6 results about "Time overhead" patented technology

The application relates to the technical field of embedded multi-core computer systems, and provides a non-symmetrical multi-core flow parallel processing method based on clock interrupt synchronization, which comprises the following steps: dividing a task to be executed into n sub-tasks according to data correlation and execution sequence, and binding one processor core to each sub-task; using a general counter on the processor to periodically generate an interrupt at a specified time interval; and responding to the interrupt by an interrupt service program of each core, simulating a synchronous clock rising edge through the interrupt and setting an identification bit, so that relatively independent processor cores can simultaneously start executing three stages of the respective sub-tasks at the clock rising edge. According to the method, multi-core resources can be fully utilized, the execution of the whole task can still obtain parallel acceleration when there is data correlation among the sub-tasks, the scalability of multi-core application is enhanced, multi-core scheduling management is simplified, the system design complexity is reduced, and the multi-core management time cost is lowered.

Embodiments of the present application disclose a method and device for running an application program and a computer device, which are used for reducing time overhead and improving running efficiency of the application program. The method comprises the following steps: a processor runs a first program segment based on data in a first storage space, the first program segment is used for modifying the data in the first storage space, the data in the first storage space comprises values of M first variables and values of N second variables, and each value of the first variable corresponds to at least one value of the second variable; a DMA backs up the data in the first storage space based on a target rule to obtain first backup data stored in a second storage space; for the first variable and the corresponding second variable, a modification order indicated by the first program segment is opposite to a backup order indicated by the target rule, so if the first backup data comprises at least one value of the first variable after the first program segment is run, the processor determines that the first backup data is incorrect.

The present application relates to a kind of lightweight scalable multi-core embedded operating system scheduler design method, belong to operating system task scheduling field.The present application is from three angles of architecture, scalability and performance, by the analysis of the running flow of scheduler, the implementation and data structure of the architecture of scheduler, execution flow, key module are designed, the architecture and processing flow of scheduler are simplified, the time overhead caused by scheduler operation is reduced, while convenient interface is provided for the expansion and upgrade of scheduler.The present application is conducive to the design and implementation of more efficient and general scheduler, is conducive to subsequent extension, effectively reduces the overhead caused by ready queue management.

The application discloses an OpenMP static scheduling method for random loop load balancing. After the configuration of OMPi compiler in the linux environment, the random loop part in the calculation program is isolated. Then the execution time in each loop iteration is obtained by using the idea of iterative compilation, and the execution time is used to represent the load contained in the random loop. Then according to the obtained load information and the actual running thread number required, the load of each iteration in the random loop, the total load and the average load are obtained, the start and end indexes of each thread distribution to the iteration block are calculated, and the start and end index values are respectively stored in the corresponding pointers. Finally, the code about OpenMP scheduling in the compiler is changed to realize the scheduling strategy. The application overcomes the shortcoming of additional time overhead caused by pre-running, has no scheduling overhead, realizes the load balancing and speeds up the execution efficiency of the program.

This application relates to a register allocation method, apparatus, computer device, computer-readable storage medium, and computer program product. The method includes: reading a target instruction; the target instruction including a third source operand and a destination operand; calculating the time overhead of reading and writing the target instruction when storing the third source operand and the destination operand in the same physical register unit and when storing them in different physical register units; determining a register allocation method based on the time overhead; and determining the target storage location of the target instruction based on the register allocation method. This method can improve register utilization.

A minimum time cost resource allocation method based on directed acyclic graph and related device, including: for the data transmission energy and transmission rate of user node, energy constraint and information transmission constraint are established respectively; according to the priority order and time delay requirement of task, a directed acyclic graph is established; based on the directed acyclic graph, the execution time constraint of task is established, and based on all constraint conditions, the system objective function is established; the task unloading decision is calculated, and the system minimum time cost is calculated given the unloading decision. The present application studies the problems of task unloading and minimum time delay cost in wireless energy supply communication network, jointly considers the dependence relationship of task, the processing rate of edge node to different tasks, the transmission rate from edge node to edge node, the acquisition energy of user node, etc., so as to make the optimal task unloading strategy and time allocation decision.