units are generated through the minimum segmentation unit, and the utilization rate and scheduling flexibility of heterogeneous AI computing power resources are remarkably improved.

Described are techniques for data integrity monitoring of point-in-time backups. The techniques include obtaining a point-in-time backup of a virtual computing resource that executes in a computing environment which is monitored by a controller component of a disaster recovery system. The techniques further include starting a temporary virtual computing resource in a virtual private network from the point-in-time backup of the virtual computing resource. The techniques further include establishing communication between the controller component and the temporary virtual computing resource to enable the controller component to initiate an integrity check of data included in the point-in-time backup. The techniques further include, in response to an indication that the point-in-time backup passed the integrity check, preserving the point-in-time backup as a validated safe backup of the virtual computing resource.

The embodiment of the invention provides a physical machine, a resource scheduling method, equipment and a storage medium. In the embodiment of the invention, a physical computing resource object of a physical machine bears a virtual computing resource object required for running a virtualization instance, and different resource scheduling strategies are adopted to perform time-sharing scheduling on the virtual computing resource object; in the process of scheduling the virtual computing resources according to the currently used resource scheduling strategy, the running state data of the physical computing resource object and / or the currently borne virtual resource object is monitored, and the currently used resource scheduling strategy is dynamically adjusted according to the change condition of the running state data. Therefore, the resource scheduling strategy matched with the running state of the physical computing resource object and / or the virtual computing resource object is adopted, reasonable scheduling of the virtual computing resource object can be achieved, and the running performance of the virtual computing resource object and the resource utilization rate of the physical computing resource object are improved.

The invention relates to the technical field of power grid operation monitoring, and discloses a computer for monitoring operation of a power distribution network, and a method which can be executed by the computer comprises the following steps: processing a virtual computing resource topological graph and a monitoring task demand matrix through a virtual network slicing algorithm to obtain a special monitoring network set; processing the special monitoring network set and the operator scheduling strategy through a distributed collaborative learning system to obtain a resource scheduling scheme; processing the resource scheduling scheme and monitoring the task state data in real time through a self-adaptive task migration system to obtain a task migration execution scheme; processing the task migration execution scheme and the regional monitoring data through a regional adaptive resource regulation and control system to obtain a key regional resource configuration scheme; according to the method, a plurality of logically isolated and collaborative special monitoring networks are constructed on existing computing resources in a software definition mode, so that the running state of the power distribution network is comprehensively monitored.

Methods and apparatuses are described for automatically provisioning and managing secure database resources in a cloud computing environment. A server provisions virtual computing resources in the cloud computing environment using resource templates and creates a database instance in each of the virtual computing resources. The server integrates the database instances and the virtual computing resources in the cloud computing environment with an identity authentication service. The server configures the database instances in two or more of the virtual computing resources to synchronize data. The server monitors each of the plurality of virtual computing resources using a monitoring service. The server updates the database instances by detaching a physical disk drive from the database instance, deleting the virtual computing resource that contains the database instance, provisioning a new virtual computing resource, creating a new database instance in the new virtual computing resource, and re-attaching the physical disk drive.