Research on Parallel Algorithm for 3D Seismic Wave Simulation

With advancements in computational capabilities and algorithmic sophistication, 3D seismic simulations have become pivotal in geophysics, earthquake engineering, and disaster prevention efforts. However, the application of fast scanning methods in 3D seismic simulations presents significant challenges due to strong data dependencies, which hinder the parallelism in solving equations within the programmed functions. This limitation often precludes practical engineering applications. To overcome these constraints, we have developed an innovative approach that transcends the traditional 2D methodologies by extending these methods to three dimensions. We introduce a novel 3D diagonal direction chunking algorithm that utilizes Manhattan distance, accompanied by a foundational integral optimization algorithm. Experimental evaluations indicate that our proposed method enhances performance, achieving an optimization acceleration ratio of 1.47 on a single core. When scaled to a 56-core single node, the parallel efficiency reaches $\mathbf{4 2 \%}$. In practical engineering computations, the implementation of 56 OpenMP threads facilitates an acceleration by a factor of 23, demonstrating substantial improvements over existing algorithms.

Authors

Institutions

Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/eeiss65394.2025.11085522
Primary Topic
Geological Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Parallel Algorithm for 3D Seismic Wave Simulation

Yuxu Peng, Chunye Gong, Dong Cui, Hao Cao et al.
Geological Modeling and Analysis
article

Research on Parallel Algorithm for 3D Seismic Wave Simulation

Yuxu Peng, Chunye Gong, Dong Cui, Hao Cao, Qingzhen Ma, Taihui Yin
article en

Abstract

With advancements in computational capabilities and algorithmic sophistication, 3D seismic simulations have become pivotal in geophysics, earthquake engineering, and disaster prevention efforts. However, the application of fast scanning methods in 3D seismic simulations presents significant challenges due to strong data dependencies, which hinder the parallelism in solving equations within the programmed functions. This limitation often precludes practical engineering applications. To overcome these constraints, we have developed an innovative approach that transcends the traditional 2D methodologies by extending these methods to three dimensions. We introduce a novel 3D diagonal direction chunking algorithm that utilizes Manhattan distance, accompanied by a foundational integral optimization algorithm. Experimental evaluations indicate that our proposed method enhances performance, achieving an optimization acceleration ratio of 1.47 on a single core. When scaled to a 56-core single node, the parallel efficiency reaches $\mathbf{4 2 \%}$. In practical engineering computations, the implementation of 56 OpenMP threads facilitates an acceleration by a factor of 23, demonstrating substantial improvements over existing algorithms.

National University of Defense Technology (CN), Research Institute of Petroleum Exploration and Development (CN), Medtronic (China) (CN), National Supercomputing Center of Tianjin (CN), Changsha University of Science and Technology (CN)
Climate action
Openalex Percentile: Top 84%
Geological Modeling and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.