Spark distributed system and GPU parallel computing

Abstract

This study mainly uses virtual reality technology (Virtual Reality, VR) to create the basic theoretical knowledge and analysis of real-time data processing and GPU parallel computing in Spark+GPU heterogeneous environment. The quadratic programming algorithm and time sliding window algorithm are analyzed in detail from theory to practical application, and in the Spark+GPU cluster environment built in the virtual environment, the feasibility of the above algorithm is verified by real-time data processing, GPU scheduling and parallel computing. Through the numerical experiments of test functions and practical engineering applications, the GPU optimization after interval segmentation is more powerful than CPU, the algorithm is sensitive, and the global optimization of surface model provides a new solution.