Here you will find a list of publications focused either on developing Devito or using Devito.
We love to see what the community is doing with Devito and this list also helps build up the community. Therefore, we encourage everyone to contribute to this list by submitting a pull request to the Devito website repository.
If you are the Julia user, the https://slim.gatech.edu team (the developers of JUDI) also has links to the GitHub repo’s with the corresponding software for all their publications.
If you are writing a paper, please remember to cite Devito. Also, tag @devitocodes on twitter for a retweet!
As part of our commitment to open science, we encourage everyone to post preprints of papers to arXiv as they are submitted. We all know that the peer-review process can be a slow (and sometimes painful) experience - why not let everyone read and receive kudos for your hard work immediately!
2024
G. Bisbas, A. Lydike, E. Bauer, N. Brown, M. Fehr, L. Mitchell, G. Rodriguez-Canal, M. Jameson, P. H.J. Kelly, M. Steuwer, T. Grosser. A shared compilation stack for distributed-memory parallelism in stencil DSLs. 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3 (ASPLOS ’24). paper
G. Bisbas, A. Lydike, E. Bauer, N. Brown, M. Fehr, L. Mitchell, G. Rodriguez-Canal, M. Jameson, P. H.J. Kelly, M. Steuwer, T. Grosser. A shared compilation stack for distributed-memory parallelism in stencil DSLs. Poster presented at ASPLOS’24, 2024. [poster]
G. Bisbas, R. Nelson, M. Louboutin, P. H.J. Kelly, F. Luporini, G. Gorman. Automated MPI-X code generation for scalable finite-difference solvers. Poster presented at RICE Energy HPC, 2024. [poster]
2023
G. Bisbas, Automated cache optimisations of stencil computations for partial differential equations. [phd thesis]
G. Bisbas, F. Luporini, R. Nelson, M. Louboutin, E. Caunt, G. Gorman, P H.J. Kelly, The Devito DSL and Compiler Framework: From Symbolic PDEs to HPC Code Presented at SIAM-CSE 2023, MS307: PDE Simulations with High-Productivity Languages at the Dawn of Exascale. [slides]
G. Bisbas, F. Luporini, M. Louboutin, R. Nelson, G. Gorman, P H.J. Kelly, Automated Temporal Blocking in the Devito DSL and Compiler framework Presented at SIAM-CSE 2023, MS243: Stencil Computation for Scientific Applications. [slides]
2022
Jean-Francois Aubry, Oscar Bates, Christian Boehm, Kim Butts Pauly, Douglas Christensen, Carlos Cueto, Pierre Gelat, Lluis Guasch, Jiri Jaros, Yun Jing, Rebecca Jones, Ningrui Li, Patrick Marty, Hazael Montanaro, Esra Neufeld, Samuel Pichardo, Gianmarco Pinton, Aki Pulkkinen, Antonio Stanziola, Axel Thielscher, Bradley Treeby, Elwin van’t Wout Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models arxiv
Belucci, B., 2022. Modelamento sısmico por diferenças finitas: aplicaçao do pacote Devito para resoluçao da equaçao da onda1 (Doctoral dissertation, Universidade Estadual de Campinas). paper
Berti, S., Aleardi, M. and Stucchi, E., A BAYESIAN APPROACH TO FULL-WAVEFORM INVERSION: PRELIMINARY RESULTS. paper
Botelho, S., Mukherjee, S., Rao, V. and Adavani, S., 2022, August. Deep learning software accelerators for full-waveform inversion. In Second International Meeting for Applied Geoscience & Energy (pp. 3681-3685). Society of Exploration Geophysicists and American Association of Petroleum Geologists. paper
E. Caunt, R. Nelson, F. Luporini, G. Gorman Devitoboundary: an open-source tool for topography implementation in finite-difference wavesolvers with Devito Presented at Energy High Performance Computing at Rice University 2022. [slides]
Javier Cudeiro-Blanco, Carlos Cueto, Oscar Bates, George Strong, Tom Robins, Matthieu Toulemonde, Mike Warner, Meng-Xing Tang, Oscar Calderón Agudo, Lluis Guasch, Design and Construction of a Low-Frequency Ultrasound Acquisition Device for 2-D Brain Imaging Using Full-Waveform Inversion Ultrasound in Medicine & Biology, Volume 48, Issue 10, 2022, Pages 1995-2008 paper
Cueto, C., Guasch, L., Luporini, F., Bates, O., Strong, G., Agudo, O.C., Cudeiro, J., Kelly, P., Gorman, G. and Tang, M.X., 2022, April. Tomographic ultrasound modelling and imaging with Stride and Devito. In Medical Imaging 2022: Ultrasonic Imaging and Tomography (p. PC1203805). SPIE. paper
Cueto, C., Bates, O., Strong, G., Cudeiro, J., Luporini, F., Agudo, Ò.C., Gorman, G., Guasch, L. and Tang, M.X., 2022. Stride: A flexible software platform for high-performance ultrasound computed tomography. Computer Methods and Programs in Biomedicine, 221, p.106855. paper
Dolci, D.I., Silva, F.A., Peixoto, P.S. and Volpe, E.V., 2022. Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion. Geoscientific Model Development Discussions, pp.1-36. paper
Gorman, G., Luporini, F., St-Cyr, A., Loddoch, A., Souza, A., Hester, K., Witte, P., Dupros, F. and Araya, M., 2022, September. HPC18-Open Benchmarking Platform for Data Inversion Methods. In Sixth EAGE High Performance Computing Workshop (Vol. 2022, No. 1, pp. 1-3). European Association of Geoscientists & Engineers. abstract
Thomas J Grady II and Rishi Khan and Mathias Louboutin and Ziyi Yin and Philipp A Witte and Ranveer Chandra and Russell J Hewett and Felix J Herrmann Towards Large-Scale Learned Solvers for Parametric PDEs with Model-Parallel Fourier Neural Operators arXiv preprint arXiv:2204.01205, 2022 paper
Hugues, M. and Tadepalli, S., 2022, September. HPC08-Performance and Best Practices to Run Finite Difference Kernel in the Cloud using Devito. In Sixth EAGE High Performance Computing Workshop (Vol. 2022, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. paper
Jesus, L., Nogueira, P., Speglich, J. and Boratto, M., 2022. GPU Performance analysis for viscoacoustic wave equations using fast stencil computation from the symbolic specification. paper
Kukreja, N., Hückelheim, J., Louboutin, M., Washbourne, J., Kelly, P.H. and Gorman, G.J., 2022. Lossy checkpoint compression in full waveform inversion: a case study with ZFPv0. 5.5 and the overthrust model. Geoscientific Model Development, 15(9), pp.3815-3829. paper
Ladino, O.M., Pestana, R. and Souza, A., 2022, June. An Efficient Implementation of Least-Squares Reverse Time Migration Based on Stable Pseudo-Acoustic Tti Wave Equation. In 83rd EAGE Annual Conference & Exhibition (Vol. 2022, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. paper
Oscar López and Rajiv Kumar and Nick Moldoveanu and Felix Herrmann Graph spectrum based seismic survey design arXiv preprint arXiv:2202.04623, 2022 paper
Louboutin, M., Witte, P., Siahkoohi, A., Rizzuti, G., Yin, Z., Orozco, R. and Herrmann, F.J., 2022, August. Accelerating innovation with software abstractions for scalable computational geophysics. In Second International Meeting for Applied Geoscience & Energy (pp. 1482-1486). Society of Exploration Geophysicists and American Association of Petroleum Geologists. paper
Mathias Louboutin and F Herrmann Enabling wave-based inversion on GPUs with randomized trace estimation 83rd EAGE Annual Conference & Exhibition 2022 (1), 1-5, 2022 paper
Orozco, R., Louboutin, M. and Herrmann, F.J., 2022. Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging. arXiv preprint arXiv:2204.11850. paper
Ovadia, O., Kahana, A. and Turkel, E., 2022. A Convolutional Dispersion Relation Preserving Scheme for the Acoustic Wave Equation. paper
Ali Siahkoohi and Mathias Louboutin and Felix J Herrmann Velocity continuation with Fourier neural operators for accelerated uncertainty quantification arXiv preprint arXiv:2203.14386, 2022 paper
Siahkoohi, A., Orozco, R., Rizzuti, G. and Herrmann, F.J., 2022. Wave-equation-based inversion with amortized variational Bayesian inference. arXiv preprint arXiv:2203.15881. paper
Siahkoohi, A., Rizzuti, G. and Herrmann, F.J., 2022. Deep Bayesian inference for seismic imaging with tasks. Geophysics, 87(5), pp.S281-S302. paper
Ali Siahkoohi and Gabrio Rizzuti and Rafael Orozco and Felix J Herrmann Reliable amortized variational inference with physics-based latent distribution correction arXiv preprint arXiv:2207.11640, 2022 paper
Tong, J., Wang, X., Ren, J., Lin, M., Li, J., Sun, H., Yin, F., Liang, L. and Liu, Y., 2022. Transcranial Ultrasound Imaging with Decomposition Descent Learning based Full Waveform Inversion. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. papers
Wellmann, F., Virgo, S., Escallon, D., de la Varga, M., Jüstel, A., Wagner, F.M., Kowalski, J., Zhao, H., Fehling, R. and Chen, Q., 2022. Open AR-Sandbox: A haptic interface for geoscience education and outreach. Geosphere, 18(2), pp.732-749. paper
Zhan, C., Zhang, L., Zhao, X., Lee, C.C. and Huang, S., 2022. Neural Architecture Search for Inversion. paper
Ziyi Yin and Ali Siahkoohi and Mathias Louboutin and Felix J Herrmann Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators, 2022 paper
2021
Ali M Alfaraj and Eric Verschuur and Felix J Herrmann Residual statics correction without NMO—A rank-based approach First International Meeting for Applied Geoscience & Energy, 2565-2569, 2021 paper
George Bisbas, Fabio Luporini, Mathias Louboutin, Rhodri Nelson, Gerard Gorman, and Paul HJ Kelly. Temporal blocking of finite-difference stencil operators with sparse” off-the-grid” sources. In 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (pp. 497-506). IEEE. [Proceedings]
G. Bisbas, F. Luporini, M. Louboutin, R. Nelson, G. Gorman, P. Kelly Temporal blocking for wave propagation with sparse off-the-grid sources Presented at High performance computing in Oil and Gas at Rice University 2021. [slides] [video]
Caunt, E., Nelson, R., Luporini, F. and Gorman, G., 2021, October. Generalised Algorithm and Implementation of Topography Within Finite Difference Wave Solvers. In 82nd EAGE Annual Conference & Exhibition (Vol. 2021, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. paper
E. Caunt, R. Nelson, F. Luporini, G. Gorman A flexible, high-level abstraction for topography implementation within finite difference wave solvers Presented at High performance computing in Oil and Gas at Rice University 2021. [slides] [video]
E. Caunt, R. Nelson, F. Luporini, G. Gorman An open-source tool for accurate topography implementation within finite-difference wave solvers Presented at Proceedings. [slides]
Coelho, G.A.A., UMA ANÁLISE COMPARATIVA ENTRE DIFERENTES TÉCNICAS DE INTERPOLAÇÃO APLICADAS NA FWI UTILIZANDO A DSL DEVITO. paper
Cueto, C., Bates, O., Strong, G., Cudeiro, J., Luporini, F., Agudo, O.C., Gorman, G., Guasch, L. and Tang, M.X., 2021. Stride: a flexible platform for high-performance ultrasound computed tomography. paper
Desai, A., Xu, Z., Gupta, M., Chandran, A., Vial-Aussavy, A. and Shrivastava, A., 2021. Raw Nav-merge Seismic Data to Subsurface Properties with MLP based Multi-Modal Information Unscrambler. Advances in Neural Information Processing Systems, 34, pp.8740-8752. paper
Jaimes-Osorio, L.E., Malcolm, A., Zheglova, P., Koene, E.F. and Thomsen, H.R., 2021. Reduced memory implementation of a local elastic finite-difference solver. Geophysics, 86(3), pp.F25-F33. paper
Jaimes-Osorio, L.E. and Malcolm, A., 2021, September. Inversion comparison using an elastic local solver to recover elastic parameters. In First International Meeting for Applied Geoscience & Energy (pp. 256-261). Society of Exploration Geophysicists.paper
Louboutin, M. and Herrmann, F.J., 2021, September. Ultra-low memory seismic inversion with randomized trace estimation. In First International Meeting for Applied Geoscience & Energy (pp. 787-791). Society of Exploration Geophysicists. paper
F. Luporini, R. Nelson, G.Bisbas, I. Assis, K. Hester, G. Gorman, Devito v4.3: production-grade multi-GPU support Presented at High performance computing in Oil and Gas at Rice University 2021. [slides] [video]
Mathias Louboutin and Ali Siahkoohi and Rongrong Wang and Felix J Herrmann Low-memory stochastic backpropagation with multi-channel randomized trace estimation arXiv preprint arXiv:2106.06998, 2021 paper
Jaimes Osorio, L.E., 2021. Wavefield reconstruction, inversion and imaging using local solvers (Doctoral dissertation, Memorial University of Newfoundland). phd thesis
Rafael Orozco and Ali Siahkoohi and Gabrio Rizzuti and Tristan van Leeuwen and Felix Johan Herrmann Photoacoustic imaging with conditional priors from normalizing flows NeurIPS 2021 Workshop on Deep Learning and Inverse Problems, 2021 paper
Protopapa, L. and Cueto, C., 2021. Computationally efficient full-waveform inversion of the brain using frequency-adaptive grids and lossy compression. paper
Qiu, L., 2021. Analysis of seismic inversion with optimal transportation and softplus encoding. Inverse Problems, 37(9), p.095004. paper
Yuxiao Ren and Philipp A Witte and Ali Siahkoohi and Mathias Louboutin and Ziyi Yin and Felix J Herrmann Seismic Velocity Inversion and Uncertainty Quantification Using Conditional Normalizing Flows AGU Fall Meeting 2021, 2021 paper
Ribeiro, J., Yviquel, H., Técnico-IC-PFG, R. and de Graduação, P.F., 2021. Extending a finite difference domain-specific language to a distributed runtime system. paper
Rizzuti, G., Louboutin, M., Wang, R. and Herrmann, F.J., Time-domain Wavefield Reconstruction Inversion for large-scale seismic inversion. paper
Rizzuti, G., Louboutin, M., Wang, R. and Herrmann, F.J., 2021. A dual formulation of wavefield reconstruction inversion for large-scale seismic inversion. Geophysics, 86(6), pp.R879-R893. paper
Roncoroni, G., Fortini, C., Bortolussi, L., Bienati, N. and Pipan, M., 2021. Synthetic seismic data generation with deep learning. Journal of Applied Geophysics, 190, p.104347. paper
Hamideh Sanavi and Peyman P Moghaddam and Felix J Herrmann True amplitude depth migration using curvelets Geophysics 86 (4), S299-S310, 2021 paper
Shekar, B., 2021. Full waveform inversion with random shot selection using adaptive gradient descent. Journal of Earth System Science, 130(4), pp.1-13. paper
Shin, B.S. and Shutin, D., 2021, June. ADAPT-Then-Combine Full Waveform Inversion for Distributed Subsurface Imaging In Seismic Networks. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4700-4704). IEEE. paper
Siahkoohi, A. and Herrmann, F.J., 2021, September. Learning by example: fast reliability-aware seismic imaging with normalizing flows. In First International Meeting for Applied Geoscience & Energy (pp. 1580-1585). Society of Exploration Geophysicists. paper
Ali Siahkoohi and Gabrio Rizzuti and Mathias Louboutin and Philipp A Witte and Felix J Herrmann Preconditioned training of normalizing flows for variational inference in inverse problems arXiv preprint arXiv:2101.03709, 2021 paper
Sigalingging, A.S., Winardhie, I.S. and Dinanto, E., 2021. Ekstrapolasi Frekuensi Rendah pada Full Waveform Inversion (FWI) dengan menggunakan Deep Learning. Part 1: Validasi data Sintetik. Jurnal Geofisika, 19(2), pp.74-79. paper
J Washbourne, S Kaplan, M Merino, U Albertin, A Sekar, C Manuel, S Mishra, M Chenette, A Loddoch Chevron Optimization Framework for Imaging and Inversion (Cofii)–Open-source Julia Language Framework for Seismic Inversion, 82nd EAGE Annual Conference & Exhibition. paper
John Washbourne, Sam Kaplan, Miguel Merino, Uwe Albertin, Anusha Sekar, Chris Manuel, Scott Mishra, Matthew Chenette, Alex Loddoch Chevron optimization framework for imaging and inversion (COFII)—An open source and cloud friendly Julia language framework for seismic modeling and inversion First International Meeting for Applied Geoscience & Energy paper
Xu, Z., Desai, A., Gupta, M., Chandran, A., Vial-Aussavy, A. and Shrivastava, A., 2021. Beyond convolutions: A novel deep learning approach for raw seismic data ingestion. paper
Yang, M., Graff, M., Kumar, R. and Herrmann, F.J., 2021. Low-rank representation of omnidirectional subsurface extended image volumes. Geophysics, 86(3), pp.S165-S183. paper
Yin, Z., Louboutin, M. and Herrmann, F.J., 2021, October. Compressive time-lapse seismic monitoring of carbon storage and sequestration with the joint recovery model. In SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy. OnePetro. paper
Yijun Zhang and Felix J. Herrmann Improved seismic survey design by maximizing the spectral gap with global optimization 2021 ML4Seismic meeting, 2021
Zhang, Q., Iordanescu, G., Tok, W.H., Brandsberg-Dahl, S., Srinivasan, H.K., Chandra, R., Kukreja, N. and Gorman, G., 2021, September. Hyperwavve: A cloud-native solution for hyperscale seismic imaging on Azure. In First International Meeting for Applied Geoscience & Energy (pp. 782-786). Society of Exploration Geophysicists. paper
Yijun Zhang and Felix J Herrmann A practical workflow for land seismic wavefield recovery with weighted matrix factorization SEG/AAPG/SEPM First International Meeting for Applied Geoscience & Energy, 2021 paper
2020
Ali M Alfaraj and Eric Verschuur and Felix J Herrmann Non-surface-consistent short-wavelength statics correction for dense and subsampled data: A rank-based approach SEG Technical Program Expanded Abstracts 2020, 2784-2788, 2020 paper
G. Bisbas, F. Luporini, M. Louboutin, R. Nelson, G. Gorman, P. Kelly Temporal blocking of finite-difference stencil operators with sparse “off-the-grid” sources in Devito Presented at Domain-Specific Languages in High-Performance Computing 2020. [slides]
Daskalakis, E., Herrmann, F.J. and Kuske, R., 2020. Accelerating sparse recovery by reducing chatter. SIAM Journal on Imaging Sciences, 13(3), pp.1211-1239. paper
Herrmann, J., 2020. H-revolve: a framework for adjoint computation on synchronous hierarchical platforms. ACM Transactions on Mathematical Software (TOMS), 46(2), pp.1-25. paper
N. Kukreja. High-performance backpropagation for structured-grid solvers phd thesis
Louboutin, M., 2020. Modeling for inversion in exploration geophysics (Doctoral dissertation, Georgia Institute of Technology). phd thesis
Mathias Louboutin, Fabio Luporini, Philipp Witte, Rhodri Nelson, George Bisbas, Jan Thorbecke, Felix J. Herrmann, Gerard Gorman. Scaling through abstractions – high-performance vectorial wave simulations for seismic inversion with Devito. Submitted to Supercomputing 2020. [iarXiv:2004.10519]
Louboutin, M., Rizzuti, G. and Herrmann, F.J., 2020. Time-domain wavefield reconstruction inversion in a TTI medium. arXiv.
Luporini, F., Louboutin, M., Lange, M., Kukreja, N., Witte, P., Hückelheim, J., Yount, C., Kelly, P.H., Herrmann, F.J. and Gorman, G.J., 2020. Architecture and performance of Devito, a system for automated stencil computation. ACM Transactions on Mathematical Software (TOMS), 46(1), pp.1-28. paper
F. Luporini, R. Nelson, M. Louboutin, G. Bisbas, E. Caunt, G. Gorman Devito: A DSL and compiler for automated generation of production-grade wave propagators Presented at Domain-Specific Languages in High-Performance Computing 2020. [slides][notebook][figure]
F. Luporini, G. Gorman. Automatic code generation for GPUs using Devito Presented at High performance computing in Oil and Gas at Rice University 2020. [slides]
Margenberg, N., Lessig, C. and Richter, T., 2020. Structure preservation for the deep neural network multigrid solver. arXiv
Mosser, L., Dubrule, O. and Blunt, M.J., 2020. Stochastic seismic waveform inversion using generative adversarial networks as a geological prior. Mathematical Geosciences, 52(1), pp.53-79. paper
Mojica, O.F. and Maciel, J.S., 2020, October. Seismic modeling from scratch using Devito: A demonstration with a typical Brazilian pre-salt model. In SEG International Exposition and Annual Meeting. OnePetro. paper
Moura, F.A., Silva, S.A., de Araújo, J.M. and Lucena, L.S., 2020. Progressive matching optimisation method for FWI. Journal of Geophysics and Engineering, 17(2), pp.357-364. paper
Gabrio Rizzuti and Mathias Louboutin and Rongrong Wang and Felix J Herrmann Time-domain wavefield reconstruction inversion for large-scale seismics 82nd EAGE Annual Conference & Exhibition 2020 (1), 1-5, 2020 paper
Santos, H., Eikmeier, C. and Volpe, E., 2020, May. New tools for 2D full-waveform inversion: applications on Brazilian Pre-Salt velocity model from Santos Basin. In EGU General Assembly Conference Abstracts (p. 21110). paper
Siahkoohi, A., Rizzuti, G. and Herrmann, F., 2020, December. A deep-learning based bayesian approach to seismic imaging and uncertainty quantification. In EAGE 2020 Annual Conference & Exhibition Online (Vol. 2020, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. arxiv
Siahkoohi, A., Rizzuti, G. and Herrmann, F.J., 2020. Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach. In SEG Technical Program Expanded Abstracts 2020 (pp. 1636-1640). Society of Exploration Geophysicists. arxiv
Siahkoohi, A., Rizzuti, G. and Herrmann, F.J., 2020. Weak deep priors for seismic imaging. In SEG Technical Program Expanded Abstracts 2020 (pp. 2998-3002). Society of Exploration Geophysicists. arxiv
Ali Siahkoohi and Gabrio Rizzuti and Philipp A Witte and Felix J Herrmann Faster uncertainty quantification for inverse problems with conditional normalizing flows arXiv preprint arXiv:2007.07985, 2020 paper
Targino, J., Roberts, K., Souza, J., Santos, H., Senger, H., Gioria, R. and Gomi, E., 2020, September. A Deep-Learning inversion method for seismic velocity model building. In First EAGE Conference on Machine Learning in Americas (Vol. 2020, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. paper
Witte, P.A., Louboutin, M., Modzelewski, H., Jones, C., Selvage, J. and Herrmann, F.J., 2020. An event-driven approach to serverless seismic imaging in the cloud. IEEE Transactions on Parallel and Distributed Systems, 31(9), pp.2032-2049. paper
Yang, M., 2020. Seismic imaging with extended image volumes and source estimation (Doctoral dissertation, Georgia Institute of Technology). phd thesis
Mengmeng Yang and Zhilong Fang and Philipp Witte and Felix J Herrmann Time‐domain sparsity promoting least‐squares reverse time migration with source estimation Geophysical Prospecting 68 (9), 2697-2711, 2020 paper
Yin, Z., Orozco, R., Witte, P., Louboutin, M., Rizzuti, G. and Herrmann, F.J., 2020. Extended source imaging—A unifying framework for seismic and medical imaging. In SEG Technical Program Expanded Abstracts 2020 (pp. 3502-3506). Society of Exploration Geophysicists. arxiv
Zhan, C., Lee, C.C., Zhang, L. and Chang, Y., 2020. An attempt to decode reverse-time migration through machine learning. In SEG Technical Program Expanded Abstracts 2020 (pp.1681-1685). Society of Exploration Geophysicists. paper
Mi Zhang and Ali Siahkoohi and Felix J Herrmann Transfer learning in large-scale ocean bottom seismic wavefield reconstruction SEG International Exposition and Annual Meeting, 2020 paper
Yijun Zhang and Shashin Sharan and Oscar Lopez and Felix J Herrmann Wavefield recovery with limited-subspace weighted matrix factorizations SEG International Exposition and Annual Meeting, 2020 paper
2019
AM Alfaraj and M Almubarak and FJ Herrmann Correcting for short-wavelength statics with low rank approximation 81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019 paper
Assis, I.A.S.D., 2019. Intra-node and Inter-node load balancing and other scalable approaches for high-performance seismic processing. paper
Aupy, G. and Herrmann, J., 2019. H-Revolve: a framework for adjoint computation on synchrone hierarchical platforms. paper
G. Bisbas, F. Luporini, M. Louboutin, G. Gorman, and P. H.J. Kelly. Accelerating real-world stencil computations using temporal blocking: handling sparse sources and receivers. Poster presented at SC19, 2019, [paper, poster]
Caunt, E., 2019, June. Spatially-Optimized Finite-Difference Schemes for Numerical Dispersion Suppression: an Implementation Using Symbolic Computation. In 81st EAGE Conference and Exhibition 2019 (Vol. 2019, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. paper
Caunt, E., 2021. Spatially-optimized finite-difference schemes for numerical dispersion suppression in seismic applications. MSci thesis
Curt Da Silva and Felix Herrmann A unified 2D/3D large-scale software environment for nonlinear inverse problems ACM Transactions on Mathematical Software (TOMS) 45 (1), 1-35, 2019 paper
Devoti, F., Parera, C., Lieto, A., Moro, D., Lipari, V., Bestagini, P. and Tubaro, S., 2019, September. Wavefield compression for seismic imaging via convolutional neural networks. In SEG International Exposition and Annual Meeting. OnePetro. paper
Tim Eipert and Felix Herrmann and Christoph Wick and Frank Puppe and Andreas Haug Editor support for digital editions of medieval monophonic music Proceedings of the 2nd International Workshop on Reading Music Systems, 4-7, 2019 paper
EINSIEDLER, H.C., COMPARAÇÃO DE MÉTODOS DE OTIMIZAÇÃO PARA SOLUÇÃO DO PROBLEMA DE INVERSÃO DA FORMA DE ONDA COMPLETA. paper
Felix J Herrmann and Ali Siahkoohi and Gabrio Rizzuti Learned imaging with constraints and uncertainty quantification arXiv preprint arXiv:1909.06473, 2019 paper
J. Hückelheim, N. Kukreja, SHK Narayanan, F. Luporini, G. Gorman, P. Hovland Automatic Differentiation for Adjoint Stencil Loops Presented at International Conference on Parallel Programming. [slides]
N. Kukreja, J. Hückelheim, M. Louboutin, F. Luporini, P. Kelly, P. Hovland, G. J. Gorman Inversion with Devito: Trading off memory and compute with PyRevolve Presented at STMI Workshop at USP. [slides]
Kukreja, N., Hückelheim, J., Louboutin, M., Hovland, P. and Gorman, G., 2019, August. Combining checkpointing and data compression to accelerate adjoint-based optimization problems. In European Conference on Parallel Processing (pp. 87-100). Springer, Cham.paper
Rajiv Kumar and Marie Graff and Ivan Vasconcelos and Felix J Herrmann Target‐oriented imaging using extended image volumes: a low‐rank factorization approach Geophysical Prospecting 67 (5), 1312-1328, 2019 paper
Rajiv Kumar and Bram Willemsen and Felix J Herrmann and Alison Malcolm Enabling numerically exact local solver for waveform inversion—A low-rank approach Computational Geosciences 23 (4), 829-847, 2019 paper
F. Luporini, R. Nelson, M. Louboutin, N. Kukreja, G. Bisbas, P. Witte, Amik St-Cyr, C. Yount, T. Burgess, F. Herrmann, G. Gorman Automatic Generation of Production-Grade Hybrid MPI-OpenMP Parallel Wave Propagators using Devito Presented at Platform for Advanced Scientific Computing (PASC 2019) Conference. [slides]
Fabio Luporini, Mathias Louboutin, Michael Lange, Navjot Kukreja, Jan Hückelheim, Charles Yount, Philipp Witte, Paul H. J. Kelly, Felix J. Herrmann, Gerard J. Gorman. Architecture and performance of Devito, a system for automated stencil computation. Accepted to ACM Transactions on Mathematical Software (submitted August 2019) [Proceedings]
Luporini, F., Nelson, R., Burgess, T., St-Cyr, A. and Gorman, G., 2019, October. Automated Distributed-memory Parallelism from Symbolic Specification in Devito. In Fourth EAGE Workshop on High Performance Computing for Upstream 2019 (Vol. 2019, No. 1, pp. 1-5). European Association of Geoscientists & Engineers. paper
Mathias Louboutin, Michael Lange, Fabio Luporini, Navjot Kukreja, Philipp A. Witte, Felix J. Herrmann, Paulius Velesko and Gerard J. Gorman Devito (v3.1.0): an embedded domain-specific language for finite differences and geophysical exploration. Geoscientific Model Development, Volume 12, p 1165-1187, 2019 [paper]
Jaimes-Osorio, L.E., Malcolm, A., Zheglova, P. and Koene, E., Making any elastic modelling code into a local elastic solver. paper
V. H. Mickus-Rodrigues, L. Cavalcante, M. B. Pereira, F. Luporini, I. Reguly, G. Gorman, S. Xavier-de-Souza. GPU Support for Automatic Generation of Finite-Differences Stencil Kernels Presented at Latin America High Performance Computing 2019. [arXiv]. [slides]
Mojica, O.F. and Kukreja, N., 2019. Towards automatically building starting models for full-waveform inversion using global optimization methods: A PSO approach via DEAP+ Devito. In SEG Technical Program Expanded Abstracts 2019 (pp. 5174-5178). Society of Exploration Geophysicists. paper
Nelson, R., Luporini, F. and Gorman, G., 2019, December. Immersed Boundary Finite-Difference Methods for Seismic Wave Propagation Modelling: an Implementation Using Symbolic Computation in Devito. In AGU Fall Meeting Abstracts (Vol. 2019, pp. T52C-10).
V. Pandolfo. Investigating the OPS intermediate representation to target GPUs in the Devito DSL arXiv
Peters, B. and Herrmann, F.J., 2019. Algorithms and software for projections onto intersections of convex and non-convex sets with applications to inverse problems. paper
Bas Peters and Felix J Herrmann Generalized Minkowski sets for the regularization of inverse problems arXiv preprint arXiv:1903.03942, 2019 paper
Bas Peters and Brendan R Smithyman and Felix J Herrmann Projection methods and applications for seismic nonlinear inverse problems with multiple constraints Geophysics 84 (2), R251-R269, 2019 paper
Rizzuti, G., Louboutin, M., Wang, R., Daskalakis, E. and Herrmann, F., 2019, September. A dual formulation for time-domain wavefield reconstruction inversion. In SEG International Exposition and Annual Meeting. OnePetro. slides
Gabrio Rizzuti and Ali Siahkoohi and Felix J Herrmann Learned iterative solvers for the Helmholtz equation 81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019 paper
Rodrigues, V.H.M., Cavalcante, L., Pereira, M.B., Luporini, F., Reguly, I., Gorman, G. and Souza, S.X.D., 2019, September. GPU Support for Automatic Generation of Finite-Differences Stencil Kernels. In Latin American High Performance Computing Conference (pp. 230-244). Springer, Cham. paper
H. Senger, J. F. de Souza, E.S. Gomi, F. Luporini, and G. Gorman. Performance of Devito on HPC-Optimised ARM Processors. Poster presented at SC19, 2019, [paper, poster,summary]
Siahkoohi, A., Louboutin, M. and Herrmann, F.J., 2019. Neural network augmented wave-equation simulation. arXiv
Siahkoohi, A., Louboutin, M. and Herrmann, F.J., 2019. The importance of transfer learning in seismic modeling and imaging. Geophysics, 84(6), pp.A47-A52. paper
Ali Siahkoohi and Dirk J Verschuur and Felix J Herrmann Surface-related multiple elimination with deep learning SEG International Exposition and Annual Meeting, 2019 paper
Ali Siahkoohi and Rajiv Kumar and Felix J Herrmann Deep-learning based ocean bottom seismic wavefield recovery SEG Technical Program Expanded Abstracts 2019, 2232-2237, 2019 paper
Silva, C.D. and Herrmann, F., 2019. A unified 2D/3D large-scale software environment for nonlinear inverse problems. ACM Transactions on Mathematical Software (TOMS), 45(1), pp.1-35. paper
Shashin Sharan and Rongrong Wang and Felix J Herrmann Fast sparsity-promoting microseismic source estimation Geophysical Journal International 216 (1), 164-181, 2019 paper
Philipp A. Witte, Mathias Louboutin, Navjot Kukreja, Fabio Luporini, Michael Lange, Gerard J. Gorman, Felix J. Herrmann. A large-scale framework for symbolic implementations of seismic inversion algorithms in Julia. In Geophysics, Volume 84, Issue 3, May 2019. [proceedings]
Witte, P.A., Louboutin, M., Jones, C. and Herrmann, F.J., 2019. Serverless seismic imaging in the cloud. arXiv preprint arXiv:1911.12447. paper
Philipp A. Witte, Mathias Louboutin, Fabio Luporini, Gerard J. Gorman, Felix J. Herrmann. Compressive least-squares migration with on-the-fly Fourier transforms. Accepted for publication in Geophysics on April 14, 2019. paper
Witte, P.A., Louboutin, M., Modzelewski, H., Jones, C., Selvage, J. and Herrmann, F.J., 2019. Event-driven workflows for large-scale seismic imaging in the cloud. In SEG Technical Program Expanded Abstracts 2019 (pp. 3984-3988). Society of Exploration Geophysicists. paper
Yang, M., Graff, M., Kumar, R. and Herrmann, F.J., 2019, September. Low-rank representation of subsurface extended image volumes with power iterations. In SEG International Exposition and Annual Meeting. OnePetro. slides
Yijun Zhang and Shashin Sharan and Felix J Herrmann High-frequency wavefield recovery with weighted matrix factorizations SEG Technical Program Expanded Abstracts 2019, 3959-3963, 2019 paper
2018
Gorman, G., Luporini, F., Kukreja, N., Louboutin, M., St-Cyr, A., Souza, B. and Herrmann, F., 2018, September. Devito: Fast and Scalable Full-Waveform Inversion Without the Excruciating Pain. In First EAGE Workshop on High Performance Computing for Upstream in Latin America (Vol. 2018, No. 1, pp. 1-1). European Association of Geoscientists & Engineers. paper
Felix .J. Herrmann, Gerard Gorman, Jan Hückelheim, Keegan Lensink, Paul Kelly, Navjot Kukreja, Henryk Modzelewski, Michael Lange, Mathias Louboutin, Fabio Luporini, Ali SiahKoohi, Phillipp Witte The power of abstraction in Computational Exploration Seismology Presented at Smoky Mountains Computational Sciences & Engineering Conference. [slides]
N. Kukreja, J. Hückelheim, M. Lange, M. Louboutin, A. Walther, S. W. Funke, G. J. Gorman High-level abstractions for checkpointing in PDE-constrained optimisation Presented at International Symposium for Mathematic Programming. [slides, paper]
Kukreja, N., Huckelheim, J., Louboutin, M., Hou, K., Luporini, F., Hovland, P. and Gorman, G., 2018. Combining checkpointing and data compression for large scale seismic inversion. paper
Mathias Louboutin, Philipp A. Witte, Michael Lange, Navjot Kukreja, Fabio Luporini, Gerard Gorman, and Felix J. Herrmann. Full-waveform inversion - Part 2: adjoint modeling. The Leading Edge, Volume 37, Issue 1 (January 2018) [notebook] [paper]
Louboutin, M., Witte, P. and Herrmann, F.J., 2018. Effects of wrong adjoints for RTM in TTI media. In SEG Technical Program Expanded Abstracts 2018 (pp. 331-335). Society of Exploration Geophysicists. paper
F. Luporini, C. Yount, M. Louboutin, N. Kukreja, P. Witte, T. Burges, M. Lange, P.H .J . Kelly, F. Herrmann, G. Gorman Automated loop generation for high-performance finite differences (and beyond) Presented at Dagstuhl. [slides]
F. Luporini, C. Yount, M. Louboutin, N. Kukreja, P. Witte, M. Lange, P. Kelly, F. Herrmann, G. Gorman. Devito: Automated high-performance finite differences for geophysics exploration. Presented at IXPUG Europe Spring 2018. [slides]
Sharan, S., Kumar, R., Dumani, D.S., Louboutin, M., Wang, R., Emelianov, S. and Herrmann, F.J., 2018, October. Sparsity-promoting photoacoustic imaging with source estimation. In 2018 IEEE International Ultrasonics Symposium (IUS) (pp. 206-212). IEEE. paper
N. Sim. Optimising finite-difference methods for PDEs through parameterised time-tiling in Devito arXiv
Philipp A. Witte, Mathias Louboutin, Michael Lange, Navjot Kukreja, Fabio Luporini, Gerard Gorman, and Felix J. Herrmann. Full-waveform inversion - Part 3: inversion. The Leading Edge, Volume 37, Issue 2 (January 2018) [notebook] [paper]
2017
G. Gorman, M. Lange, F. Luporini, M. Louboutin, N. Kukreja, P. Witte, C. Yount, F. Herrmann. Automatic code generation - developing high performance propagators better, faster and cheaper. Presented at EAGE 2017. [slides]
J. Hückelheim, Z. Luo, F. Luporini, N. Kukreja, M. Lange, G. Gorman, S. Siegel, M. Dwyer, P. Hovland. Towards Self-Verification in Finite Difference Code Generation. Accepted for publication in In Proceedings of Correctness’17: First International Workshop on Software Correctness for HPC Applications (Correctness’17). ACM, New York, NY [paper]
N. Kukreja, M. Lange, M. Louboutin, F. Luporini and G. Gorman. Symbolic Math for Automated Fast Finite Difference Computations Presented at SIAM-CSE 2017, MS84 Domain-Specific Abstractions for Full-Waveform Inversion. [slides]
N. Kukreja, M. Lange, M. Louboutin, F. Luporini, J. Hückelheim, P. Witte, C. Yount, F. Herrmann, G. Gorman Rapid development of seismic imaging applications using symbolic mathematics Presented at Third EAGE Workshop on High Performance Computing for Upstream[slides]
N. Kukreja, M. Louboutin, F. Luporini, P. Witte, M. Lange, F. Herrmann and G. Gorman. Leveraging symbolic math for rapid development of applications for seismic imaging Presented at High performance computing in Oil and Gas at Rice University 2017. [slides]
Kumar, R., Wason, H., Sharan, S. and Herrmann, F.J., 2017. Highly repeatable 3D compressive full-azimuth towed-streamer time-lapse acquisition—A numerical feasibility study at scale. The Leading Edge, 36(8), pp.677-687. paper
M. Lange, N. Kukreja, M. Louboutin, F. Luporini, F. Vieira, V. Pandolfo, P. Velesko, P. Kazakas and G. Gorman. Devito: Towards an efficient and sustainable finite difference DSL. Poster presented at SIAM CSE17 PP108 Minisymposterium: Software Productivity and Sustainability for CSE and Data Science, 2017 poster
M. Lange, N. Kukreja, F. Luporini, M. Louboutin, C. Yount, J. Hückelheim and G. Gorman. Optimised finite difference computation from symbolic equations. Accepted for publication in Proceedings of the 15th Python in Science Conference, 2017. [accepted] [arxiv]
M. Lange, N. Kukreja, F. Luporini, M. Louboutin, C. Yount, J. Hückelheim and G. Gorman. Optimised finite difference computation from symbolic equations. Presented at SciPy 2017. [paper, slides], [video]
M. Louboutin, M. Lange, N. Kukreja, F. Herrmann, and G. Gorman. Performance prediction of finite-difference solvers for different computer architectures. Computers & Geosciences 105 (2017): 148-157. paper
M. Louboutin, M. Lange, N. Kukreja, F. Luporini, F. Herrmann and G. Gorman. Multi-Physics Geophysical Exploration: Raising the Abstraction with Separation of Concerns Presented at SIAM-CSE 2017, MS84 Domain-Specific Abstractions for Full-Waveform Inversion. [slides]
Mathias Louboutin, Philipp A. Witte, Michael Lange, Navjot Kukreja, Fabio Luporini, Gerard Gorman, and Felix J. Herrmann. Full-waveform inversion - Part 1: forward modeling. The Leading Edge, Volume 36, Issue 12 (December 2017). [notebook] [paper]
F. Luporini, M. Lange, N. Kukreja, M. Louboutin, C. Yount, J. Hückelheim and G. Gorman. Optimised finite difference computation from symbolic equations. Presented at WOLFHPC 2017. [slides]
F. Luporini, M. Lange, M. Louboutin, N. Kukreja and G.Gorman. Vectorization and Locality Optimizations for Seismic Imagining Methods Through Automated Code Generation Presented at SIAM-CSE 2017, MS44 Efficiency of High-Order Methods on the 2nd Generation Intel Xeon Phi Processor. [slides]
Martínez, V., Serpa, M., Dupros, F., Padoin, E.L. and Navaux, P., 2017, September. Performance prediction of acoustic wave numerical kernel on Intel Xeon Phi processor. In Latin American High Performance Computing Conference (pp. 101-110). Springer, Cham. paper
D. McCormick. Applying the Polyhedral Model to Tile Time Loops in Devito arXiv
P. Witte, M. Louboutin and F. Herrmann. Large-Scale Workflows for Wave-Equation Based Inversion in Julia Presented at SIAM-CSE 2017, MS84 Domain-Specific Abstractions for Full-Waveform Inversion. [slides]
Yang, M., Daskalakis, E. and Herrmann, F., 2017, September. Fast sparsity-promoting least-squares migration with multiples in the time domain. In 2017 SEG International Exposition and Annual Meeting. OnePetro. paper.
2016
M. Aguiar, G. Gorman, F. Herrmann, N. Kukreja, M. Lange, M. Louboutin, F. Vieira, Devito: Fast finite difference computation. Poster presented at SC 2016 poster
N. Kukreja, M. Louboutin, F. Vieira, F. Luporini, M. Lange, and G. Gorman. Devito: automated fast finite difference computation. In 2016 Sixth International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC) arxiv
Kukreja, N., Louboutin, M., Lange, M., Luporini, F. and Gorman, G., Leveraging symbolic math for rapid development of applications for seismic modeling. Presented at Oil and Gas HPC, Rice 2016 paper
M. Lange, C. Jacobs, F. Luporini, L. Mitchell, D. Ham, and G. Gorman. Seigen: Seismic modelling through code generation. Poster presented at SIAM-PP16, 2016, poster
M. Lange, N. Kukreja, M. Louboutin, F. Luporini, F. Vieira, V. Pandolfo, P. Velesko, P. Kazakas, and G. Gorman. Devito: Towards a generic Finite Difference DSL using Symbolic Python. In Python for High-Performance and Scientific Computing (PyHPC), Workshop on, pp. 67-75. IEEE, 2016. arxiv
M. Lange, N. Kukreja, M. Louboutin, F. Luporini, V. Pandolfo, P. Velesko, P. Kazakas and G. Gorman. Devito: Towards a generic Finite Difference DSL using Symbolic Python Presented at PyHPC 2016. [slides]
Lange, M., Kukreja, N., Louboutin, M., Luporini, F., Vieira, F., Pandolfo, V., Velesko, P., Kazakas, P. and Gorman, G., 2016, November. Devito: Towards a generic finite difference dsl using symbolic python. In 2016 6th Workshop on Python for High-Performance and Scientific Computing (PyHPC) (pp. 67-75). IEEE.
T. Sun. OPESCI-FD: Automatic Code Generation Package for Finite Difference Models arXiv