84 results about "Thread count" patented technology

The invention provides a system operation lagging construction method and device, equipment, a medium and a program product. Relates to the technical field of system performance testing. The method comprises the steps that the CPU thread number and a watchdog threshold value of a current system are obtained; on the basis of the CPU thread number and the watchdog threshold value, the duration of the target thread executing busy waiting operation is calculated through a preset formula; initializing a spin lock of a kernel mode, and creating target threads of which the number is the same as that of the CPU threads, so that the target threads execute preset processing logic to construct system operation jamming; the preset processing logic comprises the following steps: periodically obtaining a spin lock; responding to the situation that the spin lock is not obtained, and continuing to execute the spin lock obtaining operation; and in response to obtaining the spin lock, executing a busy waiting operation. According to the method, CPU resources are continuously occupied through kernel spin lock competition, and a real system jamming scene is simulated. The busy waiting operation duration is dynamically calculated, it is ensured that the single-thread lock holding time is slightly lower than a watchdog threshold value, and crash of a system triggering unrecoverable is avoided.

The invention provides a concurrent scheduling and fault-tolerant optimization method and a concurrent scheduling and fault-tolerant optimization system for distributed jobs of a Spark application layer. The method comprises the following steps: acquiring a scheduling parameter, and analyzing the parameter to generate a configuration object; dividing data in a starting and ending date range according to business logic based on the configuration object, and generating a discrete data fragment list; based on the discrete data fragment list and the concurrent thread count, creating a thread pool, packaging each discrete data fragment into an independent task, and storing the independent task into a to-be-processed fragment queue; obtaining discrete data fragments through a thread pool working thread, calling SparkSession to execute service processing logic, and submitting a job to a cluster to obtain an execution result; performing judgment processing on the execution result, and recording a task processing state; based on all processing states, an execution report is generated. According to the method, the execution efficiency and the resource utilization rate of the Spark application are remarkably improved.

The embodiment of the invention discloses a data synchronization method and device, electronic equipment and a storage medium. The method comprises the steps that connection with a data source is established, metadata information of the data source is acquired and analyzed, and data source characteristics are obtained; determining a target index according to the real-time operation index of the data source and a local real-time allowable performance index, determining an adjustment strategy of the collection thread count according to the target index, and adjusting the current collection thread count according to the adjustment strategy; and determining the synchronization content of the to-be-synchronized data according to the data source characteristics and the database log, determining a parallel pipeline according to the synchronization content, and issuing the synchronization content to the parallel pipeline to synchronize the to-be-synchronized data. According to the method, the acquisition thread count is accurately adjusted, and the load balance of the two ends in the data transmission process is ensured while the data transmission load pressure of the data source and the local is relieved.

A system for scaling parallelism in sweeping stale data associated with multi-version data management is disclosed. The system is programmed to manage a targeted sweep of stale data stored on distributed storage associated with a set of computing nodes, where the stale data includes metadata for database transactions. The system is programmed to dynamically determine, on a computing node, how many threads to simultaneously perform deletion for the targeted sweep based on historical performance of the computing nodes, historical performance of the distributed storage associated with the computing nodes, or other factors. The system is programmed to then cause a certain number of threads to run on the computing node, where each thread identifies and deletes specific metadata for data transactions within the scope of the targeted sweep.

The invention discloses a self-adaptive memory allocation optimization method and device, terminal equipment and a storage medium, and belongs to the field of memory management. The method comprises the steps of monitoring thread data and system state data in real time, extracting thread memory behavior characteristics and resource state characteristics when one variable quantity exceeds a safety threshold value, and performing weighting calculation according to a preset weight coefficient to obtain a target strategy score; when the strategy score difference value of the target strategy score and the current strategy score is smaller than a preset difference value threshold value, the current memory allocation strategy is kept; when the strategy score difference value is not smaller than a difference value threshold value, a target memory allocation strategy is matched in a preset strategy library according to the thread memory behavior and the resource state characteristics, a current memory allocation strategy is updated, memory allocation parameters are adjusted, and a current strategy score is updated; when the current memory allocation strategy and the current strategy score are compared for the first time, the current memory allocation strategy and the current strategy score are the initial memory allocation strategy and the corresponding initial score, and the problem that efficiency and compatibility cannot be considered at the same time in the prior art is solved.

The thread allocation method, device, storage medium and computer device provided by the application, when the target task to be executed and the total number of threads to be allocated are determined, since the target task includes a plurality of concurrently executed subtasks, and the number of subtasks is not greater than the total number of threads, therefore, at the initial running of the system, the application can perform at least one thread allocation operation on each subtask according to a preset first allocation strategy until the number of allocated threads reaches the total number of threads; further, in order to avoid allocation errors caused by uneven data size, the application can set a round interval in advance, and after the thread allocation is completed, the current execution round of the target task is monitored, and when the current execution round reaches the preset round interval, at least one thread allocation operation is performed on each subtask according to a preset second allocation strategy until the number of allocated threads reaches the total number of threads, which can improve the resource utilization.

Code running on a processing unit can retain a hold on an active thread thereby preventing another thread running on the processing unit from executing. This can occur when the code requests more threads to be executed than the processing unit can give forward progress to, e.g., more threads than can be run simultaneously. Inserting the conventional yield instruction can lead to processing inefficiency such that the yield instruction can be executed more times than necessary thereby leading to an inefficiency in processing cycles of the processing unit performing the thread-switching routines. A yield occasionally instruction can be inserted into the code instead of the yield instruction. The yield occasionally can limit the times a yield instruction is executed thereby improving the efficiency of the processing cycles. The yield occasionally instruction can be used in non-terminating regions of the code, where the forward progress of other threads cannot be guaranteed.

The invention relates to the field of network communication, in particular to a software differential packet processing method, device and equipment. According to the method, firstly, after the differential request is responded, the intranet storage address is included in the exclusive downloading thread pool instead of single-thread one-time downloading, and the thread count can be flexibly allocated according to hardware resources; then file fragmentation downloading is carried out, a large file is split into small fragments for parallel transmission, network bandwidth fluctuation can be adapted, and insufficient bandwidth utilization rate or congestion during single-thread transmission is avoided; and meanwhile, the fragmentation mechanism supports accurate retry failure fragmentation, and a complete file does not need to be replayed. Through combination of thread pool dynamic scheduling and fragmentation parallel transmission, waste caused by resource exclusive occupation of a single thread is avoided, the data transmission amount in unit time is increased through multi-thread parallel, the fragmentation size and the thread number can be flexibly adjusted by adapting to different hardware resources and bandwidth conditions, finally the downloading efficiency is remarkably improved, and the downloading efficiency is improved. The problems of resource waste and low efficiency in the prior art are solved.

The present application relates to the technical field of equipment life cycle management, and specifically includes an aviation equipment full life cycle management method and system based on digital threads, the method comprising: acquiring process parameters of each stage, determining first digital thread master data and a first layer of associated test sequences, second digital thread master data and a second layer of associated test sequences, mapping the deviation of the physical equipment state and the virtual simulation state, and identifying the performance difference point under the cross-stage data correlation link; setting a management strategy for collaborative optimization. The technical problem of being unable to identify the cross-stage performance difference point equipment performance fluctuation root cause positioning in real time, causing the reliability of aviation equipment to be limited is solved, the first and second digital thread master data and the associated test sequences are constructed, the deviation of the physical equipment and the virtual simulation state is accurately mapped, the management strategy is set in combination with the double thread data and the performance difference point, and full life cycle collaborative optimization is performed, and the technical effect of effectively improving the equipment reliability is achieved.

The invention discloses a Falcon signature loop structure parallel acceleration method based on a GPU (Graphics Processing Unit) shared memory. The method comprises the following steps: S1, distributing the shared memory and sharing data in a thread block; s2, performing parallel circulation; s3, performing thread synchronization; and S4, result combination and output. And S5, a Falcon signature result is obtained. According to the method, a large temporary storage space originally distributed on a function stack is optimized into GPU shared memory distribution, and a serial loop structure related to large-scale polynomial operation is transformed into a parallel execution mode of a fixed thread count (such as 128 threads), so that the execution efficiency of Falcon signature operation is greatly improved on the premise of ensuring the calculation correctness, and the execution efficiency of the Falcon signature operation is improved. The memory occupation is reduced, and the expandability and practicability of the algorithm in a high-dimension and large-scale application scene are enhanced.

The invention discloses a data processing method and a related device, and the method comprises the steps: obtaining a first backlog data volume of a message queue at a first time, and obtaining a second backlog data volume of the message queue in a first time period, the first time period being a time period before the first time; determining whether the message queue satisfies a thread pool adjustment condition based on the first backlog data volume and the second backlog data volume; under the condition that the message queue meets the thread pool adjustment condition, adjusting the thread number of a current thread pool of the message queue to obtain a first thread pool of the message queue; and processing the data in the message queue based on the first thread pool. According to the method, the running state of the message queue can be tracked in real time, so that the adjustment opportunity is accurately determined, the thread pool of the message queue is accurately and dynamically adjusted, and abnormity of the message queue is avoided.

The application discloses a kind of real-time database monitoring methods based on ordered queue, including according to system design throughput and machine configuration, set initial parameter respectively set working thread and distribution thread number and memory capacity alarm threshold, according to the number of working thread adjustment shunt storage queue number ensure that thread queue number match, management node starts, start receiving heartbeat request, and according to preset hash algorithm is shunted storage, new received heartbeat request is stored in ordered double linked list queue head, then according to host IP information to hash table inquires whether heartbeat record exists, if the new received heartbeat record does not exist, for new online client, client information is stored to hash table then triggers new online event and persists to client database table write-in process ends.The application solves the problem that a large amount of data heartbeat information detection detection complexity rises exponentially with data volume rising by hash and double linked list structure.

The invention provides a multi-thread rapid sleep wake-up control method and system. According to the technical scheme, any multiple threads can directly enter a sleep state according to stored thread data; dormancy and awakening of the threads are controlled in a conditional variable mode, so that the threads can be awakened according to a set sequence conveniently, and the problem of awakening time sequence is solved; a unified dormancy interface is used, direct dormancy is achieved after any thread is called, and use is easy; in the thread wakeup stage, all threads can be pulled up according to a set sequence only by calling a wakeup interface once. And the application program is quickly recovered to normal execution. According to the method and the device, the sleep and wake-up efficiency of the threads can be effectively improved under the condition of many threads; hibernation awakening operation is performed through a unified interface, so that the complexity of software can be greatly relieved; the control drive is used for management, switching between a normal mode and a dormant state can be carried out, software design is simplified, and robustness and stability of the system are improved.

The invention provides a method and a device for adaptively adjusting concurrency of consumer threads. The method comprises the following steps: acquiring consumer offset and log end offset of each partition of a consumer, calculating message accumulation amount of each partition, and summarizing to obtain current message accumulation amount of the consumer; based on the current message accumulation amount, a target thread count is calculated in combination with a preset rule or a dynamic index, and the dynamic index at least comprises a change rate of the accumulation amount within a preset time and a single-thread average message processing throughput; and under the condition of determining that the preset adjustment condition is met, adjusting the core thread count and the maximum thread count of the thread pool of the consumer to the target thread count through the interface of the Kafka consumption task executor. Based on the method, the processing capacity of the consumer can be matched with the real-time message load, the resource utilization rate is improved while the processing delay is reduced, and the stability of the system adjustment process is guaranteed.

The invention belongs to the technical field of vehicle software development, and particularly relates to a system and method for a non-real-time system to achieve hard real-time in hardware-in-loop simulation, and the system comprises a computer device, a hardware-in-loop simulation device and a hardware-in-loop simulation device. The computer device is configured to execute a task creating module and a task thread setting module; wherein the task creating module is configured to create a real-time model task and form a task program; the task thread setting module is configured to enable a task program to automatically read computer configuration and judge the number Z of processor cores of the current computer device, when the number Z of the cores does not exceed X, the thread number n is set to be equal to 1 so as to execute a real-time model task, otherwise, the thread number n is set to be equal to (Z-X) / Y so as to execute the real-time model task, wherein Y represents the number of threads of one physical core of the processor.

The application discloses a distributed scheduling method and device under a micro-service architecture and a medium. The method comprises the following steps: determining a scheduled task to be distributed, wherein the scheduled task refers to a business logic executed according to a set timer rule; according to different business types, dividing servers into a scheduling execution micro-service unit and a business micro-service unit, and distributing the business micro-service unit; determining a tenant database corresponding to the scheduling execution micro-service unit, wherein the tenant database only allows the corresponding scheduling execution micro-service unit to access; determining the number of threads corresponding to the scheduling execution micro-service unit and the working state of the threads, and determining scheduled task information; and according to the number of threads, the working state of the threads and the scheduled task information, distributing the scheduled task in the tenant database to other scheduling execution micro-service units and business micro-service units through the scheduling execution micro-service unit.

The invention relates to the technical field of software, in particular to a system updating method, electronic equipment and a medium. The system updating method comprises the following steps: in a system installation process, detecting a trigger condition (for example, the system installation reaches 60%) for compiling and optimizing a third-party application, and obtaining the temperature of the electronic equipment; according to the obtained temperature of the electronic equipment, the number of threads for compiling optimization of the third-party application is determined, when the temperature gradually rises to a specific temperature interval, the number of the threads for compiling optimization is reduced, and when the temperature falls back to the specific temperature interval, the number of the threads for compiling optimization is increased accordingly. Thus, the number of the compilation optimization threads is dynamically adjusted based on the temperature of the electronic equipment, normal operation of compilation optimization of the third-party application is achieved, at least part of the third-party application can adapt to the updated system after the electronic equipment is restarted, and user experience is improved.

The application relates to a data processing method and a computer storage medium. The method comprises the following steps: acquiring each core of a processor, and creating a corresponding thread for each core, wherein the thread is bound to the corresponding core and is in a silent state; in response to the storage system being in a standby power state, acquiring to-be-processed data, a remaining battery capacity, a battery voltage and an expected available time, and determining a power threshold according to the remaining battery capacity and the expected available time; determining the number of threads to be woken up according to a preset scheduling model, the to-be-processed data and the power threshold; according to a preset allocation strategy, allocating the to-be-processed data to the threads to be woken up to perform a disk-falling operation; in response to the storage system being restarted, detecting whether there is disk-falling data; and in response to the existence of the disk-falling data, loading the disk-falling data into the memory and resuming the execution of a task flow. Through the method, the disk-falling capability can be dynamically adjusted, the energy efficiency ratio can be improved, and the data recovery reliability can be ensured.

The invention relates to a data processing method and a computer storage medium. The method comprises the steps that all cores of a processor are obtained, corresponding threads are created for all the cores, and the threads are bound with the corresponding cores and are in a silent state; in response to the condition that the storage system is in the standby power state, acquiring to-be-processed data, battery remaining capacity, battery voltage and estimated available time, and determining a power threshold according to the battery remaining capacity and the estimated available time; determining the number of awakened threads according to a preset scheduling model, the to-be-processed data and a power threshold; distributing the to-be-processed data to the awakened thread according to a preset distribution strategy, and executing a disk falling operation; in response to restarting of the storage system, detecting whether disk falling data exists or not; in response to the existence of the disk falling data, loading the disk falling data into the memory, and recovering the task execution process. Through the method, the disk falling capacity can be dynamically adjusted, the energy efficiency ratio is improved, and the data recovery reliability is ensured.

The invention discloses an index recovery method, device and equipment and a computer readable storage medium, which are applied to the technical field of computers, and the method comprises the following steps: when a fault occurs, analyzing a data topological structure corresponding to an index data fragment stored by a node; based on the fragment access log of the node, calculating a heat value of the index data fragment by adopting a time decay model; determining a loading thread count according to the node resource state; determining the priorities of the index data fragments based on the business query priorities, the popularity values and the fragment memory efficiency, and determining a loading sequence according to the priorities; and according to the loading thread count and the loading sequence, loading the index data fragments in the nodes from the persistent storage to the cache, and constructing a memory finite state converter structure capable of being directly retrieved based on a data topological structure. According to the method, on the premise that the system architecture is not changed, the distributed retrieval system can be quickly recovered when the fault occurs, the unavailable time of the system is shortened, and the availability, stability and resource utilization rate of the system are improved.

The invention discloses a task assignment method and system based on a task graph, and relates to the technical field of sparse linear equation set solver, and the method comprises the steps: calculating task processing time based on a time estimation model during task assignment; the number of completed tasks is initialized to be zero, the number of initial idle threads is initialized to be the number of total threads, and the tasks with the initial task state being in task waiting are put into a to-be-dispatched task sequence; executing a task assignment main cycle; when the initial idle thread number is greater than zero and the to-be-dispatched task sequence is not empty, distributing a thread number for the task; when the initial idle thread count is zero, determining the fastest thread based on the task processing time; when the to-be-dispatched task sequence is empty, traversing the task chain depending on the current task to obtain the dependent task of the current task, putting the dependent task into the to-be-dispatched task sequence, and executing the task dispatching main cycle, so that the problem that the task processing time cannot be accurately predicted and the thread resources cannot be uniformly distributed in the prior art can be solved.

This application relates to a method, apparatus, computer device, readable storage medium, and program product for power message processing based on adaptive partitioning, belonging to the field of power data processing technology. This application can improve the flexibility and adaptability of power message processing. The method includes: configuring thread pools and lock-free queues for each partition according to the partition identifier of the service area-measurement point partition; dynamically adjusting the thread resource allocation of each service area-measurement point partition through an inner and outer double-loop control mechanism based on the thread pools and lock-free queues; routing measurement points to the corresponding service area-measurement point partitions for processing according to the partition mapping table based on the service area-measurement point partition structure and partition identifier to obtain message processing results; prioritizing the adjustment of the number of threads in each service area-measurement point partition through a partition load and thread resource control strategy to cope with short-term load fluctuations; if the inner-loop control cannot solve the problem, triggering structural adjustments to the service area-measurement point partition structure.

The invention discloses a method and system for realizing a dynamic thread pool based on Agent, and relates to the technical field of thread pools, and the method comprises the following steps: collecting internal operation state data of a task execution module and resource use data of a host machine through an environment perception module, and generating a system state snapshot; the central decision-making agent receives the snapshot and generates an adjustment instruction based on a built-in mixed decision-making model; the dynamic actuator module executes the instruction to modify operating parameters of the task execution module. According to the method, closed-loop dynamic control over the thread pool parameters is achieved, key configurations such as the core thread count and the maximum thread count can be adaptively adjusted according to real-time loads and resource conditions, the problems that static configuration resources are rigid and manual adjustment and optimization are difficult are solved, and the system resource utilization rate, the response capacity and the overall stability are improved.

This application relates to a method for rapidly accelerating an engine based on a dynamic thread pool in large-scale scenarios. The method includes: configuring basic parameters such as the number of core threads and the maximum number of threads, or generating parameters through a computational model for initialization; after task submission, first determining the availability of core threads, and if idle, creating threads to execute tasks based on load prediction to determine the expansion step size; when the core thread pool is full, checking the blocking queue status, storing tasks if not full, and triggering expansion if full; when the thread pool is full, executing a saturation strategy to block submissions until resources are idle; after task execution, threads enter a waiting state, and if a timeout occurs, they are released to sleep, with the remaining thread count not less than the core thread count. This method can accelerate the process of the engine calling the simulation model, ensuring the normal execution of training tasks.

Embodiments of the present specification provide a task processing method and device, wherein the task processing method comprises: in the process of task scheduling, a distributed scheduling system first reads the task processing time length of each sampling point according to the task scheduling frequency of the distributed process, and calculates the task grabbing parameter by combining the task processing time length, the number of key threads in the thread pool configured by the task processing module of the distributed process, and the task scheduling frequency; secondly, the tasks obtained by task grabbing according to the task grabbing parameter are scheduled to the thread pool for task processing, so as to calculate the task grabbing parameter before task grabbing, and realize dynamic adjustment of task grabbing and task scheduling.

The invention provides an error detection method and system for a single-instruction multi-thread processor, electronic equipment and a medium. The method comprises the steps that the number of active threads and the number of inactive threads in a current thread bundle of the single-instruction multi-thread processor are counted; the number of the active threads is compared with the number of the inactive threads, when the number of the active threads is larger than the number of the inactive threads, thread recombination operation is triggered, the current thread bundle is updated, and a new thread bundle is obtained; the number of new active threads in the new thread bundle is smaller than or equal to the number of new inactive threads; based on a new inactive thread in the new thread bundle, performing redundancy calculation on a calculation task of a new active thread in the new thread bundle to obtain a first redundancy calculation result; and comparing the first original calculation result of the new active thread in the new thread bundle with the first redundancy calculation result, and performing error detection based on the first comparison result. Through thread recombination and redundancy calculation, the error detection cost is reduced, and the resource utilization rate is increased.

The invention belongs to the technical field of vehicle software development, and particularly relates to a method for realizing hard real-time by a non-real-time system in hardware-in-loop simulation and electronic equipment, and the method for realizing hard real-time by the non-real-time system in hardware-in-loop simulation comprises the following steps: creating a real-time model task, and forming a task program; the task program automatically reads computer configuration and judges the number Z of processor cores of the current computer device, when the number Z of the cores does not exceed X, the number n of threads is set to be equal to 1 to execute the real-time model task, otherwise, the number n of the threads is set to be equal to (Z-X) / Y to execute the real-time model task, and Y represents the number of the threads of one physical core of the processor.

This invention relates to a lock-free I / O scheduling method, apparatus, and storage medium for cloud PCs. Responding to a client session request initiated by a client, the method controls a metadata coordinator to allocate storage nodes to the client and, within those storage nodes, allocates I / O shards for the client, obtaining allocation information. The metadata coordinator then returns the allocation information to the client, and the client caches this allocation information to facilitate the use of the allocation information to fulfill I / O requests. Each I / O shard includes an I / O thread bound to a first CPU core, a data plane development toolset driver, a storage performance development toolset driver, a first lock-free circular buffer, and a second lock-free circular buffer. By binding the CPU core and using lock-free circular buffers, thread switching, lock contention, and most memory copying are eliminated, reducing I / O processing latency from milliseconds to hundreds of microseconds and significantly reducing latency jitter.

The invention provides a CPU use limiting method and system based on a thread pool, electronic equipment and a medium, and the method comprises the steps that a calculation task is submitted to a task queue of a preset thread pool, and the maximum thread count of the preset thread pool is a preset threshold value; obtaining the first starting time, the first completion time and the current time of the previous calculation task in the task queue; determining the execution time of the previous calculation task according to the first start time and the first completion time, and determining the idle time of the current calculation task according to the current time and the first completion time; obtaining the core utilization rate of the CPU, and calculating the target waiting time of the current task according to the core utilization rate and the execution time; executing the current calculation task according to the target waiting time and the idle time; according to the method and device, it can be guaranteed that the CPU is not excessively occupied when executing the calculation task, sufficient resources are reserved for other tasks, and the working performance of the CPU is guaranteed.