{"id":249456,"date":"2021-01-11T23:00:00","date_gmt":"2021-01-11T22:00:00","guid":{"rendered":"https:\/\/cimne.com\/cimne-researchers-publish-a-new-paper-about-parallel-algorithms-on-siam-journal-on-scientific-computing\/"},"modified":"2025-10-27T09:18:33","modified_gmt":"2025-10-27T08:18:33","slug":"cimne-researchers-publish-a-new-paper-about-parallel-algorithms-on-siam-journal-on-scientific-computing","status":"publish","type":"post","link":"https:\/\/cimne.com\/es\/cimne-researchers-publish-a-new-paper-about-parallel-algorithms-on-siam-journal-on-scientific-computing\/","title":{"rendered":"CIMNE researchers publish a new paper about parallel algorithms on SIAM Journal on Scientific Computing"},"content":{"rendered":"<p>The CIMNE researchers <strong>Santiago Badia, Alberto F. Mart&iacute;n, Eric Neiva and Francesc Verdugo<\/strong> from<strong><a href=\"https:\/\/www.cimne.com\/1156\" title=\" Large Scale Scientific Computing Group\"> Large Scale Scientific Computing Group<\/a><\/strong> have recently published the article <a href=\"https:\/\/epubs.siam.org\/doi\/abs\/10.1137\/20M1328786\"> \u00ab<strong>A Generic Finite Element Framework on Parallel Tree-Based Adaptive Meshes\u00bb<\/strong><\/a> on<em> SIAM Journal on Scientific Computing<\/em> (Published online: 18 December 2020).<\/p>\n<p>In this work, the researchers formally <strong>derive and prove the correctness of the algorithms and data structures in a parallel, distributed-memory, <i>generic<\/i> finite element framework that supports $h$-adaptivity on computational domains represented as forest-of-trees.<\/strong> The framework is grounded on a <strong>rich representation of the adaptive mesh suitable for generic finite elements<\/strong> that is built on top of a low-level, light-weight forest-of-trees data structure handled by a specialized, highly parallel adaptive meshing engine, for which they have identified the requirements it must fulfill to be coupled into our framework. <strong>Atop this two-layered mesh representation, they build the rest of the data structures required for the numerical integration and assembly of the discrete system of linear equations.<\/strong><\/p>\n<p>They consider algorithms that are <strong>suitable for both sub-assembled and fully assembled distributed data layouts of linear system matrices<\/strong>. The proposed framework has been <strong>implemented within the FEMPAR scientific software library<\/strong>, using p4est as a practical forest-of-octrees demonstrator.<strong> A strong scaling study of this implementation when applied to Poisson and Maxwell problems reveals remarkable scalability up to 32.2K CPU cores and 482.2M degrees of freedom<\/strong>. Besides, a comparative performance study of FEMPAR and the state-of-the-art deal.II finite element software shows at least comparative performance, and at most a factor of 2&#8211;3 improvement in the $h$-adaptive approximation of a Poisson problem with first- and second-order Lagrangian finite elements, respectively.<\/p>\n<p><strong>Keywords: <\/strong>partial differential equations, finite elements, adaptive mesh refinement, forest of trees, parallel algorithms, scientific software.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The CIMNE researchers Santiago Badia, Alberto F. Mart&iacute;n, Eric Neiva and Francesc Verdugo from Large Scale Scientific Computing Group have recently published the article \u00abA Generic Finite Element Framework on Parallel Tree-Based Adaptive Meshes\u00bb on SIAM Journal on Scientific Computing (Published online: 18 December 2020). In this work, the researchers formally derive and prove the [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":249457,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","slim_seo":{"title":"CIMNE researchers publish a new paper about parallel algorithms on SIAM Journal on Scientific Computing - CIMNE","description":"The CIMNE researchers Santiago Badia, Alberto F. Mart&iacute;n, Eric Neiva and Francesc Verdugo from Large Scale Scientific Computing Group have recently publis"},"footnotes":""},"categories":[35],"tags":[446],"class_list":["post-249456","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-news","tag-researchresearch-overviewrditechnology-transferhpc"],"acf":[],"_links":{"self":[{"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/posts\/249456","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/comments?post=249456"}],"version-history":[{"count":0,"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/posts\/249456\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/media\/249457"}],"wp:attachment":[{"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/media?parent=249456"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/categories?post=249456"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/cimne.com\/es\/wp-json\/wp\/v2\/tags?post=249456"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}