260 results about "User state" patented technology

The invention provides a method and system for achieving CUDA call tracking based on an eBPF, and relates to the field of GPU call tracking of the eBPF. The method comprises the following steps: dynamically mounting an eBPF program at an API function entry and an API function exit of a user mode CUDA runtime library through an uprobe technology of the eBPF; the eBPF program captures metadata of the CUDA API calling event in a kernel mode and packages the metadata into a predefined structural body; asynchronously transmitting the structural body data to a user mode through an annular buffer area; and calling a standard function library by a user mode program to load an eBPF program, reading data in the annular buffer area in real time, and completing analysis and visual display of a CUDA calling event. According to the method, the calling parameter, the return value and the nanosecond timestamp are effectively captured, and the observability and the debugging efficiency of the GPU application program are improved.

In various embodiments, systems and methods for generating interfaces including interface elements representative of next-best actions are disclosed. A request for an interface including a set of features representative of a user associated with the request is received and a user state representation including an implicit user state representation and an explicit user state representation is generated based on the set of features and session data for at least one session associated with the user. An action reward value for each of a plurality of candidate actions is generated based on the user state representation and an interface including at least one interface element representative of a candidate action having a highest action reward value is generated.

The invention discloses an operating system containerization kernel compatibility method based on shadow structure mapping, which comprises the following steps of: constructing a multi-dimensional mapping rule base by analyzing the difference of data structures between a container system and a standard system, and creating a shadow structure comprising a data area, a metadata area and an expansion area when the container system runs on a host system; the host system allocates a shadow memory space and a memory pool, establishes mapping between a shadow structure and a physical memory page and bidirectional mapping between the shadow structure and a host structure, intercepts system call of a container application, obtains a target structure and allocates a shadow structure and a host structure memory, and sends the shadow structure and the host structure memory to the host system; according to the method, conversion from the target structure to the host structure is completed according to the multi-dimensional mapping rule base, the host machine completes calling through the host structure, then the calling result is reversely converted into the target structure and returned to the container application, and seamless compatibility of the container system and the host system is achieved under the condition that a user mode program of the container system is not modified.

A method for managing a state of a user includes: receiving a first dataset from a client, in which the user performs an activity using the client; obtaining a second dataset from a database; analyzing the first dataset and the second dataset to generate a unique digital identifier (DI) for the user; analyzing, based on a predetermined threshold, the first dataset and the second dataset to extract relevant data; making a determination that the predetermined threshold is violated; providing, based on the determination, the relevant data and the unique DI to a first infrastructure node (IN); in response to the providing, receiving a recommendation from the first IN to mitigate an issue associated with the user, in which the recommendation is generated for the unique DI; and sending the recommendation to the client to manage the state of the user.

The invention discloses a data zero-copy processing method and system based on an eBPF zero-trust gateway, and belongs to the technical field of computer network security. According to the method, an XDP program is loaded on a network card driving layer, and an AFXDP technology is combined to construct a kernel mode and user mode shared memory pool UMEM; when an original message arrives, an eBPF unit mounted by an XDP program intercepts the message in real time, a tunnel packaging space is reserved in situ in an original memory, and if the head space is insufficient, a new memory page is logically mapped from a UMEM standby buffer pool to achieve extension. Identity fingerprints are generated by extracting message feature vectors, load in-situ encryption is completed in cooperation with a kernel kTLS module, and data are prevented from being returned to a user mode for processing. According to the method, multiple copying and context switching of a kernel-user mode of a traditional SSL VPN are eliminated, the throughput is improved by 2-3 times, the delay is reduced to the microsecond level, the CPU utilization rate is reduced by 40% or above, application layer DDoS attacks are effectively defended, and the method is suitable for 5G edge computing and cloud native zero-trust gateway scenes.

The invention relates to a function operation duration detection and stack automatic collection method and device based on an eBPF technology, and aims to solve the problems that a traditional tool cannot accurately monitor function operation timeout, cross-state stack collection lags and the like. The method comprises the steps that an eBPF program is injected into an objective function (a kernel mode passes through kprobe, and a user mode passes through uprobe) entry, and a thread PID / TID and an entry timestamp are recorded into an eBPF hash table; registering a periodic perf event to trigger timed detection, calculating a function operation time length and comparing the function operation time length with a threshold value; when overtime triggering is carried out, a kernel mode stack and a user mode stack are synchronously collected through bpfgetstackid, and after an event is packaged, the kernel mode stack and the user mode stack are reported to the user mode through bpfperfeedback; and analyzing and displaying the stack in the user mode. The scheme has the advantages of non-return dependency detection (covering a blocking scene), cross-state tracking (kernel / user state function), low-overhead event driving (adapting to a production environment), cross-state stack association (accurately positioning a jamming root), low intrusion, high real-time performance and the like, and the system performance analysis efficiency is effectively improved.

The invention discloses a user behavior analysis feedback method for immersive digital interaction, and relates to the technical field of man-machine interaction, and the method comprises the steps: obtaining interaction state data of a target user in an immersive digital interaction environment, and constructing a user state sequence according to the interaction state data; dividing the user state sequence into a plurality of analysis units according to a preset time length, determining a current behavior mode of the target user according to a state density value in each analysis unit and a state transition value between adjacent analysis units, and generating a feedback control signal corresponding to the current behavior mode; and according to the feedback control signal and the current position of the target user in the immersive digital interaction environment, generating spatial positioning feedback content and rendering the spatial positioning feedback content to the immersive digital interaction environment. According to the method and the device, accurate recognition of the user behavior mode is realized, differentiated spatial positioning feedback is generated according to different behavior modes, and the problem that the user behavior state is difficult to perceive and guide in real time in an immersive environment is solved.

In some aspects, the techniques described herein relate to a method including: generating, by a reinforcement learning engine, a plurality of user states within a simulated 3-dimensional environment; generating, by the reinforcement learning engine and for each of the plurality of user states, a plurality of movement actions, wherein each of the plurality of movement actions place a virtual content object in a corresponding position within the simulated 3-dimensional environment; generating, by the reinforcement learning engine and for each corresponding position of the virtual content object, a reward value, wherein the reward value reflects a relative utility of the corresponding position of the virtual content object; and updating, by the reinforcement learning engine, a placement policy based on the reward value for each corresponding position of the virtual content object.

The invention discloses a large model training dynamic memory management method based on a multilayer hierarchical cache mechanism, and relates to the technical field of computer system architecture and storage. The method is managed on the basis of a dynamic heterogeneous memory unloading system, and comprises the following steps of: in an initial stage of a training task, constructing a user state access path, establishing a TensorID-LBA mapping table, and performing hierarchical caching and threshold presetting; in the training task running stage, the access popularity of each tensor is evaluated in real time; when occupation of the GPU video memory cache layer exceeds a threshold value or cold data is detected, a dynamic migration strategy is triggered, and the low-frequency tensor is unloaded to a CPU memory cache layer or an SSD storage layer; when the tensor access popularity is improved, automatically migrating back to a high-performance layer through a prediction mechanism; in the process, tensor self-adaptive migration is executed by a user mode I / O thread pool. According to the method, the high-performance I / O stack is constructed in the user mode, and the adaptive tensor unloading and hierarchical caching mechanism of the multi-layer heterogeneous memory is combined, so that the universal deployment of the system is realized.

The invention discloses a node distribution method and system for a GPU (Graphics Processing Unit) use process in an NUMA (Non Uniform Memory Access) environment, and the method comprises the following steps: in a kernel mode, capturing an event that the process executes a new program and collecting meta-information of the process through an eBPF program mounted at a system call entry tracking point, and judging whether the process is a target GPU process or not based on the collected meta-information of the process; if the process is the target GPU process, transmitting meta-information of the process to a user mode, and if the process is not the target GPU process, ending and exiting; and for the meta-information transmitted to each target GPU process of the user mode, reading the meta-information of the target GPU process through the user mode daemon process, evaluating each node in the NUMA environment based on a preset node allocation rule, selecting an optimal NUMA node, and binding the target GPU process to a CPU of the optimal NUMA node for execution. The GPU computing efficiency and the resource utilization rate can be improved.

The invention discloses a method for ensuring hard real-time in a Linux user mode based on a multi-core CPU, and belongs to the technical field of embedded systems. According to the method, a Linux kernel is configured to be in a completely preemptable mode, user threads with the number equal to that of CPU kernels are created and bound to different kernels, a real-time scheduling kernel is selected, the thread scheduling strategy of the real-time scheduling kernel is set to be SCHEDFIFO, the priority of the real-time scheduling kernel is equal to that of the lowest-priority soft interrupt, the thread stack space is locked, the real-time kernel is isolated through kernel parameters isolcplus and nohzfull, and the cost of tick is avoided. Finally, the real-time core is exclusively used for executing the real-time task. According to the scheme, the problem that the real-time performance of the Linux user state task is poor due to the fact that a kernel cannot be preempted, scheduling delay, memory page changing, system interference and the like is effectively solved, and extremely low delay and high certainty of user state task response are ensured through multi-level collaborative optimization.

The invention discloses an intelligent desktop management system and a dynamic resource allocation method. The intelligent desktop management system comprises a main control module; a multi-mode sensing module; a resource execution module; a man-machine interaction module; the dynamic resource allocation method comprises the following steps: S1, sensing and fusing multi-source data; s2, performing multi-level identification on a user state and an intention; s3, dynamic resource mapping based on a strategy library; and S4, performing cooperative control and instruction execution. According to the intelligent desktop management system, user states, behaviors and environment data are collected in real time through the multi-mode sensing module, a dynamic resource allocation method is combined, resource requirements are accurately mapped to cooperative control of units such as a displayer, a lighting unit and a power source, the energy allocation unit supporting the USBPD protocol can dynamically adjust power output, and the intelligent desktop management system is high in practicability. And the energy utilization efficiency is maximized.

Provided in the embodiments of the present disclosure are a file processing method, a file system in user space, a device, and a computer program product. The file processing method is applied to a file system in user space, wherein the user state file system comprises a file system process and a file system in user space (fuse) process which is in communication connection with the file system process. The file processing method comprises: a fuse process acquiring a file processing request; the fuse process caching the file processing request, wherein the fuse process comprises a caching request queue used for caching the file processing request; and when a file system process exits, the fuse process determining a request processing state of the file processing request to be a suspension state, such that a file processing link where the fuse process is located maintains a normal state. In the embodiment, when a file system process exits, a fuse process may cache a file processing request, thereby ensuring the normal operation of a user process.

The invention relates to a system calling ptrace-based operating system micro-service security protection system and method, which are characterized in that the running state of micro-service is monitored in real time through calling of a ptrace system in a user state, and dynamic integrity verification is realized in combination with an SM3 hash algorithm. The method comprises the following steps: calculating an SM3 hash value of a code segment of a micro-service when the micro-service is started, storing the SM3 hash value as a static reference, periodically reading memory data of a target process through ptrace in a running process, recalculating a dynamic hash value, and comparing the dynamic hash value with a reference value; if it is detected that the hash values are inconsistent, it is judged that code injection attacks exist, and a defense mechanism is triggered. According to the method, the system stability risk caused by kernel module injection is avoided, meanwhile, real-time interception of tampering attacks during operation is achieved through high-frequency dynamic comparison, the lightweight design enables the method to be suitable for high-reliability scenes such as spaceflight with limited resources, the integrity of a micro-service code segment can be guaranteed, low performance loss of the system can be maintained, and the system reliability is improved. The balance blank between dynamic defense and system stability in the prior art is effectively filled.

The invention discloses a file security level checking method, device, equipment, medium and product based on an API HOOK of a windows operating system, and relates to the field of computer software application, the method comprises the steps that a callback function is registered by utilizing a driving module, when the windows operating system creates a process, a created process ID is sent to a service module in a user mode in the callback function, and when the process is created, the service module in the user mode is used for checking the security level of the file; receiving a service completion message of the service module; in the service module, based on a dll injection mechanism, injecting a dll injection program of the API HOOK module into the memory space of the created process; after the dll injection program is injected, an API HOOK module is utilized to modify an entry address of a target process API, and the entry address points to a self-defined hook function; the target process is the created process; and when the application opens the file corresponding to the target process, calling the security level judgment logic of the hook function, and judging whether the user security level can open the file corresponding to the target process, thereby avoiding the problem of high-density file leakage.

The invention discloses an EtherCAT master station synchronous control method and system based on a microkernel operating system, and belongs to the technical field of industrial automation field bus control. According to the system, a microkernel architecture is adopted, an EtherCAT protocol stack and a universal network protocol stack are deployed as two independent user mode processes, and data interaction is carried out through an inter-process communication and shared memory mechanism provided by a microkernel. According to the method, through a bidirectional dynamic clock compensation mechanism, static compensation in an initialization stage and dynamic compensation in an operation stage of a system are combined; a dynamic task scheduling strategy based on load awareness is adopted, and the task execution sequence is dynamically adjusted according to the CPU utilization rate and the task priority monitored in real time; a hardware redundancy design of double clock sources and double communication links is introduced, and a progressive synchronous recovery strategy is adopted during switching. According to the invention, nanosecond-level synchronization precision and microsecond-level fault switching can be realized, and the method is suitable for industrial control scenes with extremely high requirements on real-time performance and reliability.

Aspects relate to apparatuses and methods for individualized polygraph testing. The apparatus including at least an interface configured to communicate questions to the user, at least a sensor configured to detect biofeedback signals as a function of a biofeedback of a user, wherein the biofeedback is associated with at least an answer to at least a question, and at least a computing device including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to receive the biofeedback signals, generate a user state classifier, train the user state classifier as a function of a user state training set, wherein the user state training set includes biofeedback signals correlated to answers of known veracity, and classifying a biofeedback signal of the biofeedback signals to a user state as a function of the user state classifier.

The invention discloses an information pushing method and device based on user behavior analysis, equipment and a medium. The method comprises the following steps: acquiring a multi-modal data source for user behavior analysis, inputting the multi-modal data source into a target layered spatial-temporal model, and outputting a user state vector; fusing the user behavior instant feature and the user life cycle value feature to construct a target DQN model, and inputting the user state vector into the target DQN model; based on the user activeness and the market intensity, dynamic weights of the user behavior real-time features and the user life cycle value features are adjusted in real time, and the dynamic weights of the user behavior real-time features and the user life cycle value features are used for determining output of a target DQN model; and obtaining an output target function of the target DQN model, and determining at least one target information pushing action from the candidate information pushing actions based on the target function, thereby solving the technical problems of low information pushing efficiency and relatively low flexibility in the prior art.

The invention discloses a user space file system, a file operation method and computing equipment, and belongs to the technical field of computers. The user space file system is applied to the computing device, the computing device comprises a shared memory, the user space file system comprises a kernel module and a user space daemon process, the kernel module runs in a kernel mode, and the user space daemon process runs in a user mode. The kernel module and the user space daemon process can access the shared memory so as to realize bidirectional communication between a user mode and a kernel mode. According to the user space file system, the user mode and the kernel mode can share the same memory, and then messages and data in the memory can be shared, so that frequent switching and data copying between the user mode and the kernel mode can be reduced, the overhead and time delay of file access are reduced, and the performance of the user space file system is improved.

An emotion-aware computing operating system integrates multimodal sensory inputs, stratified memory, cyclehit scoring, and history score values to predict user tasks, orchestrate autonomous cognitive agents, and adapt interface outputs in real time. A prediction module applies cyclehit scoring derived from historical task cycles and weighted history score values to forecast workflows.An orchestration kernel selects and coordinates agents, redistributes subtasks, and negotiates dynamically under cognitive load. A stratified memory fabric maintains ephemeral, situational, and long-term user models for personalization. An adaptive interface layer adjusts informational density and tool availability based on inferred user state. A certification and licensing API enforces agent onboarding, compliance, and monetization policies, requiring registration of performance metrics prior to integration. Embodiments include software, cloud, edge, and robotic platforms, enabling monetizable deployment across healthcare, finance, education, enterprise, and ambient device ecosystems.

The embodiment of the invention discloses a flow information management method and device, equipment and a medium, which can be applied to scenes such as intelligent traffic, auxiliary driving, cloud technology and artificial intelligence. The method comprises the following steps: calling an acquisition program loaded in a kernel mode, then collecting traffic information of traffic transmitted in a traffic access path through the called acquisition program, storing the traffic information in a shared area shared by the kernel mode and a user mode in an operating system, and then calling a reporting program loaded in the user mode, and the traffic information is obtained from the shared area through the called reporting program and reported. According to the technical scheme, collection and reporting of the flow information can be simply, conveniently and accurately realized, and the management reliability of the flow information is high.

The invention provides a GPU performance analysis method and device, electronic equipment, a medium and a product. The method comprises the steps that a kernel mode program responds to a data acquisition instruction triggered by a user mode process, and a target buffer area and a user mode read pointer corresponding to the data acquisition instruction are determined; the user mode reading pointer represents the reading progress of the user mode process for the target buffer area; the kernel mode program compares the user mode read pointer with the kernel mode read pointer and returns a comparison result to the user mode process; the user mode process obtains the target data from the target buffer area according to the comparison result, so that the user mode process performs GPU performance analysis based on the target data; wherein the kernel mode read pointer is used for representing the effective address range of the target buffer area. According to the method, a plurality of performance analysis tools or a plurality of process instances in the same performance analysis tool can be supported to perform concurrent data acquisition and analysis on the buffer area corresponding to the same GPU at the same time, so that the performance analysis efficiency is improved.

The invention discloses an MPSoC-based user mode solid-state storage system, which comprises a software driving module which is arranged in a user mode of an on-chip processor system, realizes reading and writing of a solid-state disk by utilizing a VFIO technology, carries out on-chip processor memory DMA mapping through an SMMU, distributes a continuous programmable logic memory as a buffer area, and transmits the buffer area to the user mode of the on-chip processor system. Frequent switching between a kernel mode and a user mode is avoided, and the read-write efficiency of the solid state disk is improved; and the FPGA hardware module is arranged in the programmable logic part and is used for receiving and analyzing the read-write request from the software driving module, generating a read-write command which can be analyzed by the NVMe host controller, calling the CDMA module to execute data transmission and returning a read-write result to the software driving module. According to the MPSoC-based user mode solid-state storage system, driving is achieved in the user mode, the problems of complexity and low efficiency of kernel mode programming are solved, meanwhile, efficient DMA mapping of the virtual address is achieved through the SMMU, and the flexibility and performance of the system are improved.

The invention belongs to the technical field of task scheduling of a storage system, and discloses a user-mode-oriented storage task self-adaptive scheduling method and system, and a more efficient task processing framework is realized by replacing an original kernel thread-based storage task scheduling scheme with a user-mode coroutine scheduling mechanism. The multi-level priority queues are directly managed in task scheduling, and CPU core binding configuration is carried out, so that the switching delay of a user mode / kernel mode is reduced, and the task execution controllability is improved. A dual-threshold self-adaptive scheduling strategy switching technology is introduced, and a greedy scheduler and a reinforcement learning scheduler are combined, so that the problem of adaptability of a static scheduling strategy in a dynamic load environment is relieved, performance loss caused by scheduling strategy solidification is avoided, and the self-adaptive capability and service quality guarantee of a system under a complex load are improved. Compared with an existing task scheduling method based on a kernel thread, the task scheduling method has the advantages that the overall performance and the resource utilization rate of a storage system can be remarkably improved while the task execution efficiency and the SLA requirement are guaranteed.

Examples are disclosed that relate to computer-based tracking of a process performed by a user. In one example, multi-modal sensor information is received via a plurality of sensors. A world state of a real-world physical environment and a user state in the real-world physical environment are tracked based on the multi-modal sensor information. A process being performed by the user within a working domain is recognized based on the world state and the user state. A current step in the process is detected based on the world state and the user state. Domain-specific instructions directing the user how to perform an expected action are presented via a user interface device. A user action is detected based on the world state and the user state. Based on the user action differing from the expected action, domain-specific guidance to perform the expected action is presented via the user interface device.

The invention relates to the technical field of computer networks, and discloses a DPDK-based high-speed data isolation method, which comprises the following steps of: S1, directly taking over a data packet transceiving function of a network card through a DPDK driver, bypassing a kernel protocol stack of an operating system, and establishing a user mode data channel; s2, based on a multi-core CPU architecture, distributing the received data packets to independent processing cores according to a preset rule, and binding each processing core to an exclusive memory pool to realize physical-level data isolation; and S3, directly transmitting the isolated data to a target application module through a zero copy technology in the user mode, and verifying the data integrity in real time through a hardware verification module. According to the method, the network card is directly taken over through the DPDK driver, the user state data channel is established, an operating system kernel protocol stack is bypassed, the zero copy technology is combined, data does not need to be copied in the whole process from receiving, processing to transmission, the end-to-end delay is reduced to 50 microseconds or below, and the method is suitable for a high throughput scene.

The invention discloses a browser sidebar intelligent assistant interaction method and system, and relates to the technical field of man-machine interaction, and the method comprises the steps: obtaining webpage data according to webpage context information, obtaining interaction data from a user interaction record, and obtaining user emotion data through the interaction data; generating a task recommendation queue based on the webpage data, the interaction data and the emotion data by using a multi-dimensional reasoning method, and generating candidate interaction items according to the task recommendation queue and the user emotion data; receiving an instruction input by a user through the candidate interaction item, generating an analysis result in combination with the webpage data, executing a preset task corresponding to the analysis result, and obtaining task result data; and selecting a visualization template according to the task result data and the user emotion data to output a task result, and updating the user personalized configuration and the semantic memory library. The method is used for solving the problems that traditional browser assistant task recommendation lacks pertinence, and the matching degree of interactive experience and user states and preferences is low.

A system S comprises a server 3 and HMDs 4. The server 3 comprises a composite space generation unit 31b that generates composite space, a user environment determination unit 32 that determines space to be recognized by each user via his HMD 4, a user state recognition unit 33 that recognizes a motion of the user, a trigger event recognition unit 35 that recognizes a trigger event which is a motion performed by the user to a virtual object, and a virtual space generation unit 37b that generates virtual space. When the trigger event is recognized, the user environment determination unit 32 causes the user to recognize the virtual space instead of the composite space.

The embodiment of the invention provides a memory leak detection method and device, equipment and a storage medium, and relates to the technical field of operating systems and performance tuning. The method comprises the following steps: monitoring memory allocation and release operation of a process by adopting a probe program; collecting memory use information of a stack of the process on memory allocation and release operation; through a collaborative caching mechanism of a kernel mode and a user mode, sharing memory use information to the user mode, and analyzing the memory use information in the user mode to obtain a comprehensive hotspot score representing a memory occupation growth trend of a stack; and determining whether the stack has memory leak according to the comprehensive hotspot score. Based on the method, whether the memory leaks or not can be accurately detected under the condition of low performance overhead.

The invention relates to a software and hardware combined fine-grained memory protection mechanism, which realizes high-speed mapping from a physical address to a fine-grained permission label by integrating a metadata search unit and a metadata conversion lookup buffer on a critical path of a processor loading / storage unit. An operating system maintains a multi-level fine-grained permission metadata table in a main memory, and the minimum memory protection granularity is refined to a 64-byte sub-page level. When a processor executes a memory access instruction, address conversion and permission verification are completed in parallel, an access type and a permission label are compared in real time within 1-2 clock periods, and when permission conflicts are detected, high-priority abnormity is triggered immediately, and illegal addresses and fault types are reported accurately. The method supports instruction set extension, buffer overflow protection, multi-level metadata management and user mode and kernel mode differentiated authority control, reduces the influence on the performance of the processor while improving the security of the memory, and is suitable for a computing system with high security and high performance.