A fully-customized dataflow engine for 3D earthquake simulation with a complex topography
A fully-customized dataflow engine for 3D earthquake simulation with a complex topography
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用于复杂地形 3D 地震模拟的完全定制数据流引擎
DOI:
10.1007/s11432-020-2976-5
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发表时间:
2021-11
期刊:
影响因子:
--
通讯作者:
Guangwen Yang
中科院分区:
文献类型:
--
作者:
Bingwei Chen;Haohuan Fu;Wayne Luk;Guangwen Yang
With HPC (high performance computing) evolving into the exascale era, improvements in computing performance and power efficiency have become increasingly more important. Based on our previous work on enabling earthquake simulations on a large scale on Sunway TaihuLight, we further explore other possibilities to improve the application through a fully-customized hardware design on reconfigurable FPGA (field programmable gate array) devices. We investigate the feasibility and the potential benefits of a complete fixed-point design. We first perform a coarse-resolution-based simulation to analyze the representation range and precision needed to capture both the total energy and the energy distribution of variables over space and time. We then derive a complete fixed-point design that identifies the suitable bitwidth for major categories of variables and dynamically represents the range through a dynamic scaling scheme. Finally, we use the optimized fixed-point design to run a case of the Wenchuan earthquake to demonstrate the potential of supporting large-scale scientific simulations on FPGA devices. The results demonstrate that an 18-bit fixed-point design already provides an almost identical description of the seismic events in the Wenchuan scenario down to a single-precision floating-point version and provides sustainable performance equivalent to 13.1 Intel Xeon Gold 6154 18-core CPUs or 2.10 Sunway 260-core processors, with performance per watt (power efficiency) improved by 15.3 and 3.72 times compared with the Intel Xeon Gold 6154 18-core CPUs and the Sunway 260-core processors, respectively.
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DOI:
10.1109/sc.2012.106
发表时间:
2012-11
期刊:
2012 International Conference for High Performance Computing, Networking, Storage and Analysis
影响因子:
--
作者:
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DOI:
10.1007/978-1-4614-1791-0_10
发表时间:
2013
影响因子:
1
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通讯作者:
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影响因子:
5.8
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影响因子:
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作者:
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DOI:
10.1109/sc.2018.00043
发表时间:
2018-11
期刊:
SC18: International Conference for High Performance Computing, Networking, Storage and Analysis
影响因子:
--
作者:
Bingwei Chen;H. Fu;Yanwen Wei;Conghui He;Wenqiang Zhang;Yuxuan Li;W. Wan;Wei Zhang-;L. Gan;Zhenguo Zhang;Guangwen Yang;Xiaofei Chen
通讯作者:
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