국방시스템 내에서의 GPU 기반 병렬처리 방법에 대한 연구

Abstract

By the mid of 2020, Korean military forces have planned to built the network centric warfare(NCW) environment by integrating advanced US/NATO standardized tactical data links and Korean unique data links. In this NCW environment, sensors, reconnaissance and weapon systems will be integrated with command and control systems utilizing tactical data links These inter-systems integrations bring out the dramatic growth of exchanging data and computing resources for real time processing. However, these issues could not be easily resolved with current CPU based computing architectures. Because, CPU is not dedicated parallel processing device, it is usually very expensive and multi-thread programming using CPU is very difficult even for expert programmers. By the way, the high-speed arithmetic dedicated GPUs(Graphic Processing Unit) with hundreds or thousands cores are being developed rapidly and applied commercially in the area of genetic analysis, hydrodynamics and cryptography in these days. It also provides grid-block-thread architectures for parallel data processing and software development kits(SDK) for developers to exchange data and functions between hosts systems and GPUs at ease. In a huge military system, there are lots of high computing power required areas such as receiving and transmitting tactical messages with specific rules, data fusions and management, threat evaluation, weapon assignment and drawing situational display. This study will identify those areas in detail and suggest GPU based parallel processing ideas which can be adaptable with several examples and experiments.