Accelerating Half-Precision Seismic Simulation on Neural Processing Unit

Yinuo Wang

doi:10.1109/TPDS.2025.3584773

2025-10-01

PRE

DOI：10.1109/TPDS.2025.3584773

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由于处理不规则感兴趣区域的优越性，曲线网格有限差分法（CGFDM）已在地震模拟中广泛应用于地震灾害评估和地震物理理解。本文提出了一种新颖的方法，该方法在Ascend这一先进的神经网络处理器（NPU）上优化CGFDM求解器，采用半精度存储和混合精度算术。该方法提高了数据吞吐量和计算效率，实现了更有效的地震建模。此外，我们提出了一种高效的矩阵单元启用的3D差分算法，该算法利用NPU上的矩阵单元来加速计算。通过充分利用矩阵单元和宽SIMD通道的能力，我们的Ascend求解器在性能上比两颗AMD CPU上的并行求解器提升了4.19倍，并已成功模拟了真实的汶川地震。据我们所知，我们是首次在NPU上开展地震模拟研究。

Keyword:

Seismic simulation

half-precision

finite difference method

AI accelerator

ascend

NPU

期刊

IEEE Transactions on Parallel and Distributed Systems

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5.2K

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Beijing University of Posts and Telecommunications

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tsinghua university

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shandong university

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Southern University of Science and Technology

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