44 results about "Runtime system" patented technology

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 present disclosure provides a method for managing allocation of compute resources in a distributed database. Each request on every task is allocated a certain number of tokens when it arrives, such as by using a token bucket algorithm. This initial allocation may be the per-request maximum usage permitted in the system. This request is made to a central quota server in the region to coordinate allocations between tasks. As the task runs, the system evaluates how much of the limit the request is using, and adjusts its limit up or down to keep the quota allocation tight on the actual usage of the request. If there aren't enough tokens to keep the request active, the request can be evicted.

The invention discloses a machine learning platform and method based on workflow, electronic equipment and a storage medium, and the platform comprises a management scheduling system, a workflow engine system and an operator runtime system. A user is allowed to construct a visual business process in a dragging and connecting mode, and each component corresponds to a specific AI algorithm processing unit written by Python; the platform supports the realization of multi-node business logic by using an operator concept by referring to a BPMN specification, automatically analyzes a flow chart designed by a user into a directed acyclic graph, converts the directed acyclic graph into an API calling sequence for a Python runtime system, disassembles a complex business system into a multi-branch and multi-step configurable process, and executes local logic by each node to realize multi-node business logic. The whole process is visually arranged, the development threshold is remarkably reduced, and the execution efficiency and the system flexibility are improved.

A human-machine interface (HMI) development and runtime system leverages generative artificial intelligence (AI) to create HMI dashboards or graphical interfaces without the need for manual coding based on natural language prompts submitted by the user, which specify the information the user wishes to see. In one or more embodiments, the system can support industry-specific prompt engineering services that assist a user in generating a customized HMI dashboard that satisfies specified criteria using natural language prompts that describe functional and visual requirements of the dashboard. The system can make use of a generative AI model and associated neural networks to generate suitable dashboards in accordance with functional requirements provided to the system as intuitive natural language inputs (e.g., spoken or written natural language text).

The invention relates to the technical field of compatibility testing, and discloses a multi-platform compatibility automatic testing method, which comprises the following steps of: establishing a three-dimensional heterogeneous association graph of three types of nodes, namely user behavior sequence data, system resource interaction data during application operation and test equipment bottom layer platform feature data through a time sequence alignment algorithm; an enhanced graph neural network fusing a dynamic attention mechanism and time sequence graph convolution accurately identifies a high-risk behavior sequence; constructing an operation atom-parameter matrix-expected result ternary structure case library based on the risk sequence, and deploying an edge-cloud collaborative shadow test architecture to realize millisecond-level preliminary verification and depth test; a backbone network + platform adaptive branch modular design is adopted, and new platform risk identification is adaptively adjusted in combination with a memory replay mechanism, so that the test efficiency and accuracy can be improved, the problems of resource waste and misjudgment in multi-platform compatibility test are effectively solved, and accurate positioning and efficient repair of compatibility problems are realized.

The invention belongs to the field of GPU computing performance testing, and provides a GPU flow scheduling performance measurement method and device.The method comprises the steps that in a pre-established basic execution environment, N null-kernel functions are submitted to a reference flow in sequence, and the reference flow executes the received null-kernel functions and measures the reference execution duration; alternately submitting the N null kernel functions to the first test flow and the second test flow, introducing a cross-flow synchronization event, and measuring the total execution duration; and according to the reference execution duration and the total execution duration, calculating to obtain synchronization time consumption between the streams. According to the method, the influence of a tracking tool and the like on the performance of the measured object is eliminated, the method has obvious advantages in accuracy and stability, high-precision and low-interference GPU scheduling performance measurement is realized, and a quantitative basis is provided for performance optimization of a system during GPU driving and operation.

The invention discloses a component arrangement method, device and equipment of a runtime system and a storage medium, relates to the technical field of component arrangement, and discloses the component arrangement method of the runtime system, which comprises the following steps: acquiring configuration file information of a to-be-arranged component in the runtime system, the configuration file information comprises a dependency interface and a provision interface of the to-be-arranged component; and arranging the to-be-arranged component according to the dependency interface and the provision interface to obtain a component dependency relationship network so as to realize the function of the runtime system based on the component dependency relationship network. According to the invention, the system expansibility during operation is improved.

The invention discloses a multi-operator coarse-grained parallel scheduling method based on a heterogeneous data stream architecture, which belongs to the field of runtime systems, and comprises the following steps of: dividing a computing load of an operator with in-degree of 0 in a computing graph to be executed into a plurality of sub-tasks Task and packaging the sub-tasks into independent Task objects; constructing four priority queues which are respectively used for storing Task objects which have different preferences on four functional parts in the processing unit, putting index Task objects of operators into the corresponding priority queues according to the preferences of the operators on the functional parts and the number of instructions of the operators, and sorting the index Task objects, k (K < = 4) Tasks with complementary resource requirements are selected from the four priority queues to form a new composite operator, and the new composite operator is executed by the processing unit array; according to the method, the new operator is generated by identifying the preference of the operator function part and dynamically combining the Task, so that the utilization rate of the internal function part of the PE can be fully improved, and the operation efficiency of the whole data flow program is accelerated.

Systems, apparatuses, and methods for updating and optimizing task scheduling policies are disclosed. A new policy is obtained and updated at runtime by a client based on a server analyzing a wide spectrum of telemetry data on a relatively long time scale. Instead of only looking at the telemetry data from the client's execution of tasks for the previous frame, the server analyzes the execution times of tasks for multiple previous frames so as to determine a more optimal policy for subsequent frames. This mechanism enables making a more informed task scheduling policy decision as well as customizing the policy per application, game, and user without requiring a driver update. Also, this mechanism facilitates improved load balancing across the various processing engines, each of which has their own task queues. The improved load balancing is achieved by analyzing the telemetry data including resource utilization statistics for the different processing engines.

Techniques are provided for resource scheduling of multiple application types in a heterogeneous endpoint device. One method comprises monitoring an execution of applications on a heterogeneous endpoint device, wherein the applications are of different application types and the heterogeneous endpoint device comprises multiple application runtime systems each supporting a different one of the different application types; and initiating an adjustment of an allocation of resources, provided by the heterogeneous endpoint device, assigned to at least one of the applications based on: (i) a current resource utilization of one or more of the applications, (ii) a priority assigned to one or more of the applications and / or (iii) a resource threshold value assigned to one or more of the applications. A global scheduling engine may: (i) monitor multiple endpoint devices and / or (ii) deploy one or more applications to at least one endpoint device based on resource consumption information from the endpoint devices.

The present application belongs to the technical field of embedded processor firmware, and particularly relates to an efficient firmware running system for a neural network processor, aiming to solve the problems of slow firmware deployment speed, large occupied space and low processing efficiency of files generated after compilation by a neural network compiler of the existing neural network processor. The system comprises: a file preprocessing unit configured to obtain files generated after compilation by a neural network compiler and preprocess the files to obtain preprocessed files; an embedded hardware platform configured to store the preprocessed files to a set memory address; and an efficient firmware configured to read and parse the preprocessed files, obtain operator stream files corresponding to a neural network model, and sequentially execute each operator through a pre-built operator execution efficient optimization method until a complete calculation of the neural network model is completed. The present application improves the processing efficiency of files generated after compilation by a neural network compiler, improves the firmware deployment speed, and reduces the occupied space.

This disclosure provides a virtual machine runtime system, method, processor, and electronic device, relating to the field of virtual machine technology. The system includes: a virtual machine monitor, which runs at a first exception level and is used to create virtual machines using a virtualization environment provided by a microkernel, and to handle interrupt events associated with the virtual machines according to notifications from the microkernel; a virtual machine, which runs at a second exception level; and a microkernel, which runs at a third exception level and is used to provide the necessary virtualization environment for the virtual machine monitor to create the virtual machines, and to intercept interrupt events associated with the virtual machines and notify the virtual machine monitor to handle the interrupt events; the privilege levels of the first exception level, the second exception level, and the third exception level increase sequentially. This disclosure aims to solve the problems of centralized privileges and high resource consumption in existing virtual machine runtime systems.

The invention discloses a method and an electronic device for managing an executable program. The method comprises the steps that in response to first mounting of a system partition, the execution permission of a trusted partition is set to be executable, the read-write permission of the trusted partition is set to be read-only, so that an executable partition is obtained, and a trusted execution program and a trusted dynamic link library on which the trusted execution program depends are written in the trusted partition; setting execution permissions of other partitions except the trusted partition to be non-executable so as to obtain non-executable partitions; and forbidding to modify the read-write permission of the executable partition, and forbidding to modify the execution permission of the non-executable partition. According to the method, under the condition that system resources during operation are not consumed, execution of non-trusted programs can be effectively limited, it is ensured that only trusted programs can be executed in a system, and meanwhile the management process of executable programs is simplified.

The invention relates to the technical field of industrial control system security and industrial edge computing, and discloses a domestic industrial control security protection system with edge computing capability, which comprises a trusted state transition map generation module, a map embedding module, a map driving micro-isolation module, a mimicry verification module and a cloud edge collaboration module. The system firstly analyzes a control logic program of the industrial control equipment to construct a trusted state transition map comprising a security state, a legal instruction, a parameter space and a time sequence constraint, and the trusted state transition map and verification logic are solidified in a trusted execution environment together. During operation, the system performs micro-isolation on the real-time industrial control instruction by referring to the atlas. According to the method, an industrial control mechanism is combined with mimicry defense and trusted computing, the problems that a defense strategy of a traditional protection technology is fixed, and unknown attacks and time sequence cheating are difficult to resist are solved, and the edge protection capacity which is based on an endogenous mechanism, safe and dynamically evolved is achieved.

The present disclosure provides a method for managing allocation of compute resources in a distributed database. Each request on every task is allocated a certain number of tokens when it arrives, such as by using a token bucket algorithm. This initial allocation may be the per-request maximum usage permitted in the system. This request is made to a central quota server in the region to coordinate allocations between tasks. As the task runs, the system evaluates how much of the limit the request is using, and adjusts its limit up or down to keep the quota allocation tight on the actual usage of the request. If there aren't enough tokens to keep the request active, the request can be evicted.

A memory anomaly detection method includes: sending a startup command to an artificial intelligence (AI) application runtime system to launch the AI ​​application; during the AI ​​application's operation, identifying anomaly operators based on the actual memory access information and memory allocation information of at least one operator among multiple operators; detecting the memory access behavior of the anomaly operators based on their input / output information during the AI ​​application's operation; and obtaining detection results. This method divides the memory anomaly detection process into two stages: delimiting operators and single-operator detection, transforming the entire network problem into a single-operator problem. The entire detection process requires no compiler or hardware support, is independent of source code, and is applicable to scenarios with only binary code, exhibiting high availability. Furthermore, this method transforms the memory pressure of performing memory anomaly detection on the entire network into the memory pressure of the delimiting operator stage within the entire network, minimizing the impact of the detection process on the overall network's memory.

This disclosure provides a PLC program execution system, relating to the field of programmable logic controller (PLC) technology. It includes a runtime system and an execution mechanism. The runtime system stores data and performs network interactions, and has a unified interaction interface. The execution mechanism is connected to the runtime system through the interaction interface and is used to access memory and the network, selecting an implementation method to execute the PLC program. The execution mechanism can be implemented as an interpreted executor, a compiled executor, or a JIT executor. This disclosure, through the execution mechanism in the PLC program execution system, allows for the selection of an implementation method from multiple options to execute the PLC program. This flexible selection of implementation methods improves the flexibility of the PLC program execution system and solves the problem of insufficient flexibility in related technologies where users cannot choose the execution method of the PLC program.

The invention discloses a memory management method of a runtime system, a programmable logic controller and the runtime system, relates to the technical field of programmable logic controller management, and discloses the memory management method of the runtime system, which comprises the following steps: acquiring a memory configuration file when the runtime system is started, the memory configuration file comprises memory configuration information of a memory area in the runtime system under different scenes; and determining a target numbered memory block according to the memory configuration information and preset numbered memory block information, and performing memory management on a power-down retention variable in the memory configuration information according to the target numbered memory block. According to the method, the memory management accuracy of the system during operation is improved.

Systems and methods for generating and executing distributed code. The systems and methods include receiving serial code generated by a large language model (LLM) for vision applications and analyzing the serial code with a trained model to identify code dependencies and detect independent application programming interface (API) calls. The systems and methods further include transforming the serial code by incorporating program semantics that enable concurrent execution of the independent API calls and generating distributed code configured for execution on a container orchestration platform cluster, wherein the distributed code includes service calls that can be understood and executed by a runtime system.

According to some embodiments, systems and methods are provided including receiving a scenario including a plurality of steps; assigning each step to one of: a baseline phase, a bridge phase and a post-upgrade phase, the bridge phase including a transition from a first to a second runtime system; executing an automate for the scenario including a first pause at an end of the baseline phase and a second pause at an end of the bridge phase; initiating, during the bridge phase, the transition of the system from the first to the second runtime system in response to the first pause; resuming execution of the automate for the one or more steps assigned to the bridge phase during the transition; initiating the second pause; completing the transition to the second runtime system; and resuming execution of the automate for the post-upgrade phase. Numerous other aspects are provided.

This invention relates to a runtime server (100) for simultaneously executing multiple runtime systems (101) within an operating system (103) for a data processing device controlling an automated device based on a device control program. The runtime systems (101) are configured to execute the device control program in real time. The runtime server includes at least two runtime systems (101) for executing application modules (105) of the device control program, wherein at least one application module (105) for executing the device control program is installed on each runtime system (101), and each runtime system (101) has a data transmission interface for data transmission between runtime systems (101) and / or between application modules (105). 107), wherein each runtime system (101) has an I / O configuration (109) that defines an allocation between at least one variable of an application module (105) of the runtime system (101) and at least one hardware address of a hardware component (113) of the automation device (112) to be controlled; an I / O interface (111) having at least one I / O input (115) and / or I / O output (117) for exchanging data between at least two runtime systems (101) and the hardware component (113) of the automation device (112); and an I / O mapping intermediate layer (119) in which the I / O configurations (109) of at least two runtime systems (101) are mapped. The invention further relates to a computer program product (200) for executing a runtime server (100).

The present invention provides a heterogeneous system and method for monitoring HMI programs. The heterogeneous system includes a main processor and a coprocessor. The main processor is installed with an HMI program and a sysmgr program. The HMI program is responsible for displaying 3D images. The coprocessor is installed with a screen drawing driver, main-app, responsible for displaying 2D images. By enabling the drawing driver on one core of the heterogeneous system to monitor the HMI application on another core, the present invention not only mitigates the risk of display failure caused by an HMI program anomaly, but also mitigates the risk of display failure caused by system environment anomalies during HMI program execution. This significantly improves the robustness of the HMI program's automatic repair function after anomalies occur, while also reducing the safety risks associated with instrument screen display failure during vehicle operation.

The invention relates to a method for modularly adapting a programmable controller, comprising: providing a basic runtime system; defining unambiguous references in the basic runtime system in a prescribed order (S1, S2, S3; 330, 332, 334; 402, 404, 406, 408, 410, 412, 414); providing at least one function object (100; F1, F2, F3; 320, 322) having one or more methods (104) to be implemented and having at least one function pointer to one or more of the methods, wherein each function pointer is linked with a defined unambiguous reference; and executing at least one of the provided function objects (100; F1, F2, F3; 320, 322) based on the linked unambiguous references.

The purpose of the present application is to provide a method and device for verifying the switching of summer and winter time, which realizes the embedding of the traditional verification logic depending on external test tools and manual intervention into the firmware runtime system of the device, and constructs a closed-loop summer time DST self-verification mechanism with the capabilities of rule analysis, event pre-play, execution monitoring, result comparison and abnormal response. The mechanism does not depend on network connection or external debugging interface, and can still complete the integrity check of the DST switching behavior independently when the device is in a completely offline state, thereby solving the problems of time confusion, data distortion and service interruption caused by the lack of self-checking capability in the prior art.

In an embodiment, a computer stores, in memory or storage, many explanation profiles, many log entries, and definitions of many features that log entries contain. Some features may contain a logic statement such as a database query, and these are specially aggregated based on similarity. Based on the entity specified by an explanation profile, statistics are materialized for some or all features. Statistics calculation may be based on scheduled batches of log entries or a stream of live log entries. At runtime, an inference that is based on a new log entry is received. Based on an entity specified in the new log entry, a particular explanation profile is dynamically selected. Based on the new log entry and statistics of features for the selected explanation profile, a local explanation of the inference is generated. In an embodiment, an explanation text template is used to generate the local explanation.

The application discloses a data flow runtime system for a many-core heterogeneous platform, and relates to the field of data flow programming, which comprises a plurality of runtime subsystems; each runtime subsystem comprises a management unit and a calculation unit group; the management unit is used for receiving tasks and the dependency relationship between the tasks, generating a ready task queue, and sending the tasks meeting the dependency in the ready task queue to the calculation unit group according to a calculation unit state array; the calculation unit group comprises a plurality of calculation threads, and the plurality of calculation threads of the same calculation unit group are mapped to a calculation core array of the many-core heterogeneous platform; the calculation unit group is used for executing the tasks issued by the management unit, and releasing the subsequent dependency of the tasks after the execution is completed. The application designs an efficient data flow runtime system for the many-core architecture, and reduces the complexity of data flow programming and cross-platform transplantation under the many-core heterogeneous platform.

A method includes receiving, by a user interface layer in a client terminal, application code entered by a user, processing, by a client-as-a-service layer in the client terminal, the entered application code, and forwarding the entered application code for storage in a cloud-based repository. The method further includes synchronizing the application code stored in the cache with the application code stored in the cloud-based repository, and performing runtime reconstruction on the runtime system based on the input application code.

A system provides a user interface comprising an application interface and a control interface. The application interface can include multiple interface elements and can be associated with a software application. The control interface can include multiple control elements configured to modify one or more properties of the multiple interface elements of the application interface. While running the software application, the system can receive an input causing a modification to the application interface. The modification can be associated with an existing interface element. In response to the input, the system can determine an instance of the existing interface element in the software application that is running. The system can modify the instance of the existing interface element in the software application that is running in accordance with the input so that executing code of the modified instance of the existing interface element causes the modification to the application interface.

This invention proposes a distributed application runtime system with edge-cloud collaboration. The system includes at least the following components at the device, edge, and cloud levels: a resource proxy; an executor resource pool containing at least one executor, each configured with a corresponding resource proxy and interacting with it; the at least one executor generates computational tasks during runtime; and upon receiving a computational task offloading request, the resource proxy relocates the corresponding computational task execution schedule. This system proactively adapts to real-time changes in application resource requirements, improving the stability of the computing platform's performance and service quality.