KIPS Transactions on Software and Data Engineering (정보처리학회논문지:소프트웨어 및 데이터공학)

Korea Information Processing Society (한국정보처리학회)
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GLOVE: Distributed Shared Memory Based Parallel Visualization Tool for Massive Scientific Dataset

GLOVE: 대용량 과학 데이터를 위한 분산공유메모리 기반 병렬 가시화 도구

  • 이중연 (한국과학기술정보연구원 가시화기술개발실) ;
  • 김민아 (한국과학기술정보연구원 가시화기술개발실) ;
  • 이세훈 (한국과학기술정보연구원 가시화기술개발실) ;
  • 허영주 (한국과학기술정보연구원 가시화기술개발실)
  • Received : 2016.05.03
  • Accepted : 2016.05.17
  • Published : 2016.06.30
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Abstract

Visualization tool can be divided by three components - data I/O, visual transformation and interactive rendering. In this paper, we present requirements of three major components on visualization tools for massive scientific dataset and propose strategies to develop the tool which satisfies those requirements. In particular, we present how to utilize open source softwares to efficiently realize our goal. Furthermore, we also study the way to combine several open source softwares which are separately made to produce a single visualization software and optimize it for realtime visualization of massiv espatio-temporal scientific dataset. Finally, we propose a distributed shared memory based scientific visualization tool which is called "GLOVE". We present a performance comparison among GLOVE and well known open source visualization tools such as ParaView and VisIt.

가시화 도구는 데이터 입출력, 시각적 변환, 상호작용적인 렌더링의 세 구성요소로 구분할 수 있다. 본 논문에서는 거대용량의 과학 데이터를 실시간으로 가시화하기 위해 가시화 도구의 세 구성요소에 대한 요구사항을 분석, 정의하고 이를 만족시키기 위한 방안을 제시하고자 한다. 특히, 효율적인 가시화 도구의 개발을 위해 공개 소프트웨어 도구를 최대한 활용하고자 하였으며, 서로 다른 용도로 개발된 각 공개 소프트웨어 도구를 통합하여 하나의 가시화 도구로 개발하는 방안과 시공간적인 과학 데이터의 실시간 가시화를 위한 최적화 방법에 대해 논한다. 이를 통해 분산공유메모리 기반의 과학 데이터 병렬 가시화 도구인 GLOVE를 제안하였으며, 유동해석 분야 과학 데이터를 이용한 실험을 통해 GLOVE와 다른 데이터 가시화 소프트웨어와의 성능을 비교 분석했다.

Keywords

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