62 results about "Resource map" patented technology

The invention relates to the technical field of distributed computing and computing power scheduling, in particular to a computing power resource fusion method based on a distributed flow pipeline, which comprises the following steps of: disassembling a user computing power request into a flow pipeline unit for packaging computing logic, an input / output interface and a resource demand label; meanwhile, computing power types, real-time load rates, memory occupancy rates, network round-trip delays, geographic positioning and energy consumption data of cloud edge end nodes are collected, a hierarchical topology network framework is constructed based on the collected data, node computing power available values are calculated, an inter-node transmission cost matrix is generated, a fault probability prediction model is constructed, and a fault probability prediction model is constructed. And finally, analyzing a data dependency relationship of the pipeline unit through a four-dimensional joint decision engine, executing dynamic mapping, and preferentially mapping the high-computing-power demand unit to a GPU cluster node, so as to realize non-interruption reconstruction during pipeline topology operation. And the global computing power resource utilization rate, the task operation efficiency and the service stability are improved.

The invention discloses an intelligent fusion processing method and system for forest and grass wet resource pattern spots and annual land change survey data, and belongs to the field of space-time big data in the natural resource industry, and the method comprises the steps: completing the pattern layer fusion based on the annual land change survey data in combination with forest and grass wet pattern spot survey results; superposing county and rural boundaries to form an administrative fusion layer; performing subcompartment division based on the remote sensing image; merging broken classes according to a principle of adjacent positions and similar types; eliminating a pattern spot sharp angle; land classes are refined, and attribute information is perfected; the public welfare forest range and the protection level are optimized; automatically checking and summarizing to form a result layer; and finally performing statistics to generate various thematic reports. According to the method, technologies such as database storage, spatial index construction and a fusion algorithm are adopted, the data processing efficiency is improved by more than 50%, and the sharp angle processing time is shortened; and the labor cost and the time investment are obviously reduced.

The invention discloses an intelligent satellite communication terminal beam scheduling method based on space-time path, which comprises the following steps: constructing a space-time extension resource map for mapping a connection state in a future time window based on a terminal track prediction sequence and a whole network gateway station resource capacity model; solving a global space-time path meeting service constraints in the graph, and generating resource reservation contract data containing a specified time slice, a target beam and a reserved share; and issuing the contract to a second-level network manager, executing a local schedule based on contract agreement by the second-level network manager, and triggering re-planning only when the deviation between the actual state and the execution of the contract exceeds a threshold value. According to the method, greedy beam selection is converted into full-time-domain path planning, and the decision result is packaged into a rigidly executed resource contract, so that the problems of decision short view and difficulty in cross-gateway coordination in the prior art are solved, and resource certainty guarantee and scheduling robustness of cross-domain switching of the mobile terminal are realized.

The invention relates to a space-based cloud-oriented intelligent service management arrangement method and apparatus, and a communication device. The method comprises the following steps: a management orchestration body obtains satellite computing service demand data and global resource state data, and obtains task service level protocol parameters and a dynamic fusion resource map based on the satellite computing service demand data and the global resource state data; based on the task service level protocol parameters and the dynamic fusion resource map, generating task scheduling and resource allocation joint strategy information through a deep reinforcement learning model in combination with a preset optimization target; performing network function instance deployment and resource configuration of the satellite computing service based on the strategy information; and obtaining a service execution analysis result of the satellite calculation service, and generating a reward function according to the analysis result in combination with the task service level protocol parameters and the dynamic fusion resource map to update the parameters of the deep reinforcement learning model. According to the invention, better service quality guarantee and higher resource utilization efficiency of the satellite computing service in the space-based network can be ensured.

The invention discloses an unmanned operation and maintenance method, device and system for a photovoltaic power station, particularly relates to the technical field of automatic control, and is used for solving the problem of cooperative failure caused by conflict between centralized optimization and a local autonomous decision-making target of equipment in an unmanned operation and maintenance system for the photovoltaic power station in the prior art. A resource request instruction sequence is acquired in real time, a global resource map is synchronously constructed, and the resource request instruction sequence is matched with the global resource map to judge whether a resource allocation circular waiting chain exists or not; if yes, quantitatively evaluating the execution path intersection density of each heterogeneous operation and maintenance task in the resource allocation cyclic waiting chain in a physical space and a logic sequence, and analyzing an interference effect based on the execution path intersection density in combination with behavior randomness characteristics represented by each heterogeneous operation and maintenance device in path selection so as to trace the source of a conflict root cause; key conflicting tasks are determined based on the conflict root cause, and their execution device assignments are dynamically reconstructed to disengage the resource allocation cyclic waiting chain.

The invention provides a task collaboration-oriented distributed equipment adaptive networking method and system, and relates to the technical field of distributed equipment communication and collaboration, and the method comprises the steps: firstly receiving and analyzing cross-domain task demand information, and generating a task execution element set and a collaboration constraint condition; starting a distributed equipment capability autonomous activation process, generating atomic capability description information, and interactively converging the atomic capability description information into a global capability resource map; then, a distributed networking architecture is constructed according to the global capability resource map and the collaborative constraint conditions; and finally, the control equipment executes cross-domain task cooperative operation, and updates the networking form according to the real-time state data. According to the invention, decentralized distributed equipment self-adaptive networking is realized, the cooperative sensing and scheduling efficiency of the system is improved, and the adaptability to complex scenes is enhanced.

The invention relates to the technical field of data collaborative analysis, in particular to a printing order commission distribution and resource allocation linkage method based on multi-channel data collaboration, and the method comprises the steps: integrating various key information of an order through constructing an order-resource map, and reflecting the correlation between the order and resources; an order-resource map is input into a map neural network model to extract a map embedding vector and construct a sub-map, so that a complex relationship between orders and resources can be mined, and accurate initialization of commission distribution and resource nodes is realized; local sub-graphs are shared through distributed communication, and a global commission distribution resource map is generated, so that centralized overall planning of all channels and all resources is realized, and commission distribution and resource allocation decisions are ensured to be based on an overall optimal principle; linkage operation is executed according to the global map to generate a matrix, and an instruction is issued, so that each channel order is ensured to obtain corresponding resources and commission according to a fair and reasonable principle; and the execution node is combined with a state execution algorithm and uploads data, so that a resource allocation path can be dynamically optimized in real time.

A method is presented which enables a controlled mechanism of applying the required set of settings, e.g., for cloud-based network infrastructure, by means of “profiles”. Infrastructure Management Service (IMS) applies one or more of Compute profile, Networking profile, Storage profile, Accelerator profile, and Application (“App”) profile to cloud infrastructure. The following set of procedures are defined to achieve the profile-based infrastructure management: a) profile definition; b) cloud-infrastructure-preparation based on profile(s); c) cloud audit and monitoring; and d) cloud preparation based on capability. Applying of a profile can involve one or more of: updating the BIOS settings, e.g., using Intelligent Platform Management Interface (IPMI) commands; updating the GRUB settings; updating the system / kernel parameters; updating interfaces (e.g., alias, bonding, etc.); creating required resources (e.g., virtual functions (VFs) and corresponding bindings); creating resource maps to be used by plug-ins; and running any scripts for custom needs of the RAN application.

The invention belongs to the technical field of hardware design, and provides a sharing operation method, system and equipment of a network acceleration unit and a medium, and the method comprises the step of configuring a shared general register, an exclusive general register and an exclusive special register group for multiple hosts in a single network acceleration unit. Each host accesses the register through the low-speed bus based on the unique identifier. And the acceleration unit performs data interaction with each host through a high-speed bus according to the configuration of the register. When the host operation is processed, the management message and the data transmission message are distinguished by judging whether the basic communication resource register group is accessed or not, and high-order modification and resource mapping are carried out on a load data address in the data transmission message. When an external data packet is received, a target host is determined through analysis and address matching, and resource identifier mapping and data access are carried out. According to the invention, each host is ensured to have independent communication resources and data channels, the complexity and the cost of hardware implementation are reduced, and the resource utilization rate and the system expansibility are improved.

The invention provides a resource scheduling method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of artificial intelligence and the like. According to the specific implementation scheme, the method comprises the steps of deconstructing received task demand data into a task general outline comprising a plurality of sub-tasks; searching and generating a target execution node cluster in a pre-constructed heterogeneous resource map based on the task general outline; during the period that the target execution node cluster executes the multiple sub-tasks, based on the task general outline, consistency verification is conducted on resource fragments generated by execution nodes in the target execution node cluster, when consistency deviation is detected, the execution nodes are controlled to start correction, and correction information of the execution nodes is recorded; after the plurality of sub-tasks are finished, calculating the influence weight of each capability service node based on the task execution result of each capability service node; and based on the influence weight and the correction information, iteratively updating node attributes of the capability service nodes in the heterogeneous resource map and parameters of historical interaction edges.

The application relates to the technical field of building engineering and provides a building construction progress digital monitoring method and system. The method comprises the following steps: collecting three-dimensional point data of a construction area, comparing the three-dimensional point data with a BIM model to extract a progress deviation, associating a construction log with a BIM component node to set a first evaluation index, associating a material record with the BIM component node to set a second evaluation index, combining the deviation and the two indexes to formulate a resource atlas of a construction process logic, accumulating influences based on the atlas according to a weight attenuation coefficient, taking efficiency as a characteristic to perform multi-scale evaluation, and combining dynamic threshold adjustment to perform resource compensation reminding. The application solves the technical problem that in traditional building construction progress monitoring, data updating is lagged, and a construction process logic is disengaged, so that a progress deviation is difficult to accurately identify, achieves the technical effect that through multi-source data fusion and intelligent comparison of a BIM model, real-time and accurate analysis of construction progress is realized, dynamic optimization of resource allocation is realized in combination with multi-dimensional evaluation indexes, and the technical effect of improving construction management efficiency is achieved.

The invention discloses a method and system for verifying an RISC-V processor and a computer readable storage medium. The method comprises the following steps: analyzing an RISC-V official manual and a micro-architecture user manual, and generating a static instruction-resource mapping table; and generating a first test instruction sequence for each instruction in the static instruction-resource mapping table, executing the first test instruction sequence by using an RISC-V processor simulation model constructed by a software simulator, and dynamically calibrating the static instruction-resource mapping table in the execution process. And traversing the instruction and resource mapping relationship in the calibrated static instruction-resource mapping table, analyzing RISC-V processor verification logic, and if a conflict is found, outputting a conflict report so as to complete defect repair before RTL code writing. According to the application, hardware behaviors can be accurately associated, the problem of disjunction of semantics and micro-architecture is solved, and conflict prediction in an architecture design stage and end-to-end automatic verification from instruction semantics to micro-architecture behaviors are realized.

The invention provides a network flow multi-level security protection model, system, method, equipment and medium. According to the method, a plurality of modularized atomization protection points are constructed through a predefined eBPF program library, and network control capabilities such as matching, speed limiting and state observation are realized. In a system initialization stage, a data plane architecture comprising a plurality of kernel execution layer dispatcher programs is constructed, and persistence of the programs and resource Map is realized through pin operation. The declarative network security policy is received through the SDK module, the policy control module analyzes the declarative network security policy to generate a configuration parameter, and the user mode module loads an eBPF program according to the configuration parameter and mounts the eBPF program to a kernel execution layer. The network flow triggers a protection point according to a path and outputs observation data; and the state aggregation sub-module aggregates the data according to the strategy and feeds information back to the upper-layer application. Therefore, flexible deployment of protection points and strategy dynamic driving can be realized, and the method has good expandability and response capability.

This invention discloses a method for constructing a database for the survey of traditional Chinese medicine (TCM) cultural resources based on knowledge graphs, belonging to the field of database construction technology. Specifically, it includes: collecting classical texts and field survey texts; extracting core entity terms using sequence labeling technology; establishing an ontology model including lineage and medicinal material origin dimensions to form a knowledge architecture for the TCM field; extracting entities and events from the text using neural networks, aligning entities to ontology nodes according to the domain knowledge architecture, and generating a basic TCM resource graph; calculating feature vectors of graph nodes, using inference algorithms to mine implicit connections between origin changes and treatment customs, and completing missing semantic edges in the graph; performing multiple path searches for resource nodes, aggregating their associated nodes in the lineage and regional dimensions, and generating a subgraph containing spatiotemporal evolution trajectories; and converting the generated subgraph into topological data to complete the construction of a network survey database.

The invention provides a signal transmission method and a communication device. The method comprises: a first device receiving first indication information, the first indication information being used for determining a resource pattern of a reference signal, the resource pattern of the reference signal comprising at least one first basic pattern, the first indication information indicating a relationship between the first basic pattern and a reference resource pattern, if so, whether the first basic pattern is updated relative to the reference resource pattern is indicated; and receiving or sending the reference signal based on the first indication information. Based on this, the first device can determine each basic pattern based on the relationship between the first basic pattern and the reference resource pattern and the reference resource pattern, and further can determine the resource pattern of the reference signal based on each basic pattern. Compared with a scheme of directly indicating the resource pattern of the reference signal, the scheme can reduce the signaling overhead brought by indicating the resource pattern of the reference signal.

The application provides a home industry zone independent station building service method and system, belonging to the technical field of data processing. First, a building request containing a target area identifier and a business feature identifier is obtained. Then, based on a predefined industry resource map, a continuous geographic space associated with the target area identifier is determined. Then, according to the real-time data corresponding to the continuous geographic space, a plurality of service blocks are generated, each block is associated with a geographic sub-area, and its corresponding feature vector is determined. Then, the matching degree of the business feature identifier and each feature vector is calculated, and the proximity is calculated in combination with the real-time load state of each service block and the target area identifier. Finally, based on the matching degree and the proximity, a main service block is determined from all service blocks, and based on the feature vector of the main service block, a final independent station corresponding to the building request is determined and generated. The application realizes the matching of building service and industry zone resources in business relevance and geographic service accessibility.

The embodiment of the invention provides a computing power network control method and system based on network resource slicing. The method comprises the following steps: constructing a global resource map based on heterogeneous resource information and network connectivity; determining a plurality of logic slices and a resource table corresponding to each logic slice based on the global resource map and a slice configuration strategy; obtaining task information of a to-be-processed task, and matching a target slice for the to-be-processed task based on the task information and a task allocation rule; in response to the condition that the target slice is not matched, updating the plurality of logic slices based on a resource compression strategy, and re-matching the target slice based on the updated plurality of logic slices; and in response to the matched target slice, processing the to-be-processed task based on the target slice, and updating the resource table corresponding to the global resource map based on the target slice.

The invention discloses a cloud cost optimization suggestion generation method and device based on a resource map. The method comprises the following steps: collecting cost data, a resource relation graph and resource performance monitoring data; according to the cost data, a preset rule and the resource performance monitoring data, identifying a target resource to be optimized, executing an optimization operation on the target resource, and calculating a cost saving expectation; topological positioning is carried out in the resource relation graph, and business service nodes depending on the to-be-optimized target resources are determined; evaluating the performance influence of the optimization operation on the business service node, and calculating the performance risk degree; and according to the cost saving expectation and the performance risk degree, generating an optimization suggestion with a risk assessment level. The technical effects of dynamically simulating the influence on the performance of the business when the optimization suggestion is generated and outputting an executable scheme with risk assessment are realized.

A computer-implemented method including associating, at a resource having a plurality of task elements, a task element manifest with each task element from the plurality of task elements, thereby creating a resource map, receiving a request to complete a task; providing the request to complete the task and at least a portion of the resource map to a Large Language Model (LLM); and obtaining, from the LLM, a dynamic user interface to complete the task.

This invention discloses an intelligent agent parallel task allocation method based on SpringAI heterogeneous computing, comprising: S1, dynamically sensing and registering the network through a resource sensor, constructing and maintaining a global dynamic heterogeneous resource graph; S2, an intelligent task dispatcher intercepting requests, extracting and generating task feature vectors through a task parser; S3, a policy matching engine comprehensively evaluating the task feature vectors and resource graph status by calling a configurable policy rule base, and outputting the optimal target computing resource identifier; S4, routing requests to the corresponding endpoints for execution based on the identifiers, and performing sharding and parallel processing on parallelizable tasks; S5, aggregating the results of each unit and returning them to the client, while monitoring execution performance and adaptively optimizing the scheduling strategy through a feedback learning module, thereby achieving transparent, efficient, and adaptive scheduling of heterogeneous computing resources, improving system throughput, and reducing task latency and computational costs.

Aspects of the present disclosure relate generally to systems, devices, methods, and computer-program products for use in the implementation and / or operation of quantum information processing (QIP) systems, and more particularly, for configuration of a resource graph for a quantum computer having reconfigurable qubit registers.

The application provides a task-oriented cooperative distributed device adaptive networking method and system, relates to the technical field of distributed device communication and cooperation, and first receives and analyzes cross-domain task demand information, generates a task execution element set and a cooperative constraint condition; then starts a distributed device capability autonomous activation process, generates atomic capability description information and interacts to converge into a full-capability resource graph; then constructs a distributed networking architecture according to the full-capability resource graph and the cooperative constraint condition; finally controls the device to perform cross-domain task cooperative operation, and updates the networking form according to real-time state data. The application realizes decentralized distributed device adaptive networking, improves the cooperative perception and scheduling efficiency of the system, and enhances the adaptability to complex scenes.

The invention provides a renewable resource sorting control method and system based on artificial intelligence, and the method comprises the steps: carrying out the feature extraction of a collected renewable resource image, and obtaining an image feature vector; classifying and identifying the renewable resources according to the image feature vectors to obtain category identifiers of the renewable resources; performing target detection on the renewable resources according to the image feature vectors to obtain bounding box coordinates and grabbing point coordinates of the renewable resources; and generating a sorting action instruction of the manipulator according to the category identifier, the bounding box coordinates and the grabbing point coordinates, and performing resource sorting control on the manipulator according to the sorting action instruction. Automatic identification and accurate sorting of renewable resources are achieved through the artificial intelligence technology, the sorting efficiency and accuracy are improved, the labor cost is reduced, and the system is suitable for automatic sorting treatment of various renewable resources.

The invention relates to a cache management method and device based on tense perception and electronic equipment. The method comprises the following steps: acquiring log access data of a target cache item, and performing feature processing on the log access data to generate a time sequence feature and a user resource map feature; inputting the time sequence characteristics into a time sequence prediction model, outputting a first access probability, inputting the user resource map characteristics into an association prediction model, and outputting a second access probability; fusing the first access probability and the second access probability to obtain a comprehensive access probability of the target cache item; and inputting the comprehensive access probability and the state information of the cache system into a reinforcement learning model to enable the reinforcement learning model to output a target survival time value of the target cache item, and inputting the target survival time value into the cache system to dynamically set the survival time of the target cache item. The technical problems that cache management depends on manual rules, the maintenance cost is high, and self-adaption to dynamic changes of services and user behaviors is difficult are solved.

The invention provides a node role allocation method and device in distributed training and electronic equipment, relates to the technical field of artificial intelligence, and is used for realizing collaborative optimization of a cluster resource utilization rate and distributed training efficiency and remarkably improving system robustness, fault tolerance and automation degree. The method comprises the following steps: constructing a computing power network resource map based on computing power resource information of computing power equipment in a cluster; wherein nodes of the computing power network resource map represent computing power equipment, and attributes of the nodes comprise resource states; generating a node role allocation scheme for the to-be-executed distributed training task based on the computing power network resource map; distributing a service node role or a working node role for each computing power device in the cluster based on the node role distribution scheme, and starting a distributed training task; monitoring training performance data in a distributed training process; and optimizing the node role allocation scheme based on the training performance data, and performing node role reallocation based on the optimized node role allocation scheme.

The invention relates to a data linkage display method and device, computer equipment and a readable storage medium. The method comprises the steps of displaying a first computing power resource interface corresponding to a first geographic area; the first computing power resource interface at least comprises a first computing power resource map; the first computing power resource map at least comprises a plurality of second geographic areas and first computing power resource information; detecting a first trigger operation on the first computing power resource interface; displaying a second computing power resource interface corresponding to the target second geographic area when it is detected that the first trigger operation is the first-level switching operation; wherein the target second geographic area is any one of the plurality of second geographic areas; the second computing power resource interface at least comprises a second computing power resource map; the second computing power resource map comprises a plurality of third geographic areas and second computing power resource information. By adopting the method, the computing power resource layout can be intuitively and clearly displayed.

The application discloses a kind of based on intelligence calculation interconnection architecture computing power service decomposition method and system, the method is by receiving and analyzing service work order, matching predefined service rule to determine decomposition strategy;At the same time, real-time acquisition includes the bottom resource state of high-speed interconnection performance data, constructs global real-time resource topological atlas;Further, based on service rule and resource atlas, service target is dynamically decomposed into a series of atomic flow links and generates quantified resource demand portrait;Subsequently, using the joint optimization algorithm with the goal of minimizing total completion time, adaptively allocate computing nodes for each link, generate dynamic service execution flow chart;Finally, drive flow chart execution and monitor in whole cycle, dynamically trigger rescheduling according to performance deviation or resource change.Dynamic service execution flow chart is generated, and the joint optimization algorithm with the goal of minimizing total completion time is used to adaptively allocate computing nodes for each link, so that the real-time optimal matching between service demand and heterogeneous computing power resources is realized, and the computing efficiency and system resilience are improved.

The invention provides a multi-mode scene interaction control method and device based on a pre-generated resource atlas, and belongs to the technical field of computer interaction.According to the multi-mode scene interaction control method based on the pre-generated resource atlas, the pre-constructed scene interaction atlas can be loaded through the mode of the pre-generated resource atlas, and the scene interaction effect is improved. High delay of training is reduced, intention recognition is carried out only by spending millisecond-level time, video playing is also real-time and highly immersive, meanwhile, the trend of training nodes is strictly limited by directed edges of a graph, the risk of wrong guidance caused by illusion generated by an artificial intelligence model is reduced, and the training efficiency is improved. Therefore, high simulation immersion can be maintained and teaching / training logic can be strictly followed.

This invention provides a multimodal scenario interaction control method and device based on a pre-generated resource graph, belonging to the field of computer interaction technology. The multimodal scenario interaction control method based on a pre-generated resource graph can load a pre-constructed scenario interaction graph through the pattern of the pre-generated resource graph, reducing the high latency of training. It only takes milliseconds for intent recognition, and the video playback is also instant and highly immersive. At the same time, since the direction of training nodes is strictly limited by the directed edges of the graph, the risk of the artificial intelligence model generating illusions and leading to incorrect guidance is reduced, thereby maintaining a high degree of realism and immersion and strictly following the teaching / training logic.

The invention relates to the technical field of budget calculation management systems, in particular to a calculation management system based on a modular architecture, which comprises an intelligent semantic analysis module used for receiving policy text data, extracting a quota entity, a basic quota value and a logic constraint relationship through a natural language processing model, and analyzing the quota entity, the basic quota value and the logic constraint relationship; outputting a dynamic attribute configuration instruction and a layer reference formula; the modular layer management module is used for receiving the dynamic attribute configuration instruction and a layer reference formula, constructing a multi-level structure comprising a parameter layer, a resource layer and a reference layer, setting a constraint attribute mark for a calculation parameter in the parameter layer, and storing the constraint attribute mark in the reference layer; the constraint attribute marks are used for distinguishing the rigid constraint state and the elastic variable state of the calculation parameters. According to the method, the structured quota and constraint data capable of directly driving the measurement and calculation model are generated by automatically analyzing the policy text, so that the manual input workload is remarkably reduced, and the policy change landing efficiency and accuracy in the system are improved.