{"id":2121,"date":"2010-12-17T13:30:04","date_gmt":"2010-12-17T13:30:04","guid":{"rendered":"http:\/\/hgpu.org\/?p=2121"},"modified":"2010-12-17T13:30:04","modified_gmt":"2010-12-17T13:30:04","slug":"accelerating-correlated-quantum-chemistry-calculations-using-graphical-processing-units","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=2121","title":{"rendered":"Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units"},"content":{"rendered":"<p>Graphical processing units are now being used with dramatic effect to accelerate quantum chemistry applications. The authors give a brief introduction to electronic structure methods and describe their efforts to accelerate a correlated quantum chemistry code. They propose and analyze two new tools for accelerating matrix-multiplications where single-precision accuracy is insuffcient.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Graphical processing units are now being used with dramatic effect to accelerate quantum chemistry applications. The authors give a brief introduction to electronic structure methods and describe their efforts to accelerate a correlated quantum chemistry code. They propose and analyze two new tools for accelerating matrix-multiplications where single-precision accuracy is insuffcient.<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[66,3],"tags":[1790,165,264,20,199],"class_list":["post-2121","post","type-post","status-publish","format-standard","hentry","category-chemistry","category-paper","tag-chemistry","tag-computational-chemistry","tag-molecular-modeling","tag-nvidia","tag-tesla-c1060"],"views":1860,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2121","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=2121"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/2121\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=2121"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=2121"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=2121"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}