{"id":431,"date":"2015-03-27T04:14:19","date_gmt":"2015-03-27T04:14:19","guid":{"rendered":"http:\/\/ahay.org\/blog\/?p=431"},"modified":"2015-08-04T23:51:26","modified_gmt":"2015-08-04T23:51:26","slug":"fwi-on-gpu","status":"publish","type":"post","link":"https:\/\/ahay.org\/blog\/2015\/03\/27\/fwi-on-gpu\/","title":{"rendered":"FWI on GPU"},"content":{"rendered":"<p>A new paper is added to the <a href=\"\/wiki\/Reproducible_Documents\">collection of reproducible documents<\/a>:<br \/>\n<a href=\"\/RSF\/book\/xjtu\/gpufwi\/paper_html\/\">A graphics processing unit implementation of time-domain full-waveform inversion<\/a><br \/>\n<img loading=\"lazy\" decoding=\"async\" src=\"\/RSF\/book\/xjtu\/gpufwi\/marmtest\/Fig\/vsnap.png\" width=\"474\" height=\"301\"><\/p>\n<blockquote><p> The graphics processing unit (GPU) has become a popular device for seismic imaging and inversion due to its superior speedup performance. In this paper we implement GPU-based full waveform inversion (FWI) using the wavefield reconstruction strategy. Because the computation on GPU is much faster than CPU-GPU data communication, in our implementation the boundaries of the forward modeling are saved on the device to avert the issue of data transfer between host and device. The Clayton-Enquist absorbing boundary is adopted to maintain the efficiency of GPU computation. A hybrid nonlinear conjugate gradient algorithm combined with the parallel reduction scheme is utilized to do computation in GPU blocks. The numerical results confirm the validity of our implementation.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>A new paper is added to the collection of reproducible documents: A graphics processing unit implementation of time-domain full-waveform inversion The graphics processing unit (GPU) has become a popular device for seismic imaging and inversion due to its superior speedup performance. In this paper we implement GPU-based full waveform inversion (FWI) using the wavefield reconstruction [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_import_markdown_pro_load_document_selector":0,"_import_markdown_pro_submit_text_textarea":"","activitypub_content_warning":"","activitypub_content_visibility":"local","activitypub_max_image_attachments":4,"activitypub_interaction_policy_quote":"","footnotes":""},"categories":[5],"tags":[],"class_list":["post-431","post","type-post","status-publish","format-standard","hentry","category-documentation"],"_links":{"self":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/431","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/comments?post=431"}],"version-history":[{"count":1,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/431\/revisions"}],"predecessor-version":[{"id":484,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/posts\/431\/revisions\/484"}],"wp:attachment":[{"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/media?parent=431"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/categories?post=431"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ahay.org\/blog\/wp-json\/wp\/v2\/tags?post=431"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}