{"id":15202,"date":"2025-04-17T08:00:02","date_gmt":"2025-04-17T06:00:02","guid":{"rendered":"https:\/\/ucit.fr\/?p=15202"},"modified":"2025-05-14T13:54:20","modified_gmt":"2025-05-14T11:54:20","slug":"defining-requirements-next-hpc-cluster","status":"publish","type":"post","link":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/","title":{"rendered":"Defining the requirements of your next HPC cluster"},"content":{"rendered":"<p><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-1\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\"><p><\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-2 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-2\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-1 fusion-sep-none fusion-title-text fusion-title-size-one\"><h1 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;--fontSize:64.6;line-height:1.4;\">Defining the requirements <span style=\"font-family: var(--h1_typography-font-family); font-size: 1em; font-style: var(--h1_typography-font-style,normal); font-weight: var(--h1_typography-font-weight); letter-spacing: var(--h1_typography-letter-spacing); text-transform: var(--h1_typography-text-transform);\">of your next HPC cluster<\/span><\/h1><\/div><div class=\"elegant-image elegant-image-0 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"elegant-empty-space space-vertical fusion-clearfix \" style=\"height:80px;\"><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-3 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling hover-opacity gradient-container-3\" style=\"--awb-border-radius-top-left:20px;--awb-border-radius-top-right:20px;--awb-border-radius-bottom-right:20px;--awb-border-radius-bottom-left:20px;--awb-overflow:hidden;--awb-padding-top:0px;--awb-padding-bottom:0px;--awb-margin-top:0px;--awb-margin-bottom:0px;--awb-background-image:linear-gradient(180deg, var(--awb-color7) 0%,rgba(37,70,135,0.49) 100%);--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-2 fusion_builder_column_2_5 2_5 fusion-flex-column fusion-flex-align-self-center fusion-column-inner-bg-wrapper\" style=\"--awb-padding-top:0px;--awb-padding-right:0px;--awb-padding-bottom:0px;--awb-padding-left:0px;--awb-inner-bg-size:cover;--awb-width-large:40%;--awb-margin-top-large:0px;--awb-spacing-right-large:0px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:0px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><span class=\"fusion-column-inner-bg hover-type-none\"><a class=\"fusion-column-anchor\" href=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/Article-Defining-your-future-cluster.pdf\" rel=\"noopener noreferrer\" target=\"_blank\" aria-label=\"Download article in pdf\"><span class=\"fusion-column-inner-bg-image\"><\/span><\/a><\/span><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-center fusion-content-layout-column\"><i class=\"fb-icon-element-1 fb-icon-element fontawesome-icon fa-file-pdf fas circle-yes\" style=\"--awb-iconcolor:#ffffff;--awb-iconcolor-hover:#ffffff;--awb-circlebordersize:1px;--awb-font-size:82.72px;--awb-width:165.44px;--awb-height:165.44px;--awb-line-height:163.44px;--awb-align-self:flex-end;--awb-margin-top:0px;--awb-margin-right:0px;--awb-margin-bottom:0px;--awb-margin-left:0px;\"><\/i><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-3 fusion_builder_column_3_5 3_5 fusion-flex-column fusion-flex-align-self-center fusion-column-inner-bg-wrapper\" style=\"--awb-padding-top:0px;--awb-padding-right:0px;--awb-padding-bottom:0px;--awb-padding-left:0px;--awb-inner-bg-size:cover;--awb-width-large:60%;--awb-margin-top-large:15px;--awb-spacing-right-large:0px;--awb-margin-bottom-large:0px;--awb-spacing-left-large:0px;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><span class=\"fusion-column-inner-bg hover-type-none\"><a class=\"fusion-column-anchor\" href=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/Article-Defining-your-future-cluster.pdf\" rel=\"noopener noreferrer\" target=\"_blank\" aria-label=\"Download article in pdf\"><span class=\"fusion-column-inner-bg-image\"><\/span><\/a><\/span><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-2\" style=\"--awb-content-alignment:left;--awb-font-size:40px;--awb-text-color:#ffffff;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Download to read offline!<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-4 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-4\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-margin-top:60px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-4 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-2 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-font-size:42px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:42;line-height:1.4;\">Why planning for your next HPC cluster is more challenging than ever<\/h2><\/div><div class=\"fusion-text fusion-text-3\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Your old cluster is approaching its limits. GPUs are in demand, workloads are shifting, and AI\u2019s knocking at the door\u2026 how do you plan what\u2019s next?<\/p>\n<p style=\"font-family: Roboto; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"300\"><span style=\"font-family: Roboto; font-weight: bold; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Replacing an HPC cluster today isn\u2019t just about adding more power. It\u2019s about making the right choices in a fast-changing environment: balancing HPC and AI needs, defining the right balance between cloud and on-prem, selecting the right hardware amongst a myriad of options, and ensuring cost-efficiency\u2026 all while keeping an eye on sustainability. How can you future-proof your next investment?<\/span><\/p>\n<p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">You\u2019ve probably realized this already: workloads are changing. Traditional HPC applications like simulations and modeling now run alongside AI and data analytics, requiring different types of compute power. Should your next cluster focus solely on CPUs, or should it include GPUs and accelerators optimized for AI?<\/p>\n<p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">And the hardware question doesn\u2019t stop there. Today the choice isn\u2019t just between Intel and AMD anymore: ARM is gaining traction, and specialized processors offer new possibilities. The right decision depends on compatibility, power efficiency, and how your workloads behave. Storage, networking, and job schedulers play a critical role in performance: they add complexity to the architectural equation.<\/p>\n<p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Costs are another major factor. Many clusters suffer from inefficiencies, with idle resources leading to wasted computing power. At the same time, cloud computing offers scalability but comes with financial trade-offs. Should you keep everything on-prem, move to the cloud, or adopt a hybrid model?<\/p>\n<p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Finally, sustainability has become a growing priority. With rising energy costs and environmental concerns, organizations need to measure and optimize their cluster\u2019s carbon footprint (now a legal obligation in many regions). Power consumption, cooling strategies, and workload distribution all impact long-term efficiency. How will you approach these choices?<\/p>\n<p style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">In this article, we\u2019ll break down the key questions to ask when planning your next HPC cluster.<\/p>\n<\/div><div class=\"elegant-empty-space space-vertical fusion-clearfix \" style=\"height:80px;\"><\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-5 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-5\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-margin-top:60px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-5 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-3 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-font-size:42px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:42;line-height:1.4;\">1) Analyzing your needs<\/h2><\/div><div class=\"fusion-title title fusion-title-4 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.1) A picture of the present\u2026<\/h3><\/div><div class=\"fusion-text fusion-text-4\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Choosing your next HPC cluster starts with understanding how your current one is being used. By analyzing today\u2019s workloads, you can paint a relevant picture of the present situation: one that will help you align future infrastructure with evolving needs.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">The best way to assess the current state of your cluster and its usage is through actual data. This is where cluster logs come in handy: they contain a wealth of insights about how your infrastructure is performing, how resources are allocated, and where inefficiencies might lie.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">At UCit, we use <\/span><a href=\"https:\/\/oka.how\" target=\"_blank\" rel=\"noopener noreferrer\"><u><b style=\"font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">OKA<\/b><\/u><\/a><span style=\"font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> to ingest anonymized cluster logs and display them in easy-to-read dashboards. But you can also use other tools such as Grafana, Tableau, or even Excel to visualize the data and extract meaningful trends.<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">At this stage, the main questions we want to answer are:<\/p>\n<ul>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">What is the overall load of the cluster today?<\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> <i>\u2192 This will help understand the need for infrastructure adaptations overall.<\/i><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Which workload types are dominant? (AI, simulations, data analytics, etc.)<\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> <i>\u2192 This will help evaluate how to distribute computing resources (CPU vs GPU, etc.).<\/i><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Where are your workloads running? How are cluster resources allocated, and are they used efficiently?<\/span><b> <\/b><\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i>\u2192 This will help identify optimizations in workload execution.<\/i><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Are there any signs of an inefficient\/waste use of resources from your users?<\/span><b> <\/b><\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i>\u2192 This will help assess the potential waste of resources due to a lack of training or scheduler misconfiguration.<\/i><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Do certain workloads have specific needs?<\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> <i>\u2192 This will help adapt resources for your future clusters, and help you choose which workload should run where.<\/i><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Are there recurring workload peaks or underutilized periods?<\/span> <i><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">\u2192<\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-size: var(--awb-font-size); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> This will help determine the right mix of fixed on-premise resources vs. variable cloud resources.<\/span><\/i><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">For each of these questions, there are probably a dozen ways to play with cluster data and reach a valuable insight. Let\u2019s break some of them down.<\/p>\n<\/div><div class=\"fusion-text fusion-text-5\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-size: var(--awb-font-size); font-style: normal; letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); color: #706f6f;\">To do this, we\u2019ll take a typical example: say your organization runs different types of computations\u2014fluid dynamics simulations (CFD), engineering analytics, and machine learning models for predictive maintenance.<\/span><\/p>\n<ul>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\"><span style=\"font-family: Roboto; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><u><span style=\"color: #706f6f; font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">CFD simulations<\/span><\/u><\/span><span style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px; color: #706f6f;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: R&amp;D teams rely heavily on computational fluid dynamics to model aerodynamics for product design. These workloads are CPU-intensive, often requiring high-memory nodes with high-speed interconnects. They also generate large amounts of output data that need to be stored and post-processed.<\/span><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\"><span style=\"font-family: Roboto; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><u><span style=\"color: #706f6f; font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Engineering analytics<\/span><\/u><\/span><span style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px; color: #706f6f;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: operational teams use data analytics to evaluate product performance, optimize manufacturing processes, and assess material fatigue. These workloads are less computationally heavy but require quick access to historical datasets.<\/span><\/span><\/li>\n<li><span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\"><span style=\"font-family: Roboto; letter-spacing: 0px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><u><span style=\"color: #706f6f; font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">AI for predictive maintenance<\/span><\/u><\/span><span style=\"font-family: Roboto; font-weight: 400; letter-spacing: 0px; color: #706f6f;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: the organization has started integrating machine learning models to predict equipment failures and optimize maintenance schedules. These AI workloads benefit from GPU acceleration but don\u2019t run continuously\u2014they are triggered periodically based on new sensor data.<\/span><\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-6\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><\/div><div class=\"fusion-title title fusion-title-5 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.1.1) Analyzing total cluster load<\/h4><\/div><div class=\"fusion-text fusion-text-7\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Before diving into a detailed workload analysis, it\u2019s important to step back and assess the overall load on your cluster. This gives you a high-level understanding of how much your infrastructure is being used, whether it meets current demand, and where potential bottlenecks or inefficiencies exist.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A global view of cluster activity helps answer key questions:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">How much of your total compute power is actively used?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Are resources consistently maxed out, or are there idle periods?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Are there recurring congestion points in your queues?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">How does cluster usage translate into costs, energy consumption, and carbon footprint?<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">With OKA\u2019s Load panel for example, you can track how compute resources are being used across different timeframes. This panel provides a clear breakdown of core utilization, GPU allocation, and queue congestion.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">In the example below, we can see the core usage over time:<\/p>\n<\/div><div class=\"elegant-image elegant-image-1 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-load-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-load-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-8\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span style=\"font-family: Roboto; font-weight: 100; font-size: 16px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\">OKA&#8217;s Load panel<\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-9\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">This type of view helps determine if the cluster is adequately used, and can also give us hints to know if it is adequately sized. If demand consistently exceeds capacity, additional nodes or workload rebalancing may be required. Conversely, if significant idle time exists, it may indicate over-provisioning or an opportunity to shift workloads dynamically to the cloud.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If peak loads consistently overwhelm the cluster, this justifies expanding resources\u2014whether by adding on-prem nodes or bursting to the cloud. If demand fluctuates widely, a hybrid HPC approach could optimize efficiency and costs.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-6 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.1.2) Analyzing workload distribution<\/h4><\/div><div class=\"fusion-text fusion-text-10\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">The next question to ask is: what types of workloads are consuming your cluster\u2019s resources?<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">To answer this, you can break down the distribution of workloads across different job types in terms of:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Number of jobs submitted \u00e0 Which workloads dominate in terms of job count?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Compute resources used (core-hours, GPU-hours, memory) \u00e0 Which workloads are the most resource-intensive?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Cost impact \u00e0 How much does each workload type contribute to the overall cost of running the cluster?<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Getting this information from your logs is very easy to do using OKA\u2019s Resources panel:<\/p>\n<\/div><div class=\"elegant-image elegant-image-2 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-resources-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-resources-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-11\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span style=\"font-family: Roboto; font-weight: 100; font-size: 16px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\">OKA&#8217;s Resources panel<\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-12\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">For example, let\u2019s assume your analysis reveals the following:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">70% of jobs are traditional HPC simulations (CFD, FEA, molecular dynamics, etc.), running mostly on CPUs.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">20% are engineering analytics, which use moderate CPU resources but require significant storage capacity.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">10% are AI workloads, mostly deep learning training jobs running on GPUs.<\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-13\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">This breakdown helps you see if your current cluster is well-aligned with actual usage. If AI workloads are increasing but you have limited GPU availability, this could indicate a need for more GPU-accelerated resources in your next cluster.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-7 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.1.3) What are your workloads running on?<\/h4><\/div><div class=\"fusion-text fusion-text-14\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Once you understand what is running, the next step is to analyze how the scheduler handled workload placement. Are workloads optimally placed on the right hardware?<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">With OKA\u2019s Resources panel, you can categorize jobs based on the type of nodes or instances they ran on.<\/p>\n<\/div><div class=\"elegant-image elegant-image-3 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-resources-panel-grouping.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-resources-panel-grouping.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-15\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span style=\"font-family: Roboto; font-weight: 100; font-size: 16px;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\">OKA&#8217;s Resources panel with grouping<\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-16\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">This allows you to:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Identify if workloads are running on the appropriate compute nodes (e.g., GPU workloads on GPU nodes).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">See if any workloads are running on overpowered or underutilized hardware (e.g., simple data analysis jobs consuming high-memory compute nodes).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">We could also think of ways to detect whether workloads are spilling over to cloud instances and if those cloud resources are cost-justified.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"fusion-text fusion-text-17\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\">For the sake of our example, the analysis may show that:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Most CFD workloads run on high-core-count CPU nodes, but some large simulations are also using GPU nodes unnecessarily.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">AI training jobs run on GPUs, but demand often exceeds available GPU capacity, leading to jobs sitting in queues.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A portion of batch analytics jobs are running on expensive compute nodes, when they could be handled by lower-tier instances.<\/span><br \/>\n<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\">This data allows you to optimize workload placement and identify whether your next cluster should maintain the same balance or shift toward different configurations.<\/span><\/p>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-18\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><div><span style=\"letter-spacing: normal;\">\u00a0<\/span><\/div>\n<\/div><div class=\"fusion-title title fusion-title-8 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.1.4) Detecting wasted resources<\/h4><\/div><div class=\"fusion-text fusion-text-19\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A critical part of workload analysis is identifying wasted resources. Inefficiencies in job scheduling, poorly configured job submissions, and failed jobs can lead to significant waste.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">For example, OKA\u2019s Consumers panel helps pinpoint inefficiencies by listing users with the highest number of timed out jobs:<\/p>\n<\/div><div class=\"elegant-image elegant-image-4 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-consumers-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-consumers-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-20\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">Consumers<\/span><span style=\"letter-spacing: 0px;\"> panel<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-21\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Timed out jobs are particularly costly because they consume compute resources without delivering results.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">You can go further by analyzing the distribution of job states:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Completed jobs: delivered results successfully.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Failed jobs: consumed resources but failed before completion.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Cancelled jobs: stopped before consuming full resources.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Timed out jobs: reached their runtime limit without finishing, wasting the allocated resources.<\/span><\/li>\n<\/ul>\n<p><span style=\"letter-spacing: normal;\">\u00a0<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">In OKA\u2019s State panel, you can display the total workload distribution in both number of jobs and core-hours:<\/p>\n<\/div><div class=\"elegant-image elegant-image-5 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-state-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-state-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-22\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">State<\/span><span style=\"letter-spacing: 0px;\"> panel<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-23\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Toggling on the \u201cCost\u201d switch can reveal a completely different story: despite \u201cnon-completed\u201d jobs representing only 24% of the total amount of jobs, they cost your organization more than 54% of the total spending:<\/p>\n<\/div><div class=\"elegant-image elegant-image-6 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-state-panel-costs.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-state-panel-costs.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-24\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">State<\/span><span style=\"letter-spacing: 0px;\"> panel (toggled to Costs)<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-25\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By making good use of the Cost toggle switch, you can quantify the impact of these wasted jobs in real monetary terms. Our example suggests a need for better job scheduling policies, user training, or improved job runtime estimates.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-9 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.1.5) Analyzing peaks, dips and congestion in workload demand<\/h4><\/div><div class=\"fusion-text fusion-text-26\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Understanding when workloads peak and dip helps determine if your cluster is properly sized. If demand fluctuates significantly, a mix of fixed and cloud resources might be necessary.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Using OKA\u2019s Load and Throughput panels, you can:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Pinpoint peak activity periods: identify when compute demand is highest and whether resources are sufficient.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Analyze queue times: see how long jobs wait before execution, indicating potential bottlenecks.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Assess overall resource utilization: determine if the cluster is underutilized at certain times.<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Here is the cluster\u2019s throughput across a long period of time:<\/p>\n<\/div><div class=\"elegant-image elegant-image-7 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-throughput-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-throughput-panel.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-27\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">Throughput<\/span><span style=\"letter-spacing: 0px;\"> panel<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-28\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">And here is the same view, per hour of the day:<\/p>\n<\/div><div class=\"elegant-image elegant-image-8 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-throughput-panel-time.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-throughput-panel-time.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-29\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">Throughput<\/span><span style=\"letter-spacing: 0px;\"> panel (per submission time)<\/span><\/span><\/span><\/i><\/p>\n<p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">\u00a0<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-30\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\">For example, your analysis might show:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Heavy simulation workloads during weekdays, with underutilization on weekends.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Same pattern for certain hours of the day.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Frequent job queuing due to resource contention, leading to inefficiencies.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">AI training jobs creating occasional bursts in GPU demand, exceeding available resources. <\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-31\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Additionally, assessing cluster congestion is essential, helping assess whether resources are consistently maxed out. If congestion levels are frequently high, this could justify additional hardware investment or better job scheduling policies.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">OKA\u2019s Congestion panel provides a comparative look at the cluster\u2019s load:<\/p>\n<\/div><div class=\"elegant-image elegant-image-9 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-congestion-contention.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-congestion-contention.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-32\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">Congestion\/Contention<\/span><span style=\"letter-spacing: 0px;\"> panel<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-33\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"color: #24587a; letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">On this instant view, each dot represents a day, and you can see how the cluster\u2019s load is distributed in the various load quadrants (Optimal, Acceptable, Congestion, Contention).<\/p>\n<p style=\"color: #24587a; letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Congestion<\/span><span style=\"font-weight: 400; letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> arises when a cluster underutilizes its resources, leaving jobs waiting in queues despite available computing capacity. It simply means that you still have resources that could be used for those jobs in queue but for whatever reason, the cluster does not allocate these jobs to free resources.<\/span><\/p>\n<p style=\"color: #24587a; letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-weight: 400; letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">On the contrary, <\/span><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Contention<\/span><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"> occurs when the cluster operates at peak capacity, yet fails to meet the surging demand for resources, causing queues to pile up.<\/span><\/p>\n<p style=\"color: #24587a; letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">This other view shows the evolution of the cluster state over time:<\/p>\n<\/div><div class=\"elegant-image elegant-image-10 elegant-align-center \"><div class=\"elegant-image-wrapper\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-congestion-contention-time.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><div class=\"elegant-image-blur-shadow\"><img decoding=\"async\" src=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-congestion-contention-time.jpg\" alt=\"\" style=\"width:800px;\"\/><\/div><style type=\"text\/css\"><\/style><\/div><div class=\"fusion-text fusion-text-34\" style=\"--awb-content-alignment:center;--awb-font-size:18px;--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><i><span data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"100\"><span style=\"font-size: medium;\"><span style=\"letter-spacing: 0px;\">OKA&#8217;s <\/span><span style=\"letter-spacing: normal;\">Congestion\/Contention<\/span><span style=\"letter-spacing: 0px;\"> panel (over time)<\/span><\/span><\/span><\/i><\/p>\n<\/div><div class=\"fusion-text fusion-text-35\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">For example, by analyzing different time frames, we can observe whether the cluster is spending increasing amounts of time in a congestion state. This could indicate that resource demand typology is mismatched with availability, leading to longer queue times and reduced throughput: suggesting that a redefinition of existing resource typology is needed.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Additionally, contention may occur when demand typology aligns well with existing resource, but too little of these resources are available: suggesting that an expansion of existing resources is needed.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If congestion and\/or contention trends are worsening over months or years, it may signal the need to expand capacity, adjust job scheduling policies, reconsider current mix of resource types available, or optimize workload distribution between on-premises and cloud resources.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-10 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">1.2) \u2026to plan for the future<\/h3><\/div><div class=\"fusion-text fusion-text-36\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Now that you understand the past better, let\u2019s build the future.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By analyzing real usage data and projecting future needs, you can build an infrastructure that is not only more powerful but also better suited to your actual workloads.<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-6 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-6\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-margin-top:60px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-6 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-11 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-font-size:42px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:42;line-height:1.4;\">2) Choosing the infrastructure: a workload-based approach<\/h2><\/div><div class=\"fusion-text fusion-text-37\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">With this macro analysis of the present in hand, the next step is to align workloads with infrastructure choices. Should your new cluster maintain the same balance of resources, or should it shift based on evolving needs?<\/span><\/p>\n<\/div><div class=\"fusion-text fusion-text-38\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\">Let\u2019s go back to our example:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">CFD simulations<\/span><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: these workloads are CPU-intensive, requiring high-memory nodes with strong interconnects. Their compute demand is relatively stable but generates large amounts of data that must be stored and post-processed.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Engineering analytics<\/span><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: these jobs require moderate computing power but significant storage and fast access to historical data.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">AI for predictive maintenance<\/span><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: these workloads benefit from GPU acceleration but don\u2019t run continuously. They create bursts in demand, particularly when retraining models or processing new sensor data.<\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-39\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Now, let\u2019s break down how these insights guide your infrastructure decisions.<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">\u00a0<\/span><\/p>\n<\/div><div class=\"fusion-title title fusion-title-12 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.1) Sizing the cluster(s)<\/h3><\/div><div class=\"fusion-text fusion-text-40\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">When deciding on the size and structure of an HPC cluster, it\u2019s crucial to balance performance, scalability, and cost. A miscalculated approach can lead to wasted resources, excessive waiting times, or an infrastructure that fails to keep up with growing demands.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">To define the right cluster size, you need to evaluate:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Overall compute power needed (based on past and projected workloads).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Single vs multiple clusters (should you consolidate or separate workloads?).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Geographical distribution (local vs remote vs cloud resources).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Scalability over time (how flexible does the infrastructure need to be?).<\/span><\/li>\n<\/ul>\n<p><span style=\"letter-spacing: normal;\">\u00a0<\/span><\/p>\n<\/div><div class=\"fusion-title title fusion-title-13 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.1.1) Defining the total compute power needed<\/h4><\/div><div class=\"fusion-text fusion-text-41\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">The first step is to assess the total amount of computing resources required to meet workload demands. This means calculating:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">CPU &amp; GPU requirements<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: how many core-hours and GPU-hours do your workloads consume today? Do you need to accommodate growth?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Memory &amp; storage needs<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: what are the RAM and disk space requirements for different job types?<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Network &amp; interconnect speeds<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: how critical is low-latency communication between nodes?<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Looking at historical job data (e.g., job logs, usage patterns) can help identify:<\/span><\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Baseline usage<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: the minimum required compute capacity to support day-to-day operations.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Peak demand<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: the maximum resources used during the busiest periods (important to avoid bottlenecks).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Trends over time<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: growth in job submissions, increased use of AI, or other shifts in workload demands.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">OKA can help provide these insights by analyzing past cluster activity and estimating future needs.<\/span><\/p>\n<p>&nbsp;<\/p>\n<\/div><div class=\"fusion-title title fusion-title-14 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.1.2) Should you have one large cluster or multiple clusters?<\/h4><\/div><div class=\"fusion-text fusion-text-42\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Organizations often debate whether to consolidate all workloads into a single, shared cluster or to split resources across multiple specialized clusters. The right choice depends on:<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Diversity of workloads<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: if workloads have highly different needs (e.g., CFD vs AI vs data analytics), separate clusters may be more efficient.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">User policies<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: some organizations prefer to separate internal R&amp;D from production workloads.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Resource allocation &amp; fairness<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: in a shared cluster, job scheduling must be carefully optimized to avoid one group monopolizing resources.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"fusion-text fusion-text-43\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\"><u>Example scenarios:<\/u><\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">A single cluster<\/span><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: best for homogeneous workloads, centralized management, and shared high-speed interconnects.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Multiple clusters<\/span><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: recommended when workloads have distinct compute\/storage needs, or when different departments require separate policies, or when using Cloud compute resources.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">A hybrid model<\/span><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: a large central cluster for general workloads, with smaller clusters (or cloud bursting) for specific use cases. <\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-44\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><\/div><div class=\"fusion-title title fusion-title-15 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.1.3) Where should the compute resources be located?<\/h4><\/div><div class=\"fusion-text fusion-text-45\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">HPC clusters can be fully on-premises, distributed across multiple sites, or leveraging cloud resources. <span style=\"font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\">Key factors to consider:<\/span><\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Latency-sensitive workloads (like real-time simulations) benefit from on-prem clusters with high-speed networking.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Data sovereignty &amp; security requirements may limit cloud options for certain organizations.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Multi-site deployments can provide redundancy and disaster recovery capabilities.<\/span><\/li>\n<\/ul>\n<p><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Common strategies include:<\/span><\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">A single, centralized on-prem cluster<\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: ideal when high-speed interconnects are needed.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Regional clusters<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: useful when different teams operate in separate geographic locations.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Hybrid HPC deployments<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: a base on-prem cluster with cloud bursting for peak loads.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">All in cloud<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: a full-on deployment of all workloads onto cloud resources.<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<\/div><div class=\"fusion-title title fusion-title-16 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.1.4) Planning for scalability<\/h4><\/div><div class=\"fusion-text fusion-text-46\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Clusters need to be scalable to accommodate future growth, new applications, or sudden spikes in workload.<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Modular expansion<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: design infrastructure so nodes can be added as needed.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Flexible job scheduling<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: optimize queue policies to maximize utilization.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Cloud integration<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: keep the option open to extend compute power when required.<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By making data-driven decisions based on past usage patterns, you can right-size your HPC infrastructure while ensuring flexibility for the future.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-17 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.2) CPU vs GPU: is your balance right?<\/h3><\/div><div class=\"fusion-text fusion-text-47\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">One of the biggest questions in HPC today is how to distribute resources between CPUs and GPUs.<\/p>\n<\/div><div class=\"fusion-text fusion-text-48\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\">The workload analysis may suggest:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">CFD simulations remain CPU-heavy, meaning you will still need a strong CPU foundation in your next cluster. Investing in high-core-count CPU nodes with high memory bandwidth will be crucial.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">AI workloads, are growing (they won\u2019t remain a minority for long) and we noticed frequent GPU queuing. This suggests that expanding GPU capacity could be valuable, not just for AI but also for potential future hybrid workloads (e.g., AI-driven CFD).<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Analytics jobs don\u2019t necessarily require expensive compute nodes and could be offloaded to lower-cost hardware or cloud instances to free up resources for compute-intensive tasks. <\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-49\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If AI adoption continues to increase, you may need to explore specialized accelerators (e.g., TPUs for AI inference) or hybrid nodes that support both CPU and GPU workloads efficiently.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-18 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.3) Cloud vs on-prem: optimizing flexibility and cost<\/h3><\/div><div class=\"fusion-text fusion-text-50\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A hybrid approach (balancing cloud and on-prem resources) can help match infrastructure to workload patterns.<\/p>\n<\/div><div class=\"fusion-text fusion-text-51\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\">In our current example, we see:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">CFD workloads run at a steady pace and benefit from high-speed interconnects, making on-prem the preferred option. However, peak periods (e.g., when multiple large simulations are submitted) could justify occasional cloud bursting.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">AI training jobs generate spikes in GPU demand, leading to contention. Instead of overprovisioning on-prem GPUs, you could allocate burst capacity to the cloud, ensuring flexibility without overspending on hardware that remains idle between peaks.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Engineering analytics jobs require large storage but not high-performance computing, making them ideal candidates for cloud-based storage and processing. This avoids overloading high-performance nodes with I\/O-heavy but low-compute workloads.<\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-52\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">These insights help define a hybrid architecture that optimizes cost, performance, and scalability: keeping latency-sensitive and high-performance workloads on-prem while leveraging the cloud for burst capacity and scalable storage solutions.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-19 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.4) What configuration for your cluster(s)?<\/h3><\/div><div class=\"fusion-text fusion-text-53\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Once the size, location, and purpose of the HPC cluster are determined, the next step is defining its technical configuration. The right choices will directly impact performance, efficiency, and long-term adaptability.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-20 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.4.1) Choosing the right node configuration and processor architecture<\/h4><\/div><div class=\"fusion-text fusion-text-54\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">HPC workloads vary greatly in their compute, memory, and interconnect needs, making node selection one of the most critical decisions.<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">CPU vs GPU balance<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: some workloads are best suited for multi-core CPUs, while others (AI, molecular dynamics, etc.) benefit from GPU acceleration.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Processor architecture<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: while x86 (Intel\/AMD) has been dominant, ARM-based processors (such as AWS Graviton or NVIDIA Grace) are gaining traction due to power efficiency and cost-effectiveness.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Memory per node<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: large simulations or genomics workloads require high-memory nodes, while parallel workloads may be more CPU\/GPU bound.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Interconnects<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: low-latency, high-bandwidth connections (InfiniBand, NVLink) are crucial for tightly coupled simulations but unnecessary for loosely coupled workloads.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"fusion-text fusion-text-55\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p><u><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Example scenario:<\/span><\/u><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">CFD simulations often require high-core-count CPU nodes with fast interconnects.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">AI training workloads benefit from GPU-accelerated nodes.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Data analytics tasks may only require commodity CPU nodes with fast storage.<\/span><br \/>\n<\/span><\/li>\n<\/ul>\n<p><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By analyzing workload patterns, you can customize node configurations to fit your real needs rather than overspending on one-size-fits-all hardware.<\/span><\/p>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-56\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><\/div><div class=\"fusion-title title fusion-title-21 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.4.2) Defining the storage &amp; filesystem strategy<\/h4><\/div><div class=\"fusion-text fusion-text-57\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Storage performance is just as important as compute power in HPC environments. Selecting the right storage architecture and filesystem ensures that simulations, AI training, and data analysis workflows are not bottlenecked by slow I\/O.<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">High-speed local scratch storage<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: fast, temporary storage (e.g., NVMe SSDs) for active workloads.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Parallel filesystems<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: distributed storage (e.g., Lustre, BeeGFS, GPFS) optimized for large-scale HPC workloads.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Object storage<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: cost-effective storage (e.g., S3, Ceph) for long-term data retention or hybrid cloud workflows.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Tiered storage approach<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: mixing fast storage for active jobs with archival storage for older datasets.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"fusion-text fusion-text-58\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\"><u>Example scenario<\/u>: <\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A CFD engineer submits a job that writes large checkpoint files every few minutes \u00e0 Needs a parallel file system.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">An AI researcher pulls large datasets for training from long-term storage \u00e0 Needs object storage with caching.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A team working on climate simulations shares multi-petabyte data \u00e0 Needs a scalable parallel filesystem.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">HPC admins should map workload I\/O patterns to the right storage tiers to avoid performance bottlenecks.<\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-59\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><\/div><div class=\"fusion-title title fusion-title-22 fusion-sep-none fusion-title-text fusion-title-size-four\" style=\"--awb-font-size:32px;\"><h4 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">2.4.3) Ensuring software stack &amp; application compatibility<\/h4><\/div><div class=\"fusion-text fusion-text-60\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Hardware selection must be aligned with the software ecosystem to ensure smooth transitions, avoid performance drops, and maximize portability across architectures.<\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Application compatibility<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: ensure key applications support the selected processor architecture (x86, ARM, GPUs).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Compilers &amp; libraries<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: check whether existing workloads need specific compilers (Intel, GCC, LLVM) or optimized libraries (CUDA, ROCm, OpenMP).<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Job schedulers<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: SLURM, PBS Pro, or other scheduling tools must be optimized for the cluster\u2019s configuration.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Containerization &amp; portability<\/b><\/span><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">: using Singularity or Docker ensures software portability, especially when adopting hybrid cloud models.<\/span><\/li>\n<\/ul>\n<\/div><div class=\"fusion-text fusion-text-61\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\"><u>Example scenario<\/u>:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A research team using legacy CFD software may require x86 nodes for compatibility.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">AI developers using PyTorch or TensorFlow can benefit from ARM-based GPUs like NVIDIA Grace Hopper.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A multi-user environment may require containerized applications to ensure reproducibility across on-prem and cloud clusters.<\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-62\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By evaluating software requirements early in the planning process, you can avoid costly compatibility issues and ensure their applications make full use of new hardware.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-23 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-font-size:42px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:42;line-height:1.4;\">3) Optimizing costs &amp; resource utilization<\/h2><\/div><div class=\"fusion-text fusion-text-63\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Building a new HPC cluster is a significant investment, but the real cost extends beyond the initial hardware purchase. Poor resource allocation, inefficiencies in job scheduling, and underutilized hardware can quickly drive up operational expenses. Before finalizing a new cluster configuration, it\u2019s crucial to analyze where waste occurs and ensure that resources are sized and allocated properly.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-24 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">3.1) Improving resource allocation to reduce waste<\/h3><\/div><div class=\"fusion-text fusion-text-64\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Regarding the inefficiencies we detected in part 1), the next step is to ensure that resources are properly allocated based on workload needs. <span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\">A few practical ways to reduce waste include:<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Right-sizing job requests<\/b><\/p>\n<p><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Many HPC users request more compute time, memory, or GPUs than their job actually needs, leading to inflated queue times and underutilized resources. Analyzing historical job logs can help optimize job submissions and enforce policies to prevent excessive overprovisioning.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Reserving the right hardware for the right job<\/b><\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Assigning CFD simulations to high-core-count CPU nodes ensures they don\u2019t consume GPU resources unnecessarily.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Allocating AI training workloads exclusively to GPU nodes prevents inefficient use of general-purpose compute nodes.<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Ensuring analytics jobs run on lower-tier compute resources avoids wasting high-performance hardware.<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">\u00a0<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Eliminating bottlenecks in job scheduling<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If jobs experience long queue times due to resource shortages, it may be necessary to adjust scheduling priorities, implement preemptible jobs, or introduce resource-based fair-share scheduling to improve efficiency.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">\u00a0<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Leveraging cloud bursting for peak workloads<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If the cluster experiences occasional peaks in demand, spinning up additional cloud nodes can help avoid purchasing unnecessary on-prem hardware that sits idle during off-peak periods. <span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\">Promoting user awareness of peaks is also a very relevant direction to consider, especially when clear job submission patterns are visible throughout workweeks, project cycles, etc.<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By implementing these workload-aware resource allocation strategies, you can significantly reduce waste and maximize the value of their HPC investments.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-25 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">3.2) Modeling costs over the next 3\u20135 years<\/h3><\/div><div class=\"fusion-text fusion-text-65\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Beyond immediate resource optimization, planning for long-term costs is essential. A well-structured cost model should factor in:<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-style: var(--awb-text-font-style);\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Infrastructure ownership costs<\/b><\/span><\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Hardware acquisition and maintenance<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Cooling, power consumption, and facility costs<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Staffing and administration<\/span><\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Operational costs<\/b><\/p>\n<ul>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Software licensing fees (commercial solvers, AI frameworks)<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Storage expansion and data transfer costs<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Network upgrades for increased workloads<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--awb-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Maintenance costs<\/span><\/li>\n<\/ul>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Cloud vs on-prem cost balance<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">For variable workloads like AI training and burstable CFD jobs, estimating cloud costs vs. on-prem capacity can help determine the best long-term strategy. If cloud reliance becomes excessive, bringing more capacity in-house may be more cost-effective.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Scaling considerations<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If workloads are growing rapidly, planning for modular expansion\u2014adding nodes or storage as needed\u2014ensures that the cluster remains cost-efficient without requiring a full rebuild.<\/p>\n<\/div><div class=\"fusion-text fusion-text-66\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><blockquote>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><span style=\"font-style: normal;\"><u>Example<\/u>:<\/span><\/p>\n<ul>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If AI workloads are projected to double within 3 years, investing in additional GPU nodes today may be more cost-effective than frequent cloud expenditures.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-style: normal;\"><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If CFD simulations are growing, investing in high-memory CPU nodes might be a priority.<\/span><br \/>\n<\/span><\/li>\n<li><span style=\"font-family: Roboto; font-size: var(--body_typography-font-size); letter-spacing: 0px; text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform); font-weight: 400; font-style: normal;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If analytics workloads are becoming more storage-intensive, scaling parallel filesystems should be factored into cost projections. <\/span><\/li>\n<\/ul>\n<\/blockquote>\n<\/div><div class=\"fusion-text fusion-text-67\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By systematically analyzing inefficiencies, optimizing resource allocation, and modeling future costs, HPC teams can ensure that their next cluster delivers maximum performance at the lowest possible cost\u2014without compromising scalability or flexibility.<\/span><\/p>\n<p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">\u00a0<\/span><\/p>\n<p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">\u00a0<\/span><\/p>\n<\/div><div class=\"fusion-title title fusion-title-26 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-font-size:42px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:42;line-height:1.4;\">4) Future-proofing: long-term planning &amp; sustainability<\/h2><\/div><div class=\"fusion-text fusion-text-68\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">HPC infrastructure is a long-term investment, but the pace of technological change means that what works today might not be the best fit in a few years. Ensuring that a new cluster remains relevant over its lifespan requires future-proofing\u2014building flexibility into hardware, workload management, and sustainability strategies.<\/span><\/p>\n<p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">\u00a0<\/span><\/p>\n<p><span style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">\u00a0<\/span><\/p>\n<\/div><div class=\"fusion-title title fusion-title-27 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">4.1) Choosing a future-proof hardware strategy<\/h3><\/div><div class=\"fusion-text fusion-text-69\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">One of the biggest risks when planning a new cluster is locking into hardware that may become outdated or suboptimal before the system reaches the end of its lifecycle. This applies not only to compute but also to storage, networking, and accelerators.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">A few key considerations when selecting hardware:<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">CPU and GPU roadmap alignment<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">With major shifts in processor architectures (Intel vs. AMD vs. ARM), organizations need to ensure they are investing in hardware with long-term software ecosystem support. If AI workloads are expected to grow, choosing a GPU vendor with strong long-term driver and framework support is essential.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Scalability and modular expansion<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Rather than building one large monolithic system, designing a cluster with modular, scalable components allows for incremental upgrades. Can additional GPU nodes be added without redesigning the entire system? Can the storage solution scale with increasing dataset sizes?<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Interoperability and hybrid HPC readiness<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Many organizations are moving toward hybrid HPC environments. Ensuring compatibility with cloud HPC instances, multi-vendor architectures, and shared job scheduling frameworks prevents the cluster from becoming a technical dead-end.<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-7 fusion-flex-container nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-7\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-7 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-blend:overlay;--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-title title fusion-title-28 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">4.2) Assessing energy efficiency &amp; sustainability<\/h3><\/div><div class=\"fusion-text fusion-text-70\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Sustainability is no longer just an afterthought\u2014it has become a critical decision factor for many HPC buyers. In some regions, regulatory requirements now mandate reporting and reducing energy consumption, making energy-efficient HPC a necessity. <span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\">Key areas to evaluate:<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Current cluster power consumption<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Measuring energy usage per job, per node, and per workload type helps identify areas for improvement. OKA\u2019s analysis features can provide insights into which workloads are consuming the most power and whether resources are being used optimally.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Cooling and infrastructure efficiency<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Traditional air cooling is reaching its limits for high-density clusters. Liquid cooling, immersion cooling, and energy reuse strategies (such as repurposing waste heat) are increasingly important for keeping power costs under control.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Cloud sustainability trade-offs<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">While cloud providers offer HPC scalability, they also consume large amounts of energy. Choosing cloud regions powered by renewable energy and evaluating cloud compute efficiency vs. on-prem efficiency can help balance sustainability goals.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Optimizing job scheduling for power efficiency<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By implementing power-aware scheduling, clusters can allocate jobs to nodes that maximize performance per watt\u2014reducing overall energy consumption while maintaining throughput. Other strategies can be implemented as well: node electrical shutdowns, reduction of GPU\/CPU operating frequencies, etc.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-29 fusion-sep-none fusion-title-text fusion-title-size-three\" style=\"--awb-font-size:32px;\"><h3 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:32;line-height:1.5;\">4.3) Cost-efficient long-term operations<\/h3><\/div><div class=\"fusion-text fusion-text-71\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Beyond initial capital investment, the real cost of HPC comes from ongoing operations\u2014power, maintenance, software licensing, and cloud expenditures. <span style=\"letter-spacing: 0px; font-size: var(--awb-font-size); font-style: var(--awb-text-font-style); text-align: var(--awb-content-alignment); text-transform: var(--awb-text-transform);\">To maintain long-term efficiency:<\/span><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Regularly reassess workload placement<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">If AI workloads grow and GPUs become a bottleneck, adjusting the CPU-to-GPU ratio may be necessary. If cloud spending becomes excessive, migrating some workloads back on-prem could be cost-effective.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Flexible licensing models<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Commercial software can be a significant cost factor. Choosing scalable, usage-based licensing can prevent overpaying for underutilized software.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\"><b style=\"font-family: Roboto; font-weight: bold;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"700\">Automated monitoring and forecasting<\/b><\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Using OKA\u2019s long-term trends analysis, organizations can predict workload evolution and proactively scale resources before performance bottlenecks emerge.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">By choosing adaptable hardware, optimizing energy efficiency, and planning for long-term cost control, you can build an HPC infrastructure that remains efficient, scalable, and sustainable well into the future.<\/p>\n<\/div><div class=\"fusion-title title fusion-title-30 fusion-sep-none fusion-title-text fusion-title-size-two\" style=\"--awb-font-size:42px;\"><h2 class=\"fusion-title-heading title-heading-left fusion-responsive-typography-calculated\" style=\"margin:0;font-size:1em;--fontSize:42;line-height:1.4;\">5) Conclusion: from analysis to action<\/h2><\/div><div class=\"fusion-text fusion-text-72\" style=\"--awb-text-color:#24587a;--awb-text-font-family:&quot;Roboto&quot;;--awb-text-font-style:normal;--awb-text-font-weight:100;\"><p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Choosing your next HPC cluster is never just about hardware. It\u2019s about understanding your workloads, anticipating change, and building something that can evolve with you. Whether you\u2019re focused on performance, cost control, energy impact\u2014or all three\u2014data-driven planning is your best ally. With tools like <u><a href=\"https:\/\/oka.how\" target=\"_blank\" rel=\"noopener noreferrer\">OKA<\/a><\/u> and the right approach, you can turn infrastructure planning into a smart, forward-looking investment.<\/p>\n<p style=\"letter-spacing: 0px; font-family: Roboto; font-weight: 400;\" data-fusion-font=\"true\" data-fusion-google-font=\"Roboto\" data-fusion-google-variant=\"400\">Do you want help assessing your current cluster? Let\u2019s talk\u2014this is <u><a href=\"https:\/\/ucit.fr\" target=\"_blank\" rel=\"noopener noreferrer\">what we do<\/a><\/u>.<\/p>\n<\/div><\/div><\/div><\/div><\/div><div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-8 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling gradient-container-8\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1216.8px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-8 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:0px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-73\"><p><\/p>\n<\/div><\/div><\/div><\/div><\/div><\/p>","protected":false},"excerpt":{"rendered":"<p>In this article, we\u2019ll break down the key questions to ask when planning your next HPC cluster.<\/p>\n","protected":false},"author":1,"featured_media":15179,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[97,94],"tags":[],"class_list":["post-15202","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-oka"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Defining the requirements of your next HPC cluster - UCit<\/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:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Defining the requirements of your next HPC cluster - UCit\" \/>\n<meta property=\"og:description\" content=\"In this article, we\u2019ll break down the key questions to ask when planning your next HPC cluster.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/\" \/>\n<meta property=\"og:site_name\" content=\"UCit\" \/>\n<meta property=\"article:published_time\" content=\"2025-04-17T06:00:02+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-05-14T11:54:20+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"2000\" \/>\n\t<meta property=\"og:image:height\" content=\"1999\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"author\" content=\"ucitdev\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"ucitdev\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"22 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/\"},\"author\":{\"name\":\"ucitdev\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/#\\\/schema\\\/person\\\/8fc5d5092628810fbbb9c88ad5635752\"},\"headline\":\"Defining the requirements of your next HPC cluster\",\"datePublished\":\"2025-04-17T06:00:02+00:00\",\"dateModified\":\"2025-05-14T11:54:20+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/\"},\"wordCount\":31236,\"image\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/ucit.fr\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/oka-article-illustration2.webp\",\"articleSection\":[\"Articles\",\"OKA\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/\",\"url\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/\",\"name\":\"Defining the requirements of your next HPC cluster - UCit\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/ucit.fr\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/oka-article-illustration2.webp\",\"datePublished\":\"2025-04-17T06:00:02+00:00\",\"dateModified\":\"2025-05-14T11:54:20+00:00\",\"author\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/#\\\/schema\\\/person\\\/8fc5d5092628810fbbb9c88ad5635752\"},\"breadcrumb\":{\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[[\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/\"]]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#primaryimage\",\"url\":\"https:\\\/\\\/ucit.fr\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/oka-article-illustration2.webp\",\"contentUrl\":\"https:\\\/\\\/ucit.fr\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/oka-article-illustration2.webp\",\"width\":2000,\"height\":1999},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/2025\\\/04\\\/17\\\/defining-requirements-next-hpc-cluster\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Accueil\",\"item\":\"https:\\\/\\\/ucit.fr\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Defining the requirements of your next HPC cluster\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/#website\",\"url\":\"https:\\\/\\\/ucit.fr\\\/\",\"name\":\"UCit\",\"description\":\"Toward an optimized HPC environment\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/ucit.fr\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/ucit.fr\\\/#\\\/schema\\\/person\\\/8fc5d5092628810fbbb9c88ad5635752\",\"name\":\"ucitdev\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/d7eebb4258b39c3559114e33dc5b901ac44ff55a073f79b0b6d2bda25b1f37a8?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/d7eebb4258b39c3559114e33dc5b901ac44ff55a073f79b0b6d2bda25b1f37a8?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/d7eebb4258b39c3559114e33dc5b901ac44ff55a073f79b0b6d2bda25b1f37a8?s=96&d=mm&r=g\",\"caption\":\"ucitdev\"},\"url\":\"https:\\\/\\\/ucit.fr\\\/index.php\\\/author\\\/ucitdev\\\/\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Defining the requirements of your next HPC cluster - UCit","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:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/","og_locale":"en_US","og_type":"article","og_title":"Defining the requirements of your next HPC cluster - UCit","og_description":"In this article, we\u2019ll break down the key questions to ask when planning your next HPC cluster.","og_url":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/","og_site_name":"UCit","article_published_time":"2025-04-17T06:00:02+00:00","article_modified_time":"2025-05-14T11:54:20+00:00","og_image":[{"width":2000,"height":1999,"url":"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp","type":"image\/webp"}],"author":"ucitdev","twitter_card":"summary_large_image","twitter_misc":{"Written by":"ucitdev","Est. reading time":"22 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#article","isPartOf":{"@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/"},"author":{"name":"ucitdev","@id":"https:\/\/ucit.fr\/#\/schema\/person\/8fc5d5092628810fbbb9c88ad5635752"},"headline":"Defining the requirements of your next HPC cluster","datePublished":"2025-04-17T06:00:02+00:00","dateModified":"2025-05-14T11:54:20+00:00","mainEntityOfPage":{"@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/"},"wordCount":31236,"image":{"@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#primaryimage"},"thumbnailUrl":"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp","articleSection":["Articles","OKA"],"inLanguage":"en-US"},{"@type":"WebPage","@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/","url":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/","name":"Defining the requirements of your next HPC cluster - UCit","isPartOf":{"@id":"https:\/\/ucit.fr\/#website"},"primaryImageOfPage":{"@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#primaryimage"},"image":{"@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#primaryimage"},"thumbnailUrl":"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp","datePublished":"2025-04-17T06:00:02+00:00","dateModified":"2025-05-14T11:54:20+00:00","author":{"@id":"https:\/\/ucit.fr\/#\/schema\/person\/8fc5d5092628810fbbb9c88ad5635752"},"breadcrumb":{"@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":[["https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/"]]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#primaryimage","url":"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp","contentUrl":"https:\/\/ucit.fr\/wp-content\/uploads\/2025\/04\/oka-article-illustration2.webp","width":2000,"height":1999},{"@type":"BreadcrumbList","@id":"https:\/\/ucit.fr\/index.php\/2025\/04\/17\/defining-requirements-next-hpc-cluster\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Accueil","item":"https:\/\/ucit.fr\/"},{"@type":"ListItem","position":2,"name":"Defining the requirements of your next HPC cluster"}]},{"@type":"WebSite","@id":"https:\/\/ucit.fr\/#website","url":"https:\/\/ucit.fr\/","name":"UCit","description":"Toward an optimized HPC environment","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/ucit.fr\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Person","@id":"https:\/\/ucit.fr\/#\/schema\/person\/8fc5d5092628810fbbb9c88ad5635752","name":"ucitdev","image":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/secure.gravatar.com\/avatar\/d7eebb4258b39c3559114e33dc5b901ac44ff55a073f79b0b6d2bda25b1f37a8?s=96&d=mm&r=g","url":"https:\/\/secure.gravatar.com\/avatar\/d7eebb4258b39c3559114e33dc5b901ac44ff55a073f79b0b6d2bda25b1f37a8?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/d7eebb4258b39c3559114e33dc5b901ac44ff55a073f79b0b6d2bda25b1f37a8?s=96&d=mm&r=g","caption":"ucitdev"},"url":"https:\/\/ucit.fr\/index.php\/author\/ucitdev\/"}]}},"_links":{"self":[{"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/posts\/15202","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/comments?post=15202"}],"version-history":[{"count":23,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/posts\/15202\/revisions"}],"predecessor-version":[{"id":15228,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/posts\/15202\/revisions\/15228"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/media\/15179"}],"wp:attachment":[{"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/media?parent=15202"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/categories?post=15202"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ucit.fr\/index.php\/wp-json\/wp\/v2\/tags?post=15202"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}