Barnes-hut treecode on GPU

General-purpose computation on graphics processing units (GPGPU) has become a popular field of study. Due to its high computing capacity and relatively low price, GPU has been an ideal processing unit for many scientific applications, among which is N-body simulation. According to the published pape...

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Bibliographic Details
Main Authors: Hu Jiang, Qianni Deng
Format: Conference Proceeding
Language:English
Subjects:
Force
GPGPU
Graphics processing unit
Memory management
N-body simulation
Parallel processing
tree algorithm
Online Access:Request full text
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Summary:General-purpose computation on graphics processing units (GPGPU) has become a popular field of study. Due to its high computing capacity and relatively low price, GPU has been an ideal processing unit for many scientific applications, among which is N-body simulation. According to the published papers, a simple O(N^2) algorithm of N-body simulation has achieved some enhancements, but tree-algorithm doesn't work well on GPU. This paper proposes a new implementation of tree-algorithm on GPU using CUDA, which has obtained more than 100X speedup when computing forces between bodies. This paper also rises up a new method to build tree in this algorithm, making the performance even better.
DOI:10.1109/PIC.2010.5687868