4 results about "Multicore computing" patented technology

A system may comprise one or more devices in a network. The devices may be configured to: receive network slice performance data; and determine whether a network slice to which a User Equipment (UE) device is connected meets one or more criteria based on the network slice performance data. When the network slice does not meet the one or more criteria, the one or more devices may identify a different network slice that meets the one or more criteria; obtain an application identifier (app ID) or a traffic descriptor from a UE Route Selection Policy (URSP) rule whose slice ID matches a slice ID of the different network slice; and send the app ID or the traffic descriptor to the UE device.

This invention provides a method for improving the real-time performance of Linux operating system applications based on a multi-core CPU. The method includes, during system startup, modifying Linux kernel startup parameters to reallocate tasks across the cores of the multi-core CPU, concentrating basic Linux system tasks on the zeroth core; when the target application creates a task, it sets task affinity based on the task's real-time requirements by calling system functions; non-real-time critical tasks are assigned to the first core; real-time critical tasks are assigned to the second core; and sub-real-time critical tasks are assigned to the third core. This invention effectively reduces the response latency of specific interrupts with strict real-time requirements in the Linux system by utilizing different cores of a multi-core CPU to allocate different tasks, improving device real-time performance and meeting the real-time requirements of fields such as power distribution automation.

This invention discloses a multi-agent collaboration method and system for domestically developed operating systems, belonging to the field of intelligent technology for domestically developed desktop operating systems. It aims to solve the core problems of existing solutions, such as lack of collaboration standards, black-box decision-making, and difficulty in reusing experience. The method establishes a collaboration system by building an MCP protocol stack and a native DBus mapping, generating a structured inference chain through the System-2 inference engine, and achieving a closed loop through dynamic task distribution, three-level memory reuse, and visual auditing. The system includes a main agent, a cluster of sub-agents, and multiple core modules to collaboratively support the implementation of the method. This solution enables plug-and-play intelligent agents, full traceability of decision-making, and improves the execution efficiency of similar tasks by more than 30%. It is deeply adapted to multiple versions of openKylin and domestically developed hardware, meeting the security compliance and efficient collaboration needs of key scenarios such as government affairs and finance.

This invention discloses a multi-core CPU power consumption dynamic adjustment system for an all-in-one computer, comprising: a parameter acquisition unit, a benchmark setting unit, a demand analysis unit, and a dynamic adjustment unit. The parameter acquisition unit collects operating status parameters of the all-in-one computer's CPU. The benchmark setting unit sets adjustment benchmarks and dynamic adjustment mechanisms for each parameter based on the type of the operating status parameters. This invention relates to the field of computer hardware power consumption management technology. This multi-core CPU power consumption dynamic adjustment system for an all-in-one computer collects real-time operating frequency, operating voltage, core temperature, load rate, and instantaneous power consumption parameters of each CPU core. Combined with the adjustment benchmarks and dynamic adjustment mechanisms set by the benchmark setting unit, and the precise comparison and analysis of parameters by the demand analysis unit, it can accurately determine the direction and magnitude of power consumption adjustment based on the actual operating status of the CPU, achieving precise power consumption adjustment and avoiding unnecessary power waste.