{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/libemm-a-fictious-wave-domain-3d-csem","title":"libEMM: A fictious wave domain 3D CSEM modelling library bridging sequential and parallel GPU implementation","arxiv_id":"2304.00233","date":"2023-04-01","proceeding":null,"authors":["Pengliang Yang"],"abstract":"This paper delivers a software -- libEMM -- for 3D controlled-source electromagnetics (CSEM) modelling in fictitious wave domain, based on the newly developed high-order finite-difference time-domain (FDTD) method on non-uniform grid. The numerical simulation can be carried out over a number of parallel processors using MPI-based high performance computing architecture. The FDTD kernel coded in C has been parallelized with OpenMP for speedup using local shared memory. In addition, the software features a GPU implementation of the same algorithm based on CUDA programming language, which can be cross-validated and compared in terms of efficiency. A perspective of libEMM on the horizon is its application to 3D CSEM inversion in land and marine environment.","url_abs":"https://arxiv.org/abs/2304.00233v1","url_pdf":"https://arxiv.org/pdf/2304.00233v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"libemm-a-fictious-wave-domain-3d-csem","repo_url":"https://github.com/yangpl/libemm","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}