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Accelerating Streamline Tracking in Groundwater Flow Modeling on GPUs
Author(s) -
Ji Xiaohui,
Luo Mulan,
Wang XuSheng
Publication year - 2019
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/gwat.12959
Subject(s) - streamlines, streaklines, and pathlines , computer science , parallel computing , speedup , computational science , thread (computing) , grid , graphics , cuda , general purpose computing on graphics processing units , tracking (education) , flow (mathematics) , computer graphics (images) , geology , geometry , mechanics , psychology , pedagogy , physics , geodesy , mathematics , operating system
Streamline simulation in groundwater flow modeling is a time‐consuming process when a large number of streamlines are analyzed. We develop a parallelization method on graphics processing units (GPUs) for the semi‐analytical particle tracking algorithm developed by Pollock (1988). Compute Unified Device Architecture was used to implement the parallel method. Forward and backward tracking of a streamline is handled by an individual thread. A GPU includes a grid of blocks where a block handles 32 threads. We use multi‐GPUs to accelerate streamline tracking in a flow model with millions of particles. The method was examined to simulate streamlines for identifying three‐dimensional (3D) flow systems in a Tóthian basin. The speedup exceeds 1000 when 8 NVIDIA GPUs are used to simulate 5 million or more streamlines.