1246 results about "Cross-platform" patented technology

Systems and methods for integrating generative artificial intelligence (AI) within Software-as-a-Service (SaaS) platforms to automate data operations, synchronize cross-platform workflows, and enable intent-based interactions. A platform displays table structures of items and characteristics linked to a common objective, provides input interfaces, and enrolls AI agents as credentialed users with read / write privileges. The system prompts agents with column types, structural relations, and role profiles to generate and execute editing instructions that progress workflow objectives, detect missing or inconsistent data, and notify users or request information as needed. Hierarchical access schemes permit multiple agent instances with inherited privileges and resource limits managed through an AI center. Agents can operate as autonomous team members, analyze outputs, and support natural-language explanation sessions. Additional embodiments coordinate inter-service updates, maintain deviation detection tools, and construct tailored products and platform elements. These capabilities improve robust automation, decision support, and operational efficiency in complex SaaS environments.

The present disclosure describes systems and methods for detecting and preventing data misconfigurations within a security-focused data fabric platform. The system integrates an advanced script migration engine designed to streamline the translation of security rules and scripts across different scripting languages while ensuring alignment with the fabric's unified schema. The method involves receiving inputs from data sources, mapping these inputs to entities of a target schema, monitoring real-time data changes, and simulating impacts on operational dependencies to detect misconfigurations proactively. Leveraging AI-driven mechanisms, including Large Language Models (LLMs), the system dynamically identifies breaking changes in third-party data streams, issues alerts, and provides suggested fixes. The script migration engine further enhances the platform's functionality by automating cross-platform script translations and enabling faster onboarding of security tools. Together, these innovations ensure scalable, accurate, and resilient integration and management of security data across heterogeneous sources, strengthening operational integrity and minimizing security risks.

The invention discloses an electric power communication network visual operation and maintenance method based on digital twinning, and the method comprises the steps: carrying out the coupling mapping of a global data mirror image and multiple sources, collecting data through a reconfigurable sensing array, and outputting a three-domain digital mirror image through time alignment; semantic topology reconstruction is carried out, and a dynamically growing semantic topology is generated by using a graph semantic engine; based on explainable causal chain fault tracing, an event-causal-countermeasure knowledge network is constructed; performing multi-target balancing operation and maintenance decision making, and screening an optimal strategy by using a three-dimensional Pareto model; immersive visualization and interactive intervention are performed, and a cross-platform engine is injected to realize multi-dimensional display. According to the method, through multi-source data accurate mapping, topology dynamic adaptation, causal interpretable traceability and scientific decision making, the problems of data islands, topology lagging and low decision making efficiency in existing operation and maintenance are solved, and the operation and maintenance accuracy and efficiency of the electric power communication network are improved.

Systems and methods for integrating generative artificial intelligence (AI) within Software-as-a-Service (SaaS) platforms to automate data operations, synchronize cross-platform workflows, and enable intent-based interactions. A platform displays table structures of items and characteristics linked to a common objective, provides input interfaces, and enrolls AI agents as credentialed users with read / write privileges. The system prompts agents with column types, structural relations, and role profiles to generate and execute editing instructions that progress workflow objectives, detect missing or inconsistent data, and notify users or request information as needed. Hierarchical access schemes permit multiple agent instances with inherited privileges and resource limits managed through an AI center. Agents can operate as autonomous team members, analyze outputs, and support natural-language explanation sessions. Additional embodiments coordinate inter-service updates, maintain deviation detection tools, and construct tailored products and platform elements. These capabilities improve robust automation, decision support, and operational efficiency in complex SaaS environments.

The invention discloses a cross-platform virtual-real fusion scene construction method and system based on AI space calculation, and relates to the technical field of artificial intelligence and space calculation, and the method comprises the steps: carrying out the multi-scale feature fusion based on a received cross-modal conversion instruction set, and generating an initial image sequence; carrying out implicit field coding on a target object by combining a three-dimensional reconstruction algorithm to obtain an initial parameterized model; performing space-time alignment on the multi-view video stream, loading a digital scene asset package in combination with physical sensing data and a preset spatial index structure, and establishing a bidirectional data channel between a virtual scene and a physical sensor; performing rendering and illumination parameter adjustment on the initial parameterized model to obtain an optimized parameter model; performing differential coding processing on the optimization parameter model to obtain a target virtual-real scene fusion model; and distributing the target virtual-real scene fusion model to a preset terminal. The invention provides a virtual-real fusion construction method for end-to-end collaborative optimization, which is suitable for cross-platform live broadcast or dynamic interaction scenes.

The invention discloses a multi-platform-oriented intelligent interface adaptation and rendering optimization method and system, and belongs to the technical field of interface rendering. The method comprises the following steps: firstly, acquiring and analyzing interface description information, and extracting hierarchical structures and constraint relationships of interface elements to obtain abstract description features; performing adaptive layout mapping based on the environment characteristic parameters of the target platform, and dynamically adjusting space occupation and display priorities under the constraint of keeping the relative position relationship of interface elements unchanged to obtain a layout scheme after platform adaptation; determining resource consumption nodes according to interface element distribution characteristics, and determining a layered rendering strategy by analyzing visibility states and updating frequency characteristics; applying the layout scheme and the rendering strategy to a rendering execution process to generate output; and collecting performance feedback data to adaptively update a space occupation and rendering strategy. According to the method and the device, automatic adaptation and rendering performance optimization of the cross-platform interface are realized, and the multi-platform interface rendering efficiency and the user experience are improved.

The invention discloses a ground engineering construction quality supervision digital delivery system, which relates to the technical field of engineering supervision, and comprises the steps of generation and multi-source data checking, activity record structuring and anti-verification before hiding, space-time reference unification and point cloud fusion playback, rule checking and differential rectification, and object-level marshalling delivery and asset authority management. According to the method, a unified data pool, activities, events and evidence chains are constructed through object codes to achieve time-space consistent association, image, point cloud and detection consistency check is conducted before hiding, blocking difference and unified reference fusion point cloud are generated, indexes support three-dimensional playback, rule base batch check is conducted, and issuing rectification is conducted. And the object-level delivery list and fingerprints support cross-platform identification and auditing to form a traceable link.

The invention discloses a dynamic security authentication method for cross-platform information system integration, and relates to the technical field of cross-platform dynamic authentication. A non-tampering identity trust chain is established through a block chain consensus algorithm, the problems of single-point fault and expansibility of centralized identity management are solved, cross-platform unified identity verification is realized, the problem that multi-factor authentication lacks intelligent risk assessment is solved through intelligent contract automatic verification and user behavior analysis, threats can be dynamically responded, and the user experience is improved. The authority is dynamically adjusted based on the risk level, and a real-time access control decision engine is combined, so that the problem of response lag of traditional access control is solved, accurate authority control is realized, and finally, a continuously optimized security authentication mechanism and a unified and coordinated cross-platform security protection system are formed.

The invention relates to the technical field of computer data processing, and discloses an automatic format conversion and incremental synchronization method for cross-platform heterogeneous document data. The method comprises the following steps: capturing an atomic data change event from a source system transaction log; aggregating into logic transaction units according to the transaction identifiers; converting into a unified intermediate normal form; generating a target system operation instruction set based on the metadata mapping rule; the synchronization sites are executed and persisted in a transactional manner. According to the method, through log-level capture and transactional synchronization, data integrity, sequence and high consistency are ensured, and efficient and reliable data synchronization between heterogeneous systems is supported.

The invention provides a simulation scene construction and simulation method and system for a large-scale unmanned cluster, and relates to the technical field of unmanned system simulation. The method comprises the steps of modeling a target task based on execution logic for the target task of the large-scale unmanned cluster to obtain an execution structure; decoupling the target task into a plurality of weak coupling subsystems based on the execution structure, and constructing a parallel simulation environment for the target task; based on the execution function category of the target task, constructing a bus interface of a corresponding category; constructing an intelligent algorithm plug-in corresponding to the execution function category based on the bus interface of each category; integrating the intelligent algorithm plug-in into the execution structure of the target task to form an execution model of the target task; and deploying the execution model to a parallel simulation environment to obtain a simulation scene of the target task. The problems that in large-scale unmanned cluster complex task simulation, the calculated amount is large, real-time simulation cannot be achieved, and the simulation accuracy and effect of cross-platform complex tasks are poor are solved.

The invention discloses an intelligent monitoring method for a hydrogeological environment, and the method comprises the steps: 1, constructing a space-air-ground integrated sensing network, and dynamically adjusting the monitoring frequency through a self-adaptive sampling strategy; 2, developing cross-platform data middleware, realizing conversion from multi-protocol data to a WaterML 2.0 standard, constructing an anomaly detection model in combination with a deep residual network, and correcting regional parameter deviation; 3, designing a hybrid fusion architecture, processing time sequence data by using an improved Transform at a bottom layer to capture long-term dependence, constructing a graph neural network at a top layer to fuse spatial connectivity, and outputting a prediction result with a confidence interval through an attention mechanism and a Bayesian network; step 4, establishing an edge-cloud hierarchical computing system, deploying lightweight model real-time early warning at an edge end, integrating complex models such as 3D geological modeling at the cloud end to generate a regional report, and adopting federal learning cooperative training and embedding differential privacy protection; and 5, developing a three-dimensional geological visualization platform and an intelligent decision-making system.

The invention discloses an inference task collaborative scheduling system and method oriented to multiple terminals of a swan gap. The inference task collaborative scheduling system comprises a communication module Broker, a system monitoring module SystemProfilter, a scheduling module Scheduler and an inference task execution module Worker. According to the method, a structured resource state vector is constructed based on an NDK native interface so as to comprehensively represent the real-time availability of equipment; a lightweight MQTT protocol is adopted to support low-overhead and high-robustness cross-terminal state synchronization and task distribution; a comprehensive load scoring mechanism fusing task priorities and dynamic weights is designed, a multi-objective optimization problem based on a non-dominated sorting genetic algorithm (NSGA-II) is introduced, task delay is minimized in a combined mode, terminal loads are balanced, and energy consumption is controlled; meanwhile, the execution time delay is efficiently estimated in combination with a proxy model based on linear regression, and the scheduling overhead caused by real reasoning and calling is avoided; the whole architecture is deeply adaptive to a swan-mong system, and is compatible with an Android platform through modular packaging and unified communication interface design, and efficient, self-adaptive and cross-platform collaborative scheduling oriented to a swan-mong multi-terminal reasoning task is realized for the first time.

The invention discloses an online order full-process automatic processing system and method. The system comprises an order state analysis module, a cross-platform collaborative adaptation module, a resource scheduling planning module, an environment load evaluation module and a task scheduling optimization module. According to the invention, by analyzing the trend of the key time sequence change of the order life cycle, the circulation bottleneck can be identified and the time section exceeding the threshold value can be generated, so that the task sequence is matched with the system load, the scheduling coordination and the response precision are enhanced, the execution capability is dynamically compared to form the optimal distribution instruction, and the cooperation efficiency and the transmission continuity are improved. Based on a utilization rate change identification trend, resource distribution is balanced, scheduling flexibility and controllability are enhanced, resource and energy consumption cooperative adjustment is realized through environment load evaluation, operation stability and environment adaptability are improved, high efficiency and continuous optimization of an order flow are realized, and processing capability and operation toughness of a system under high concurrency are enhanced.

The invention provides a performance testing method and device for a large language model and related equipment. The performance testing method comprises the steps that multiple testing platforms for testing, testing scene configuration parameters and a structured testing data set for testing are determined; on the basis of the test scene configuration parameters and the structured test data set, synchronous constraint parameters are generated and distributed to the multiple test platforms, and then a preset load generator is used for controlling the multiple test platforms to concurrently execute reasoning test tasks about the large language model; and when the test is executed, collecting multiple dimension performance indexes of each test platform in real time for data analysis, and generating a reasoning performance comparison evaluation report of the large language model in the multiple test platforms according to a data analysis result. According to the method, the cross-platform performance evaluation period is greatly shortened, and the waste of computing resources is reduced. Manual operation errors are avoided, comparability of multi-platform performance indexes is guaranteed, and more accurate and reliable multi-platform performance test results can be obtained.

The invention belongs to the technical field of software management, and particularly relates to a cross-platform repair method and system based on a large language model.The method comprises the steps that a cross-platform package manager interface is used for conducting static analysis on a dependency list of a target software project, a cross-platform dependency tree is obtained, and the target software project is repaired based on the cross-platform dependency tree; respectively injecting lightweight monitoring probes into at least two operating system platforms, and collecting dynamic tracking data of each dependency component in the dependency tree; fusing the dependency tree and the dynamic tracking data, and establishing a cross-platform security map comprising a dependency calling edge, a version conflict edge and a platform vulnerability association edge; according to the method, the lightweight monitoring probe is injected into the multi-operating system platform, the loading sequence, the function call sequence and the memory layout difference of the dependent components are dynamically collected, and the cross-platform security map is constructed in combination with the static dependency tree, so that the specific potential safety hazard of the platform can be accurately identified, and the comprehensiveness and the accuracy of cross-platform risk perception are remarkably improved.

The invention relates to the technical field of artificial intelligence and automatic testing, and particularly discloses an AI-based automatic testing method and device. The method comprises the following steps: capturing and recording complete execution historical information in a process of executing a test task by an AI agent, and serializing and storing the complete execution historical information as reusable cache data; before the test is executed, the validity of the cache is judged through a multi-dimensional verification mechanism including data integrity, timeliness, functionality and the like; when the cache verification is passed, a result is quickly obtained based on the cache data playback test process; when cache verification is not passed or execution fails, triggering an AI agent to perform new reasoning and steps to generate and update cache data; and meanwhile, a caching strategy is dynamically adjusted according to test case changes and resource conditions. The device comprises a test executor, an AI agent manager, an intelligent cache manager and a dynamic cache management module, and all the modules work cooperatively to improve the test efficiency, reduce the calling cost of a large language model and enhance the stability of a test result. The method is suitable for Web / APP automatic testing, cross-platform testing, CI / CD process testing and other scenes, the execution efficiency can be remarkably improved, the cost is reduced, and resource utilization is optimized.

The invention discloses a virtual space multi-person interaction synchronous control method oriented to an end-cloud collaborative architecture. The invention relates to a computer graphics and three-dimensional modeling technology, and discloses a cross-format lightweight and geometric consistency maintenance method based on a three-dimensional model. Through format-independent geometric representation and a self-adaptive lightweight strategy, efficient compression and precision maintenance of three-dimensional model cross-format conversion are realized. The method specifically comprises the following steps: performing format analysis and geometric feature extraction on an input model, and establishing a unified internal representation; adaptively selecting a multi-level LOD lightweight strategy based on the complexity of the model; the accuracy of key information is ensured through geometric feature keeping and topology consistency detection; the geometric consistency is dynamically maintained by combining error monitoring and an iterative correction mechanism; and generating a target format lightweight model and carrying out quality verification. According to the method, adaptive precision control, multi-level consistency maintenance and format irrelevant processing are combined, the model size and conversion errors are effectively reduced, and cross-platform compatibility and geometric fidelity are improved. The method can be widely applied to the fields of industrial design, game development, virtual reality and the like.

The invention discloses a debugging system and a debugging method of an RISC-V architecture, and relates to the field of processor debugging, the debugging system comprises a debugging host, a transport layer interface, a debugging module, a debugging logic module in a processor core and a monitoring module, and all the components are in communication connection in sequence. According to the invention, by supporting an RV32 / RV64 double-word-length processor, being compatible with a U / S / M full privilege level operation mode and adapting to various mainstream open-source RISC-V cores and self-defined cores, compared with the existing scheme only supporting a single architecture variant, the method does not need to reconstruct debugging logic for different core types, reduces the core adaptation cost, does not need to customize a debugging instruction or a tool chain process, and has the advantages that the debugging efficiency is improved, and the debugging cost is reduced. Through the register and protocol standardization, the method has high compatibility, and the cross-platform debugging cost is reduced.

The invention relates to the technical field of computer graphics and virtual reality, and discloses a meta-universe social space generation method and system. The method comprises the following steps: acquiring multi-modal input data of a user and constructing an intention vector; extracting social relation characteristics based on the intention vector, and generating a multi-dimensional scene constraint condition; generating a three-dimensional virtual environment and optimizing a topological structure by adopting a generative adversarial network according to a scene constraint condition; and fusing the scene data with the user social behavior data, and outputting a multi-terminal interactive rendering result. The system comprises a data acquisition and intention modeling module, a scene constraint mapping and environment generation module and a fusion rendering and interactive output module. According to the invention, multi-user immersive social space interaction can be realized on the VR head-mounted display, the AR glasses and the mobile terminal, and the method has the advantages of low delay, high simulation degree and cross-platform synchronization.

The invention provides a cross-platform video decoding method and device, computing equipment and a computer readable storage medium, and the method is combined with a factory mode to completely package bottom layer differences of all platform types, and an application layer developer does not need to care about the bottom layer platform differences. The optimal implementation can be automatically selected on different engines and platforms through a uniform API (Application Program Interface); during rendering, a single-frame memory management strategy is used, and only one frame which is currently displayed is reserved in a memory; and in the aspect of performance, the advantages of a multi-thread platform and the parallel computing characteristics of the GPU are fully utilized. According to the embodiment of the invention, through deep fusion of a cross-platform soft decoding architecture, single-frame memory optimization, multi-thread parallel, GPU acceleration and other technologies, perfect balance of cross-platform, high performance and low memory is realized, and the development efficiency of the whole project is improved.

The invention provides a building information model compliance processing method and device based on artificial intelligence, electronic equipment and a storage medium, and the method comprises the steps: analyzing a standard document through a natural language processing model, and constructing a structured compliance knowledge graph containing a forced parameter, a naming rule, a geometric constraint and a data mapping relation; when the components are loaded, geometric feature vectors of the components are extracted, a hierarchical topological graph is modeled and nested, and a digital twin file containing geometric attributes, a parameter list and risk scores is generated; and matching and comparing the archive with the knowledge graph, dynamically generating a processing strategy sequence, and scheduling a geometric optimization and data encapsulation module to execute adaptive processing. Geometric optimization adopts a deep learning driven non-uniform grid simplification algorithm, key region details are reserved, and topological defects are repaired; and the data packaging realizes intelligent matching and binding from the custom parameters to the standard attribute set through semantic mapping. Through the method and the device, the efficiency, the accuracy and the automation level of cross-platform compliance conversion of the building information model can be remarkably improved.

The invention discloses an optimization method, system and device for an audio production test system and a storage medium, and relates to the technical field of audio, and the method comprises the steps: building a multi-level code scanning data return stabilization mechanism, and guaranteeing the uploading reliability of code scanning data in a production test process through a local buffer queue, network state real-time evaluation and an intelligent retry strategy; constructing a multi-version application processor AP compiling adaptation framework, and automatically loading corresponding function libraries and compiling parameters through version automatic identification, compatibility index evaluation and dynamic link library management; a cross-platform compatible work order query interface is constructed, the work order query interface is dynamically rendered through a self-adaptive layout algorithm, a compiling adaptation frame suitable for different AP versions is adopted, dynamic link library management and automatic compiling parameter configuration are combined, the universality and expansibility of a tool are greatly improved, meanwhile, a cross-platform interface self-adaptive rendering technology is adopted, and the working efficiency is improved. Therefore, the work order query tool can provide consistent user experience under multiple operating systems.

The invention provides a heterogeneous database structure dynamic synchronization and fault-tolerant migration method, system and device, and belongs to the technical field of database migration. The method comprises the following steps: detecting a structural difference through combination of active detection and passive triggering; realizing DDL statement conversion of different databases by utilizing AST analysis through a cross-platform DDL converter; defining a migration process by adopting a migration state machine model so as to ensure orderly migration; and a breakpoint resume and consistency guarantee mechanism is utilized to ensure that migration fault tolerance is consistent with data by means of a vernier triple, an intelligent recovery strategy and a bidirectional check protocol. According to the method, the problems of structure synchronization and migration fault tolerance of the heterogeneous database in an environment without native change log support are effectively solved, the automation, high efficiency, stability and reliability of database migration are improved, and the method has wide application value.

The invention provides a cross-platform fusion access method, system and device of equipment and electronic equipment, the method is applied to the technical field of Internet of Things, and the method comprises the following steps: a mobile terminal performs security authentication on target central control equipment; the mobile terminal sends a structured configuration file including the equipment information of the plurality of smart home equipment, the region division rule, the scene mode and the linkage rule to the target central control equipment; the target central control equipment receives and analyzes the structured configuration file, and updates the corresponding smart home equipment according to an analysis result; the target central control equipment receives a control instruction of the cloud platform, converts the control instruction into an internal protocol instruction and then issues the internal protocol instruction so as to control the corresponding smart home equipment to execute operation; the target central control device synchronizes the state information of the smart home device to the cloud platform; and when an upgrading instruction of the cloud platform is received, issuing an upgrading task to execute an upgrading process. According to the method, the real-time performance of remote control of the smart home equipment and the accuracy of state feedback are guaranteed.

The invention discloses a lightweight cross-platform PLC (Programmable Logic Controller) multi-language code generation method, which relates to the field of industrial process control, and firstly provides a unified intermediate data model, and on the basis, a module for converting each PLC language into the unified intermediate data model is realized; on the basis of a standardized JSON data structure, a modularized unified intermediate language conversion chain is further supported, an analyzer and a generator communicate through a JSON interface, a cross-platform conversion path is supported, and unified intermediate language conversion from PLC to JSON to XML to ST to C is completed; the method comprises the following steps of: integrating an open source compiler and runtime, constructing an open and pluggable automatic execution framework, compiling a generated C code into a platform executable file by using an adaptive GCC tool chain aiming at different target platforms, and deploying a program generated by compiling to a soft PLC runtime system supporting multiple platforms. According to the method, a JSON intermediate data structure which is light in weight, unrelated to languages and uniform in structure and a matched conversion framework of the JSON intermediate data structure are constructed.

The invention discloses a cross-platform content generation and distribution method based on a multi-modal AI, and belongs to the technical field of cross-platform content generation and distribution, and the method comprises the steps: carrying out the content analysis and feature extraction of an original material based on a multi-modal AI model, and generating a structured content label and a semantic vector. By combining a vector matching degree formula of target portrait features and platform features, an adaptation strategy is dynamically generated, it is ensured that content not only conforms to platform rules, but also can accurately reach a target group, the conversion rate and user viscosity are finally improved, visual, text and semantic vectors are aligned through a Transform multi-modal fusion model, a cross-modal joint representation vector is generated, and the user experience is improved. And in combination with an adversarial generative network, differentiated variants of the same theme are generated in batches, and a content diversity score mechanism ensures that generated contents are balanced between creativity and compliance.

The invention relates to the technical field of speech synthesis, in particular to a corpus training library cross-platform calling method and system, and the method comprises the steps: obtaining the text content of a to-be-synthesized audio, disassembling the text content to obtain a pause position sequence, selecting a corresponding corpus training library according to a preset language identifier, extracting the pronunciation duration of character phonemes, and calculating the duration of basic phonemes. Text emotion features are recognized through an emotion classification model, a three-dimensional emotion feature vector containing emotion density, emotion variance and distribution entropy is constructed, and a first phoneme adjustment coefficient is determined according to the three-dimensional emotion feature vector to correct basic phoneme duration. And when a difference value exists between the corrected phoneme duration and the target audio duration, carrying out compression processing on the phonemes when the difference value is a positive number, and generating an optimal second phoneme adjustment coefficient sequence and a pause duration sequence by using a genetic algorithm when the difference value is a negative number. According to the invention, the problem of speech speed and pause duration optimization under the preset audio length is solved.

This invention discloses a full lifecycle management system and method for scientific computing programs. The system includes a build environment subsystem and a production environment subsystem. The former provides computer resources for the build process of the scientific computing program throughout its lifecycle, while the latter provides computer resources for the testing and deployment processes. This invention, through a full lifecycle management method for scientific computing programs, operates on corresponding computing resources, encompassing a series of steps including querying, triggering scheduling, build execution, result distribution, and test deployment. It automatically generates the executable file of the scientific computing program and configures its runtime dependencies. Simultaneously, it automatically generates a corresponding description file recording the entire lifecycle process. Furthermore, based on version management of these description files and their sets, it achieves full lifecycle traceability and cross-platform migration and deployment of scientific computing programs in a high-performance computing environment.

The invention discloses a cross-platform session state reconstruction method and system based on event traceability, and relates to the field of cross-platform customer service integration, and the method comprises the steps: introducing a measurable business influence weight for a cross-platform field event through an event formatting mode based on business semantics, and maintaining a cross-platform event sequence in combination with a vector clock; according to the method, the real key events in the business meaning are adaptively selected to generate a state abstract through the time sequence accumulation calculation of the event weights, and snapshot is not carried out based on fixed time or a fixed number, so that the data transmission quantity and the calculation overhead required by state reconstruction are remarkably reduced; in the recovery stage of the client, only the abstract and the increment event after the abstract need to be transmitted, so that the client can still quickly reestablish the state at lower cost in a weak network and low bandwidth environment. Therefore, differential compression and recovery of a cross-platform event traceability semantic level are realized, and session reconstruction efficiency and resource utilization efficiency in a customer service large-scale multi-platform scene are greatly improved.

The invention provides a key value cache scheduling method and device, a data processing method and device, a server and a medium. Relates to the technical field of data processing. The key value cache scheduling method is applied to a cache manager in a server for deploying a large model, and is used for uniformly scheduling cache resources when a heterogeneous accelerator executes large model reasoning. The method comprises the steps of obtaining a first request sent by a heterogeneous accelerator based on to-be-reasoned data, and determining the number of required cache blocks; selecting a plurality of target cache blocks from a preset memory cache region according to the cache block occupation state; and aggregating the logic addresses to generate a key value cache address and sending the key value cache address to the heterogeneous accelerator for accessing the key value data. According to the method, through a multi-level cache division and state awareness scheduling mechanism, the cache resource utilization rate and the cross-platform compatibility are effectively improved, the problems that an existing method is low in resource allocation efficiency and poor in compatibility are solved, and the large model reasoning efficiency and the system stability are remarkably improved.