基于webgpu的超声无损检测声波模拟器

André P. Galera, Daniele Rossato, F. D. Gutierrez, G. Pires, T. Passarin, G. A. Guarneri, D. Pipa
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引用次数: 0

摘要

超声无损检测是一种标准的工业技术,用于海底输油管道等多种结构的健康监测和缺陷识别。其主要目的是形成被检查对象内部结构的代表性图像,在许多情况下,提供结构不连续的早期预警,使其有可能降低维修成本和降低风险。全波形反演(full - waveinvetion, FWI)是超声和地震学界越来越关注的成像方法之一,它将无损检测系统获得的信息与理论模拟数据相比较,估计出检测区域的速度模型。由于FWI算法依赖于连续的超声波模拟,因此必须确保每个模拟都是优化的,并且对总运行时间的贡献很小。声波模拟可以使用图形处理单元(GPU)进行优化,通过并行性提供硬件加速,其中模拟区域的每个点可以同时计算。在所有可用的gpuapi中,WebGPU是下一代标准图形Web API,它通过向用户提供对gpu的低级通用访问来暴露现代计算机图形功能。该API旨在有效地映射到本地GPU API,这使得应用程序可以在不同的GPU上运行,使实现更具可扩展性和可互换性。在这种灵活性的激励下,我们通过实现基于WebGPU的超声波无损检测声波模拟器来探索WebGPU API的加速能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A WebGPU-based acoustic wave simulator for ultrasound NDT
Ultrasound NDT is a standard industrial technique for health monitoring and flaw identification in several structures, such as subsea oil pipelines. Its primary purpose is to form a representative image of the internal structure of the inspected object, which provides, in many cases, early warning of structure discontinuities, making it possible to reduce repair costs and mitigate risks. One of the imaging methods that has been receiving increasing attention in the ultrasound and seismology communities is the Full Waveform Inversion (FWI), which estimates the velocity model for the inspection area by confronting the acquired information obtained by the NDT system with theoretical simulated data. Since FWI algorithms rely on successive ultrasonic wave simulations, it is essential to ensure that each simulation is optimized and contributes little to the total running time. Acoustic wave simulations can be optimized using a graphical processing unit (GPU), which provides hardware acceleration through parallelism, where each point of the simulated area can be computed simultaneously. Among all available GPU APIs, WebGPU is the next-generation standard graphics Web API that exposes modern computer graphics capabilities by giving the user low-level, general-purpose access to the GPUs. This API is designed to efficiently map to native GPU APIs, which enables applications to run on different GPUs, making implementations more scalable and interchangeable. Motivated by this flexibility, we explore the acceleration capabilities of the WebGPU API by implementing a WebGPU-based acoustic wave simulator for ultrasound NDT.
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