{"id":808,"date":"2016-07-21T14:25:55","date_gmt":"2016-07-21T18:25:55","guid":{"rendered":"http:\/\/carleton.ca\/scs\/?page_id=808"},"modified":"2025-05-09T14:38:22","modified_gmt":"2025-05-09T18:38:22","slug":"cuda-gpu-computing","status":"publish","type":"page","link":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/","title":{"rendered":"SCS GPU Computing with Openstack"},"content":{"rendered":"<h2>GPU Computing Introduction<\/h2>\n<p>The SCS GPU allow you to program using its CUDA (Compute Unified Device Architecture) cores. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia. The CUDA platform is accessible to software developers through CUDA-accelerated libraries, compiler directives, and extensions to industry-standard programming languages.<\/p>\n<p>GPU programming has been widely used in the area of Deep learning and have been applied to fields such as:<\/p>\n<ul>\n<li>computer vision,<\/li>\n<li>machine vision,<\/li>\n<li>speech recognition,<\/li>\n<li>natural language processing,<\/li>\n<li>audio recognition,<\/li>\n<li>social network filtering,<\/li>\n<li>machine translation,<\/li>\n<li>bioinformatics,<\/li>\n<li>drug design,<\/li>\n<li>medical image analysis,<\/li>\n<li>material inspection,<\/li>\n<li>board game programs.<\/li>\n<\/ul>\n<p>Deep learning have produced results comparable to and in some cases surpassing human expert performance.<\/p>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-gpu-hardware\" aria-expanded=\"false\" aria-controls=\"slideme-gpu-hardware\" class=\"slideme__heading slideme__trigger\">GPU Hardware<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-gpu-hardware\" aria-hidden=\"true\"><p><\/p>\n<p>The School has the following GPU hardware (January 2024):<\/p>\n<table style=\"border-collapse: collapse; width: 74.583%;\">\n<tbody>\n<tr>\n<td style=\"width: 35%;\"><strong>NVIDIA GPU<\/strong><\/td>\n<td style=\"width: 10%;\"><strong>VRAM<\/strong><\/td>\n<td style=\"width: 15%;\"><strong>CUDA Cores<\/strong><\/td>\n<td style=\"width: 15%;\"><strong>Tensor Cores<\/strong><\/td>\n<td style=\"width: 25%;\"><strong>Ray Tracing Cores<\/strong><\/td>\n<\/tr>\n<tr>\n<td>RTX 4090<\/td>\n<td>24<\/td>\n<td>16,384<\/td>\n<td>512<\/td>\n<td>176<\/td>\n<\/tr>\n<tr>\n<td>RTX 4070 Ti Super<\/td>\n<td>16<\/td>\n<td>8,448<\/td>\n<td>264<\/td>\n<td>66<\/td>\n<\/tr>\n<tr>\n<td>A16<\/td>\n<td>16<\/td>\n<td>1,280<\/td>\n<td>40<\/td>\n<td>10<\/td>\n<\/tr>\n<tr>\n<td>RTX 3060 Ti<\/td>\n<td>8<\/td>\n<td>4,864<\/td>\n<td>152<\/td>\n<td>38<\/td>\n<\/tr>\n<tr>\n<td>RTX 3060<\/td>\n<td>12<\/td>\n<td>3,584<\/td>\n<td>112<\/td>\n<td>28<\/td>\n<\/tr>\n<tr>\n<td>Titan V<\/td>\n<td>12<\/td>\n<td>5,120<\/td>\n<td>640<\/td>\n<td>0<\/td>\n<\/tr>\n<tr>\n<td>RTX 2080 SUPER<\/td>\n<td>8<\/td>\n<td>3,072<\/td>\n<td>384<\/td>\n<td>48<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><\/p>\n<p>The school has various VM flavors that assign the number of vCPU&#8217;s, memory and disk space. Virtual machines are provisioned using the school&#8217;s Openstack cloud.<\/p>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-request-a-gpu-virtual-machine\" aria-expanded=\"false\" aria-controls=\"slideme-request-a-gpu-virtual-machine\" class=\"slideme__heading slideme__trigger\">Request a GPU virtual machine<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-request-a-gpu-virtual-machine\" aria-hidden=\"true\"><p><\/p>\n<p>Students currently taking a course that requires a GPU account can fill out this form to request a GPU VM:<\/p>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/tech-support\/scs-open-stack\/scs-gpu-request-form\/\" target=\"_blank\" rel=\"noopener noreferrer\">SCS GPU Request Form<\/a><\/li>\n<\/ul>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-accounts\" aria-expanded=\"false\" aria-controls=\"slideme-accounts\" class=\"slideme__heading slideme__trigger\">Accounts<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-accounts\" aria-hidden=\"true\"><p><\/p>\n<p>You will need the following accounts to use the SCS GPU VM&#8217;s:<\/p>\n<ol>\n<li>MyCarletonOne account account (university wide or ITS account) &#8211; needed to<a href=\"https:\/\/carleton.ca\/its\/help-centre\/remote-access\/\" target=\"_blank\" rel=\"noopener noreferrer\"> VPN<\/a><\/li>\n<li>GPU VM account &#8211; created by the SCS Tech Staff<\/li>\n<\/ol>\n<blockquote><p>Please note the GPU account is a local account and you are responsible for your own backups!<\/p><\/blockquote>\n<p><strong>More Account information:<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/tech-support\/accounts\/\">SCS Accounts<\/a><\/li>\n<\/ul>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-change-your-default-password\" aria-expanded=\"false\" aria-controls=\"slideme-change-your-default-password\" class=\"slideme__heading slideme__trigger\">Change your default Password<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-change-your-default-password\" aria-hidden=\"true\"><p><\/p>\n<p>Please change your default GPU VM password once you login. The simplest way to do that in Linux is to:<\/p>\n<ol>\n<li>login to your Linux VM<\/li>\n<li>start an xterminal or command windows<\/li>\n<li>at the command prompt type &#8216;passwd&#8217; and follow the instructions<\/li>\n<\/ol>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-openstack-gpu-virtual-machine-images\" aria-expanded=\"false\" aria-controls=\"slideme-openstack-gpu-virtual-machine-images\" class=\"slideme__heading slideme__trigger\">Openstack GPU Virtual Machine Images<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-openstack-gpu-virtual-machine-images\" aria-hidden=\"true\"><p><\/p>\n<p>Specific help for an Open Stack image:<\/p>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/scs-gpu-vm-2024-5\/\" target=\"_blank\" rel=\"noopener noreferrer\">SCS GPU VM Fall 2024-5<\/a><\/li>\n<\/ul>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-accessing-the-gpu-servers\" aria-expanded=\"false\" aria-controls=\"slideme-accessing-the-gpu-servers\" class=\"slideme__heading slideme__trigger\">Accessing the GPU Servers<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-accessing-the-gpu-servers\" aria-hidden=\"true\"><p><\/p>\n<blockquote><p>Note that you require VPN for remote accessing your instances! &#8211; <a href=\"https:\/\/carleton.ca\/its\/help-centre\/remote-access\/\" target=\"_blank\" rel=\"noopener noreferrer\">Remote Access &#8211; VPN<\/a><\/p><\/blockquote>\n<p>You can access the GPU&#8217;s as follows:<\/p>\n<ol>\n<li>Using a remote desktop<\/li>\n<li>using a command line ssh client<\/li>\n<\/ol>\n<h4>Logging in using x2go (remote desktop)<\/h4>\n<p>The preferred way to access the GPU server is to VPN to Carleton or use a lab on campus such as the <a href=\"https:\/\/carleton.ca\/scs\/technical-support\/computer-laboratories\/\">SCS Computer labs <\/a>and then remote desktop (x2go) directly to the server (see diagram). The x2go session will give you a full GUI desktop. Detailed x2go instructions are here:<\/p>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/tech-support\/scs-open-stack\/openstack-technical-support\/x2go\/\" target=\"_blank\" rel=\"noopener noreferrer\">x2go Remote Desktop Client<\/a><\/li>\n<\/ul>\n<h4>Logging in using ssh (command line)<\/h4>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/2019\/connecting-to-openstack-instances-ssh-with-putty\/\">Openstack \u2013 Connecting to an Instance \u2013 SSH (putty)<\/a><\/li>\n<li><a href=\"https:\/\/carleton.ca\/scs\/tech-support\/secure-shell-ssh\/\" target=\"_blank\" rel=\"noopener noreferrer\">Secure Shell (ssh)<\/a><\/li>\n<\/ul>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-backing-up-files\" aria-expanded=\"false\" aria-controls=\"slideme-backing-up-files\" class=\"slideme__heading slideme__trigger\">Backing up Files<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-backing-up-files\" aria-hidden=\"true\"><p><\/p>\n<p>Once the VM is shut down it no longer exists so its important to backup your files especially once you have completed your experiments.<\/p>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/technical-support\/backups\/\" target=\"_blank\" rel=\"noopener noreferrer\">Backing up files<\/a><\/li>\n<\/ul>\n<p><\/p><\/dd><dl><\/div>\n<div class=\"slideme\"><dl class=\"slideme__list\"><dt class=\"slideme__term\"><a href=\"#slideme-when-you-are-finished\" aria-expanded=\"false\" aria-controls=\"slideme-when-you-are-finished\" class=\"slideme__heading slideme__trigger\">When you are finished<\/a><\/dt><dd class=\"slideme__description\" id=\"slideme-when-you-are-finished\" aria-hidden=\"true\"><p><\/p>\n<p>Every GPU VM has an expiry date.\u00a0Once you completed your GPU experiments and you have <strong>backed up your files<\/strong> your VM can be terminated. Please note once your VM is terminated it cannot be recovered.<\/p>\n<blockquote><p>If you finish your experiments before your VM expiry date please let us know. This will allow another student the opportunity to use your GPU.<\/p><\/blockquote>\n<p>To help us improve our service, please fill out this exit questionnaire once you are finished:<\/p>\n<ul>\n<li><a href=\"https:\/\/carleton.ca\/scs\/scs-forms\/scs-gpu-exit-questionnaire\/\" target=\"_blank\" rel=\"noopener noreferrer\">SCS GPU Exit Questionnaire<\/a><\/li>\n<\/ul>\n<p><\/p><\/dd><dl><\/div>\n<p><\/p>\n<p><a href=\"https:\/\/youtu.be\/h9Z4oGN89MU?si=EiKgLPC7Nl7SdTEv\" class=\"ccms__fancybox\" data-caption=\"How do Graphics Cards Work? Exploring GPU Architecture (YouTube)\">How do Graphics Cards Work? Exploring GPU Architecture (YouTube)<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>GPU Computing Introduction The SCS GPU allow you to program using its CUDA (Compute Unified Device Architecture) cores. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia. The CUDA platform is accessible to software developers through CUDA-accelerated libraries, compiler directives, and extensions to industry-standard programming languages. GPU programming has [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"parent":6535,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>SCS GPU Computing with Openstack - School of Computer Science<\/title>\n<meta name=\"description\" content=\"GPU Computing Introduction The SCS GPU allow you to program using its CUDA (Compute Unified Device Architecture) cores. CUDA is a parallel computing\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/\",\"url\":\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/\",\"name\":\"SCS GPU Computing with Openstack - School of Computer Science\",\"isPartOf\":{\"@id\":\"https:\/\/carleton.ca\/scs\/#website\"},\"datePublished\":\"2016-07-21T18:25:55+00:00\",\"dateModified\":\"2025-05-09T18:38:22+00:00\",\"description\":\"GPU Computing Introduction The SCS GPU allow you to program using its CUDA (Compute Unified Device Architecture) cores. CUDA is a parallel computing\",\"breadcrumb\":{\"@id\":\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/carleton.ca\/scs\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Technical Support\",\"item\":\"https:\/\/carleton.ca\/scs\/tech-support\/\"},{\"@type\":\"ListItem\",\"position\":3,\"name\":\"SCS GPU Computing with Openstack\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/carleton.ca\/scs\/#website\",\"url\":\"https:\/\/carleton.ca\/scs\/\",\"name\":\"School of Computer Science\",\"description\":\"Carleton University\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/carleton.ca\/scs\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"SCS GPU Computing with Openstack - School of Computer Science","description":"GPU Computing Introduction The SCS GPU allow you to program using its CUDA (Compute Unified Device Architecture) cores. CUDA is a parallel computing","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/","twitter_misc":{"Est. reading time":"3 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/","url":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/","name":"SCS GPU Computing with Openstack - School of Computer Science","isPartOf":{"@id":"https:\/\/carleton.ca\/scs\/#website"},"datePublished":"2016-07-21T18:25:55+00:00","dateModified":"2025-05-09T18:38:22+00:00","description":"GPU Computing Introduction The SCS GPU allow you to program using its CUDA (Compute Unified Device Architecture) cores. CUDA is a parallel computing","breadcrumb":{"@id":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/carleton.ca\/scs\/"},{"@type":"ListItem","position":2,"name":"Technical Support","item":"https:\/\/carleton.ca\/scs\/tech-support\/"},{"@type":"ListItem","position":3,"name":"SCS GPU Computing with Openstack"}]},{"@type":"WebSite","@id":"https:\/\/carleton.ca\/scs\/#website","url":"https:\/\/carleton.ca\/scs\/","name":"School of Computer Science","description":"Carleton University","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/carleton.ca\/scs\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"en-US"}]}},"acf":{"banner_image_type":"upload","banner_uploaded_image":{"ID":15557,"id":15557,"title":"RTX3090 component","filename":"rtx3090-2-1600x700-1.jpg","filesize":437225,"url":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1.jpg","link":"https:\/\/carleton.ca\/scs\/tech-support\/cuda-gpu-computing\/rtx3090-2-1600x700\/","alt":"RTX3090 component","author":"7","description":"RTX3090 component","caption":"","name":"rtx3090-2-1600x700","status":"inherit","uploaded_to":808,"date":"2022-09-20 18:28:47","modified":"2022-09-20 18:29:14","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/carleton.ca\/scs\/wp\/wp-includes\/images\/media\/default.png","width":1600,"height":700,"sizes":{"thumbnail":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-160x70.jpg","thumbnail-width":160,"thumbnail-height":70,"medium":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-240x105.jpg","medium-width":240,"medium-height":105,"medium_large":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-768x336.jpg","medium_large-width":768,"medium_large-height":336,"large":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-400x175.jpg","large-width":400,"large-height":175,"gallery-thumb":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-300x230.jpg","gallery-thumb-width":300,"gallery-thumb-height":230,"1536x1536":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-1536x672.jpg","1536x1536-width":1536,"1536x1536-height":672,"2048x2048":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1.jpg","2048x2048-width":1600,"2048x2048-height":700,"banner":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1.jpg","banner-width":1600,"banner-height":700,"people":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-200x200.jpg","people-width":200,"people-height":200,"post-thumb":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-300x230.jpg","post-thumb-width":300,"post-thumb-height":230,"rotator-image":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-800x600.jpg","rotator-image-width":800,"rotator-image-height":600,"video-thumb":"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/rtx3090-2-1600x700-1-360x158.jpg","video-thumb-width":360,"video-thumb-height":158}},"banner_opacity":"dark","banner_button":"no"},"_links":{"self":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/808"}],"collection":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/comments?post=808"}],"version-history":[{"count":4,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/808\/revisions"}],"predecessor-version":[{"id":21085,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/808\/revisions\/21085"}],"up":[{"embeddable":true,"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/pages\/6535"}],"wp:attachment":[{"href":"https:\/\/carleton.ca\/scs\/wp-json\/wp\/v2\/media?parent=808"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}