Red Hat, the world's leading provider of open source solutions, and AMD today announced a strategic collaboration to propel AI capabilities and optimize virtualized infrastructure. With this deepened alliance, Red Hat and AMD will expand customer choice across the hybrid cloud, from deploying optimized, efficient AI models to more cost-effectively modernizing traditional virtual machines (VMs). As workload demand and diversity continue to rise with the introduction of AI, organizations must have the capacity and resources to meet these escalating requirements. The average datacenter, however, is dedicated primarily to traditional IT systems, leaving little room to support intensive workloads such as AI. To answer this need, Red Hat and AMD are bringing together the power of Red Hat's industry-leading open source solutions with the comprehensive portfolio of AMD high-performance computing architectures.

AMD and Red Hat: Driving to more efficient generative AI
Red Hat and AMD are combining the power of Red Hat AI with the AMD portfolio of x86-based processors and GPU architectures to support optimized, cost-efficient and production-ready environments for AI-enabled workloads. AMD Instinct GPUs are now fully enabled on Red Hat OpenShift AI, empowering customers with the high-performing processing power necessary for AI deployments across the hybrid cloud without extreme resource requirements. In addition, using AMD Instinct MI300X GPUs with Red Hat Enterprise Linux AI, Red Hat and AMD conducted testing on Microsoft Azure ND MI300X v5 to successfully demonstrate AI inferencing for scaling small language models (SLMs) as well as large language models (LLM) deployed across multiple GPUs on a single VM, reducing the need to deploy across multiple VMs and reducing performance costs.

Vultr, the world's largest privately-held cloud infrastructure company, today announced that it is one of the first cloud providers to offer the new AMD EPYC 4005 Series processors. The AMD EPYC 4005 Series processors will be available on the Vultr platform, enabling enterprise-class features and leading performance for businesses and hosted IT service providers. The AMD EPYC 4005 Series processors extend the broad AMD EPYC processor family, powering a new line of cost-effective systems designed for growing businesses and hosted IT services providers that demand performance, advanced technologies, energy efficiency, and affordability. Servers featuring the high-performance AMD EPYC 4005 Series CPUs with streamlined memory and I/O feature sets are designed to deliver compelling system price-to-performance metrics on key customer workloads. Meanwhile, the combination of up to 16 SMT-capable cores and DDR5 memory in the AMD EPYC 4005 Series processors enables smooth execution of business-critical workloads, while maintaining the thermal and power efficiency characteristics crucial for affordable compute environments.

"Vultr is committed to delivering the most advanced cloud infrastructure with unrivaled price-to-performance," said J.J. Kardwell, CEO of Vultr. "The AMD EPYC 4005 Series provides straightforward deployment, scalability, high clock speed, energy efficiency, and best-in-class performance. Whether you are a business striving to scale reliably or a developer crafting the next groundbreaking innovation, these solutions are designed to deliver exceptional value and meet demanding requirements now and in the future." Vultr's launch of systems featuring the AMD EPYC 4245P and AMD EPYC 4345P processors will expand the company's robust line of Bare Metal solutions. Vultr will also feature the AMD EPYC 4345P as part of its High Frequency Compute (HFC) offerings for organizations requiring the highest clock speeds and access to locally-attached NVMe storage.

MangoBoost, a provider of cutting-edge system solutions designed to maximize AI data center efficiency, has set a new industry benchmark with its latest MLPerf Inference v5.0 submission. The company's Mango LLMBoost AI Enterprise MLOps software has demonstrated unparalleled performance on AMD Instinct MI300X GPUs, delivering the highest-ever recorded results for Llama2-70B in the offline inference category. This milestone marks the first-ever multi-node MLPerf inference result on AMD Instinct MI300X GPUs. By harnessing the power of 32 MI300X GPUs across four server nodes, Mango LLMBoost has surpassed all previous MLPerf inference results, including those from competitors using NVIDIA H100 GPUs.

Unmatched Performance and Cost Efficiency
MangoBoost's MLPerf submission demonstrates a 24% performance advantage over the best-published MLPerf result from Juniper Networks utilizing 32 NVIDIA H100 GPUs. Mango LLMBoost achieved 103,182 tokens per second (TPS) in the offline scenario and 93,039 TPS in the server scenario on AMD MI300X GPUs, outperforming the previous best result of 82,749 TPS on NVIDIA H100 GPUs. In addition to superior performance, Mango LLMBoost + MI300X offers significant cost advantages. With AMD MI300X GPUs priced between $15,000 and $17,000—compared to the $32,000-$40,000 cost of NVIDIA H100 GPUs (source: Tom's Hardware—H100 vs. MI300X Pricing)—Mango LLMBoost delivers up to 62% cost savings while maintaining industry-leading inference throughput.

The battle of AI acceleration in the data center is, as most readers are aware, insanely competitive, with NVIDIA offering a top-tier software stack. However, AMD has tried in recent years to capture a part of the revenue that hyperscalers and OEMs are willing to spend with its Instinct MI300X accelerator lineup for AI and HPC. Despite having decent hardware, the company is not close to bridging the gap software-wise with its competitor, NVIDIA. According to the latest report from SemiAnalysis, a research and consultancy firm, they have run a five-month experiment using Instinct MI300X for training and benchmark runs. And the findings were surprising: even with better hardware, AMD's software stack, including ROCm, has massively degraded AMD's performance.

"When comparing NVIDIA's GPUs to AMD's MI300X, we found that the potential on paper advantage of the MI300X was not realized due to a lack within AMD public release software stack and the lack of testing from AMD," noted SemiAnalysis, breaking down arguments in the report further, adding that "AMD's software experience is riddled with bugs rendering out of the box training with AMD is impossible. We were hopeful that AMD could emerge as a strong competitor to NVIDIA in training workloads, but, as of today, this is unfortunately not the case. The CUDA moat has yet to be crossed by AMD due to AMD's weaker-than-expected software Quality Assurance (QA) culture and its challenging out-of-the-box experience."

IBM and AMD have announced a collaboration to deploy AMD Instinct MI300X accelerators as a service on IBM Cloud. This offering, which is expected to be available in the first half of 2025, aims to enhance performance and power efficiency for Gen AI models such as and high-performance computing (HPC) applications for enterprise clients. This collaboration will also enable support for AMD Instinct MI300X accelerators within IBM's watsonx AI and data platform, as well as Red Hat Enterprise Linux AI inferencing support.

"As enterprises continue adopting larger AI models and datasets, it is critical that the accelerators within the system can process compute-intensive workloads with high performance and flexibility to scale," said Philip Guido, executive vice president and chief commercial officer, AMD. "AMD Instinct accelerators combined with AMD ROCm software offer wide support including IBM watsonx AI, Red Hat Enterprise Linux AI and Red Hat OpenShift AI platforms to build leading frameworks using these powerful open ecosystem tools. Our collaboration with IBM Cloud will aim to allow customers to execute and scale Gen AI inferencing without hindering cost, performance or efficiency."

During the Open Compute Project (OCP) Summit 2024, Meta, one of the prime members of the OCP project, showed its NVIDIA "Blackwell" GB200 systems for its massive data centers. We previously covered Microsoft's Azure server rack with GB200 GPUs featuring one-third of the rack space for computing and two-thirds for cooling. A few days later, Google showed off its smaller GB200 system, and today, Meta is showing off its GB200 system—the smallest of the bunch. To train a dense transformer large language model with 405B parameters and a context window of up to 128k tokens, like the Llama 3.1 405B, Meta must redesign its data center infrastructure to run a distributed training job on two 24,000 GPU clusters. That is 48,000 GPUs used for training a single AI model.

Called "Catalina," it is built on the NVIDIA Blackwell platform, emphasizing modularity and adaptability while incorporating the latest NVIDIA GB200 Grace Blackwell Superchip. To address the escalating power requirements of GPUs, Catalina introduces the Orv3, a high-power rack capable of delivering up to 140kW. The comprehensive liquid-cooled setup encompasses a power shelf supporting various components, including a compute tray, switch tray, the Orv3 HPR, Wedge 400 fabric switch with 12.8 Tbps switching capacity, management switch, battery backup, and a rack management controller. Interestingly, Meta also upgraded its "Grand Teton" system for internal usage, such as deep learning recommendation models (DLRMs) and content understanding with AMD Instinct MI300X. Those are used to inference internal models, and MI300X appears to provide the best performance per Dollar for inference. According to Meta, the computational demand stemming from AI will continue to increase exponentially, so more NVIDIA and AMD GPUs is needed, and we can't wait to see what the company builds.

Dell Technologies (NYSE: DELL) expands the world's broadest generative AI (GenAI) solutions portfolio with Dell AI Factory additions tailored for AMD environments. These solutions offer enterprises enhanced AI capabilities, including greater scalability and flexibility, to stay competitive in the evolving technology landscape.

"By integrating AMD technology into the latest Dell servers, AI solutions and services through the Dell AI Factory, we're providing the performance and efficiencies enterprises need today and in the future," said Arthur Lewis, president, Infrastructure Solutions Group, Dell Technologies. "Together with AMD, we are setting new standards in AI performance, giving enterprises powerful and cost-effective solutions essential for modern data-driven environments."

During its "Advancing AI" conference today, AMD has updated its AI accelerator portfolio with the Instinct MI325X accelerator, designed to succeed its MI300X predecessor. Built on the CDNA 3 architecture, Instinct MI325X brings a suite of improvements over the old SKU. Now, the MI325X features 256 GB of HBM3E memory running at 6 TB/s bandwidth. The capacity memory alone is a 1.8x improvement over the old MI300 SKU, which features 192 GB of regular HBM3 memory. Providing more memory capacity is crucial as upcoming AI workloads are training models with parameter counts measured in trillions, as opposed to billions with current models we have today. When it comes to compute resources, the Instinct MI325X provides 1.3 PetaFLOPS at FP16 and 2.6 PetaFLOPS at FP8 training and inference. This represents a 1.3x improvement over the Instinct MI300.

A chip alone is worthless without a good platform, and AMD decided to make the Instinct MI325X OAM modules a drop-in replacement for the current platform designed for MI300X, as they are both pin-compatible. In systems packing eight MI325X accelerators, there are 2 TB of HBM3E memory running at 48 TB/s memory bandwidth. Such a system achieves 10.4 PetaFLOPS of FP16 and 20.8 PetaFLOPS of FP8 compute performance. The company uses NVIDIA's H200 HGX as reference claims for its performance competitiveness, where the company claims that the Instinct MI325X outperforms NVIDIA H200 HGX system by 1.3x across the board in memory bandwidth, FP16 / FP8 compute performance and 1.8x in memory capacity.

AMD today announced that Oracle Cloud Infrastructure (OCI) has chosen AMD Instinct MI300X accelerators with ROCm open software to power its newest OCI Compute Supercluster instance called BM.GPU.MI300X.8. For AI models that can comprise hundreds of billions of parameters, the OCI Supercluster with AMD MI300X supports up to 16,384 GPUs in a single cluster by harnessing the same ultrafast network fabric technology used by other accelerators on OCI. Designed to run demanding AI workloads including large language model (LLM) inference and training that requires high throughput with leading memory capacity and bandwidth, these OCI bare metal instances have already been adopted by companies including Fireworks AI.

"AMD Instinct MI300X and ROCm open software continue to gain momentum as trusted solutions for powering the most critical OCI AI workloads," said Andrew Dieckmann, corporate vice president and general manager, Data Center GPU Business, AMD. "As these solutions expand further into growing AI-intensive markets, the combination will benefit OCI customers with high performance, efficiency, and greater system design flexibility."

ASUS today announced its ambitious All in AI initiative, marking a significant leap into the server market with a complete AI infrastructure solution, designed to meet the evolving demands of AI-driven applications from edge, inference and generative AI the new, unparalleled wave of AI supercomputing. ASUS has proven its expertise lies in striking the perfect balance between hardware and software, including infrastructure and cluster architecture design, server installation, testing, onboarding, remote management and cloud services - positioning the ASUS brand and AI server solutions to lead the way in driving innovation and enabling the widespread adoption of AI across industries.

Meeting diverse AI needs
In partnership with NVIDIA, Intel and AMD, ASUS offer comprehensive AI-infrastructure solutions with robust software platforms and services, from entry-level AI servers and machine-learning solutions to full racks and data centers for large-scale supercomputing. At the forefront is the ESC AI POD with NVIDIA GB200 NVL72, a cutting-edge rack designed to accelerate trillion-token LLM training and real-time inference operations. Complemented by the latest NVIDIA Blackwell GPUs, NVIDIA Grace CPUs and 5th Gen NVIDIA NVLink technology, ASUS servers ensure unparalleled computing power and efficiency.

AMD has quietly added some interesting codenames to its ROCm hardware support list. The biggest surprise is the appearance of "RDNA 4" and "Navi 44" codenames, hinting at a potential successor to the current RDNA 3 GPU architecture powering AMD's Radeon RX 7000 series graphics cards. The upcoming Radeon RX 8000 series could see Navi 44 SKU with a codename "gfx1200". While details are scarce, the inclusion of RDNA 4 and Navi 44 in the ROCm list suggests AMD is working on a new GPU microarchitecture that could bring significant performance and efficiency gains. While RDNA 4 may be destined for future Radeon gaming GPUs, in the data center GPU compute market, AMD is preparing a CDNA 4 based successors to the MI300 series. However, it appears that we haven't seen all the MI300 variants first. Equally intriguing is the "MI300X1" codename, which appears to reference an upcoming AI-focused accelerator from AMD.

While we wait for more information, we can't decipher whether the Navi 44 GPU SKU is for the high-end or low-end segment. If previous generations are for reference, then the Navi 44 SKU would target the low end of the GPU performance spectrum. The previous generation RDNA 3 had Navi 33 as an entry-level model, whereas the RDNA 2 had a Navi 24 SKU for entry-level GPUs. We have reported on RDNA 4 merely being a "bug correction" generation to fix the perf/Watt curve and offer better efficiency overall. What happens finally, we have to wait and see. AMD could announce more details in its upcoming Computex keynote.

Today at Microsoft Build, AMD (NASDAQ: AMD) showcased its latest end-to-end compute and software capabilities for Microsoft customers and developers. By using AMD solutions such as AMD Instinct MI300X accelerators, ROCm open software, Ryzen AI processors and software, and Alveo MA35D media accelerators, Microsoft is able to provide a powerful suite of tools for AI-based deployments across numerous markets. The new Microsoft Azure ND MI300X virtual machines (VMs) are now generally available, giving customers like Hugging Face, access to impressive performance and efficiency for their most demanding AI workloads.

"The AMD Instinct MI300X and ROCm software stack is powering the Azure OpenAI Chat GPT 3.5 and 4 services, which are some of the world's most demanding AI workloads," said Victor Peng, president, AMD. "With the general availability of the new VMs from Azure, AI customers have broader access to MI300X to deliver high-performance and efficient solutions for AI applications."

AMD's Instinct family has welcomed a new addition—the MI388X AI accelerator—as discovered in a lengthy regulatory 10K filing (submitted to the SEC). The document reveals that the unannounced SKU—along with the MI250, MI300X and MI300A integrated circuits—cannot be sold to Chinese customers due to updated US trade regulations (new requirements were issued around October 2023). Versal VC2802 and VE2802 FPGA products are also mentioned in the same section. Earlier this month, AMD's Chinese market-specific Instinct MI309 package was deemed to be too powerful for purpose by the US Department of Commerce.

AMD has not published anything about the Instinct MI388X's official specification, and technical details have not emerged via leaks. The "X" tag likely implies that it has been designed for AI and HPC applications, akin to the recently launched MI300X accelerator. The designation of a higher model number could (naturally) point to a potentially more potent spec sheet, although Tom's Hardware posits that MI388X is a semi-custom spinoff of an existing model.

Ryan McCurdy, President of Lenovo North America, revealed ambitious forward-thinking product roadmap during an interview with CRN magazine. A hybrid strategic approach will create an anticipated AI fast lane on future hardware—McCurdy, a former Intel veteran, stated: "there will be a steady stream of product development to add (AI PC) hardware capabilities in a chicken-and-egg scenario for the OS and for the (independent software vendor) community to develop their latest AI capabilities on top of that hardware...So we are really paving the AI autobahn from a hardware perspective so that we can get the AI software cars to go faster on them." Lenovo—as expected—is jumping on the AI-on-device train, but it will be diversifying its range of AI server systems with new AMD and Intel-powered options. The company has reacted to recent Team Green AI GPU supply issues—alternative units are now in the picture: "with NVIDIA, I think there's obviously lead times associated with it, and there's some end customer identification, to make sure that the products are going to certain identified end customers. As we showcased at Tech World with NVIDIA on stage, AMD on stage, Intel on stage and Microsoft on stage, those industry partnerships are critical to not only how we operate on a tactical supply chain question but also on a strategic what's our value proposition."

McCurdy did not go into detail about upcoming Intel-based server equipment, but seemed excited about AMD's Instinct MI300X accelerator—Lenovo was (previously) announced as one of the early OEM takers of Team Red's latest CDNA 3.0 tech. CRN asked about the firm's outlook for upcoming MI300X-based inventory—McCurdy responded with: "I won't comment on an unreleased product, but the partnership I think illustrates the larger point, which is the industry is looking for a broad array of options. Obviously, when you have any sort of lead times, especially six-month, nine-month and 12-month lead times, there is interest in this incredible technology to be more broadly available. I think you could say in a very generic sense, demand is as high as we've ever seen for the product. And then it comes down to getting the infrastructure launched, getting testing done, and getting workloads validated, and all that work is underway. So I think there is a very hungry end customer-partner user base when it comes to alternatives and a more broad, diverse set of solutions."

Brett Simpson, Partner and Co-Founder of Arete Research, sat down with AMD CTO Mark Papermaster during the former's "Investor Webinar Conference." A transcript of the Arete + AMD question and answer session appeared online last week—the documented fireside chat concentrated mostly on "AI compute market" topics. Papermaster was asked about his company's competitive approach when taking on NVIDIA's very popular range of A100 and H100 AI GPUs, as well as the recently launched GH200 chip. The CTO did not reveal any specific pricing strategies—a "big picture" was painted instead: "I think what's important when you just step back is to look at total cost of ownership, not just one GPU, one accelerator, but total cost of ownership. But now when you also look at the macro, if there's not competition in the market, you're going to see not only a growth of the price of these devices due to the added content that they have, but you're -- without a check and balance, you're going to see very, very high margins, more than that could be sustained without a competitive environment."

Papermaster continued: "And what I think is very key with -- as AMD has brought competition market for these most powerful AI training and inference devices is you will see that check and balance. And we have a very innovative approach. We've been a leader in chiplet design. And so we have the right technology for the right purpose of the AI build-out that we do. We have, of course, a GPU accelerator. But there's many other circuitry associated with being able to scale and build out these large clusters, and we're very, very efficient in our design." Team Red started to ship its flagship accelerator, Instinct MI300X, to important customers at the start of 2024—Arete Research's Simpson asked about the possibility of follow-up models. In response, AMD's CTO referenced some recent history: "Well, I think the first thing that I'll highlight is what we did to arrive at this point, where we are a competitive force. We've been investing for years in building up our GPU road map to compete in both HPC and AI. We had a very, very strong harbor train that we've been on, but we had to build our muscle in the software enablement."

GIGABYTE Technology, an IT pioneer advancing global industries through cloud and AI computing systems, is presenting innovative enterprise computing solutions at MWC 2024, featuring trailblazing servers, green computing solutions, and edge AI technologies, under the theme "Future of COMPUTING." These advancements usher in new possibilities for agile and sustainable IT strategies, enabling industries to harness real-time intelligence across hyperconnected data centers, cloud, edge, and devices, resulting in enhanced efficiency, cost-effectiveness, and competitive advantages, all propelled by the synergies of 5G and AI technologies.

GIGABYTE presents G593-ZX1/ZX2, the AI server featuring AMD Instinct MI300X 8-GPU, which is a new addition to GIGABYTE's flagship AI/HPC server series. Other highlighted exhibits include the high-density H223-V10 supporting the NVIDIA Grace Hopper Superchip, the G383-R80 server supporting four AMD Instinct MI300A APUs, and a G593 series AI server equipped with the powerful NVIDIA HGX H100 8-GPU.

GIGABYTE Technology, an IT pioneer whose focus is to advance global industries through cloud and AI computing systems, is coming to MWC 2024 with its next-generation servers empowering telcos, cloud service providers, enterprises, and SMBs to swiftly harness the value of 5G and AI. Featured is a cutting-edge AI server boasting AMD Instinct MI300X 8-GPU, and a comprehensive AI/HPC server series supporting the latest chip technology from AMD, Intel, and NVIDIA. The showcase will also feature integrated green computing solutions excelling in heat dissipation and energy reduction.

Continuing the booth theme "Future of COMPUTING", GIGABYTE's presentation will cover servers for AI/HPC, RAN and Core networks, modular edge platforms, all-in-one green computing solutions, and AI-powered self-driving technology. The exhibits will demonstrate how industries extend AI applications from cloud to edge and terminal devices through 5G connectivity, expanding future opportunities with faster time to market and sustainable operations. The showcase spans from February 26th to 29th at Booth #5F60, Hall 5, Fira Gran Via, Barcelona.

AMD's December 2023 launch of new Instinct series accelerators has generated a lot of tech news buzz and excitement within the financial world, but not many folks are privy to Team Red's MSRP for the CDNA 3.0 powered MI300X and MI300A models. A Citi report has pulled back the curtain, albeit with "projected" figures—an inside source claims that Microsoft has purchased the Instinct MI300X 192 GB model for ~$10,000 a piece. North American enterprise customers appear to have taken delivery of the latest MI300 products around mid-January time—inevitably, top secret information has leaked out to news investigators. SeekingAlpha's article (based on Citi's findings) alleges that the Microsoft data center division is AMD's top buyer of MI300X hardware—GPT-4 is reportedly up and running on these brand new accelerators.

The leakers claim that businesses further down the (AI and HPC) food chain are having to shell out $15,000 per MI300X unit, but this is a bargain when compared to NVIDIA's closest competing package—the venerable H100 SXM5 80 GB professional card. Team Green, similarly, does not reveal its enterprise pricing to the wider public—Tom's Hardware has kept tabs on H100 insider info and market leaks: "over the recent quarters, we have seen NVIDIA's H100 80 GB HBM2E add-in-card available for $30,000, $40,000, and even much more at eBay. Meanwhile, the more powerful H100 80 GB SXM with 80 GB of HBM3 memory tends to cost more than an H100 80 GB AIB." Citi's projection has Team Green charging up to four times more for its H100 product, when compared to Team Red MI300X pricing. NVIDIA's dominant AI GPU market position could be challenged by cheaper yet still very performant alternatives—additionally chip shortages have caused Jensen & Co. to step outside their comfort zone. Tom's Hardware reached out to AMD for comment on the Citi pricing claims—a company representative declined this invitation.

LaminiAI appeared to be one of the first customers to receive an initial shipment of AMD's Instinct MI300X accelerators, as disclosed by their CEO posting about functioning hardware on social media late last week. A recent Taiwan Economic Daily article states that the "MI300X is rumored to have begun supply"—we are not sure about why they have adopted a semi-secretive tone in their news piece, but a couple of anonymous sources are cited. A person familiar with supply chains in Taiwan divulged that: "(they have) been receiving AMD MI300X chips one after another...due to the huge shortage of NVIDIA AI chips, the arrival of new AMD products is really a timely rainfall." Favorable industry analysis (from earlier this month) has placed Team Red in a position of strength, due to growing interest in their very performant flagship AI accelerator.

The secrecy seems to lie in Team Red's negotiation strategies in Taiwan—the news piece alleges that big manufacturers in the region have been courted. AMD has been aggressive in a push to: "cooperate and seize AI business opportunities, with GIGABYTE taking the lead and attracting the most attention. Not only was GIGABYTE the first to obtain a partnership with AMD's MI300A chip, which had previously been mass-produced, but GIGABYTE was also one of the few Taiwanese manufacturers included in AMD's first batch of MI300X partners." GIGABYTE is expected to release two new "G593" product lines of server hardware later this year, based on combinations of AMD's Instinct MI300X accelerator and EPYC 9004 series processors.

LaminiAI appears to be one of AMD's first customers to receive a bulk order of Instinct MI300X GPUs—late last week, Sharon Zhou (CEO and co-founder) posted about the "next batch of LaminiAI LLM Pods" up and running with Team Red's cutting-edge CDNA 3 series accelerators inside. Her short post on social media stated: "rocm-smi...like freshly baked bread, 8x MI300X is online—if you're building on open LLMs and you're blocked on compute, lmk. Everyone should have access to this wizard technology called LLMs."

An attached screenshot of a ROCm System Management Interface (ROCm SMI) session showcases an individual Pod configuration sporting eight Instinct MI300X GPUs. According to official blog entries, LaminiAI has utilized bog-standard MI300 accelerators since 2023, so it is not surprising to see their partnership continue to grow with AMD. Industry predictions have the Instinct MI300X and MI300A models placed as great alternatives to NVIDIA's dominant H100 "Hopper" series—AMD stock is climbing due to encouraging financial analyst estimations.

With NVIDIA's Ampere and Hopper GPUs enjoying a domination in the AI acceleration industry, compute companies are turning to AMD's Instinct CDNA series accelerators to look for alternatives. It seems like they've found one. This has financial market analysts excited, causing the AMD company stock to hit near record highs. AMD recently launched the Instinct MI300X and MI300A processors based on the CDNA 3 architecture, which the company claims beat NVIDIA's H100 "Hopper" processors at competitive prices, which has encouraged analysts from major financial institutions, including Barclays, KeyBanc Capital, and Susquehanna Financial Group, to increase their price targets for the AMD stock. As of market closure at Jan 17, 7:59:56 PM UTC, the AMD stock stood at $160.17, near its November 2021 record high of $164.46.

AMD's data center business looks to ramp up Instinct CDNA accelerators through 2024. These large chiplet-based GPUs are based on the same 5 nm TSMC foundry nodes to NVIDIA's H100 "Hopper," and to maximize the use of its foundry allocation, it's been reported that AMD might even forego large gaming GPUs based on its Radeon RX RDNA4 architecture, to maximize its allocation for high-margin CDNA3 chips. The Instinct MI300X features a colossal 304 compute units worth 19,456 stream processors capable of AI-relevant math formats, and 192 GB of 8192-bit HBM3 memory, with 5.2 TB/s of memory bandwidth on tap.

During the recent IEDM conference, TSMC previewed its process roadmap for delivering next-generation chip packages packing over one trillion transistors by 2030. This aligns with similar long-term visions from Intel. Such enormous transistor counts will come through advanced 3D packaging of multiple chipsets. But TSMC also aims to push monolithic chip complexity higher, ultimately enabling 200 billion transistor designs on a single die. This requires steady enhancement of TSMC's planned N2, N2P, N1.4, and N1 nodes, which are slated to arrive between now and the end of the decade. While multi-chipset architectures are currently gaining favor, TSMC asserts both packaging density and raw transistor density must scale up in tandem. Some perspective on the magnitude of TSMC's goals include NVIDIA's 80 billion transistor GH100 GPU—among today's largest chips, excluding wafer-scale designs from Cerebras.

Yet TSMC's roadmap calls for more than doubling that, first with over 100 billion transistor monolithic designs, then eventually 200 billion. Of course, yields become more challenging as die sizes grow, which is where advanced packaging of smaller chiplets becomes crucial. Multi-chip module offerings like AMD's MI300X and Intel's Ponte Vecchio already integrate dozens of tiles, with PVC having 47 tiles. TSMC envisions this expansion to chip packages housing more than a trillion transistors via its CoWoS, InFO, 3D stacking, and many other technologies. While the scaling cadence has recently slowed, TSMC remains confident in achieving both packaging and process breakthroughs to meet future density demands. The foundry's continuous investment ensures progress in unlocking next-generation semiconductor capabilities. But physics ultimately dictates timelines, no matter how aggressive the roadmap.

Supermicro, Inc., a Total IT Solution Manufacturer for AI, Cloud, Storage, and 5G/Edge, is announcing three new additions to its AMD-based H13 generation of GPU Servers, optimized to deliver leading-edge performance and efficiency, powered by the new AMD Instinct MI300 Series accelerators. Supermicro's powerful rack scale solutions with 8-GPU servers with the AMD Instinct MI300X OAM configuration are ideal for large model training.

The new 2U liquid-cooled and 4U air-cooled servers with the AMD Instinct MI300A Accelerated Processing Units (APUs) accelerators are available and improve data center efficiencies and power the fast-growing complex demands in AI, LLM, and HPC. The new systems contain quad APUs for scalable applications. Supermicro can deliver complete liquid-cooled racks for large-scale environments with up to 1,728 TFlops of FP64 performance per rack. Supermicro worldwide manufacturing facilities streamline the delivery of these new servers for AI and HPC convergence.

Generative AI (GenAI) is the decade's most promising accelerator for innovation with 78% of IT decision makers reporting they're largely excited for the potential GenAI can have on their organizations.¹ Most see GenAI as a means to provide productivity gains, streamline processes and achieve cost savings. Harnessing this technology is critical to ensure organizations can compete in this new digital era.

Dell Technologies and AMD are coming together to unveil an expansion to the Dell Generative AI Solutions portfolio, continuing the work of accelerating advanced workloads and offering businesses more choice to continue their unique GenAI journeys. This new technology highlights a pivotal role played by open ecosystems and silicon diversity in empowering customers with simple, trusted and tailored solutions to bring AI to their data.

Today at the "Advancing AI" event, AMD was joined by industry leaders including Microsoft, Meta, Oracle, Dell Technologies, HPE, Lenovo, Supermicro, Arista, Broadcom and Cisco to showcase how these companies are working with AMD to deliver advanced AI solutions spanning from cloud to enterprise and PCs. AMD launched multiple new products at the event, including the AMD Instinct MI300 Series data center AI accelerators, ROCm 6 open software stack with significant optimizations and new features supporting Large Language Models (LLMs) and Ryzen 8040 Series processors with Ryzen AI.

"AI is the future of computing and AMD is uniquely positioned to power the end-to-end infrastructure that will define this AI era, from massive cloud installations to enterprise clusters and AI-enabled intelligent embedded devices and PCs," said AMD Chair and CEO Dr. Lisa Su. "We are seeing very strong demand for our new Instinct MI300 GPUs, which are the highest-performance accelerators in the world for generative AI. We are also building significant momentum for our data center AI solutions with the largest cloud companies, the industry's top server providers, and the most innovative AI startups ꟷ who we are working closely with to rapidly bring Instinct MI300 solutions to market that will dramatically accelerate the pace of innovation across the entire AI ecosystem."