{"id":7846,"date":"2025-06-19T13:51:25","date_gmt":"2025-06-19T12:51:25","guid":{"rendered":"https:\/\/research.reading.ac.uk\/act\/?post_type=kbe_knowledgebase&#038;p=7846"},"modified":"2025-07-01T12:11:07","modified_gmt":"2025-07-01T11:11:07","slug":"aifs-on-racc2","status":"publish","type":"kbe_knowledgebase","link":"https:\/\/research.reading.ac.uk\/act\/knowledgebase\/aifs-on-racc2\/","title":{"rendered":"AIFS Single 1.0 on RACC2"},"content":{"rendered":"<p>This article is contributed by <a href=\"mailto:r.w.lee@reading.ac.uk\">Robert Lee<\/a>. Please contact the author directly for any AIFS related questions and comments. For all other RACC2 or research computing related queries, as always please raise them to the Digital Research Computing Team via the <a href=\"https:\/\/uor.topdesk.net\/tas\/public\/ssp\/content\/detail\/service?unid=e63b0cf459054cbf92f7a1d37a2b8425&amp;from=c5e3063f-66be-4726-903b-f4b0ff38f8c8\">Self Service Portal<\/a>.<\/p>\n<p>AIFS\u202fSingle\u202fv1 is the first fully operational deterministic machine\u2011learning forecast model released by ECMWF on 25\u202fFebruary\u202f2025. It replaces the earlier experimental version (v0.2.1) and is implemented using the open-source Anemoi framework. This latest version improves upper\u2011atmosphere and precipitation forecasts, adds outputs like 100\u202fm wind, snowfall, radiation, and soil variables, and marks ECMWF&#8217;s first AI-driven model integrated into its regular forecasting system. More information can be found on the AIFS Single v1 website.<\/p>\n<h2><\/h2>\n<h2 class=\"rt-level-1\"><strong>How to run AIFS Single 1.0 on RACC2<\/strong><\/h2>\n<p>First, log in to the Reading Academic Computing Cluster (RACC2). If you&#8217;re unfamiliar with our cluster, please first consult the articles in our<a href=\"https:\/\/research.reading.ac.uk\/act\/knowledgebase_category\/racc2\/\"> RACC2 knowledgebase category.<\/a><\/p>\n<p data-start=\"80\" data-end=\"277\"><strong data-start=\"80\" data-end=\"99\">AIFS Single 1.0<\/strong> is installed in a Conda environment on RACC2 and can only be run on a GPU via batch jobs submitted to the GPU node. Users must use the gpuscavenger partition for this purpose.<\/p>\n<p data-start=\"279\" data-end=\"579\"><strong data-start=\"279\" data-end=\"288\">Note:<\/strong> The GPU node was funded by a separate project grant. As such, access through the gpuscavenger partition is only allowed during idle periods. Jobs submitted to this partition are subject to preemption <strong data-start=\"480\" data-end=\"494\">&#8211; <\/strong>they may be terminated and re-queued if higher-priority tasks require GPU resources.<\/p>\n<p>&nbsp;<\/p>\n<h4 class=\"rt-level-2\"><strong>Step 1: Prepare Your Job Files<\/strong><\/h4>\n<p>A working example is available at:<br \/>\n\/software\/slurm_examples\/anemoi\/<\/p>\n<p>This includes the following:<\/p>\n<ul class=\"rt-list\">\n<li>submit_AIFS_GPU.sh \u2013 a SLURM batch script to submit the job<\/li>\n<li>run_AIFS_Single_1_12hr_test.py \u2013 a Python script that runs a 12-hour forecast and saves an output figure<\/li>\n<\/ul>\n<p>You can copy the example to your own working directory and modify as needed.<\/p>\n<p>&nbsp;<\/p>\n<h4 class=\"rt-level-2\"><strong>Step 2: Submit the Batch Job<\/strong><\/h4>\n<p>Load the pre-installed environment and submit your job:<\/p>\n<pre>module load anaconda\/2023.09-0\/anemoi\r\nsbatch submit_AIFS_GPU.sh<\/pre>\n<p>This will queue your job to run on the GPU via the gpuscavenger partition.<\/p>\n<p class=\"rt-level-2\"><strong>Optional: Check Job Status<\/strong><br \/>\nTo check the status of your submitted job, run the command:<\/p>\n<pre>squeue -u $USER<\/pre>\n<p>($USER will automatically use your own username)<\/p>\n<p>&nbsp;<\/p>\n<h4 class=\"rt-level-2\"><strong>Step 3: Check the Output<\/strong><\/h4>\n<p>Once the job completes, you will find:<\/p>\n<ul class=\"rt-list\">\n<li>A log file, e.g. aifs_single_1_12hr_test_output.log<\/li>\n<li>A PNG forecast figure saved under the figures\/ directory<\/li>\n<\/ul>\n<h2><\/h2>\n<h6 class=\"rt-level-2\"><strong>Additional Notes<\/strong><\/h6>\n<ul class=\"rt-list\">\n<li>This example uses the\u00a0<a href=\"https:\/\/huggingface.co\/ecmwf\/aifs-single-1.0\/blob\/main\/run_AIFS_v1.ipynb\">AIFS Single 1.0 inference notebook<\/a>, adapted to run in batch mode.<\/li>\n<li>Full documentation for the Anemoi framework is available at:\n<ul class=\"rt-list\">\n<li><a href=\"https:\/\/anemoi.readthedocs.io\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/en\/latest\/<\/a><\/li>\n<li>anemoi-datasets \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/datasets\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/datasets\/en\/latest\/<\/a><\/li>\n<li>anemoi-graphs \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/graphs\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/graphs\/en\/latest\/<\/a><\/li>\n<li>anemoi-inference \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/inference\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/inference\/en\/latest\/<\/a><\/li>\n<li>anemoi-models \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/models\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/models\/en\/latest\/<\/a><\/li>\n<li>anemoi-plugins \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/plugins\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/plugins\/en\/latest\/<\/a><\/li>\n<li>anemoi-registry \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/registry\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/registry\/en\/latest\/<\/a><\/li>\n<li>anemoi-training \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/training\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/training\/en\/latest\/<\/a><\/li>\n<li>anemoi-transform \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/transform\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/transform\/en\/latest\/<\/a><\/li>\n<li>anemoi-utils \u2013\u00a0<a href=\"https:\/\/anemoi.readthedocs.io\/projects\/utils\/en\/latest\/\">https:\/\/anemoi.readthedocs.io\/projects\/utils\/en\/latest\/<\/a><\/li>\n<\/ul>\n<\/li>\n<li>The versions currently installed are:\n<ul class=\"rt-list\">\n<li>anemoi-datasets 0.5.24<\/li>\n<li>anemoi-graphs 0.6.1<\/li>\n<li>anemoi-inference 0.4.9<\/li>\n<li>anemoi-models 0.3.1<\/li>\n<li>anemoi-plugins 0.1.0<\/li>\n<li>anemoi-registry 0.2.1<\/li>\n<li>anemoi-training 0.3.1<\/li>\n<li>anemoi-transform 0.1.10<\/li>\n<li>anemoi-utils 0.4.23<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This article is contributed by Robert Lee. Please contact the author directly for any AIFS related questions and comments. For all other RACC2 or research computing related queries, as always please raise them to the Digital Research Computing Team via the Self Service Portal.    AIFS\u202fSingle\u202fv1 is the first fully operational deterministic machine\u2011learning<\/p>\n","protected":false},"author":421,"featured_media":7848,"template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"__cvm_playback_settings":[],"__cvm_video_id":"","_links_to":"","_links_to_target":""},"kbe_taxonomy":[61],"kbe_tags":[],"class_list":["post-7846","kbe_knowledgebase","type-kbe_knowledgebase","status-publish","has-post-thumbnail","hentry","kbe_taxonomy-academic-cluster-articles"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.8.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AIFS Single 1.0 on RACC2 - Academic Computing Team<\/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:\/\/research.reading.ac.uk\/act\/knowledgebase\/aifs-on-racc2\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AIFS Single 1.0 on RACC2 - Academic Computing Team\" \/>\n<meta property=\"og:description\" content=\"This article is contributed by Robert Lee. 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