Direct current fault screening method designed in combination with GPU hardware and software architecture characteristics

Abstract

The invention discloses a direct current fault screening method designed in combination with GPU hardware and software architecture characteristics. The method includes the steps that optimal design is conducted on task assignment of kernel functions of a GPU according to GPU hardware and software parameters; one cut-off is calculated with a thread block; a CPU reads power network data and sends the required data to the GPU; two CUDA currents are adopted, and asynchronous execution of branch cut-off fault screening and electric generator cut-off fault screening is achieved while the GPU executes the kernel functions; according to the first CUDA current, the first kernel function and the second kernel function in the GPU screen a branch cut-off fault set S1 and send the fault set S1 back to the CPU; according to the second CUDA current, the third kernel function and the fourth kernel function in the GPU screen an electric generator cut-off fault set S2 and send the fault set S2 back to the CPU. One thread block is utilized to calculate one cut-off, the total number of used threads is increased, the calculation amount of a single thread is reduced, and hardware resources and calculation capacity of the GPU are fully utilized.

Description

technical field [0001] The invention belongs to the application field of high-performance computing in power systems, relates to power system fault screening, and in particular relates to a DC fault screening method designed in combination with the characteristics of GPU software and hardware architecture. Background technique [0002] The GPU is a many-core parallel processor, which far exceeds the CPU in the number of processing units. Traditionally, the GPU is only responsible for graphics rendering, and most of the processing is handed over to the CPU. The current GPU has become a multi-core, multi-threaded, programmable processor with powerful computing capabilities and extremely high memory bandwidth. Under the general computing model, the GPU works as a coprocessor of the CPU, and completes high-performance computing through reasonable task allocation and decomposition. At present, GPU has been successfully used in medical imaging, computational fluid dynamics, envi...

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Problems solved by technology

For a power system with N components, in practical applications, using DC power flow to screen some serious faults that may threaten the safety of the power grid, CPU processing is relatively time-consuming

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