基于CUDA的超声二维声场EFIT仿真

宋波; 李威; 廉国选

doi:10.13700/j.bh.1001-5965.2018.0675

基于CUDA的超声二维声场EFIT仿真

doi: 10.13700/j.bh.1001-5965.2018.0675

宋波^1, ,,
李威²,
廉国选¹

1.
中国科学院声学研究所声场声信息国家重点实验室, 北京 100190
2.
武汉武船计量试验有限公司, 武汉 430060

基金项目:

国家自然科学基金 11504403

详细信息

作者简介:
宋波男, 硕士, 副研究员。主要研究方向:超声计算成像与检测应用

通讯作者:
宋波, E-mail: songbo@mail.ioa.ac.cn

中图分类号: TP391.9;O429
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- 被引次数: 0
出版历程
- 收稿日期: 2018-11-20
- 录用日期: 2019-02-17
- 网络出版日期: 2019-07-20

EFIT simulation of 2D ultrasonic sound field based on CUDA

SONG Bo^{1
, ,},
LI Wei²,
LIAN Guoxuan¹

1.
State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2.
Wuhan WUCHUAN Measurement & Test Co., Ltd., Wuhan 430060, China

Funds:

National Natural Science Foundation of China 11504403

More Information

Corresponding author: SONG Bo, E-mail: songbo@mail.ioa.ac.cn

摘要

摘要:
随着图形处理器（GPU）的快速发展，基于计算设备统一构架（CUDA）可以方便地将并行计算技术应用于超声声场数值仿真计算，极大地提升计算效率。阐述了弹性动力学有限积分算法（EFIT）的原理，在采用CPU实现带吸收边界的钢材料二维点源激励声场仿真的基础上，基于GPU实现了仿真模型的并行计算，介绍了GPU程序的设计流程和参数优化方法，包括纹理内存使用、吸收边界优化和数据传输优化。对比了相同条件下CPU和GPU仿真计算的耗时和平均计算效率，定量分析了GPU对于EFIT模型效率的提升。比对结果表明，EFIT具有良好的并行计算条件，采用并行计算方法能够有效提升模型计算速度，对于复杂声场仿真应用具有广阔的应用前景。
- 并行计算 /
- 弹性动力学有限积分算法(EFIT) /
- 二维声场 /
- 图形处理器(GPU) /
- 计算设备统一构架(CUDA)
Abstract:
With the rapid development of graphic processing unit (GPU), the parallel computing technology could be easily applied in the numerical simulation of ultrasonic sound field based on compute unified device architecture (CUDA). The calculating efficiency could be greatly promoted by using the parallel computing technology. The theory of elastodynamic finite integration technology (EFIT) is illustrated in this article. An EFIT 2D ultrasonic sound field model with point source and absorption boundary in steel material is established by CPU, and on the basis of CPU code, the GPU model is built with parallel computing technology. The flow design procedure and parameter optimization method of GPU model are introduced, including the texture memory use, absorption boundary optimization and data transmission optimization. Based on the comparison of time consumption and average calculating efficiency, the efficiency promotion of EFIT model of CPU and GPU version are quantitatively analyzed. The result reveal that the EFIT model with GPU has much higher calculating efficiency. According to the comparison result, the calculation speed of EFIT model is promoted significantly with the parallel computing technology. And it has broad application prospects in complicated acoustic field simulation.
- parallel computing /
- elastodynamic finite integration technology (EFIT) /
- 2D sound field /
- graphic processing unit (GPU) /
- compute unified device architecture (CUDA)

HTML全文

图 1 单个计算单元内速度与应力的分布

Figure 1. Velocity and stress distribution in single calculation unit

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图 2 未设置吸收边界的声场分布

Figure 2. Sound field distribution without absorption boundary

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图 3 设置吸收边界的声场分布

Figure 3. Sound field distribution with absorption boundary

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图 4 并行计算流程

Figure 4. Flowchart of parallel calculation

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图 5 纹理内存线程寻址示意图

Figure 5. Schematic diagram of texture memory thread addressing

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图 6 GPU与CPU计算结果对比

Figure 6. Comparison of GPU and CPU computing results

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图 7 GPU与CPU计算耗时对比

Figure 7. Comparison of computing time consumption of GPU and CPU

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图 8 GPU与CPU平均每秒迭代次数对比

Figure 8. Comparison of average iteration times in one second of GPU and CPU

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