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Abstract

Summary

By building on recent advances in the use of randomized trace estimation to drastically reduce the memory footprint of adjoint-state methods, we present and validate an imaging approach that can be executed exclusively on accelerators. Results obtained on field-realistic synthetic datasets, which include salt and anisotropy, we show that our method produces high-fidelity images. These findings open the enticing perspective of 3D wave-based inversion technology with a memory footprint that matches the hardware and that runs exclusively on clusters of GPUs without the undesirable need to offload certain tasks to CPUs.

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/content/papers/10.3997/2214-4609.202210531
2022-06-06
2025-04-24

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/content/papers/10.3997/2214-4609.202210531
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Enabling Wave-Based Inversion on Gpus with Randomized Trace Estimation
Conference Proceedings 2022, 1 (2022); https://doi.org/10.3997/2214-4609.202210531
/content/papers/10.3997/2214-4609.202210531
/content/papers/10.3997/2214-4609.202210531
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