652 results about "Concurrency" patented technology

The invention provides a dynamic tool integration method and system for an intention-driven AI dialogue system, and the method comprises the steps: S5, extracting resource occupation information from a transaction log according to a state persistence record, carrying out the resource release and temporary context cleaning of each heterogeneous component, and obtaining a released resource list; s6, searching a breakpoint state snapshot and a transaction log from the distributed database according to the released resource list, and reconstructing a tool chain execution flow historical state to obtain a fault context analysis result; and S8, according to the context recovery state and the semantic feature vector, updating a tool chain execution stream, and reallocating computing resources through a heterogeneous component coordination mechanism to obtain a task continuity confirmation result. According to the method, the recovery efficiency and the resource utilization rate of the tool chain in an abnormal scene are remarkably improved, and the task continuity and the system robustness in a high-concurrency environment are guaranteed.

The invention provides a heat supply digital twinborn intelligent regulation and control method, and relates to the technical field of intelligent regulation and control, and the method comprises the steps: executing millisecond-level high-concurrency numerical simulation according to a dynamic digital twinborn body, so as to obtain a simulation result; based on the simulation result, coupling the electricity price fluctuation data and the weather prediction data, performing future heat supply system multi-working-condition deduction, and dynamically optimizing a heat source unit start-stop combination and pipe network valve opening strategy to obtain a deduction result and an optimization strategy; generating an equipment regulation and control instruction set according to the deduction result and the optimization strategy; and an equipment regulation and control instruction set is issued to an edge computing node, a variable-frequency circulating pump and an electric control valve executing mechanism are controlled, and dynamic closed-loop regulation of the flow and the pressure of the heat supply pipe network is achieved. According to the invention, the pipe network flow and pressure regulation response time can be shortened to a second level.

The invention relates to the technical field of computers, and discloses a multi-mode audio and video synchronous processing method and system based on a distributed architecture. The method comprises the following steps: generating a unique logic sequence identifier consisting of a device code, a media type and a frame number for each frame of audio and video data; distributing the frame carrying the identifier to a distributed node for processing and adding a local timestamp; and the sink node reconstructs an original frame sequence according to the identifier, calculates a synchronous offset by combining high-precision clock calibration, and realizes dynamic reordering and output through a double-buffer structure and a self-adaptive drift compensation algorithm. The system comprises a source end acquisition module, an identifier generation module, a task scheduling module, a distributed processing cluster module, a convergence synchronization module and a synchronous output module. According to the scheme, the system effectively guarantees the audio and video synchronization precision in a high-concurrency heterogeneous environment, the synchronization error is controlled within 20 milliseconds, and the playing quality and the user experience of scenes such as live broadcast and cloud games are remarkably improved.

The invention discloses an intelligent resource scheduling method and system based on task characteristics and system state perception, and relates to an operating system kernel optimization technology. According to the method, resource demand types, importance labels and time sensitivity of tasks are captured in real time through an eBPF technology, system bottlenecks are recognized by combining / proc and sysfs file system data, a dynamic scheduling strategy is generated by adopting an improved Q-Learning model, and resource allocation is executed through a schemed * function and a cgroup v2 interface. The problems that a traditional scheduler is poor in self-adaptive capacity and resources are mismatched are solved, the actually-measured resource utilization rate is increased to 85%-92%, and the key task delay standard reaching rate gt is achieved; the method is suitable for edge computing, cloud servers and other high-concurrency scenes.

The invention provides a heterogeneous reasoning computing power scheduling method and device and a storage medium, and the method comprises the steps: receiving a reasoning request, splitting the reasoning request, and obtaining at least one reasoning task; according to the coding length of each reasoning task, scheduling the reasoning tasks to a long task queue or a short task queue; when it is monitored that reasoning tasks with to-be-processed task states exist in the long task queue and the short task queue, the working state of the reasoning service of the first processor is judged based on the number of tasks in processing of the first processor in the long task queue and the short task queue and the maximum concurrency of the first processor; the maximum concurrency of the first processor is obtained based on the current conditions of the long task queue and the short task queue; and on the basis of the working state of the first processor reasoning service, the reasoning task to be processed is scheduled to the first processor reasoning service or the second processor reasoning service so as to maximize and reasonably utilize the mixed computing power resource of the heterogeneous processor.

The invention discloses a method and a device for optimizing dynamic task scheduling resources of a distributed system. The method comprises the following steps of: monitoring a task dependency relationship and hardware resource state data in real time; a dependency release amount R representing the downstream task activation capability is generated based on the dependency relationship; generating an index A representing the resource utilization efficiency based on the resource state; a scheduling strategy is dynamically selected according to the load state: when the load is low, the task with the maximum R is preferentially allocated to improve the CPU parallelism degree, when the load is stable, allocation is carried out according to R and A weighted values to balance resource utilization, and when the load is high, the task with the maximum A is preferentially allocated to reduce the memory pressure; and finally driving task execution and updating a resource state. By dynamically sensing the task topological relation and the resource state, adaptive scheduling under load fluctuation is realized, the collaborative utilization efficiency of CPU and memory resources is effectively improved, and the problem of performance bottleneck of a traditional scheme under complex dependence and high-concurrency scenes is solved.

The invention relates to a lightweight asynchronous message processing method and system for a high-concurrency scene, and the method comprises the steps: receiving a message request of a client, carrying out the preprocessing of the message request, and generating a to-be-processed message; distributing the to-be-processed message to a multi-level priority queue based on a priority scheduling mechanism; dynamically adjusting the number of core threads and the maximum number of threads of the thread pool according to the resource state data, and forming a thread pool resource configuration scheme of the current scheduling period; dynamically calculating the message processing quantity of the current scheduling batch based on the message accumulation quantity of each priority queue, the thread pool resource configuration scheme, the CPU utilization rate in the resource state data and the JVM heap memory utilization rate; and based on the out-of-heap memory buffer area reference, assigning the to-be-processed message object to a corresponding processing thread to execute a service processing logic until the processing operation of the messages in all the scheduling units is completed. The method has the effect of improving the resource adaptability of the asynchronous message processing architecture.

The invention relates to the field of database reading, and particularly discloses an efficient database reading method based on multi-level cache optimization and dynamic index fragment.The efficient database reading method comprises the steps that high-frequency query data is accurately recognized through a sliding window algorithm, a dynamic cache loading and preheating strategy is implemented, query delay is effectively shortened, and the database burden is relieved; intelligent distribution of index fragments is realized by applying a consistent Hash algorithm, and the query efficiency is greatly improved in cooperation with distributed query routing and transaction processing optimization; the query load balancing ensures stable and efficient operation of the system in a high-concurrency scene by means of weighted polling and a minimum connection strategy in combination with real-time monitoring and an elastic capacity expansion and contraction mechanism. According to the method, the database access efficiency and the dynamic adaptive capacity are remarkably improved, and the method is particularly suitable for a large-scale distributed data processing environment.

The invention discloses a concurrency control method and device, electronic equipment, a storage medium and a product. The method is applied to a concurrency control system comprising a processor and a bus controller, and comprises the steps that the processor responds to an atomic operation request of a target thread and sequentially sends a storage area switching instruction and a register operation instruction to the bus controller; the bus controller responds to the storage area switching instruction and the register operation instruction, executes storage area switching operation, generates a bus occupation maintaining signal and continuously executes register read-write operation in a target storage area; the processor sends a scheduling request to an operating system, so that the operating system improves the priority of the target thread to be a first priority; and the bus controller generates a bus release signal after the atomic operation of the target thread is finished. According to the scheme, through cooperation of the processor and the bus controller, atomized execution of thread Bank switching and register reading and writing is achieved, and the concurrency performance is improved while the reliability and consistency of data are ensured.

The invention discloses a U.2 interface-based server intelligent integrated hierarchical storage system and method, relates to the technical field of computer server storage, and is used for solving the problem of optimization of multi-type SSD data access efficiency and storage resource utilization rate. Firstly, a multi-protocol parallel channel is established by redefining U.2 interface reserved pins, signal integrity parameters are monitored in real time and fused with equipment I / O access features, and an I / O feature sequence of physical layer state information is generated; then, based on a time sequence convolutional neural network, extracting access mode multi-scale features, calculating a data block access heat probability, mapping and determining a target storage hierarchy, and generating a scheduling instruction containing a source physical address, the target hierarchy and a migration priority; the migration execution module realizes zero-copy migration of the data block between the shared DRAM pool and the SSD according to the instruction; and the resource coordination module monitors system load in real time, dynamically adjusts migration concurrency and an I / O sampling strategy, and realizes self-adaptive optimization of storage performance and resource utilization.

The invention discloses a white list state synchronous processing method and system combined with database transaction control, and relates to the technical field of database transaction control and data synchronous processing. The method comprises the following steps: recording a white list state change event based on a pre-writing mechanism of a database transaction log; change events in a transaction log are classified and aggregated according to a white list and then are asynchronously written into a specified buffer area, when a transaction is submitted, the sequence of data in the buffer area is controlled through a lightweight lock mechanism to be refreshed to a physical disk, and the priority of a disk IO queue is dynamically adjusted according to the transaction isolation level to reduce concurrent conflicts; according to the white list state synchronization processing method and system combined with database transaction control, the transaction concurrent processing performance and the database response efficiency are remarkably improved, and the expansion capability and stability of the white list synchronization system in a complex business environment are also improved.

The invention discloses a model performance test method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence. The theoretical maximum lexical throughput of a target large language model is calculated based on the video memory bandwidth of a graphics processor, the model parameter quantity, the byte number corresponding to the quantization precision and the video memory bandwidth utilization rate; meanwhile, the benchmark performance throughput is obtained, a theoretical corresponding first concurrency number is calculated in combination with the theoretical maximum lexical unit throughput and the concurrency competition loss coefficient, then the model test is executed based on the first concurrency number to obtain the actual maximum lexical unit throughput and a corresponding second concurrency number, and a model performance test result is generated. The problems that in the prior art, due to the fact that manual testing is conducted depending on manual intervention, a continuous approaching attempt mode is adopted, a reasonable test starting point is not deduced in combination with hardware core bottlenecks and key parameters, evaluation is time-consuming and labor-consuming, the result is prone to being affected by artificial factors, and accuracy and consistency are poor can be solved.

The invention provides a file system client kernel mode and user mode communication method based on asynchronous communication. According to the asynchronous communication-based file system client kernel mode and user mode communication method provided by the embodiment of the invention, the context switching overhead of communication between the user mode and the kernel mode can be reduced, the data transmission throughput is improved, the resource utilization rate is optimized through dynamic queue management, and the problem of performance bottleneck in a high-concurrency scene is effectively solved.

The invention discloses a heterogeneous computing scheduling method and device based on a proxy thread, computer equipment and a storage medium, the scheduling method comprises the steps that a working thread group and the proxy thread are created, the working thread group comprises at least one working thread, and a lockless communication queue is established to connect the working thread group and the proxy thread; in response to the received to-be-processed task of the execution unit, the working thread submits an operation request of the to-be-processed task to the proxy thread through the lock-free communication queue; in response to successful submission of the operation request, performing local data calculation by the working thread, and entering dormancy if the local data calculation is completed; in response to the operation request received by the proxy thread, the proxy thread submits the operation request to an execution unit and polls whether the to-be-processed task is processed or not; in response to completion of processing of the to-be-processed task, the proxy thread wakes up a corresponding working thread through a callback function and returns a processing result; by means of the method, the high concurrency performance and the compatibility of heterogeneous equipment can be remarkably improved.

The invention provides a method, a device and equipment for realizing a high-concurrency extensible hash table (hash table) in a multi-thread environment and a medium. The implementation content of the method comprises two parts: 1) realizing high concurrency by a hash table fine-grained lock: realizing by adding the fine-grained lock to the hash table, locking each bucket of a bucket array of the hash table, and improving the concurrency of accessing the hash table in a multi-thread environment; 2) expandability of the hash table double-bucket array structure: two bucket arrays are used, the original bucket array is used for storing hash table elements in a non-expansion state, the expansion bucket array is used for storing newly added hash table elements and elements migrated from the original bucket array in an expansion state, the expansion bucket array is used as the original bucket array in an expansion state after migration is completed, and the expansion bucket array is used as the original bucket array; according to the method, the problem of realizing the high-concurrency extensible hash table in the multi-thread environment is solved, the high-concurrency access of the hash table in the multi-thread environment is ensured, the expandability of the hash table in the multi-thread environment is also ensured, the high concurrency and the expandability are carried out in parallel without conflict, and the hash table can adapt to the change of the data scale.

The invention discloses a multi-modal KV cache retrieval method and system based on a hybrid architecture, relates to the technical field of data processing, and aims to solve the technical problem that in the prior art, due to the adoption of a full-online computing architecture and lack of a unified cross-modal representation framework, the computing efficiency and the modal fusion effect are difficult to consider at the same time. By constructing a hybrid processing architecture of offline pre-calculation and online processing, multi-modal data is subjected to unified fragmentation coding and KV cache and semantic fingerprints of the multi-modal data are pre-calculated in an offline stage, and cache fragments are intelligently assembled and position codes are dynamically remapped based on a user query intention in an online stage; therefore, online repeated calculation of multi-modal content is fundamentally avoided, coherent alignment and efficient fusion of cross-modal semantics are achieved, the real-time response capability, the cache reuse rate and the multi-modal generation quality of the system are remarkably improved, and high-concurrency scenes can be dynamically adapted.

The invention relates to the technical field of e-commerce, and discloses an e-commerce customer service processing system with intelligent quality inspection and high-concurrency simulation capabilities. According to the invention, millisecond index calculation and real-time alarm of full customer service dialogues are realized through a bypass monitoring technology, a traditional lagging mode of post sampling inspection is changed, and management response is converted from passive remedy to active intervention; a high-concurrency pressure simulation module reproduces a business scene in an e-commerce peak period by simulating a script of a real user behavior and a distributed cluster, and a real basis is provided for system capacity planning and stability guarantee; the integrated intelligent verbal skill evaluation module deeply analyzes the dialogue quality from multiple dimensions such as semantics, compliance and emotional change based on a natural language processing technology, and generates an evaluation report with guidance, so that the professional level of customer service is improved; and the service quality, the operation robustness and the management intelligence level of the e-commerce customer service system are improved.

The invention discloses a self-adaptive CPU (central processing unit) priority scheduling method based on near-end strategy optimization, which comprises the following steps of: firstly, establishing a task scheduling model in a simulation environment, performing matrix processing on a current task queue state and a task characteristic into an environment state for input, and extracting a task sequence time sequence characteristic by introducing a gating circulation unit; and respectively outputting task priority strategy distribution and state value estimation by using a dual-network architecture of PPO. In the training process, a course learning mechanism is adopted to gradually transit from a short task load scene to a complex mixed load. During operation, the trained scheduling agent is deployed to an operating system kernel scheduler, the priority of each task is output in real time according to the current state, and a rapid scheduling decision is realized by means of a priority heap. Through a multi-target reward function, the intelligent agent is guided to optimize the system throughput, the task average response time and the hunger prevention index at the same time, and extreme unfair scheduling is avoided. Experiments show that the method shows relatively high performance, stability and robustness in heterogeneous task, high concurrency and long-tail load scenes, and the system resource utilization rate and the user experience are effectively improved.

The invention discloses an RDMA asynchronous communication optimization method and system based on a lock-free queue, a medium and a processor, and relates to the technical field of remote communication. The method comprises the following steps: constructing a lock-free annular buffer area at an edge node, registering the lock-free annular buffer area as an RDMA memory area, and configuring a queue and a thread pool; the collection thread concurrently writes data, and the RDMA submission thread asynchronously completes remote transmission based on a buffer area state; and the queue processing thread performs closed-loop linkage transmission and buffer area states through'batch polling-result analysis-state synchronization-exception processing ', and dynamically adjusts the buffer area and queue parameter optimization performance at the same time. The problems that an existing RDMA scheme is poor in thread cooperation, weak in resource adaptation, not timely in state linkage and the like are solved, transmission delay and CPU overhead are greatly reduced, communication stability and the resource utilization rate are improved, and the method is suitable for edge computing and other high-concurrency data interaction scenes.

The invention relates to the technical field of computers, and discloses an equipment protocol adaptive analysis and instruction scheduling method for an intelligent central control system, and the method comprises the steps: obtaining an original communication data flow of heterogeneous equipment, and extracting a protocol feature fingerprint to recognize a protocol type; calling a corresponding pluggable protocol parser to generate a standardized instruction object; analyzing instruction semantics and dynamically calculating priorities in combination with a system load; and performing non-blocking scheduling and execution monitoring on the instruction based on a resource token bucket mechanism. The system comprises a data acquisition module, a protocol identification module, a self-adaptive analysis module, a semantic analysis module, a priority calculation module, an instruction sorting module, a token management module, a scheduling execution module, an execution monitoring module and a response generation module. According to the method, through protocol self-learning, dynamic priority quantification and multi-dimensional resource isolation scheduling, the response certainty, expansibility and operation stability of the system in a high-concurrency scene are remarkably improved.

The invention particularly relates to a task scheduling method and system based on a distributed scheduling framework, and relates to the technical field of distributed computing and task scheduling. The resource coordinator is connected with a conflict detection module; a conflict resolution arbitration module; and a final consistency state synchronization module. According to the invention, the lock-free design of the optimistic scheduling decision module and the local cache mechanism break through the dependence of the traditional scheduling on the global real-time consistent state, and realize the top-speed decision in the high-concurrency scene; the local cache with timeliness deviation adopts a hierarchical index structure and a dual-mode updating mechanism, so that a scheduler is supported to complete calculation only by depending on local data while the cache freshness and the updating overhead are balanced, cross-node real-time communication is not needed, and the decision delay is lower.

The invention discloses a multi-modal self-adaptive online shopping comment authenticity and score credibility evaluation system, which belongs to the technical field of online shopping comment analysis and comprises an enhanced text semantic understanding module, an image authenticity verification module, a user behavior deep modeling module, a self-adaptive weight distribution module and a two-dimensional prediction module. According to the multi-modal self-adaptive online shopping comment authenticity and score credibility evaluation system, the false comment recognition capability is greatly improved, the misjudgment rate is effectively reduced, comment authenticity and score two-dimensional evaluation is achieved, the multi-modal fusion effect is better than that of simple feature splicing, high-concurrency processing is supported, complex scenes can be covered, and the online shopping comment authenticity and score credibility evaluation method is suitable for large-scale popularization and application. And the engineering practicability is high.

The invention discloses an LLM-DoS attack protection method based on a multi-level defense strategy and a related device, and belongs to the field of artificial intelligence security. According to the method, denial of service attacks aiming at a large language model are effectively prevented through a three-layer defense strategy: firstly, dynamic frequency control is carried out on an API request, a three-stage rate limiting system is established, a load-aware dynamic adjustment algorithm is introduced, and when the system load is too high, the quota is automatically adjusted; secondly, constructing an input perception classifier by adopting a lightweight Transform model, breaking through context limitation in combination with a random fragment compression and length penalty strategy, and realizing hierarchical interception of attack requests through a harmfulness scoring function; and finally, a request hash mapping and streaming response multiplexing technology is implemented at a server side, and real-time detection and response multiplexing are performed on repeated high-concurrency attack requests, so that consumption of computing resources is reduced. According to the method, the security and availability of the large language model service can be effectively improved, and the influence of DoS attacks on the system is reduced.

The invention relates to the technical field of process orchestration, and discloses an automatic orchestration system and implementation method based on event driving and context management, and the system comprises a model orchestration module which receives an external request through an OpenAPI, carries out the model packaging based on namespace attributes, and abstracts the workflow execution capability into a configurable model entity; the workflow engine module is used for providing a dynamic arrangement and execution mechanism based on a directed graph structure and carrying out unified context management; the parameter configuration module is used for constructing a global data constraint and management mechanism of a parameter-result double-layer model, and establishing a data mapping relation between an execution layer and a display layer of the process; and the data source management module uniformly manages and configures the external service capability units which can be called by the nodes in the workflow. According to the method, asynchronous, self-driven and distributed parallel execution of the workflow nodes can be realized, the operation efficiency in a high-concurrency scene is improved, and organic unification of performance, stability and expansibility is realized.

The invention discloses a dynamic interface implementation method based on a JavaSpringBoot framework, which relates to the technical field of project development and comprises the following steps: shielding SpringBoot default mapping; initializing a dynamic rule engine, and loading and caching an interface rule; the records meeting the enabling and version conditions are constructed into routing objects; constructing a dynamic routing directory, and dynamically registering and binding a routing object and the processing flow template; the user-defined entry agent intercepts an HTTP (Hyper Text Transport Protocol) request, submits the context of the request to the DynamicRouteCatalog, and performs efficient matching; and uniformly packaging the response data into a JSON format. Through cooperative work of the dynamic rule engine, the dynamic routing manager and the responsibility chain execution framework, interface dynamic registration, high-performance matching, multi-version parallel and online switching, pluggable business process and end-to-end observability are realized on the basis of ensuring the analysis capability of a SpringBoot native container; the flexibility and the maintainability of the system are improved, and the stability and the safety in a high-concurrency scene are also considered.

The invention relates to the technical field of large language models, in particular to a high-concurrency large language model high-speed reasoning deployment method, which comprises the following steps of: extracting a weight coefficient corresponding to a user identity identifier, an emergency degree numerical value mapped by a request type and a resource occupation value converted by an estimated calculation amount according to the user identity, the request type and the estimated calculation amount; according to the method, the dynamic priority is generated by performing comprehensive operation on the user identity, the request type and the estimated calculation amount, so that differentiated services for reasoning tasks are realized, interactive requests with high urgency degree can bypass batch processing tasks with long time consumption, the response delay and delay jitter of key services are reduced, and the user experience is improved. Meanwhile, according to the complexity of the request text and the geographic coordinates of the user, the task is intelligently routed to the model node with the most suitable scale in the distributed network, so that the wide area network transmission delay is greatly reduced through edge processing, and the computing power waste caused by using a super-large-scale model to process the simple task is also avoided.

The embodiment of the invention discloses a multi-engine task processing system and method, electronic equipment and a readable storage medium, and relates to the technical field of computers. According to the multi-engine task processing system provided by the embodiment of the invention, a plurality of service clusters can be configured to execute the task processing instructions corresponding to different instance identifiers, so that a task allocation process and a task execution process can be decoupled, and the same task processing instruction is executed by the same target service cluster as far as possible; and the same instruction is prevented from being processed across multiple databases. Due to the fact that the dependency relationship does not exist between the service clusters and the process engines in the service clusters, a user can randomly increase or reduce the service clusters and the process engines in the multi-engine task processing system, the problems that the bearing capacity of the system is insufficient, the transformation cost is high, and capacity expansion is difficult are solved, and the user experience is improved. And meanwhile, the system has the capabilities of high concurrency, large capacity, high stability and high expandability.

The invention relates to the technical field of artificial intelligence infrastructure, in particular to a large-model high-concurrency reasoning storage hierarchical acceleration system, which comprises an access popularity acquisition module, a pressure analysis module, a migration execution module and a heterogeneous storage pool, the access popularity acquisition module is used for acquiring the access frequency A and the access delay D of model parameters in real time. The effects of sensing system pressure in real time and accurately triggering migration are achieved by arranging the access popularity acquisition module and the pressure analysis module, the access popularity acquisition module continuously monitors the access frequency and delay of model parameters, and the pressure analysis module calculates and stores a pressure index based on a historical peak value and a dynamic threshold value. When the index exceeds the preset threshold value, migration operation is triggered immediately, the problem that delay exceeds the standard due to storage I / O bottleneck in the financial transaction peak period is solved, the system can still keep millisecond-level response under tens of thousands of concurrent requests per second, and risk misinformation and missing report caused by delay jitter are avoided.

The invention discloses a management system for an integrated circuit test, and relates to the technical field of integrated circuit test management, and the system comprises a task scheduling module which is used for receiving a plurality of test task requests, and generating a test task scheduling sequence based on the priority parameter of each test task, the current state of a test resource, and a historical execution result; and the resource coordination module is used for acquiring the running states of the plurality of test devices, executing resource allocation operation according to the test task scheduling sequence, and generating a coordination abnormal event if resource conflict or scheduling failure is detected in the execution process. According to the invention, a dependency graph between test equipment and bottom hardware resources is constructed through the resource coordination module, and accurate modeling of a resource mutual exclusion relationship, concurrent capacity and conflict risk is supported, so that resource conflicts are pre-judged before scheduling, and the problems of resource scrambling and deadlock are effectively avoided.

The invention discloses an integrated design management system with an automatic registration communication agent engine and a method thereof, and relates to the technical field of software integrated design simulation. The method has a heterogeneous integration breakthrough, the five communication modes are matched with the software without the API / command line / file, different heterogeneous software can support one communication mode, and the integration cost is remarkably reduced; dynamic expansibility is achieved, a newly added software module only needs to deploy a proxy engine and configure registration, and zero-shutdown upgrading of the platform is achieved; high concurrency reliability is achieved, resource conflicts are solved for an instance mechanism, and parallel task efficiency is improved; and full-process automation is achieved, and the cross-software design process execution time is obviously shortened.