Abstract:
5G virtual reality has attracted many manufacturers and users with its unique immersion, interactivity and imagination characteristics, which has become the focus of new ...Show MoreNotes: IEEE Xplore ® Notice to Reader: “Spark Distributed Real-Time Data and GPU Parallel Computing Based on 5G Virtual Reality” by Ying Chang, Dajun Chang, Li Li, and Zhangquan Qiao published in the IEEE Consumer Electronics Magazine (Early Access) Digital Object Identifier: 10.1109/MCE.2022.3159349. It has been recommended by the authors and Editor-in-Chief of the IEEE Consumer Electronics Magazine that this article will not be published in its final form and should not be considered for citation purposes. We regret any inconvenience this may have caused. Norbert Herencsar Editor-in-Chief IEEE Consumer Electronics Magazine
Metadata
Abstract:
5G virtual reality has attracted many manufacturers and users with its unique immersion, interactivity and imagination characteristics, which has become the focus of new markets. The purpose of this article is to use Spark distributed real-time data system and GPU parallel computing to quickly process and analyze data. This article mainly designs a general-purpose real-time data analysis and processing system based on Spark, which mainly includes new ETL and real-time processing engine modules, and is committed to achieving higher real-time performance than traditional Hadoop. And realize fast calculation. At the same time there is universality and stability. Includes real-time flow calculations. Fast batch processing and machine learning The various types of data computers are included in this article by preparing the cutting device and adjusting the cutting output. The device is ready to effectively terminate the CUDA environment. The cudamalloc function is used to allocate a linear space of bytes to the device, and then transfer the data from the host to the device to determine the number of GPU blocks and threads. GPU parallel computing can increase the data processing speed by 27%, while the secondary programming algorithm can reduce the optimization time of the cup by 12%.
Notes: IEEE Xplore ® Notice to Reader: “Spark Distributed Real-Time Data and GPU Parallel Computing Based on 5G Virtual Reality” by Ying Chang, Dajun Chang, Li Li, and Zhangquan Qiao published in the IEEE Consumer Electronics Magazine (Early Access) Digital Object Identifier: 10.1109/MCE.2022.3159349. It has been recommended by the authors and Editor-in-Chief of the IEEE Consumer Electronics Magazine that this article will not be published in its final form and should not be considered for citation purposes. We regret any inconvenience this may have caused. Norbert Herencsar Editor-in-Chief IEEE Consumer Electronics Magazine
Published in: IEEE Consumer Electronics Magazine ( Early Access )
