{"id":699,"date":"2025-01-16T11:00:53","date_gmt":"2025-01-16T02:00:53","guid":{"rendered":"https:\/\/neuron.catholic.ac.kr\/wordpress\/?p=699"},"modified":"2025-01-20T20:36:24","modified_gmt":"2025-01-20T11:36:24","slug":"alphafold3%ea%b0%80-rtx-4090%ec%97%90%ec%84%9c-%ec%8b%a4%ed%96%89%ea%b0%80%eb%8a%a5%ed%95%9c%ea%b0%80","status":"publish","type":"post","link":"https:\/\/neuron.catholic.ac.kr\/?p=699","title":{"rendered":"Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00?"},"content":{"rendered":"\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><a href=\"https:\/\/github.com\/google-deepmind\/alphafold3\/issues\/9\">https:\/\/github.com\/google-deepmind\/alphafold3\/issues\/9<\/a><\/p>\n<cite><strong><a href=\"https:\/\/github.com\/linuxfold\">linuxfold<\/a>\u00a0<\/strong>commented\u00a0<a href=\"https:\/\/github.com\/google-deepmind\/alphafold3\/issues\/9#issuecomment-2475584605\">on Nov 14, 2024<\/a>\u00a0\u2022\u00a0edited\u00a0<br>Great news! Have you tested the impact of maximum sequence length on performance or results?<br>Can confirm successful predictions on both 24GB 3090 and 4090 and &#8211;gpu device=0 flag works fine.<br>I tried doing a trimer prediction for the test file and a hexamer prediction for the test file &#8211; both produced an output without any errors.<br>I also did a prediction of 3 chains with around 800 amino acids total &#8211; worked perfectly fine and output structure as expected and essentially the same as online alphafoldserver output.<br>All predictions use around 23GB of VRAM (with maybe an increase of a few hundred MiB) so VRAM usage is not a good predictor of how much longer the sequence can be. These were all done with stock settings (not using unified memory). Overall looks like it works well based on these few test cases.<\/cite><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>https:\/\/github.com\/google-deepmind\/alphafold3\/issues\/9 linuxfold\u00a0commented\u00a0on Nov 14, 2024\u00a0\u2022\u00a0edited\u00a0Great news! Have you tested the impact of maximum sequence length on performance or results?Can confirm successful predictions on both 24GB 3090 and 4090 and &#8211;gpu device=0 flag works fine.I tried doing a trimer prediction for the test file and a hexamer prediction for the test file &#8211; both produced an&hellip;&nbsp;<a href=\"https:\/\/neuron.catholic.ac.kr\/?p=699\" rel=\"bookmark\">\ub354 \ubcf4\uae30 &raquo;<span class=\"screen-reader-text\">Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00?<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[24,36,25],"tags":[32,33],"class_list":["post-699","post","type-post","status-publish","format-standard","hentry","category-ai","category-alphafold","category-protenix","tag-alphafold3","tag-rtx-4090"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00? - Neuropharm<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/neuron.catholic.ac.kr\/?p=699\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00? - Neuropharm\" \/>\n<meta property=\"og:description\" content=\"https:\/\/github.com\/google-deepmind\/alphafold3\/issues\/9 linuxfold\u00a0commented\u00a0on Nov 14, 2024\u00a0\u2022\u00a0edited\u00a0Great news! Have you tested the impact of maximum sequence length on performance or results?Can confirm successful predictions on both 24GB 3090 and 4090 and &#8211;gpu device=0 flag works fine.I tried doing a trimer prediction for the test file and a hexamer prediction for the test file &#8211; both produced an&hellip;&nbsp;\ub354 \ubcf4\uae30 &raquo;Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00?\" \/>\n<meta property=\"og:url\" content=\"https:\/\/neuron.catholic.ac.kr\/?p=699\" \/>\n<meta property=\"og:site_name\" content=\"Neuropharm\" \/>\n<meta property=\"article:published_time\" content=\"2025-01-16T02:00:53+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-01-20T11:36:24+00:00\" \/>\n<meta name=\"author\" content=\"Choi\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"Choi\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/?p=699#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/?p=699\"},\"author\":{\"name\":\"Choi\",\"@id\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/#\\\/schema\\\/person\\\/9dd53f622e6bcf6465e81bddfa7ff224\"},\"headline\":\"Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00?\",\"datePublished\":\"2025-01-16T02:00:53+00:00\",\"dateModified\":\"2025-01-20T11:36:24+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/?p=699\"},\"wordCount\":152,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/#organization\"},\"keywords\":[\"Alphafold3\",\"RTX 4090\"],\"articleSection\":[\"AI\",\"Alphafold\",\"Protenix\"],\"inLanguage\":\"ko-KR\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/neuron.catholic.ac.kr\\\/?p=699#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/?p=699\",\"url\":\"https:\\\/\\\/neuron.catholic.ac.kr\\\/?p=699\",\"name\":\"Alphafold3\uac00 RTX 4090\uc5d0\uc11c \uc2e4\ud589\uac00\ub2a5\ud55c\uac00? 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