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The Contact and Parallel Analysis of SPH Using Cartesian Coordinate Based Domain Decomposition Method

Cartesian 좌표기반 동적영역분할을 고려한 SPH의 충돌 및 병렬해석

  • Moonho Tak (Innovation Center for Engineering Education, College of Engineering, Hanyang University)
  • Received : 2024.02.28
  • Accepted : 2024.03.11
  • Published : 2024.04.01

Abstract

In this paper, a parallel analysis algorithm for Smoothed Particle Hydrodynamics (SPH), one of the numerical methods for fluidic materials, is introduced. SPH, which is a meshless method, can represent the behavior of a continuum using a particle-based approach, but it demands substantial computational resources. Therefore, parallel analysis algorithms are essential for SPH simulations. The domain decomposition algorithm, which divides the computational domain into partitions to be independently analyzed, is the most representative method among parallel analysis algorithms. In Discrete Element Method (DEM) and Molecular Dynamics (MD), the Cartesian coordinate-based domain decomposition method is popularly used because it offers advantages in quickly and conveniently accessing particle positions. However, in SPH, it is important to share particle information among partitioned domains because SPH particles are defined based on information from nearby particles within the smoothing length. Additionally, maintaining CPU load balance is crucial. In this study, a highly parallel efficient algorithm is proposed to dynamically minimize the size of orthogonal domain partitions to prevent excess CPU utilization. The efficiency of the proposed method was validated through numerical analysis models. The parallel efficiency of the proposed method is evaluated for up to 30 CPUs for fluidic models, achieving 90% parallel efficiency for up to 28 physical cores.

본 논문에서는 유동체를 해석할 수 있는 수치해석기법 중 하나인 SPH(Smoothed Particle Hydrodynamics)의 병렬해석 알고리즘이 소개된다. 무요소법(meshless method)의 SPH는 연속체 거동을 입자기반으로 표현하기 때문에 컴퓨팅하는데 높은 자원을 요구한다. 그래서 병렬해석 알고리즘은 SPH 시뮬레이션에서 필수적으로 고려되어야 한다. 계산영역을 일정한 간격으로 분할시켜 독립적으로 해석하는 영역분할 알고리즘은 병렬해석 알고리즘 중에 가장 대표적인 방법이다. 그리고 그 중 Cartesian 좌표계의 영역분할 방법은 입자들의 좌표를 빠르고 편리하게 검색할 수 있는 장점이 있어, DEM(Discrete Element Method)이나 MD(Molecular Dynamics)에서 대중적으로 사용되고 있다. 그러나 SPH의 경우 입자들이 smoothing 길이 이내의 주위 입자 정보가 필요하기 때문에 분할 영역 간의 입자정보 공유가 중요하다. 그리고 이에 따른 CPU의 로드밸런스가 중요하다. 본 연구에서는 직교 영역분할의 크기를 동적으로 미소화 시켜 잉여 CPU가 발생하지 않도록 하는 높은 병렬효율성의 알고리즘이 제안되었다. 그리고 수치해석 모델을 통하여 효율성을 검증하였다. 유동체 모델에 대해 총 30 CPU까지 제안된 방법의 병렬효율성을 검토하였고, 28개의 물리적 코어 수까지 90%의 병렬효율성을 얻을 수 있었다.

Keywords

Acknowledgement

본 연구는 2019년 정부(교육부)의 재원으로 한국연구재단 이공분야 기초연구사업의 지원을 받아 수행된 연구임(NRF-2019R1I1A1A01059014).

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