21 results about "Fair scheduling" patented technology

The invention relates to a shared GPU resource fair scheduling method and system based on multi-dimensional priority, and belongs to the field of cloud computing and container orchestration.The method comprises the steps that pooling and virtualization segmentation are conducted on physical GPU resources in a cluster, and a unified GPU resource pool is formed; calculating the comprehensive priority weight of the task according to the user level, the task type and the service quality in combination with a multi-dimensional priority model; a scheduling decision is made based on a weighted dominant resource fair algorithm, task priority weights and dominant resource proportions are comprehensively considered, and fair scheduling and optimal distribution of GPU resources are achieved; through a resource monitoring and feedback mechanism, the GPU utilization rate, the task execution state and the resource allocation result are monitored in real time, priority parameters and scheduling weights are dynamically adjusted, and finally fair scheduling of shared GPU resources is achieved. According to the method, intelligent allocation, resource sharing and fair scheduling of tasks can be realized in a GPU virtualization environment, and the scheduling efficiency and the overall cluster utilization rate are improved.

The invention discloses a thread scheduling method, electronic equipment, a storage medium and a program product, and relates to the technical field of computers, security check is performed on a source thread and a target thread through a thread switching request initiated by the source thread, an allocatable time period of the source thread allocated to the target thread is calculated according to a security detection result, and the allocatable time period of the source thread allocated to the target thread is sent to the electronic equipment. Bypassing a processing mechanism of a completely fair scheduler, updating the virtual running time of a source thread, distributing an allocable time period to a target thread, calling a context switching function to execute thread switching operation on the source thread and the target thread, and synchronously updating the virtual running time of the target thread when the target thread consumes the allocable time period. According to the thread scheduling method and device, the problem that in the related technology, when a complete fair scheduler processes high-frequency and collaborative thread tasks, due to the indirect handover mechanism and fair scheduling characteristics of the complete fair scheduler, the delay of thread scheduling is improved is solved, and the delay of thread scheduling is reduced.

The invention discloses a fair resource management method and system for multi-user shared large language model reasoning, and the method is characterized in that the method employs a cold data recognition elimination mechanism and a fair cache distribution mechanism, carries out the unified quantification of the resource consumption of a request in GPU calculation, decoding and cache transmission, and carries out the fair scheduling based on the accumulated CPI value of each user; the system comprises a user request management module, a CPI fair scheduling module, a model reasoning execution module, a resource monitoring module and a cache management module. Compared with the prior art, the method has the advantages that users can share computing and caching resources fairly, efficient operation performance of the system is guaranteed, users with high cache hit rate are prevented from excessively occupying GPU execution opportunities due to low apparent computing overhead, the overall reasoning efficiency and the cache hit rate of the system are remarkably improved, and the user experience is improved. Unified and fair distribution of computing resources and cache resources is achieved, the effect is prominent especially in a multi-tenant high-load scene, and the method has good application prospects and commercial development value.

The embodiment of the invention provides an intelligent scheduling method and system. The method comprises the following steps: acquiring historical work order data in all time periods, accurately counting key indexes such as on-duty duration, work order processing quantity and work order processing time of an operator on duty, and building a data foundation for subsequent decision making; then, based on historical work order data, a comprehensive score of the employees is determined according to a preset algorithm, the score can comprehensively reflect the performance condition of each employee in historical work in a time period, meanwhile, the limitation of traditional operation and maintenance scheduling is broken through with the help of a genetic algorithm, and scientific and fair scheduling management is achieved; based on the comprehensive scores of the employees, determining corresponding fitness according to a preset scheduling rule, and ensuring that an algorithm search direction conforms to a fair scheduling target; and finally, when the current fitness reaches a preset iteration frequency threshold value, generating a fairness target scheduling scheme containing detailed on-duty personnel, modes and time period information, thereby providing a reliable basis for efficient development of operation and maintenance work. The intelligent scheduling mode is realized, and the waste of human resources is reduced.

The application provides a critical resource scheduling method and device, equipment and a storage medium, and relates to the technical field of computers. The method comprises: receiving a plurality of initial resource requests sent by a plurality of preset users; preprocessing the initial resource requests to determine a target resource request from the plurality of initial resource requests, wherein the preprocessing at least comprises load balancing processing and atomic increment processing; according to the target resource request, calling a target critical resource corresponding to the target resource request from a preset critical resource pool, and distributing the target critical resource to a target user corresponding to the target resource request. Through the embodiments provided by the application, the combination of load balancing technology and atomic increment technology is used to realize efficient and fair scheduling of critical resources.

The application discloses an application thread scheduling method and device, a storage medium and an electronic device, relates to the technical field of computers, and comprises the following steps: creating an application process of a target application that is started, wherein the application process comprises an auxiliary thread and a main thread; setting the type of the auxiliary thread as a fair scheduling class and setting the type of the main thread as a deadline scheduling class; creating an application drawing thread and setting the type of the application drawing thread as a deadline scheduling class; and scheduling the auxiliary thread, the main thread and the application drawing thread according to thread scheduling priorities corresponding to the deadline scheduling class and the fair scheduling class, so as to run the target application. The application effectively avoids the phenomenon of application running jamming and improves the smoothness of application use.

The application discloses a constraint-aware heterogeneous cluster fair scheduling method and system based on space-time sharing. The method comprises the following steps: obtaining a task execution request of a user, and constructing a task constraint matrix; generating a task execution list based on space sharing and maximum minimum fairness; performing constraint-aware fair scheduling among servers, and allocating a target server for a highest priority task; performing round-based time sharing dynamic adjustment until the end of the current round of time; and continuously performing round scheduling until the task execution list is empty. The constraint-aware heterogeneous cluster fair scheduling method based on space-time sharing comprehensively considers task constraints and heterogeneous resource fairness, thereby coordinating and managing distributed computing tasks, ensuring fairness among users, and improving computing efficiency.

The invention discloses a proportional fair scheduling method based on a block chain. The method comprises the steps that a user and an operator complete identity authentication and registration through a registration contract; a user periodically uploads channel state information and bandwidth requirements through a state reporting contract; the scheduling contract calculates the scheduling priority of each user according to a proportional fairness principle, determines a to-be-scheduled user for each operator, and completes the updating of the historical throughput of the user; and the settlement contract generates a bill according to the scheduling result and carries out chaining for evidence storage. The invention further discloses a cross-network joint scheduling performance evaluation method in the multi-operator collaborative environment, and a mathematical characterization model of the long-term average throughput of the user and the network utility is constructed. According to the method, automatic scheduling is realized by using the intelligent contract, and the scheduling operation is recorded on the chain in a tampering-free manner, so that the whole scheduling process is open, transparent, safe and credible, cross-network resource aggregation and cooperative scheduling in a multi-operator environment are realized, and the utilization efficiency of spectrum resources and the overall performance of the network are effectively improved.

The invention relates to the technical field of computer system resource scheduling, in particular to a dynamic fair scheduling method and system and a computer readable storage medium. According to the method, when a producer generates a new message, the message is stored in a corresponding exclusive message queue; then, whether the identifier corresponding to the producer exists or not is inquired in a polling queue, if not, the identifier corresponding to the producer is added to the tail of the polling queue, and the polling queue is used for registering the identifier of the producer with the message to be processed currently; and finally, during message scheduling, taking out a producer identifier from the queue head of the polling queue, taking out a message from the exclusive message queue corresponding to the producer for processing, and resetting the producer identifier into the queue tail of the polling queue if the exclusive message queue is not empty after the processing is completed. According to the invention, through a cooperation mechanism of the dynamic polling queue and the tenant exclusive queue, self-adaptive resource scheduling without physical isolation is realized.

The invention discloses a deep model resource fair scheduling method for multi-task service quality assurance in a cloud-edge collaborative environment. The method comprises the following steps: S1, a task request sensing module; s2, an online model evaluation module; s3, a model fair selection module; s4, an isomorphic model migration module; s5, a heterogeneous model collaborative scheduling module; and S6, a service quality fairness guarantee module. The method has high engineering practical value, and can be applied to various real-time reasoning scenes such as intelligent medical treatment, intelligent security and protection, industrial internet and the like.

The invention discloses a task request scheduling method and device, equipment, a medium and a program product. In response to the task scheduling instruction, a plurality of first users whose task queues are not empty are determined, and one user corresponds to one task queue; in the dynamic priorities of the users participating in scheduling, the dynamic priority of the first user is obtained, the dynamic priority is generated based on the static basic weights of the users and the dynamic credit points of the users, the dynamic priority and the static basic weights are in positive correlation, and the dynamic priority and the dynamic credit points are in positive correlation; in the plurality of first users, determining the first user corresponding to the highest dynamic priority as a target user; and executing the target task request in the task queue corresponding to the target user. According to the embodiment of the invention, fair scheduling in a user dimension in a real sense can be realized, and system stability and service quality are guaranteed.

The invention discloses a charging pile intelligent operation management method and system based on big data, and the method comprises the steps: collecting and preprocessing multi-source heterogeneous data, and generating a real-time state set; establishing a priority voucher contract template, generating constraint and price parameters, and initializing a generated contract; receiving a user charging request, and calling the feasible region prover to output a deliverability certificate; calculating a waiting interval, an arrival time window and migration excitation, and generating a reservation and queuing instruction; under the constraint, permissible fair scheduling is executed, and power and queues are distributed and interrupted or continued; monitoring operation data and evaluating risks, and executing cross-station migration and difference compensation when a threshold value is exceeded; and the contract is settled, and if the target electric quantity is not reached or overtime occurs, claim payment or compensation is performed according to repurchase parameters. According to the method, efficient utilization of the charging pile network and remarkable reduction of the user waiting time are realized through provable fair scheduling and cross-station migration optimization driven by big data.

The invention provides a remote sensing task fair scheduling method and device based on a multistage feedback queue, and relates to the technical field of satellite remote sensing, and the method comprises the steps: obtaining a to-be-scheduled satellite remote sensing task, and carrying out the analysis to obtain a corresponding structured task parameter, then, calculating multi-dimensional scores of the satellite remote sensing task in the aspects of user end fairness, task type fairness and space-time demand fairness to allocate real-time task resources to the satellite remote sensing task, and according to the real-time task resources and a task execution window of the satellite remote sensing task, executing the satellite remote sensing task according to the real-time task resources; and determining the scheduling priority of the satellite remote sensing task in the multi-level feedback queue, finally selecting an optimally matched remote sensing platform according to the scheduling priority, and executing the satellite remote sensing task. The method is used for solving the problem of low response efficiency of task processing caused by unreasonable scheduling and resource allocation of satellite remote sensing tasks in the prior art.

The invention relates to the technical field of wireless optical communication, and discloses a hybrid fair scheduling method and system based on a wireless optical communication network. Time slots are dynamically distributed by comprehensively considering user channel capacity and throughput requirements on the basis of different throughput and time delay requirements of interactive users and transmission users; meanwhile, a scheduling structure is reconstructed according to different service types; for the interactive users, through an iteration mechanism of preferentially allocating a time slot to the interactive user with the maximum service guiding priority, and through presetting the minimum reallocation time slot, resources are rapidly obtained, it is ensured that the time slot to be recombined is preferentially consumed, and time delay accumulation caused by waiting for the long time slot of the transmission type user is avoided; and for the transmission type users, after the time slots of the interactive type users are distributed, the time slots are distributed to the transmission type users in a centralized manner according to the service oriented priority, so that the throughput loss caused by context switching is reduced, the requirement of completing large-volume data transmission within several seconds is met, and the network real-time performance and the resource utilization rate are integrally improved.

This invention relates to a multi-chip fairness scheduling method based on ZNS SSDs, comprising: calculating the latency penalty ratio of each current data flow in each chip queue for all current data flows of the ZNS SSD; calculating the fairness of each chip queue based on the latency penalty ratio of each current data flow in each chip queue; for each chip queue, taking the latest transaction allocated to each chip queue as the transaction to be scheduled, and scheduling the transaction to be scheduled forward in the chip queue based on the latency penalty ratio of the current data flows related to each chip queue in the chip queue, with the optimization objective of maximizing the fairness of the chip queue; and scheduling all transactions related to the request of the transaction to be scheduled to the maximum position in the corresponding chip queue according to the maximum position of all transactions in the corresponding chip queue, thereby improving the response time of the request. This invention improves the performance of ZNS SSDs.

The application discloses a kind of based on multi-thread fair scheduling's electronic archives archiving method and device, receive the electronic archives to be archived, feature analysis is carried out to the electronic archives, form feature analysis result, according to the feature analysis result, the electronic archives is divided into archiving task type.According to the archiving task type corresponding to the electronic archives, the corresponding thread pool is allocated to the electronic archives, according to the feature analysis result, the scheduling weight is calculated, and the scheduling time slice is set according to the scheduling weight.The electronic archives is distributed to the thread of corresponding thread pool by using scheduling engine and executes archiving processing, before archiving processing execution, the checkpoint for fault recovery is created, after archiving processing execution, archiving task is completed and is marked, and the thread occupied by the electronic archives is automatically released.The application can greatly improve the scheduling fairness and archiving efficiency when electronic archives is archived, ensure archiving data integrity, eliminate thread starvation phenomenon.

When scheduling a task to be executed by a target virtual machine, a scheduler first obtains at least one top-priority task in a to-be-executed task queue of the first target virtual machine to first ensure that the top-priority task is preferentially executed, determines a first task with a minimum virtual runtime from the at least one top-priority task, and controls the target virtual machine to execute the first task. This ensures fair task scheduling of at least one task with the same priority. The scheduler can ensure both preferential scheduling of a high-priority task and fair scheduling of tasks with the same priority when scheduling the task on the first target virtual machine.

The invention discloses an RISC-V CLIC pre-arbitration method and system based on hierarchical priority and cycle perception, and belongs to the technical field of embedded systems. The method comprises the following steps of: firstly, dividing an interrupt source into a hard real-time domain L1 and a fair scheduling domain L2 according to real-time and security requirements, directly preempting the interrupt source L1 in a hard manner according to original semantics, and ensuring a deterministic response of a security-level task; the L2 interrupt source can select three dynamic arbitration logics, and flexible scheduling is realized through parameter configuration in combination with token bucket current limiting, waiting time compensation and a period sensing mechanism. Two implementation modes of an external preposed arbitration module or an internal integrated dynamic arbitration sub-module are supported, a shift addition lightweight hardware design is adopted, low overhead and high real-time performance are both considered, and compatibility with a CLIC interface is achieved; and the method can be applied to scenes such as a vehicle regulation MCU (Microprogrammed Control Unit), industrial control, an edge computing gateway and the like.

The application discloses a charging pile intelligent operation management method and system based on big data, comprising: collecting and preprocessing multi-source heterogeneous data to generate a real-time state set; establishing a priority certificate contract template, generating constraint and price parameters and initializing in a generated contract; receiving a user charging request, calling a feasible domain prover to output a deliverability certificate; calculating a waiting interval, a station arrival time window and a migration incentive to generate a reservation and queuing instruction; executing a provable fair scheduling under constraints, allocating power and queue and interrupting or renewing; monitoring operation data and evaluating risks, performing cross-station migration and difference compensation when exceeding a threshold; settling the contract, and compensating or compensating according to the repurchase parameters when the target power is not reached or the time is exceeded. The application aims to realize efficient utilization of the charging pile network and significant reduction of user waiting time through big data driven provable fair scheduling and cross-station migration optimization.

This application discloses a thread scheduling method, electronic device, storage medium, and program product, relating to the field of computer technology. It involves a thread switching request initiated by a source thread, performing security checks on both the source and target threads. Based on the security check results, it calculates the allocatable time period allocated from the source thread to the target thread, bypassing the processing mechanism of the Completely Fair Scheduler (CFS). It updates the virtual runtime of the source thread and allocates the allocatable time period to the target thread. A context switching function is then called to perform a thread switching operation on both the source and target threads. Simultaneously, when the target thread consumes the allocatable time period, its virtual runtime is updated to complete the thread scheduling switch. This solves the problem in related technologies where the CFS, due to its indirect handover mechanism and the characteristics of fair scheduling, increases thread scheduling latency when handling high-frequency and cooperative thread tasks, thus reducing thread scheduling latency.