{"id":54286,"date":"2023-12-11T17:54:18","date_gmt":"2023-12-11T17:54:18","guid":{"rendered":"https:\/\/prosfunds.com\/news\/amd-ai-gpu-revolution-powers-next-data-center-frontier-nasdaqamd\/"},"modified":"2023-12-11T17:54:21","modified_gmt":"2023-12-11T17:54:21","slug":"amd-ai-gpu-revolution-powers-next-data-center-frontier-nasdaqamd","status":"publish","type":"post","link":"https:\/\/prosfunds.com\/?p=54286","title":{"rendered":"AMD: AI GPU Revolution Powers Next Data Center Frontier (NASDAQ:AMD)"},"content":{"rendered":"<div data-test-id=\"content-container\">\n<p><figure class=\"getty-figure\" data-type=\"getty-image\"><picture>  <\/picture><figcaption> <\/figcaption><\/figure>\n<\/p>\n<p><strong>Advanced Micro Devices, Inc.<\/strong> (<span class=\"ticker-hover-wrapper\">NASDAQ:AMD<\/span>) is one of the top semiconductor companies in the world, with a strong foothold in the CPU and GPU markets. Both these chips are a core component for servers used in data centers<span class=\"paywall-full-content invisible\"> and businesses. We previously <\/span>covered<span class=\"paywall-full-content invisible\"> how Nvidia Corporation (<\/span>NVDA<span class=\"paywall-full-content invisible\">) is dominating the data center space, with the company clearly highlighting the 6 types of data center customers it serves. More recently, we <\/span>determined<span class=\"paywall-full-content invisible\"> the effects of Artificial Intelligence, or AI, on Nvidia\u2019s portfolio of chips to discover the numerous enhancing benefits AI brings.<\/span><\/p>\n<p class=\"paywall-full-content invisible\">AMD previously highlighted its strategies related to AI, particularly related to its new MI300 GPU chips. In its latest earnings briefing, AMD further emphasized its continued progress in its Data Center GPU business and \u201csignificant customer traction\u201d for its next-gen GPUs. At the start of the year, we already highlighted<span class=\"paywall-full-content no-summary-bullets invisible\"> AMD\u2019s continuous GPU performance improvement.<\/span><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">In light of AMD\u2019s new GPU developments of the MI300 chips and &#8220;design wins in AI deployments,&#8221; we analyze how AI has increased the competitiveness of its server GPUs and where they stand in comparison to Nvidia and Intel (INTC).<\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>AMD Revenue Breakdown ($ mln)<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2017<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2018<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2019<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2020<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2021<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2022<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Data Center CPU Estimate<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>1,153<\/p>\n<\/td>\n<td>\n<p>2,939<\/p>\n<\/td>\n<td>\n<p>4,131<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>155.0%<\/p>\n<\/td>\n<td>\n<p>40.6%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Data Center GPU Estimate<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>532<\/p>\n<\/td>\n<td>\n<p>755<\/p>\n<\/td>\n<td>\n<p>1,040<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>41.8%<\/p>\n<\/td>\n<td>\n<p>37.7%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Data Center DPU Estimate<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>655.2<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p>Data Center FPGA Estimate<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>217<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-y\">\n<td>\n<p>Total Data Center<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>1,685<\/p>\n<\/td>\n<td>\n<p>3,694<\/p>\n<\/td>\n<td>\n<p>6,043<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-y\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>119.2%<\/p>\n<\/td>\n<td>\n<p>63.6%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Client<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>5,189<\/p>\n<\/td>\n<td>\n<p>6,887<\/p>\n<\/td>\n<td>\n<p>6,201<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>32.7%<\/p>\n<\/td>\n<td>\n<p>-10.0%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Gaming<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>2,746<\/p>\n<\/td>\n<td>\n<p>5,607<\/p>\n<\/td>\n<td>\n<p>6,805<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>104.2%<\/p>\n<\/td>\n<td>\n<p>21.4%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Embedded<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>143<\/p>\n<\/td>\n<td>\n<p>246<\/p>\n<\/td>\n<td>\n<p>4,552<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>72.0%<\/p>\n<\/td>\n<td>\n<p>1750.4%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p><strong>Total AMD<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>5,253<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>6,475<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>6,731<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>9,763<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>16,434<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>23,601<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p><strong>Growth %<\/strong><\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p><strong>23.3%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>4.0%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>45.0%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>68.3%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>43.6%<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: Company Data, Khaveen Investments.<\/em><\/p>\n<h2 class=\"paywall-full-content invisible no-summary-bullets\"><strong>AI Demand Boosts for Data Centers<\/strong><\/h2>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>How AI Makes Data Centers Better<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089637278204.png\" alt=\"ai benefit data centers\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>Venture Beat, Uptime Institute<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">There are numerous ways AI enhances data center operations such as:<\/p>\n<ul class=\"paywall-full-content invisible no-summary-bullets\">\n<li>Improved data security,<\/li>\n<li>Reduced energy consumption,<\/li>\n<li>Improved predictive maintenance, compliance, and capacity planning<\/li>\n<li>Improved reliability<\/li>\n<li>Advanced monitoring<\/li>\n<li>Server optimization<\/li>\n<li>Downtime reduction.<\/li>\n<\/ul>\n<p class=\"paywall-full-content invisible no-summary-bullets\">The important point to highlight is that AI is a type of technology, and it takes a combination of products and systems to run it to its full potential. Among the most important are chips such as GPUs and CPUs.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><picture> <img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089636090093.png\" alt=\"llm computing power\" contenteditable=\"false\" loading=\"lazy\"> <\/picture><figcaption>\n<p class=\"item-caption\"><span>The Economist<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AI\u2019s large language models\u2019 capabilities come at a cost \u2013 the need for high computing performance. This requirement stems from the extensive size of these models, with parameters in the range of hundreds of billions to trillions. These parameters signify connections and weights in the neural network, facilitating learning from data and performing complex tasks. The vast number of parameters necessitates massive computational power to manage and update them during training and inference.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">This is exactly where chips come in:<\/p>\n<blockquote class=\"paywall-full-content invisible no-summary-bullets\">\n<p>GPUs (Graphics Processing Units) are used in AI to accelerate the training of deep neural networks. GPUs are designed to perform parallel computations, which makes them ideal for training large neural networks. The parallel architecture of GPUs allows them to perform many calculations simultaneously, which speeds up the training process. \u2013 <em>Bing Chat (GPT-4), Microsoft and OpenAI.<\/em><\/p>\n<p>CPUs (Central Processing Units) are used in AI for a variety of tasks, including data preprocessing, model training, and inference. In addition, CPUs can be used for running AI algorithms that are not computationally intensive. For example, CPUs can be used for running rule-based systems or decision trees. \u2013 <em>Bing Chat (GPT-4), Microsoft and OpenAI.<\/em><\/p>\n<\/blockquote>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>AMD AI Strategy <\/strong><\/h3>\n<blockquote class=\"paywall-full-content invisible no-summary-bullets\">\n<p>The pace of innovation in the Instinct GPUs in particular is happening even faster than AMD and its initial customers had anticipated. \u2013 The Next Platform.<\/p>\n<\/blockquote>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Chipmakers understand their core importance in AI, and AMD even has a specific AI strategy to capitalize on this.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><picture> <img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089625575473.png\" alt=\"amd ai strategy\" contenteditable=\"false\" loading=\"lazy\"> <\/picture><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We evaluate the success of AMD\u2019s AI strategy by examining each of the 3 areas it mentions:<\/p>\n<ol class=\"paywall-full-content invisible no-summary-bullets\">\n<li>Broad Product Portfolio for AI<\/li>\n<li>Open software platform for AI<\/li>\n<li>Established Partnerships.<\/li>\n<\/ol>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Product Portfolio<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AMD has long been established as a leading player in the GPU and CPU space. We also previously discussed AMD&#8217;s expansion into FPGAs and DPUs, acquired through its Xilinx and Pensando acquisitions. Thus, we believe the company is indeed executing well in this area.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089637795026.png\" alt=\"amd portfolio\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AMD\u2019s AI portfolio includes its Instinct platform of data center GPUs, EPYC product line of data center CPUs as well as Ryzen PC CPUs. With the acquisition of Xilinx, the company added its Versal ACAP and Alveo FPGA to its AI portfolio. In 2016, AMD first introduced its MI6 GPU as part of its Instinct family which it touted as \u201ctraining and an inference accelerator for machine intelligence and deep learning.\u201d<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><picture> <img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-1702208962716919.png\" alt=\"amd infinity link\" contenteditable=\"false\" loading=\"lazy\"> <\/picture><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Furthermore, AMD has its Infinity Fabric interconnect technology which facilitates data communication between components such as the CPU and GPU for better performance, reduced latencies and higher power efficiency. It is designed to reduce data movement between storage units in GPUs, CPU cache or system memory \u201cculminating in a coherent CPU + GPU technology that aims to improve system performance (and especially HPC performance) by leaps and bounds.\u201d<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Software<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">The memory requirements of large language models pose a significant challenge as they exceed the capacity of a single GPU or GPU cluster. To tackle this issue, specialized distributed software and hardware configurations are necessary for effective data management during training. This is why good software programs are necessary for AI to operate to its fullest. Some of the software AMD has deployed includes AMD ROCm, PyTorch, Hugging Face, AMD Secure Encrypted Virtualization (SEV) technology and so on.<\/p>\n<ul class=\"paywall-full-content invisible no-summary-bullets\">\n<li> <strong>AMD ROCm<\/strong>: AMD ROCm is an open-source software platform for GPU computing that provides a set of tools and APIs for programming GPUs, offering flexibility and high performance. It supports various accelerator vendors and architectures, enabling researchers to use AMD Instinct accelerators for scientific and computational tasks.<\/li>\n<li> <strong>PyTorch<\/strong>: A widely regarded open-source machine learning library that offers GPU acceleration and deep learning tools. It can be used with AMD GPUs through AMD ROCm.<\/li>\n<li> <strong>Hugging Face<\/strong>: Hugging Face creates machine learning tools, including the Transformers library for natural language processing. AMD partnered with Hugging Face so its GPUs can be utilized and optimized for Hugging Face&#8217;s tools.<\/li>\n<li> <strong>AMD Secure Encrypted Virtualization<\/strong>: AMD Secure Encrypted Virtualization (SEV) is a technology that encrypts the memory of each virtual machine enhancing security.<\/li>\n<\/ul>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089637947307.png\" alt=\"amd ai platform\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Data Center Partners<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">While chips are the core of every technology like the brain of a human, it still needs other hardware components to enable it to carry out the almost limitless number of functions it can do. Just like the brain needs a skull to protect it and limbs to execute its nervous impulses, AMD needs a wide ecosystem of partners to reach the market.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-1702208963775227.png\" alt=\"amd partners\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">From the image above, AMD\u2019s partners include cloud providers, server manufacturers and software providers. We believe its partnerships with certain customers are essential. For example, Microsoft (MSFT) and Amazon (AMZN) are among the top 3 cloud players, and Dell (DELL), Lenovo (LNVGY), and Hewlett Packard (HPE) are among the top 5 server makers.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">What we find assuring is the numerous partners and customers on this list attesting to the breakthrough technology that AMD&#8217;s products bring. The companies highlighting their excitement and commitment to AMD products include Microsoft, Dell, Lenovo and Ericsson (ERIC).<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Outlook<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">As we identified, there are numerous use cases of AI in Data Centers. Data Centers consist of numerous servers that enable the delivery of cloud infrastructure services to the market.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">According to Institutional Real Estate, \u201cthe average full-scale data center is 100,000 square feet in size and runs around 100,000 servers.\u201d<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><strong>Server Market Share<\/strong><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089640635202.png\" alt=\"server market share\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>IDC, Statista<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">In terms of market share, the top players seem to have maintained their market share over the past few years, but there is a notable increase in sales to direct ODMs.<\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>Server Market<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2018<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2019<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2020<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2021<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2022<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Server Market Shipments (&#8216;mln&#8217;)<\/p>\n<\/td>\n<td>\n<p>11.75<\/p>\n<\/td>\n<td>\n<p>11.75<\/p>\n<\/td>\n<td>\n<p>12.17<\/p>\n<\/td>\n<td>\n<p>13.55<\/p>\n<\/td>\n<td>\n<p>14.24<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>0.0%<\/p>\n<\/td>\n<td>\n<p>3.6%<\/p>\n<\/td>\n<td>\n<p>11.3%<\/p>\n<\/td>\n<td>\n<p>5.1%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Server ASP<\/p>\n<\/td>\n<td>\n<p>6,769<\/p>\n<\/td>\n<td>\n<p>6,635<\/p>\n<\/td>\n<td>\n<p>6,389<\/p>\n<\/td>\n<td>\n<p>6,138<\/p>\n<\/td>\n<td>\n<p>5,960<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>-2.0%<\/p>\n<\/td>\n<td>\n<p>-3.7%<\/p>\n<\/td>\n<td>\n<p>-3.9%<\/p>\n<\/td>\n<td>\n<p>-2.9%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Market Revenue ($ bln)<\/p>\n<\/td>\n<td>\n<p>79.53<\/p>\n<\/td>\n<td>\n<p>77.96<\/p>\n<\/td>\n<td>\n<p>77.75<\/p>\n<\/td>\n<td>\n<p>83.17<\/p>\n<\/td>\n<td>\n<p>84.87<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>-2.0%<\/p>\n<\/td>\n<td>\n<p>-0.3%<\/p>\n<\/td>\n<td>\n<p>7.0%<\/p>\n<\/td>\n<td>\n<p>2.0%<\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: IDC, Statista, Khaveen Investments.<\/em><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Based on the chart above, the server market growth has been low over the past 5 years with growth mainly driven by shipment growth rather than ASPs. From our previous analysis of TSMC (TSM), we highlighted the increasing lifespan of servers as \u201cthe average life of a traditional server has increased from between 3 to 4 years to 6 years for Tier 1 companies and up to 10 years for Tier 2 companies.\u201d This explains the low server market growth. However, the cloud infrastructure market has seen tremendous growth as seen below.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"> <picture> <\/picture><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-1702209418093575.jpg\" alt=\"cloud market projections\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>IDC, Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<blockquote class=\"paywall-full-content invisible no-summary-bullets\">\n<p>Driven by the advent of AI, HPC, IoT and edge computing, data creation is projected to grow in the next 5 years. This would require greater cloud infrastructure to handle the increase in data. To determine the growth in cloud infrastructure revenues, we identified the factor of correlation of cloud infrastructure revenues to data volume growth over <em>the past 10 years. \u2013 <\/em><em>Khaveen Investments<\/em>.<\/p>\n<\/blockquote>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Despite the high cloud market growth, the server market has remained stagnant in comparison. The reason for the discrepancy between the cloud market and server markets is the increasing performance of newer servers. According to the IDC, server upgrades enable companies to have fewer but more powerful systems enabling improved performance. Despite the improved performance, server prices have declined by -3.1% per year on average. This is because the performance increase was not due to the server hardware (which encompasses the mainframe containing the infrastructure components within it), but instead the chips within the server such as CPUs and GPUs among other chips. In our previous analysis, we compared different generations of AMD and Intel server CPUs and determined the increasing performance of each new generation since 2017. Furthermore, according to The Register, the efficiency of servers increases with each new generation of hardware with higher processor utilization. Therefore, we believe the increasing performance of server systems due to better chip powering enables companies such as cloud providers to use it to increase their services without needing to scale up more server hardware.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AI, like machine learning, needs a lot of data, making data processing a big task. Tasks such as cleaning and organizing data become complex with large datasets. The training of machine learning models, particularly deep learning models containing millions of parameters, necessitates considerable computational resources. The substantial computational demands of AI underscore the need for high-performance computing.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Given that chips are responsible for increased performance that is needed in data centers utilizing AI for the computational requirements of processing the ever-increasing data volume, we believe that demand for chips will skyrocket in line with data volume growth.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Comparing the performance of AMD\u2019s server GPUs across different product generations (AI and non-AI), we derived a proprietary Server GPU Benchmark score encompassing various performance metrics including Texture Rate and Processing Power (FP16, 32 &amp; 64). We obtained data from a total of 15 AMD server GPU chips encompassing its Radeon Pro V series (non-AI) and its Instinct series (AI) and categorized them based on their architecture.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"> <picture> <\/picture><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-1702209447898358.jpg\" alt=\"amd server gpu scores\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>TechPowerUp, Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr class=\"bg-b\">\n<td>\n<p><strong>AMD Radeon Pro V Series Server GPU (Non-AI)<\/strong><\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p><strong>GCN 5<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>RDNA<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>RDNA 2<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>Average<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Khaveen Investments Benchmark Score<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>185.9<\/p>\n<\/td>\n<td>\n<p>119.0<\/p>\n<\/td>\n<td>\n<p>327.1<\/p>\n<\/td>\n<td> <\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>-36.0%<\/p>\n<\/td>\n<td>\n<p>175.0%<\/p>\n<\/td>\n<td>\n<p>69.5%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p><strong>AMD Instinct Server GPU (AI)<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>GCN 3<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>GCN 4<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>GCN 5<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>CDNA<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>CDNA 2<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>CDNA 3<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>Average<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Khaveen Investments Benchmark Score<\/p>\n<\/td>\n<td>\n<p>130.8<\/p>\n<\/td>\n<td>\n<p>90.8<\/p>\n<\/td>\n<td>\n<p>218.2<\/p>\n<\/td>\n<td>\n<p>397.0<\/p>\n<\/td>\n<td>\n<p>667.2<\/p>\n<\/td>\n<td>\n<p>931.5<\/p>\n<\/td>\n<td> <\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>-30.6%<\/p>\n<\/td>\n<td>\n<p>140.4%<\/p>\n<\/td>\n<td>\n<p>82.0%<\/p>\n<\/td>\n<td>\n<p>68.1%<\/p>\n<\/td>\n<td>\n<p>39.6%<\/p>\n<\/td>\n<td>\n<p>59.9%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Difference<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>213.6%<\/p>\n<\/td>\n<td>\n<p>560.9%<\/p>\n<\/td>\n<td>\n<p>284.7%<\/p>\n<\/td>\n<td>\n<p>353.1%<\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: TechPowerUp, Khaveen Investments.<\/em><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Based on the table, AMD\u2019s AI GPU average score is higher across all 3 generations compared to its non-AI GPUs with an average difference of 353.1%. For its Radeon Pro V Series GPUs, our RDNA average benchmark score is lower than the prior GCN 5 due to the lower average texture rate and processing power of its RDNA GPU. We compiled the average PassMark benchmark score for its RDNA PC GPUs and also found its average score lower than the prior GCN5 average by 17%.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"> <picture> <\/picture><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022094844535975.jpg\" alt=\"gpu demand forecasts\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">To estimate the increase in demand for chips in terms of GPUs due to AI, we first calculated how much AI can process data faster which we based on ITBrief of a 1000x increase which equals to 99,900% that we assumed to be achieved over 10 years. Then, we calculated how much AMD AI GPUs can process data faster by comparing our derived benchmark score for AMD\u2019s Radeon Pro V Series and Instinct generations to obtain the % difference (353.1%) which we applied its Instinct historical benchmark score growth average of 60% through 2032. Comparing the growth rate of AI Data processing speed increase of 76% with AMD AI Chips data processing speed increase of 56%, we obtain a shortfall of 16%, which implies the need for an additional 16% GPUs per year in the market required to support AI. Thus, we believe the rise of AI could boost demand for AMD serve GPUs by 16% over our baseline forecast.<\/p>\n<h2 class=\"paywall-full-content invisible no-summary-bullets\"><strong>AMD AI GPU Advantages<\/strong><\/h2>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AMD claims that it has the \u201cworld\u2019s most advanced accelerator for Generative AI.\u201d While we recognize AMD\u2019s prowess, we attempt to determine the validity of this ourselves by analyzing AMD\u2019s AI GPU in comparison with its top two competitors, Intel and Nvidia.<\/p>\n<blockquote class=\"paywall-full-content invisible no-summary-bullets\">\n<p>The Instinct MI300X is \u201cthe most complex thing we&#8217;ve ever built. &#8211;<em>CEO Lisa Su<\/em>.<\/p>\n<\/blockquote>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><picture> <img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089644189346.png\" alt=\"amd gen ai chip\" contenteditable=\"false\" loading=\"lazy\"> <\/picture><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<blockquote class=\"paywall-full-content invisible no-summary-bullets\">\n<p>GPUs (Graphics Processing Units) are typically preferred over CPUs for training deep neural networks because they can perform matrix operations much faster than CPUs. \u2013 <em>Bing Chat (GPT-4), Microsoft and OpenAI.<\/em><\/p>\n<\/blockquote>\n<p class=\"paywall-full-content invisible no-summary-bullets\">GPUs excel in training deep neural networks due to their ability to accelerate matrix operations, perform parallel computations, and handle large networks efficiently, thanks to their parallel architecture, ultimately speeding up the training process.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-170220896364078.jpg\" alt=\"amd gpu advantage\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<blockquote class=\"paywall-full-content invisible no-summary-bullets\">\n<p>In addition, GPUs can be used for inference, which is the process of using a trained model to make predictions on new data. Inference requires less computational power than training, so it can be performed on a wider range of devices, including mobile phones and embedded systems. \u2013 <em>Bing Chat (GPT-4), Microsoft and OpenAI.<\/em><\/p>\n<\/blockquote>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AMD claims to have an inference advantage as seen from its investor presentation slide above, where it compared its Instinct MI300x capabilities with competitors, highlighting that the number of GPUs needed across 4 LLMs is considerably lower than its competitors. However, as we can see in the following section, the competition has caught up significantly.<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Performance<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">The table below compares the latest Data Center GPU chips of AMD, Intel and Nvidia based on various performance and informational metrics.<\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>Data Center GPU Comparison Metrics<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>AMD (MI300x)<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>Nvidia (H100 NVL)<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>Intel (Gaudi 2)<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Process<\/p>\n<\/td>\n<td>\n<p>5nm (TSMC)<\/p>\n<\/td>\n<td>\n<p>4nm (TSMC)<\/p>\n<\/td>\n<td>\n<p>7nm (TSMC)<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Transistors (&#8216;bln&#8217;)<\/p>\n<\/td>\n<td>\n<p>153<\/p>\n<\/td>\n<td>\n<p>160<\/p>\n<\/td>\n<td>\n<p>&gt;100<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Engine Clock Peak<\/p>\n<\/td>\n<td>\n<p>1.700 GHz<\/p>\n<\/td>\n<td>\n<p>1.98GHz<\/p>\n<\/td>\n<td>\n<p>&#8211;<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>FP16 Peak (Teraflops)<\/p>\n<\/td>\n<td>\n<p>1532<\/p>\n<\/td>\n<td>\n<p>3958<\/p>\n<\/td>\n<td>\n<p>839<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>INT 8 (Teraops)<\/p>\n<\/td>\n<td>\n<p>3,064<\/p>\n<\/td>\n<td>\n<p>7,916<\/p>\n<\/td>\n<td>\n<p>1,628<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Memory Clock<\/p>\n<\/td>\n<td>\n<p>1.9GHz<\/p>\n<\/td>\n<td>\n<p>5.1GHz<\/p>\n<\/td>\n<td>\n<p>1.56Ghz<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Memory Capacity<\/p>\n<\/td>\n<td>\n<p>192GB HBM3<\/p>\n<\/td>\n<td>\n<p>188GB<\/p>\n<\/td>\n<td>\n<p>96GB<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Memory Bandwidth<\/p>\n<\/td>\n<td>\n<p>5.2TB\/sec<\/p>\n<\/td>\n<td>\n<p>7.8TB\/s<\/p>\n<\/td>\n<td>\n<p>2.45TB\/sec<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Interconnect Bandwidth<\/p>\n<\/td>\n<td>\n<p>896 GB\/sec<\/p>\n<\/td>\n<td>\n<p>600GB\/s<\/p>\n<\/td>\n<td>\n<p>100GB\/s<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Max Power Consumption<\/p>\n<\/td>\n<td>\n<p>700W<\/p>\n<\/td>\n<td>\n<p>800W (2x400W)<\/p>\n<\/td>\n<td>\n<p>600W<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Price ($)<\/p>\n<\/td>\n<td>\n<p>$27,381 (Estimate)<\/p>\n<\/td>\n<td>\n<p>$80,000 (Estimate)<\/p>\n<\/td>\n<td>\n<p>&#8211;<\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: Company Data, The Next Platform, VideoCardz, Intel Habana, ANAND Tech, Gaming Deputy, HPCWire, TechPowerUp, Khaveen Investments.<\/em><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Based on the data in the table, starting with process technology, the AMD MI300x is built on a 5nm process from TSMC. The Nvidia H100 NVLink is fabricated on a 4nm process, which is even more advanced and efficient. On the other hand, the Intel Gaudi 2 is manufactured on a 7nm process, which is slightly less advanced than AMD and Nvidia.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Nvidia&#8217;s H100 NVLink has the highest number of transistors, with 160 bln, while AMD&#8217;s MI300x follows closely with 153bln transistors. Intel&#8217;s Gaudi 2 is reported to have more than 100 billion transistors. In terms of engine clock peak, the Nvidia H100 NVLink has the highest clock speed at 1.98 GHz, followed by the AMD MI300x at 1.7 GHz. In terms of performance, Nvidia&#8217;s H100 NVLink leads in FP16 peak performance with a whopping 3,958 teraflops. Additionally, Nvidia\u2019s strong performance is also seen in terms of INT 8 at 7,916, twice higher than AMD.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">However, when it comes to memory capacity, AMD&#8217;s MI300x offers the highest with 192GB of HBM3 memory, followed by Nvidia&#8217;s 188 GB. Intel&#8217;s Gaudi 2 has the smallest memory capacity at 96GB. Memory bandwidth is led by Nvidia&#8217;s H100 NVLink with 7.8TB\/s, followed by AMD&#8217;s MI300x with 5.2TB\/s and Intel&#8217;s Gaudi 2 with 2.45TB\/s. Additionally, AMD&#8217;s MI300x offers the highest interconnect bandwidth at 896GB\/s, while Nvidia&#8217;s H100 NVLink provides 600GB\/s, and Intel&#8217;s Gaudi 2 has 100GB\/s.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Nvidia&#8217;s H100 NVLink has the highest power consumption at 800W, which is not surprising given its high performance. AMD&#8217;s MI300x consumes 700W, and Intel&#8217;s Gaudi 2 is the most power-efficient at 600W.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">However, Intel\u2019s Gaudi2 is claimed to surpass Nvidia in the BridgeTower AI-based vision model benchmarks by Hugging Face at up to 2.5x faster than Nvidia\u2019s A100 and 1.4x H100.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><strong>Full Stack Advantage<\/strong><\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>Data Center Portfolio<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>Nvidia<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>AMD<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>Intel<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>CPU<\/p>\n<\/td>\n<td>\n<p>Launching 2024<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>GPU<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>DPU<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes (IPU)<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Networking Interconnects<\/p>\n<\/td>\n<td>\n<p>NVLink<\/p>\n<\/td>\n<td>\n<p>Infinity Fabric<\/p>\n<\/td>\n<td>\n<p>CXL Interconnect<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Software<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<td>\n<p>Yes<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td>\n<p>Integrated Hardware Solution<\/p>\n<\/td>\n<td>\n<p>Yes (DGX)<\/p>\n<\/td>\n<td>\n<p>N\/A<\/p>\n<\/td>\n<td>\n<p>N\/A<\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: Company Data, Khaveen Investments.<\/em><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We updated our comparison table of the data center portfolios of Nvidia, AMD and Intel. In terms of CPUs, AMD and Intel currently offer x86 server CPUs but Nvidia is launching its Arm-based CPUs in 2024. As we previously identified, we determined that AMD has the advantage in CPUs with the highest average benchmark score compared to Intel. Furthermore, all 3 companies have GPUs, which we explained above with Nvidia having the most powerful product with its 2023 new H100 NVL. All 3 companies also have DPUs and networking interconnects.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">In terms of Software integrations, all 3 companies also have similar software integrations such as Hugging Face, PyTorch and Tensor Flow as AMD, Intel and Nvidia have all formed partnerships with these companies and are open-source AI frameworks. Though, in our previous analysis, we identified Nvidia as having the greatest number of AI software integrations with its own proprietary software solutions and development kits such as \u201cover 450 NVIDIA AI libraries and software development kits to serve industries such as gaming, design, quantum computing, AI, 5G\/6G, and robotics.\u201d Furthermore, Intel also has AI software such as Intel oneAPI AI Analytics toolkit for accelerating machine learning applications.<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Partnerships <\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We already covered earlier how AMD has established an ecosystem of partners with various levels in the value chain such as cloud players and server manufacturers. However, we discovered that this is not a specific competitive advantage that AMD has, as Intel and Nvidia also have similar partner ecosystems established.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089637471054.png\" alt=\"nvidia partners\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>Nvidia<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">As seen from the image above, Nvidia also has partnerships with server manufacturers, software partners and others. This includes the top 3 server makers.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Intel also has various partners it works with including Microsoft and Google which are among the top 3 cloud providers as well as the top 5 server makers such as Dell, HPE, Inspur, Lenovo and IBM (IBM).<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Outlook <\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">While AMD claims its GPUs as the most advanced, our analysis of its competitors shows that Nvidia and Intel also have their own legs to stand on. In terms of performance, all three companies have advantages in certain areas. It would be precipitous to label one company as the clear winner. We believe each company has made tremendous leaps in innovation and has merits to claim its competitive place in the market. Regarding having a full-stack advantage, all three companies again have established a similar portfolio of products. Even the software and hardware integrations used to link these different chips are on par. While Nvidia is the slowest to market in CPUs (launching in 2024), it has a tremendous lead in the market for GPU share and also has the most AI software integrations.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">With these 3 companies dominating the entire GPU market, it is not surprising to see their partner ecosystems are also similar with all three ingrained with the same companies across the value chain. We believe all three companies are competitive in their own right, and we withhold on assigning a competitive factor scoring on any one company, considering each to be on par.<\/p>\n<h2 class=\"paywall-full-content invisible no-summary-bullets\"><strong>AMD Data Center Outlook<\/strong><\/h2>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We have previously covered AMD\u2019s data center market. While AMD does not break down the data center segment by type of chip, we were able to estimate the breakdown ourselves through numerous calculations as we previously explained.<\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>AMD Revenue Breakdown ($ mln)<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2020<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2021<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2022<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Data Center CPU Estimate<\/p>\n<\/td>\n<td>\n<p>1,153<\/p>\n<\/td>\n<td>\n<p>2,939<\/p>\n<\/td>\n<td>\n<p>4,131<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>155.0%<\/p>\n<\/td>\n<td>\n<p>40.6%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Data Center GPU Estimate<\/p>\n<\/td>\n<td>\n<p>532<\/p>\n<\/td>\n<td>\n<p>755<\/p>\n<\/td>\n<td>\n<p>1,040<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>41.8%<\/p>\n<\/td>\n<td>\n<p>37.7%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Data Center DPU Estimate<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>655.2<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p>Data Center FPGA Estimate (Xilinx)<\/p>\n<\/td>\n<td> <\/td>\n<td> <\/td>\n<td>\n<p>217<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-y\">\n<td>\n<p><strong>Total Data Center<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>1,685<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>3,694<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>6,043<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-y\">\n<td>\n<p><strong>Growth %<\/strong><\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p><strong>119.2%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>63.6%<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: Company Data, Khaveen Investments.<\/em><\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Revenue Model<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We had previously covered Nvidia and determined its unique subscription-based model for its DGX. Nvidia\u2019s DGX platform is are powerful system that is a combination of NVIDIA\u2019s products such as its H100 data center GPUs as well as well as other chips such as CPUs from AMD and Intel with software such as Nvidia AI Enterprise Software featuring its pre-trained AI models and optimized frameworks. The Nvidia DGX costs between $200,000 to $400,000 for a single unit. Additionally, Nvidia also provides a subscription model for its DGX SuperPods which has 4 DGX servers for a subscription price of $90,000 per month. In comparison, one Nvidia\u2019s A100 server GPU has a price of $10,000.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">AMD\u2019s EPYC 7742 server CPU has a product pricing of $6,950 while its MI225 server GPU was reported to be priced at $16,500 for the Japanese market. Additionally, Intel\u2019s Xeon Platinum 8180 server CPU has a recommended pricing of $10,000 each.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-1702208963430535.png\" alt=\"amd instinct\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>AMD<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">While the specific prices are not provided in the comparison, Nvidia&#8217;s H100 NVLink is estimated to be much more expensive than AMD&#8217;s.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><strong>Market Share<\/strong><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><strong>Data Center GPU<\/strong><\/p>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>Data Center GPU Share Estimate<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2020<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2021<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2022<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Nvidia Revenue ($ mln)<\/p>\n<\/td>\n<td>\n<p>6,696<\/p>\n<\/td>\n<td>\n<p>10,613<\/p>\n<\/td>\n<td>\n<p>15,005<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Nvidia % share<\/p>\n<\/td>\n<td>\n<p>92.6%<\/p>\n<\/td>\n<td>\n<p>88.6%<\/p>\n<\/td>\n<td>\n<p>88.9%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>AMD Revenue ($ mln)<\/p>\n<\/td>\n<td>\n<p>532<\/p>\n<\/td>\n<td>\n<p>755<\/p>\n<\/td>\n<td>\n<p>1,040<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>AMD % share<\/p>\n<\/td>\n<td>\n<p>7.4%<\/p>\n<\/td>\n<td>\n<p>6.3%<\/p>\n<\/td>\n<td>\n<p>6.2%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Intel Revenue ($ mln)<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>605<\/p>\n<\/td>\n<td>\n<p>836<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Intel % share<\/p>\n<\/td>\n<td>\n<p>0.0%<\/p>\n<\/td>\n<td>\n<p>5.0%<\/p>\n<\/td>\n<td>\n<p>5.0%<\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: Company Data, JPR, Khaveen Investments.<\/em><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Based on our server GPU market share table above, Nvidia had dominated the market in the past 3 years with almost 89% share in 2022, followed by AMD in second place with a fairly stable market share in the past 2 years. In 2021, Intel launched its Ponte Vecchio data center GPU and took share from Nvidia and AMD that year and remained stable in 2022.<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Data Center CPU Market<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089649710665.png\" alt=\"server cpu market share\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>PassMark, Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">In the past 10 years, Intel has dominated the server CPU market with over 90% of the market share. However, since 2021, AMD has gained market share at the expense of Intel but remained much smaller compared to Intel.<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>FPGA Market<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089636168592.jpg\" alt=\"FPGA share\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>PassMark, Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">In our FPGA market share, Xilinx dominates the market with a 53% market share with Intel trailing behind at 26.7% in 2022. The companies\u2019 market share has been stable in the past 2 years.<\/p>\n<h3 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Outlook<\/strong><\/h3>\n<p class=\"paywall-full-content invisible no-summary-bullets\">As we established earlier, our stance regarding the competitiveness of the three companies in the server GPU market is that they are all on par. The market shares of the companies over the past three years seem to corroborate this as all have been relatively stable. We believe their market share will continue to remain stable moving forward. Similarly, for FPGA and DPU we expect market shares to remain stable, which is what we factored into our projections. For CPUs, Intel managed to regain some share in the server CPU market between Q1 to Q3 2023. We believe this is due to the launch of Xeon Sapphire Rapids which we identified delivered a significant performance improvement compared to its previous gen. However, we still expect AMD to slightly gain market share moving forward based on our previous analysis in determining its competitive edge in CPU servers over Intel.<\/p>\n<h2 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Risk: Competition in AI Chips<\/strong><\/h2>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022089646106188.png\" alt=\"ai chips\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>Alexander Thamm, Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">While AMD, Intel, and Nvidia are the clear and established chipmakers in the market and at the forefront of AI, we believe AI has opened up the doors for other companies to tap into the market or enhance their in-house production. As we identified above, companies like Google have developed AI accelerators for internal use, which reduced their reliance on chipmakers. Other companies like IBM, Cerebras Systems, Graphcore, Hailo, and Groq have also developed AI processors that could eat into the chip processor markets of AMD, Intel and Nvidia.<\/p>\n<h2 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Valuation<\/strong><\/h2>\n<p> <span class=\"table-responsive paywall-full-content invisible no-summary-bullets\"><span class=\"table-scroll-wrapper\"><span data-intersection-boundary=\"start\"><\/span><\/p>\n<table>\n<tr>\n<td>\n<p><strong>AMD Revenue Forecast ($ mln)<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2022<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2023F<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2024F<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>2025F<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Client (PC CPU)<\/p>\n<\/td>\n<td>\n<p>6,201<\/p>\n<\/td>\n<td>\n<p>4,253<\/p>\n<\/td>\n<td>\n<p>5,681<\/p>\n<\/td>\n<td>\n<p>6,491<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td>\n<p>-10.0%<\/p>\n<\/td>\n<td>\n<p>-31.4%<\/p>\n<\/td>\n<td>\n<p>33.56%<\/p>\n<\/td>\n<td>\n<p>14.27%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Gaming Console Estimate<\/p>\n<\/td>\n<td>\n<p>5,740<\/p>\n<\/td>\n<td>\n<p>6,371<\/p>\n<\/td>\n<td>\n<p>7,001<\/p>\n<\/td>\n<td>\n<p>7,632<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td>\n<p>81.53%<\/p>\n<\/td>\n<td>\n<p>10.99%<\/p>\n<\/td>\n<td>\n<p>9.90%<\/p>\n<\/td>\n<td>\n<p>9.01%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Gaming (PC GPU) Estimate<\/p>\n<\/td>\n<td>\n<p>1,065<\/p>\n<\/td>\n<td>\n<p>964<\/p>\n<\/td>\n<td>\n<p>1,156<\/p>\n<\/td>\n<td>\n<p>1,281<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td>\n<p>-56.4%<\/p>\n<\/td>\n<td>\n<p>-9.5%<\/p>\n<\/td>\n<td>\n<p>19.9%<\/p>\n<\/td>\n<td>\n<p>10.8%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p>Data Center CPU Estimate<\/p>\n<\/td>\n<td>\n<p>4,131<\/p>\n<\/td>\n<td>\n<p>3,121<\/p>\n<\/td>\n<td>\n<p>4,880<\/p>\n<\/td>\n<td>\n<p>6,606<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td>\n<p>40.57%<\/p>\n<\/td>\n<td>\n<p>-24.44%<\/p>\n<\/td>\n<td>\n<p>56.34%<\/p>\n<\/td>\n<td>\n<p>35.37%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-y\">\n<td>\n<p>Data Center GPU Estimate<\/p>\n<\/td>\n<td>\n<p>1,040<\/p>\n<\/td>\n<td>\n<p>2,000<\/p>\n<\/td>\n<td>\n<p>3,067<\/p>\n<\/td>\n<td>\n<p>4,703<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-y\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td>\n<p>37.69%<\/p>\n<\/td>\n<td>\n<p>92.4%<\/p>\n<\/td>\n<td>\n<p>53.3%<\/p>\n<\/td>\n<td>\n<p>53.3%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Data Center DPU Estimate<\/p>\n<\/td>\n<td>\n<p>217<\/p>\n<\/td>\n<td>\n<p>275<\/p>\n<\/td>\n<td>\n<p>344<\/p>\n<\/td>\n<td>\n<p>423<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-b\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>26.9%<\/p>\n<\/td>\n<td>\n<p>24.9%<\/p>\n<\/td>\n<td>\n<p>22.9%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Data Center FPGA Estimate<\/p>\n<\/td>\n<td>\n<p>655.2<\/p>\n<\/td>\n<td>\n<p>751<\/p>\n<\/td>\n<td>\n<p>860<\/p>\n<\/td>\n<td>\n<p>986<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-g\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>14.60%<\/p>\n<\/td>\n<td>\n<p>14.60%<\/p>\n<\/td>\n<td>\n<p>14.60%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Embedded<\/p>\n<\/td>\n<td>\n<p>4,552<\/p>\n<\/td>\n<td>\n<p>5,217<\/p>\n<\/td>\n<td>\n<p>5,978<\/p>\n<\/td>\n<td>\n<p>6,851<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-gn\">\n<td>\n<p>Growth %<\/p>\n<\/td>\n<td> <\/td>\n<td>\n<p>14.60%<\/p>\n<\/td>\n<td>\n<p>14.60%<\/p>\n<\/td>\n<td>\n<p>14.60%<\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p><strong>Total<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>23,601<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>22,952<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>28,967<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>34,973<\/strong><\/p>\n<\/td>\n<\/tr>\n<tr class=\"bg-r\">\n<td>\n<p><strong>Growth %<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>43.6%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>-2.8%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>26.2%<\/strong><\/p>\n<\/td>\n<td>\n<p><strong>20.7%<\/strong><\/p>\n<\/td>\n<\/tr>\n<\/table>\n<p> <span data-intersection-boundary=\"end\"><\/span><\/span><button class=\"table-enlarge-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 16 16\" class=\"table-enlarge-icon\"><path fill-rule=\"evenodd\" clip-rule=\"evenodd\" d=\"M16 11a5 5 0 0 1-5 5H5a5 5 0 0 1-5-5V5a5 5 0 0 1 5-5h6a5 5 0 0 1 5 5v6zm-4.5-2.5h2v-6h-6v2h4v4zm-9-1h2v4h4v2h-6v-6z\"><\/path><\/svg>Click to enlarge<\/button><\/span> <\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\"><em>Source: Company Data, Khaveen Investments.<\/em><\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We updated our revenue projections for AMD by its segment breakdown. For the Client segment, we prorated its Q1 to Q3 revenues to estimate a decline of 31.4% for the full year. Whereas for its Gaming GPU segment, we updated our projections for shipment growth taking into account our PC market growth forecast of -11.7% before recovering in 2024.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">For its Data Center segment, we updated our 2023 revenue projections by CPU, GPU, DPU, and FPGA revenue estimates. For Data Center GPU, we based 2023 on management guidance of $2 bln in revenues from its latest earnings briefing and based our forecast in 2024 on our cloud market growth projections at an average of 37.3% and factored in an increase of 16% which we derived based on our estimate of the increase of chips demanded for AI. For the remaining Data Center FPGA and DPU as well as Embedded segments, we based its growth of the FPGA and DPU market forecast CAGR. For Data Center CPU revenue estimates in 2023, we prorated its Q1 to Q3 total Data Center revenues and subtracted our estimates of its GPU, FPGA and DPU revenues but recovering in 2024 based on our previous projections of its shipment and ASP growth.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">\n<figure class=\"regular-img-figure paywall-full-content invisible\" contenteditable=\"false\"><span><img decoding=\"async\" src=\"https:\/\/prosfunds.com\/wp-content\/uploads\/2023\/12\/49636850-17022098420944095.jpg\" alt=\"amd valuation\" contenteditable=\"false\" loading=\"lazy\"><\/span><figcaption>\n<p class=\"item-caption\"><span>Khaveen Investments<\/span><\/p>\n<\/figcaption><\/figure>\n<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">We valued the company with a discounted cash flow (&#8220;DCF&#8221;) valuation as the company\u2019s FCF margins have improved significantly over the past years with an FCF margin of 20.4% in the past 2 years. Based on a discount rate of 13.1% (company\u2019s WACC), we derived an upside of 33.3% from our DCF model with its terminal value based on the U.S.-only average chipmaker EV\/EBITDA of 23.59x.<\/p>\n<h2 class=\"paywall-full-content invisible no-summary-bullets\"><strong>Verdict<\/strong><\/h2>\n<p class=\"paywall-full-content invisible no-summary-bullets\">In conclusion, we believe AMD&#8217;s strategies, encompassing a broad product portfolio for AI, an open software platform for AI, and established partnerships, position the company as a significant player in the rapidly growing field of artificial intelligence. The computational demands of AI, especially in data-intensive tasks like machine learning, highlight the crucial role of high-performance chips. AMD&#8217;s focus on GPUs, along with its competitors Nvidia and Intel, underscores the industry-wide recognition of the importance of advanced chip technology in meeting the escalating demands of AI applications.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">While AMD claims superiority in GPU technology, our analysis reveals that Nvidia and Intel also exhibit strengths in various aspects. The competitive environment is fluid, with each company showcasing innovation and expertise, thus we believe it would be premature to declare a clear winner, as all three companies contribute significantly to the AI hardware market. Their diverse strengths, encompassing hardware, software, and integration capabilities, make them formidable contenders.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Examining market dynamics, we anticipate a stable market share for AMD, Nvidia, and Intel in the GPU sector. Despite differences in launch timelines and specific strengths, the overall competitive landscape remains balanced. The similarity in partner ecosystems and market shares across the GPU, FPGA, and DPU segments suggests a collective dominance by these three companies.<\/p>\n<p class=\"paywall-full-content invisible no-summary-bullets\">Consequently, we believe that moving forward, the market shares for AMD, Nvidia, and Intel will remain stable, in line with the projected growth in AI and data-intensive computing applications. We revised our company valuation using a DCF approach, taking into account the substantial improvement in its margins, averaging 20.4% over the past two years. Consequently, we set a higher price target of <em>$160.20<\/em> and maintain our <em>Strong Buy<\/em> rating for the company.<\/p>\n<\/div>\n<p>Read the full article <a href=\"https:\/\/seekingalpha.com\/article\/4657269-amd-ai-gpu-revolution-powers-next-data-center-frontier?source=feed_all_articles\" target=\"_blank\" rel=\"noopener\">here<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Advanced Micro Devices, Inc. (NASDAQ:AMD) is one of the top semiconductor companies in the world, with a strong foothold in the CPU and GPU markets. Both these chips are a core component for servers used in data centers and businesses. We previously covered how Nvidia Corporation (NVDA) is dominating the data center space, with the [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":54287,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[38],"tags":[],"class_list":{"0":"post-54286","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-news"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>AMD: AI GPU Revolution Powers Next Data Center Frontier (NASDAQ:AMD) | Prosfunds<\/title>\n<meta name=\"description\" content=\"Advanced Micro Devices, Inc. (NASDAQ:AMD) is one of the top semiconductor companies in the world, with a strong foothold in the CPU and GPU markets. 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