129results about How to "Implement scheduling" patented technology

The invention belongs to the technical field of computing power scheduling, and particularly relates to a computing power scheduling method in a distributed computing environment. According to the task scheduling method and system, the task needing to be processed at present is obtained through the task management system, the task is divided into the real-time task set, the priority task set and the common task set, and the related tasks are scheduled by adopting the corresponding scheduling strategy based on the set corresponding to the current task and the priority in the set. Resource scheduling and allocation in a distributed computing environment are realized; according to the method, through the steps of task classification, real-time resource monitoring, resource demand estimation, priority ranking, reasonable scheduling strategy, load calculation, resource migration and the like, the technical problem of computing resource scheduling and allocation in a distributed environment is effectively solved, timely processing of high priority is ensured, the system load is balanced, and the system performance is improved. And efficient utilization of resources and stable operation of the system are realized, so that the performance and reliability of the whole distributed computing environment are improved.

One or more embodiments of the invention provide a load-aware scheduling method of an inference system and the inference system. The method is applied to a global scheduler in the inference system. The inference system further comprises an inference engine. The inference engine comprises at least one computing instance deployed on each computing node in a computing cluster; computing resources of the computing examples comprise GPUs carried on the computing nodes where the computing examples are located; the global scheduler maintains dynamically updated GPU load information of each calculation instance; the method comprises the steps of obtaining a to-be-executed target reasoning request; based on the maintained GPU load information of each calculation instance, determining a target calculation instance of which the GPU load meets a preset condition; and sending the target reasoning request to the target calculation instance, so that the target calculation instance executes the target reasoning request.

One or more embodiments of the invention provide a load-aware scheduling method of an inference system and the inference system. The method is applied to the inference system comprising a global scheduler and an inference engine. The inference engine comprises a Prefill engine and a Decode engine; the Prefill engine and the Decode engine respectively comprise at least one calculation instance; computing resources of the computing instances comprise GPUs carried on the computing nodes where the computing instances are located; the method comprises the following steps: a global scheduler obtains a target reasoning request to be executed, determines a first calculation instance in a Prefill engine of which the GPU load meets a first preset condition based on maintained GPU load information, and sends the target reasoning request to the first calculation instance to execute reasoning calculation in a Prefill stage; and a first local scheduler corresponding to the first calculation instance in the Prefill engine determines a second calculation instance in the Decode engine with the GPU load meeting a second preset condition based on the maintained GPU load information, and sends an inference calculation result of the Prefill stage to the second calculation instance to execute inference calculation of the Decode stage.

The invention discloses an intelligent nursing data task scheduling management system based on cloud computing, and relates to the technical field of nursing scheduling management. The cloud computing platform is in communication connection with a data acquisition module, a data storage module, a data processing and analysis module, a nursing evaluation module, a task scheduling module, a report generation module and a user interaction module, and all the modules are in electric signal connection. According to the intelligent nursing data task scheduling management system based on cloud computing, through calculation of the task scheduling evaluation model and the emergency degree evaluation value, the emergency degree and priority of the nursing tasks are evaluated, priority ranking is carried out on the nursing tasks, intelligent scheduling of the nursing tasks is achieved, it is ensured that the emergency and important tasks are processed preferentially, and the task scheduling efficiency is improved. The nursing efficiency and quality are improved, meanwhile, reasonable allocation can be carried out according to the priority of the tasks and available nursing resources, and resource utilization is further optimized.

The invention discloses a ship distributed hybrid energy system and an evaluation method thereof, the system comprises a solar photovoltaic module, a wind driven generator module, a diesel generator module, an energy storage system, a converter module, a combined heat and power generation module and a thermal load controller, and the method comprises the steps of obtaining ship data information; performing analysis according to the ship data information; according to the power load analysis, heat energy converted by the residual electric quantity in the energy storage system through the combined heat and power generation module is obtained; obtaining an optimal combination according to an analysis result of the thermal load analysis; performing power demand-based dynamic pricing analysis, environmental influence evaluation analysis and social factor evaluation analysis on the optimal combination; according to the evaluation analysis result, determining that the corresponding optimal combination is a solution for comprehensive and sustainable use of the ship energy; the problems that in the prior art, many defects exist in the aspects of an energy structure, intelligent management and system integration, and efficient utilization, intelligent management and sustainable development of an energy system cannot be achieved are solved.

The invention relates to the technical field of load regulation, in particular to a transformer load regulation method and device, equipment and a storage medium. The method comprises the following steps: identifying downstream electric equipment of a current transformer, and marking the downstream electric equipment as an electric equipment node; carrying out real-time load monitoring on the electric equipment nodes, and carrying out multi-period load characteristic analysis to obtain a multi-period load curve of each electric equipment node; carrying out multi-time-point discretization processing on the multi-period load curve of each power utilization node, and carrying out node-by-node load change trend analysis to generate load fluctuation trend data of each node; performing current flow direction logic analysis on the nodes of the electric equipment so as to generate node flow direction logic data; and performing topology connection reconstruction based on the node flow logic data, and constructing a node topology distribution network. According to the invention, efficient and balanced transformer load control is realized.

The invention relates to a bandwidth scheduling method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: determining the excess bandwidth amount of a node to be scheduled according to the cost bandwidth amount and the current bandwidth amount of the node to be scheduled; determining a plurality of associated nodes of the node to be scheduled, and determining respective residual bandwidth amounts of the plurality of associated nodes according to respective cost bandwidth amounts and respective current bandwidth amounts of the plurality of associated nodes; determining affiliation information of the to-be-scheduled node and respective affiliation information of the plurality of associated nodes, and constructing a node relation graph based on each piece of affiliation information; and generating a bandwidth scheduling path for the excess bandwidth amount based on the node relation graph and the residual bandwidth amount of each associated node. By adopting the method, the scheduling of bandwidth resources can be realized.

The invention relates to a virtual power plant system scheduling method and device and computer equipment. The method comprises the steps of obtaining a day-ahead energy price, a day-ahead energy load and a day-ahead power prediction value of renewable energy power generation power in a preset time period, and determining a day-ahead scheduling strategy of a virtual power plant system according to the day-ahead energy price, the day-ahead energy load and the day-ahead power prediction value, and based on the day-ahead planned output curve, predicting to obtain a time-ahead energy price and a time-ahead power prediction value of the renewable energy power generation power, adjusting a day-ahead scheduling strategy according to the time-ahead energy price and the time-ahead power prediction value to obtain a target scheduling strategy, executing the target scheduling strategy, and scheduling the virtual power plant system. By adopting the scheme, the accuracy of the target scheduling strategy can be improved.

The invention discloses a paper machine wastewater treatment monitoring system, and particularly relates to a wastewater treatment monitoring technology, the system comprises a pretreatment module, a process section wastewater monitoring module, a wastewater abnormity tracing module, a process section wastewater diversion module, a process section wastewater confluence module, a wastewater treatment pool scheduling module, a wastewater treatment evaluation module and a database. According to the pollution index of the wastewater of each process section monitored each time in history, the pollution index of the wastewater of each process section monitored currently is predicted, and the initial flow guide direction of the wastewater of each process section is set. According to the predicted water inlet amount, the discharge amount and the residual capacity of the wastewater pool of each treatment grade, intelligent automatic scheduling between the wastewater pool of each treatment grade and the buffer is realized, scientific treatment of wastewater to flow into the wastewater pool of each treatment grade is effectively realized, efficient treatment of papermaking machine wastewater is realized, and the production efficiency is improved.

The invention discloses a robot scheduling method and device, equipment, a medium and a product, and relates to the technical field of robot control, and the method comprises the steps: responding to a scheduling request sent by a controller, and querying the current states of all robots in a target scene; the scheduling request comprises a target task and a target scene; the current state of the robot comprises a first state or a second state; if the current state of the robot is a first state, determining that the robot is a target robot, and sending a target task to the target robot; and obtaining an execution result of executing the target task by the target robot, and updating the current state of the target robot according to the execution result to respond to next scheduling. The scheduling efficiency of the robot can be effectively improved.

The invention discloses a cloud side end scheduling collaboration method and system for a cloud game. The method comprises the steps of cloud game service application, service receiving and task analysis, computing network service arrangement (computing network resource perception and network quality perception data intelligence injection), computing power resource calculation and network path calculation (cloud edge collaborative network path and game user access network channel path), computing network resource planning (computing resource allocation service calling), and computing network resource planning (cloud edge collaborative network path and game user access network channel path calling). And network computing service scheduling and network computing service plug-in execution configuration issuing are carried out to complete network computing resources, and finally, the cloud game service carries out business deployment online application. According to the method and the system, intelligent arrangement and scheduling are realized, a'computing network unified brain 'is constructed, and global intelligent arrangement, scheduling and optimization of cloud, edge, end and network resources are realized.

The embodiment of the utility model discloses a battery charging and discharging test system, which comprises at least one control unit, a plurality of switch elements, a plurality of charging and discharging machines and a battery pack, and is characterized in that the control unit is used for controlling the on-off state of at least one switch element electrically connected with each charging and discharging machine; the state of the charging and discharging motor is a working state or a standby state; the charging and discharging machine in the standby state is controlled to carry out charging and discharging testing on the target battery pack electrically connected with the charging and discharging machine, and the target battery pack is one or more of the multiple battery packs; the charging and discharging machine is used for carrying out charging and discharging tests on the connected single or multiple battery packs under the condition that the charging and discharging machine is in a working state; wherein the configured actual operation power of the battery charging and discharging test system is smaller than the sum of the maximum rated power of each charging and discharging motor.

The invention relates to the technical field of rural energy scheduling, in particular to an intelligent monitoring and scheduling method for rural energy. The method comprises the following steps: performing rural energy real-time monitoring processing through a rural energy digital twinborn platform, and constructing a rural energy distribution network according to real-time rural energy data; performing rural energy consumption anomaly analysis according to the historical rural energy consumption data, and performing energy distribution network optimization reconstruction processing on the rural energy distribution network based on the rural energy consumption anomaly data; performing rural energy correction processing on the rural energy storage abnormal transmission data based on the reconstructed rural energy distribution network, designing a rural energy scheduling strategy based on the rural energy supply demand data and the corrected rural energy data, executing rural energy scheduling operation, and performing rural energy scheduling data monitoring processing in real time; and performing dynamic optimization operation on the rural energy scheduling strategy based on the real-time rural energy scheduling data. According to the invention, intelligent monitoring and scheduling of rural energy are realized.

The invention relates to the technical field of automatic production, and discloses an HTRB aging test scheduling method and device, electronic equipment and a storage medium. In the method, an upper computer inquires a test station corresponding to a product; the upper computer sends storage location information of the test station to the PLC, so that the PLC controls the mechanical device to place products; the upper computer receives the information that the product is placed in the storage location; the upper computer sends a product code of the product in the storage location to the aging cabinet for the aging cabinet to age the test product; the upper computer sends the information that the aging test of the product in the aging cabinet is completed to the PLC, so that the PLC controls the mechanical device to take out the product; and the upper computer judges whether the product is qualified or not according to the test result of the product and is used for controlling the mechanical device to transport the product to an outbound area by the PLC. According to the technical scheme, the method is used for efficient scheduling of the HTRB aging test, manual work order switching is changed into equipment program switching, the time for replacing work orders for production of products is greatly shortened, and the production efficiency is improved.

The invention discloses a satellite communication system network control service access architecture system and method based on a software bus, and the architecture comprises a management application layer, a core service layer, an access adaptation layer, and a data service layer. The management application layer comprises management and control service software, network management and control business service software, data operation service software and synchronization service software; the core service layer controls information protocol format conversion software and manages information communication protocol conversion software, and provides an interactive interface of the data service layer and the core service layer; the access adaptation layer provides registration management and information input interfaces for software of the data service layer, and provides registration management and information output interfaces for application services for software of the management application layer; and the data service layer configures user operation and parameters and provides a human-computer interaction interface. According to the invention, unified planning and scheduling of network resources and management and access control of users are realized, visual presentation is provided for managers, and network control service experience is improved.

The invention discloses a power transmission quantity data analysis method and system based on a virtual power plant, electronic equipment and a storage medium, and belongs to the technical field of data analysis. Through an AI knowledge mining branch in a joint data analysis algorithm, initial distributed sensing measurement information is deeply mined, and a power transmission state change knowledge vector containing rich power grid power transmission state information is obtained. Therefore, the monitoring precision of the power transmission state of the power grid is improved, and comprehensive and real-time data support is provided for the scheduling decision of a power grid company. Meanwhile, by combining a distributed lightweight algorithm and an edge decision tree branch in the virtual power plant resource coordination system, accurate optimization and scheduling of the power transmission state of the power grid are realized.

The invention discloses a resource scheduling method and device of a kubernetes cluster, a storage medium and electronic equipment. The method comprises the steps that in response to a resource scheduling request, a first persistent volume declaration and a second persistent volume declaration of a predefined type are created, the first persistent volume declaration and the second persistent volume declaration are associated with a storage pool, the first persistent volume declaration is a native persistent volume declaration of a kubernetes cluster, and the second persistent volume declaration is a non-native persistent volume declaration of the kubernetes cluster. Capacity configuration information is set in the first persistent volume declaration and the second persistent volume declaration respectively, and the second persistent volume declaration supports increase and decrease of the capacity configuration information; associating a pre-created pod node with the first persistent volume declaration; and creating a storage volume based on the first persistent volume declaration, and mounting the storage volume to the pod node. A new Kubertes custom resource type is introduced, a second persistent volume declaration of a predefined type is created, the second persistent volume declaration supports increase adjustment and decrease adjustment of capacity configuration information, and capacity expansion and capacity reduction of the created storage volume are further supported.

The invention is suitable for the technical field of nuclear power stations, and provides a nuclear power station spare part order scheduling method and electronic equipment. Arranging and combining all the purchasing links to obtain at least one link arrangement result; performing permutation and combination on the target business personnel according to all the purchasing links to obtain at least one personnel permutation result; combining each link arrangement result and each personnel arrangement result to obtain at least one scheduling result; for each scheduling result, determining the total duration required by the target business personnel corresponding to the personnel arrangement result in the scheduling result to process the target purchase link; and screening out the minimum total duration from the total durations, and allocating processing items of the purchasing link of the nuclear power station spare part order to corresponding target business personnel for processing according to a scheduling result corresponding to the minimum total duration. In this way, the purchasing efficiency of the nuclear power station spare parts can be improved.

The invention discloses a pole-mounted terminal storage battery intelligent detection system and method, and relates to the field of power distribution automation, and the pole-mounted terminal storage battery intelligent detection system comprises a plug-and-play connection module, a data acquisition and processing unit, a wireless communication module, a cloud service platform, and an energy management module. Data acquisition and analysis processing are performed on the storage battery through the data acquisition and processing unit, the data are sent to the cloud service platform through the wireless communication module, a remote control instruction from the cloud service platform is received through the wireless communication module, and automatic management of energy is realized through the energy management module. All-weather intelligent detection of the pole-mounted terminal storage battery is achieved, it is guaranteed that the pole-mounted terminal storage battery is in the optimal working state, the workload of operation and maintenance personnel is reduced, and the pole-mounted terminal storage battery detection system has the advantages of being intelligent, efficient, high in adaptability and high in reliability.

The application discloses a kind of cluster resource scheduling methods based on kubernetes, including the following steps: creating resource pool, setting the label and the stain of resource pool, part of cluster nodes in cluster is pulled into resource pool;Create tenant, allocate part of cluster resource to tenant, become tenant resource;Project is created under tenant, and part of tenant resource is allocated to project, become project resource;K8s resource Namespace is created under project, and part of project resource is allocated to Namespace;Workload is created under Namespace;Dynamic admission control in k8s is used, the creation or update of Pod is monitored, and the label selection and stain tolerance of Pod are set according to the Namespace to which Pod belongs;Pod is scheduled to the cluster node with corresponding label and stain set according to label selection and stain tolerance.The application also discloses a kind of cluster resource scheduling system based on kubernetes.The application realizes the overall scheduling and management of cluster resource, and can effectively improve the utilization of cluster resource.

The present application relates to the technical field of magnetic element modeling and control, and particularly relates to a multi-factor magnetic core loss prediction method based on machine learning. The method first acquires the magnetic flux density data of the magnetic element, extracts its distribution characteristics and shape characteristics, and realizes excitation waveform recognition by constructing a classification model; secondly, a temperature index correction term is introduced based on the Steinmetz equation to establish a temperature-sensitive loss model; further, the entropy weight method and statistical analysis are used to evaluate the importance of multiple factors; an integrated learning model of random forest and LightGBM is used to construct a magnetic core loss prediction model; and a single-objective optimization model is established by combining differential evolution and simulated annealing algorithm with the objectives of minimum loss and maximum magnetic energy transmission. The method improves the generalization ability and prediction accuracy of the model, can adapt to the modeling needs of magnetic core loss under multiple material, multiple waveform and multiple working condition conditions, and is suitable for application scenarios such as high-frequency magnetic element design and power electronic system optimization.

The invention provides a road emergency vehicle scheduling method and device, and relates to the technical field of emergency scheduling, and the method comprises the steps: collecting road data, and generating a road network which comprises a plurality of nodes; screening the nodes to delete end nodes in the nodes, and determining the remaining nodes as target nodes; emergency rescue related information is acquired, and the total time cost of each emergency vehicle under various decision variables is calculated; adjusting the decision variable according to a constraint condition to reduce the time cost, and obtaining a target value of the decision variable; and performing task arrangement and scheduling on each emergency vehicle according to the target value of the decision variable. The total time cost of each emergency vehicle in the road network is calculated, and the decision variable is adjusted according to the constraint condition to reduce the time cost, so that task arrangement and scheduling of the emergency vehicles are realized, and the material transportation efficiency of the emergency rescue system is improved.

The invention relates to a universal peripheral equipment function behavior level modeling and simulation method, and belongs to the field of equipment modeling and simulation. According to the method, firstly, a device description file *. Vdl is defined according to the characteristics of the peripheral device, and general information of the peripheral device is described; secondly, behavior-level modeling is carried out on the peripheral equipment, and contents such as a register and an IO interface are included; then, perfecting the functions of the equipment model, completing function simulation such as register reading and writing, data receiving and transmitting, equipment initialization and the like, and translating an equipment model description file into an equipment C code; and finally, checking the consistency of the device function model, and compiling the C code into a device dynamic library which can be called after the checking is passed. According to the universal peripheral device behavior level function simulation method achieved through the method, the modeling process is standard, model attributes and interface description is clear, logic function description is accurate, the universal and efficient peripheral device modeling and simulation method is formed, and the simulation efficiency of the peripheral device is improved.

The present application discloses a data processing method, device, equipment and storage medium. The method includes obtaining a task flow to be executed, the task flow includes task characteristics; according to the task characteristics, determining the scheduling information of at least two operator nodes that execute the logical operation instruction of the task flow and the logical operation instruction, the at least two operator nodes include a first operator node and a second operator node, and the operator types of the at least two operator nodes are different; according to the scheduling information, the first operator node and the second operator node are called by a preset mixed operator node to execute the logical instruction, and the target task result of the task flow is obtained. According to the data processing method provided in the embodiment of the present application, geographic information services can be effectively provided to users in complex service scenarios by hybrid arrangement of nodes from different sources and different operator types.

The invention discloses a multi-terminal fusion system and method for a three-dimensional data space, and the system comprises an application layer which provides the front-end effect display of the system for a user through detecting a video image rendered by a server; the interface layer is used for providing various service modules for supporting business functions and data processing; the service layer is responsible for data storage, management, query and analysis, at least comprises space rendering service, scheduling service, user authentication, session service, instruction control, security service and data storage, and is used for providing data support for the system; various types of data generated by the system are used for supporting operation of the system, and the data storage layer at least comprises a service database, a conference database, an instruction information base and a message event. The application breaks through the limitation of single-channel data transmission and planar presentation, and realizes integration and synchronous display of multimedia data such as voice, video, image and the like in the same space.

The invention relates to the technical field of automatic production, and discloses a hybrid line scheduling method and device, electronic equipment and a storage medium. In the method, a product and / or a carrier are / is controlled to flow through an in-out station node, and a process corresponding to the product is inquired; if the equipment corresponding to the access node is single-station equipment and belongs to the next process, controlling the product to enter the station for production; if the equipment corresponding to the in-out station node is the equipment contained in the parallel work station, firstly detecting whether the equipment accords with the process sequence of the current product, and if so, continuing to detect the available state of the equipment; and if the equipment is idle, the product is controlled to enter the station for production, if the equipment is busy, the available state of other equipment contained in the parallel work station is detected, and if the idle equipment exists, the in-and-out node releases the product flow to the next node. According to the technical scheme, scheduling of the hybrid line body is efficient, flexible, accurate and orderly, hybrid automatic production of various types and various process products can be met, and the optimal utilization rate of equipment can be guaranteed.

The invention relates to the technical field of satellite communication, and particularly discloses a beam scheduling method for a multi-satellite communication system, which comprises the following steps of: constructing a system architecture comprising S low-earth orbit satellites and M ground cells, and aiming at maximizing the average system capacity of the ratio of the total data flow to the number of satellites required for scheduling; establishing a complex non-convex optimization problem limited by the passing time of the satellite, the number of beam pairs and business matrix decomposition; an optimization problem is modeled as a Markov decision process, a proximity policy optimization algorithm is adopted as a core solver, and policy learning is performed through an actor-evaluator network structure; meanwhile, a matrix decomposition technology is used as an embedded module, and a high-dimensional service matrix is decomposed into a low-dimensional configuration matrix, so that the dimensionality of an action space and the calculation complexity of an algorithm are remarkably reduced. According to the method, intelligent selection and scheduling of the ground cell in a dynamic network environment are realized, and finally, the average system capacity is remarkably improved while the data transmission continuity is ensured.

The embodiment of the invention provides a sample analyzer and a sample analysis system, and a sample scheduling device of the sample analyzer comprises a storage channel used for a user to put in and take out a sample rack used for bearing samples; the sample suction channel is used for the analysis device to suck the sample carried by the sample rack in the sample suction channel; the dispatching assembly is at least used for dispatching the sample frames between the storage channel and the sample suction channel, the dispatching assembly comprises a first guide rail and a dispatching part used for bearing the sample frames, and the dispatching part is connected with the first guide rail and can move in the extending direction of the first guide rail relative to the first guide rail; the dispatching component dispatches the sample rack between the storage channel and the sample suction channel; wherein, when the scheduling part moves to the second free end of the first guide rail, the first orthographic projection of the scheduling part on the horizontal reference plane along the axis of the first guide rail can be at least partially located outside the second orthographic projection of the first guide rail on the horizontal reference plane.

The embodiments of the present application provide an I / O offloading method, device, system and storage medium in a cloud environment. In the embodiments of the present application, a queue component is added to the CPU of the host, and it is innovatively proposed to use the queue component in the I / O processing process. Based on this, a virtual I / O device and a device queue corresponding to the virtual I / O device can be provided for the instances on the host through the queue component; within the CPU, the device queue is used to schedule the I / O requests that occur between the instance and the virtual I / O device; and the original I / O offloading card only needs to be responsible for listening to the I / O requests in the device queue and transferring the data related to the I / O requests. In this way, the device queue in the I / O processing process can be moved up to the CPU, so that in the I / O scheduling process, it can联动 with each component in the CPU, obtain the real-time loads of each core in the CPU, and thus more reasonably implement I / O scheduling instead of blindly scheduling, which can effectively improve the I / O processing efficiency. It should be noted that the "联动" in the original text seems to be a misspelling. It might be "联动" which is not a standard English word. I've translated it as "联动" for now. If it has a specific correct English expression, please let me know and I can adjust it.