{"id":3311,"date":"2024-07-18T17:43:09","date_gmt":"2024-07-18T17:43:09","guid":{"rendered":"https:\/\/www.velocitymicro.com\/blog\/?p=3311"},"modified":"2024-07-16T21:11:32","modified_gmt":"2024-07-16T21:11:32","slug":"choosing-the-perfect-ai-pc-components","status":"publish","type":"post","link":"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/","title":{"rendered":"Choosing the Perfect AI PC Components"},"content":{"rendered":"<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter size-large\" src=\"https:\/\/velocitymicro.com\/img\/AI\/banner_still.jpg\" alt=\"AI Banner Image\" width=\"3840\" height=\"900\" \/><br \/>\nAI PCs. So hot right now. It seems like the hype is everywhere you turn. I think by now, we\u2019re all familiar with generative AI chat bots like ChatGPT, but wrapping our organic based brains around the real world applications for AI is much more difficult. Can it really improve our lives, make us more productive, and solve the world\u2019s problems? Or have we just invented our own Skynet?<\/p>\n<p>Those important quandaries aside, for users <a href=\"https:\/\/www.velocitymicro.com\/blog\/maximizing-the-potential-of-ai-programs-with-a-high-performance-pc\/\">building AI models locally<\/a> rather than working in the cloud, another important question emerges \u2013 what\u2019s the ideal set of AI PC components to minimize <a href=\"https:\/\/www.velocitymicro.com\/blog\/unlocking-the-power-of-ai-workstations-pre-training-and-inference\/\">inference and analytic<\/a> times? Read on to learn more.<\/p>\n<h2><img decoding=\"async\" loading=\"lazy\" class=\"alignnone size-large\" src=\"https:\/\/velocitymicro.com\/img\/blog\/AI_cpu.jpg\" alt=\"CPUs banner\" width=\"1920\" height=\"400\" \/><\/h2>\n<h2><strong>Choosing a Processor for an AI PC<\/strong><\/h2>\n<p>Most generative AI applications are heavily threaded CPU intensive, meaning like many other workstation applications, they\u2019ll benefit from utilizing multiple cores. Where that core count should max out depends on your budget, but also the complexity of your models. For simpler generative AI models, a 16 to 24 core CPU like AMD Ryzen or 14<sup>th<\/sup> Gen Intel Core is likely sufficient. Some of the newer AMD and Intel architecture will actually accelerate these workloads. But as model complexity increases, so then do CPU requirements, making an <a href=\"https:\/\/velocitymicro.com\/amd-threadripper-pro.php\">AMD Threadripper Workstation<\/a> or even <a href=\"https:\/\/velocitymicro.com\/promagix-hd360a-epyc-workstation-pc.php\">Epyc Workstation<\/a> the best choice.<\/p>\n<h2><img decoding=\"async\" loading=\"lazy\" class=\"alignnone size-large\" src=\"https:\/\/velocitymicro.com\/img\/blog\/AI_gpu.jpg\" alt=\"GPUs banner\n\" width=\"1920\" height=\"400\" \/><\/h2>\n<h2>Choosing a GPU for an AI PC<\/h2>\n<p>Since its introduction of the first CUDA core enabled GPU in 2006, NVIDIA has been guiding us toward a future where the GPU is king. Now with the proliferation of Tensor cores and HBM2 memory, it seems that future is now. We could write a full post (or series of posts) just on utilizing GPUs to accelerate AI applications, but for these purposes, let\u2019s just breakdown the three classes of GPU available and quickly discuss which is best for what user.<\/p>\n<p style=\"text-align: left; padding-left: 40px;\"><strong>Geforce Graphics<\/strong> \u2013 These are the consumer grade graphics cards typically marketed toward home users and gamers, but if your main concern is maxing out Tensor and CUDA cores per dollar without concern for double precision computation, these cards are actually a fine option. They\u2019re the best choice for single GPU towers and users without major performance requirements.<\/p>\n<p style=\"text-align: left; padding-left: 40px;\"><strong>Professional Graphics<\/strong> \u2013 <a href=\"https:\/\/www.velocitymicro.com\/blog\/geforce-vs-quadro-whats-the-difference\/\">Formally known as Quadro<\/a>, NVIDIA\u2019s professional graphics provide additional scalability and official support of rackmount form factors. The most powerful cards in this stack, like the RTX 6000 ADA, offer double the computational cores than Geforce counterparts and can be NVlinked together for resource pooling. Ideal for more higher-end AI models and computations.<\/p>\n<p style=\"text-align: left; padding-left: 40px;\"><strong>Computational GPUs<\/strong> \u2013 These datacenter GPUs like the NVIDIA H100 are designed to do the heaviest lifting on the most massive models. Thermal limitations really make these enterprise solutions only.<\/p>\n<p>*Want the power of an H100 but can\u2019t support a datacenter or rackmount form factor? Check out the actively cooled NVIDIA A800, now available on our workstation class <a href=\"https:\/\/velocitymicro.com\/desktop-workstation-pc.php\">desktop workstations<\/a>.<\/p>\n<h2><img decoding=\"async\" loading=\"lazy\" class=\"alignnone size-large\" src=\"https:\/\/velocitymicro.com\/img\/blog\/AI_components.jpg\" alt=\"Other AI Components Banner\" width=\"1920\" height=\"400\" \/><\/h2>\n<h2>Other AI PC Components<\/h2>\n<p>CPU and GPU are clearly the most important AI components here, but don\u2019t ignore the following:<\/p>\n<p style=\"padding-left: 40px;\"><strong>Memory channels<\/strong> \u2013 We\u2019ve discussed the <a href=\"https:\/\/www.velocitymicro.com\/blog\/multi-channel-memory\/\">importance of memory channels<\/a> in previous posts, but they\u2019re especially notable in AI configurations. 8 (Intel Xeon\/Threadripper Pro) and even 12 (AMD Epyc) channel memory will vastly accelerate computation, especially with very memory dense configurations.<\/p>\n<p style=\"padding-left: 40px;\"><strong>Storage Speed<\/strong> \u2013 The ability for your PC to read and write to storage quickly will result in faster Inference and Analysis. If your chipset supports it, we recommend at least <a href=\"https:\/\/www.velocitymicro.com\/blog\/client-ssd-vs-enterprise-ssd-whats-the-difference\/\">PCIe Gen 4 NVMe at enterprise grade<\/a> level for additional durability.<\/p>\n<h2>What is an ASIC?<\/h2>\n<p>This discussion would not be complete without at least a mention of ASICs, or Application Specific Integrated Circuits. At a high level, ASICs are purpose-built chips with architecture that\u2019s optimized for one specific task, for example crypto mining or AI. That optimization is extremely specialized, so for example while an ASIC may be incredibly efficient at generative AI, it would not be able to handle other AI applications, or in many cases most basic applications either. So, in this example, the generative AI user may see incredible ROI when choosing an ASIC over a general purpose integrated circuit CPU, but for that application only. But as AI becomes more specialized and sophisticated in the coming years, ASICs will likely play a more prominent role in the industry.<\/p>\n<p>Learn more about our <a href=\"https:\/\/velocitymicro.com\/ai.php\">AI PCs here<\/a> or give our expert sales team a call at 804-419-0900 for assistance putting together you perfect configuration.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>AI PCs. So hot right now. It seems like the hype is everywhere you turn. I think by now, we\u2019re&hellip;<\/p>\n","protected":false},"author":1,"featured_media":3315,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[90],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\r\n<title>Choosing the Perfect AI PC Components<\/title>\r\n<meta name=\"description\" content=\"For users building AI models locally, what\u2019s the ideal set of AI PC components to minimize inference and analytic times?\" \/>\r\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\r\n<link rel=\"canonical\" href=\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\" \/>\r\n<meta property=\"og:locale\" content=\"en_US\" \/>\r\n<meta property=\"og:type\" content=\"article\" \/>\r\n<meta property=\"og:title\" content=\"Choosing the Perfect AI PC Components\" \/>\r\n<meta property=\"og:description\" content=\"For users building AI models locally, what\u2019s the ideal set of AI PC components to minimize inference and analytic times?\" \/>\r\n<meta property=\"og:url\" content=\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\" \/>\r\n<meta property=\"og:site_name\" content=\"Custom Gaming &amp; Workstation PC Blog | Velocity Micro\" \/>\r\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/VelocityMicro\/\" \/>\r\n<meta property=\"article:published_time\" content=\"2024-07-18T17:43:09+00:00\" \/>\r\n<meta property=\"article:modified_time\" content=\"2024-07-16T21:11:32+00:00\" \/>\r\n<meta property=\"og:image\" content=\"https:\/\/velocitymicro.com\/img\/AI\/banner_still.jpg\" \/>\r\n<meta name=\"author\" content=\"Josh Covington\" \/>\r\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Josh Covington\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\r\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\"},\"author\":{\"name\":\"Josh Covington\",\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/#\/schema\/person\/ed5bde2afc7b486d5d555720e8f61d32\"},\"headline\":\"Choosing the Perfect AI PC Components\",\"datePublished\":\"2024-07-18T17:43:09+00:00\",\"dateModified\":\"2024-07-16T21:11:32+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\"},\"wordCount\":739,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/#organization\"},\"articleSection\":[\"AI\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\",\"url\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\",\"name\":\"Choosing the Perfect AI PC Components\",\"isPartOf\":{\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/#website\"},\"datePublished\":\"2024-07-18T17:43:09+00:00\",\"dateModified\":\"2024-07-16T21:11:32+00:00\",\"description\":\"For users building AI models locally, what\u2019s the ideal set of AI PC components to minimize inference and analytic times?\",\"breadcrumb\":{\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/choosing-the-perfect-ai-pc-components\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/www.velocitymicro.com\/blog\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Choosing the Perfect AI PC Components\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.velocitymicro.com\/blog\/#website\",\"url\":\"https:\/\/www.velocitymicro.com\/blog\/\",\"name\":\"Custom Gaming &amp; 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