Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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A Study on the Performance Improvement of Software Digital Filter using GPU

GPU를 이용한 소프트웨어 디지털 필터의 성능개선에 관한 연구

  • Yeom, Jae-Hwan (Radio Astronomy Division, Korea Astronomy and Space Science Institute) ;
  • Oh, Se-Jin (Radio Astronomy Division, Korea Astronomy and Space Science Institute) ;
  • Roh, Duk-Gyoo (Radio Astronomy Division, Korea Astronomy and Space Science Institute) ;
  • Jung, Dong-Kyu (Radio Astronomy Division, Korea Astronomy and Space Science Institute) ;
  • Hwang, Ju-Yeon (Radio Astronomy Division, Korea Astronomy and Space Science Institute) ;
  • Oh, Chungsik (Radio Astronomy Division, Korea Astronomy and Space Science Institute) ;
  • Kim, Hyo-Ryoung (Radio Astronomy Division, Korea Astronomy and Space Science Institute)
  • 염재환 (한국천문연구원 전파천문본부) ;
  • 오세진 (한국천문연구원 전파천문본부) ;
  • 노덕규 (한국천문연구원 전파천문본부) ;
  • 정동규 (한국천문연구원 전파천문본부) ;
  • 황주연 (한국천문연구원 전파천문본부) ;
  • 오충식 (한국천문연구원 전파천문본부) ;
  • 김효령 (한국천문연구원 전파천문본부)
  • Received : 2018.12.15
  • Accepted : 2018.12.24
  • Published : 2018.12.31
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Abstract

This paper describes the performance improvement of Software (SW) digital filter using GPU (Graphical Processing Unit). The previous developed SW digital filter has a problem that it operates on a CPU (Central Processing Unit) basis and has a slow speed. The GPU was introduced to filter the data of the EAVN (East Asian VLBI Network) observation to improve the operation speed and to process data with other stations through filtering, respectively. In order to enhance the computational speed of the SW digital filter, NVIDIA Titan V GPU board with built-in Tensor Core is used. The processing speed of about 0.78 (1Gbps, 16MHz BW, 16-IF) and 1.1 (2Gbps, 32MHz BW, 16-IF) times for the observing time was achieved by filtering the 95 second observation data of 2 Gbps (512 MHz BW, 1-IF), respectively. In addition, 2Gbps data is digitally filtered for the 1 and 2Gbps simultaneously observed with KVN (Korean VLBI Network), and compared with the 1Gbps, we obtained similar values such as cross power spectrum, phase, and SNR (Signal to Noise Ratio). As a result, the effectiveness of developed SW digital filter using GPU in this research was confirmed for utilizing the data processing and analysis. In the future, it is expected that the observation data will be able to be filtered in real time when the distributed processing optimization of source code for using multiple GPU boards.

본 논문은 GPU를 이용한 소프트웨어(SW) 디지털 필터의 성능개선에 대해 기술한다. 기존에 개발한 SW 디지털 필터는 CPU 기반에서 동작하여 속도가 느린 문제점이 있었는데, EAVN 관측데이터의 디지털 필터링을 위해 GPU를 도입하여 연산속도를 개선하였고, 필터링을 통하여 다른 관측국과의 데이터 처리가 가능하도록 하였다. SW 디지털 필터의 연산속도를 개선하기 위해 Tensor Core가 내장된 NVIDIA Titan V GPU 보드를 사용하였으며, 2Gbps (512 MHz BW, 1-IF)의 95초 관측데이터를 필터링하는데 관측시간의 약 1.1배, 1Gbps (16MHz BW, 16-IF)로 필터링하는데 약 0.78배 처리속도를 각각 달성하였다. 또한 KVN으로 1, 2Gbps 동시관측한 데이터에 대해 2Gbps 데이터를 디지털 필터링하여 기존 1Gbps와 비교한 결과, 교차전력스펙트럼, 위상, SNR 등이 유사한 값을 얻어 본 연구에서 개발한 SW 디지털 필터를 활용한 데이터 처리와 분석을 수행하는데 유효함을 확인하였다. 향후에는 여러 개의 GPU 보드를 사용하기 위한 소스 코드의 분산처리 최적화를 수행할 경우 실시간으로 관측데이터를 필터링할 수 있을 것으로 기대된다.

Keywords

References

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