Huawei announced its CloudMatrix 384 system super node, which the company touts as its own domestic alternative to NVIDIA's GB200 NVL72 system, with more overall system performance but worse per-chip performance and higher power consumption. While NVIDIA's GB200 NVL72 uses 36 Grace CPUs paired with 72 "Blackwell" GB200 GPUs, the Huawei CloudMatrix 384 system employs 384 Huawei Ascend 910C accelerators to beat NVIDIA's GB200 NVL72 system. It takes roughly five times more Ascend 910C accelerators to deliver nearly twice the GB200 NVL system performance, which is not good on per-accelerator bias, but excellent on per-system level of deployment. SemiAnalysis argues that Huawei is a generation behind in chip performance but ahead of NVIDIA in scale-up system design and deployment.

When you look at individual chips, NVIDIA's GB200 NVL72 clearly outshines Huawei's Ascend 910C, delivering over three times the BF16 performance (2,500 TeraFLOPS vs. 780 TeraFLOPS), more on‑chip memory (192 GB vs. 128 GB), and faster bandwidth (8 TB/s vs. 3.2 TB/s). In other words, NVIDIA has the raw power and efficiency advantage at the chip level. But flip the switch to the system level, and Huawei's CloudMatrix CM384 takes the lead. It cranks out 1.7× the overall PetaFLOPS, packs in 3.6× more total HBM capacity, and supports over five times the number of GPUs and the associated bandwidth of NVIDIA's NVL72 cluster. However, that scalability does come with a trade‑off, as Huawei's setup draws nearly four times more total power. A single GB200 NVL72 draws 145 kW of power, while a single Huawei CloudMatrix 384 draws ~560 kW. So, NVIDIA is your go-to if you need peak efficiency in a single GPU. If you're building a massive AI supercluster where total throughput and interconnect speed matter most, Huawei's solution actually makes a lot of sense. Thanks to its all-to-all topology, Huawei has delivered an AI training and inference system worth purchasing. When SMIC, the maker of Huawei's chips, gets to a more advanced manufacturing node, the efficiency of these systems will also increase.

CoreWeave today became one of the first cloud providers to bring NVIDIA GB200 NVL72 systems online for customers at scale, and AI frontier companies Cohere, IBM and Mistral AI are already using them to train and deploy next-generation AI models and applications. CoreWeave, the first cloud provider to make NVIDIA Grace Blackwell generally available, has already shown incredible results in MLPerf benchmarks with NVIDIA GB200 NVL72 - a powerful rack-scale accelerated computing platform designed for reasoning and AI agents. Now, CoreWeave customers are gaining access to thousands of NVIDIA Blackwell GPUs.

"We work closely with NVIDIA to quickly deliver to customers the latest and most powerful solutions for training AI models and serving inference," said Mike Intrator, CEO of CoreWeave. "With new Grace Blackwell rack-scale systems in hand, many of our customers will be the first to see the benefits and performance of AI innovators operating at scale."

Supermicro, Inc., a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, announced a new optimized storage server for high-performance software-defined storage workloads. This first-of-its-class storage server from a major Tier 1 provider utilizes Supermicro's system design expertise to create a high-density storage server for software-defined workloads found in AI and ML training and inferencing, analytics and enterprise storage workloads. Supermicro worked closely with NVIDIA and WEKA to enable customers to create power-efficient high-performance storage systems for their AI factories.

"The Supermicro Petascale server with the NVIDIA Grace CPU Superchip highlights Supermicro's focus on innovation and customer choice," said Charles Liang, president and CEO of Supermicro. "We have developed the Petascale storage server using the NVIDIA Grace CPU with 144 Arm Neoverse V2 cores enabling high-performance I/O for software-defined storage workloads. We have demonstrated that the system can fully unleash the system's PCIe Gen 5 performance SSD bandwidth with linear scalability. Supermicro continues to bring to market the most advanced and optimized storage solutions available."

Supermicro, Inc., a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, is announcing new systems and rack solutions powered by the NVIDIA's Blackwell Ultra platform, featuring the NVIDIA HGX B300 NVL16 and NVIDIA GB300 NVL72 platforms. Supermicro and NVIDIA's new AI solutions strengthen leadership in AI by delivering breakthrough performance for the most compute-intensive AI workloads, including AI reasoning, agentic AI, and video inference applications.

"At Supermicro, we are excited to continue our long-standing partnership with NVIDIA to bring the latest AI technology to market with the NVIDIA Blackwell Ultra Platforms," said Charles Liang, president and CEO, Supermicro. "Our Data Center Building Block Solutions approach has streamlined the development of new air and liquid-cooled systems, optimized to the thermals and internal topology of the NVIDIA HGX B300 NVL16 and GB300 NVL72. Our advanced liquid-cooling solution delivers exceptional thermal efficiency, operating with 40℃ warm water in our 8-node rack configuration, or 35℃ warm water in double-density 16-node rack configuration, leveraging our latest CDUs. This innovative solution reduces power consumption by up to 40% while conserving water resources, providing both environmental and operational cost benefits for enterprise data centers."

Today, at NVIDIA GTC, Lenovo unveiled new Lenovo Hybrid AI Advantage with NVIDIA solutions designed to accelerate AI adoption and boost business productivity by fast-tracking agentic AI that can reason, plan and take action to reach goals faster. The validated, full-stack AI solutions enable enterprises to quickly build and deploy AI agents for a broad range of high-demand use cases, increasing productivity, agility and trust while accelerating the next wave of AI reasoning for the new era of agentic AI.

New global IDC research commissioned by Lenovo reveals that ROI remains the greatest AI adoption barrier, despite a three-fold spend increase. AI agents are revolutionizing enterprise workflows and lowering barriers to ROI by supporting employees with complex problem-solving, coding, and multistep planning that drives speed, innovation and productivity. As CIOs and business leaders seek tangible return on AI investment, Lenovo is delivering hybrid AI solutions that unleash and customize agentic AI at every scale.

Giga Computing, a subsidiary of GIGABYTE and an industry leader in generative AI servers and advanced cooling technologies, today announced participation at NVIDIA GTC 2025 to bring to the market the best in GPU-based solutions for generative AI, media acceleration, and large language models (LLM). To this end, GIGABYTE booth #1409 at NVIDIA GTC showcases a rack-scale turnkey AI solution, GIGAPOD, that offers both air and liquid-cooling designs for the NVIDIA HGX B300 NVL16 system. Also, on display at the booth is a compute node from the newly announced NVIDIA GB300 NVL72 rack-scale solution. And for modularized compute architecture are two servers supporting the newly announced NVIDIA RTX PRO 6000 Blackwell Server Edition.

Complete AI solution - GIGAPOD
With the depth of expertise in hardware and system design, Giga Computing has combined infrastructure hardware, platform software, and architecting service to deliver scalable units composed of GIGABYTE GPU servers with NVIDIA GPU baseboards, while running GIGABYTE POD Manager, a powerful software suite designed to enhance operational efficiency, streamline management, and optimize resource utilization. GIGAPOD's scalable unit is designed for either nine air-cooled racks or five liquid-cooled racks. Giga Computing offers two approaches for the same goal, one powerful GPU cluster using NVIDIA HGX Hopper and Blackwell GPU platforms at scale to meet demand for all AI data centers.

NVIDIA today unveiled NVIDIA DGX personal AI supercomputers powered by the NVIDIA Grace Blackwell platform. DGX Spark—formerly Project DIGITS—and DGX Station, a new high-performance NVIDIA Grace Blackwell desktop supercomputer powered by the NVIDIA Blackwell Ultra platform, enable AI developers, researchers, data scientists and students to prototype, fine-tune and inference large models on desktops. Users can run these models locally or deploy them on NVIDIA DGX Cloud or any other accelerated cloud or data center infrastructure.

DGX Spark and DGX Station bring the power of the Grace Blackwell architecture, previously only available in the data center, to the desktop. Global system builders to develop DGX Spark and DGX Station include ASUS, Dell, HP Inc. and Lenovo.

AI reasoning models and agents are set to transform industries, but delivering their full potential at scale requires massive compute and optimized software. The "reasoning" process involves multiple models, generating many additional tokens, and demands infrastructure with a combination of high-speed communication, memory and compute to ensure real-time, high-quality results. To meet this demand, CoreWeave has launched NVIDIA GB200 NVL72-based instances, becoming the first cloud service provider to make the NVIDIA Blackwell platform generally available. With rack-scale NVIDIA NVLink across 72 NVIDIA Blackwell GPUs and 36 NVIDIA Grace CPUs, scaling to up to 110,000 GPUs with NVIDIA Quantum-2 InfiniBand networking, these instances provide the scale and performance needed to build and deploy the next generation of AI reasoning models and agents.

NVIDIA GB200 NVL72 on CoreWeave
NVIDIA GB200 NVL72 is a liquid-cooled, rack-scale solution with a 72-GPU NVLink domain, which enables the six dozen GPUs to act as a single massive GPU. NVIDIA Blackwell features many technological breakthroughs that accelerate inference token generation, boosting performance while reducing service costs. For example, fifth-generation NVLink enables 130 TB/s of GPU bandwidth in one 72-GPU NVLink domain, and the second-generation Transformer Engine enables FP4 for faster AI performance while maintaining high accuracy. CoreWeave's portfolio of managed cloud services is purpose-built for Blackwell. CoreWeave Kubernetes Service optimizes workload orchestration by exposing NVLink domain IDs, ensuring efficient scheduling within the same rack. Slurm on Kubernetes (SUNK) supports the topology block plug-in, enabling intelligent workload distribution across GB200 NVL72 racks. In addition, CoreWeave's Observability Platform provides real-time insights into NVLink performance, GPU utilization and temperatures.

NVIDIA today unveiled NVIDIA Project DIGITS, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of the NVIDIA Grace Blackwell platform. Project DIGITS features the new NVIDIA GB10 Grace Blackwell Superchip, offering a petaflop of AI computing performance for prototyping, fine-tuning and running large AI models.

With Project DIGITS, users can develop and run inference on models using their own desktop system, then seamlessly deploy the models on accelerated cloud or data center infrastructure. "AI will be mainstream in every application for every industry. With Project DIGITS, the Grace Blackwell Superchip comes to millions of developers," said Jensen Huang, founder and CEO of NVIDIA. "Placing an AI supercomputer on the desks of every data scientist, AI researcher and student empowers them to engage and shape the age of AI."

Giga Computing, a subsidiary of GIGABYTE and an industry leader in generative AI servers and advanced cooling technologies, announced new GIGABYTE G893 series servers using the NVIDIA HGX B200 platform. The launch of these flagship 8U air-cooled servers, the G893-SD1-AAX5 and G893-ZD1-AAX5, signifies a new architecture and platform change for GIGABYTE in the demanding world of high-performance computing and AI, setting new standards for speed, scalability, and versatility.

These servers join GIGABYTE's accelerated computing portfolio alongside the NVIDIA GB200 NVL72 platform, which is a rack-scale design that connects 36 NVIDIA Grace CPUs and 72 NVIDIA Blackwell GPUs. At CES 2025 (January 7-10), the GIGABYTE booth will display the NVIDIA GB200 NVL72, and attendees can engage in discussions about the benefits of GIGABYTE platforms with the NVIDIA Blackwell architecture.

NVIDIA "Blackwell" series is barely out with B100, B200, and GB200 chips shipping to OEMs and hyperscalers, but the company is already setting in its upgraded "Blackwell Ultra" plans with its upcoming GB300 AI server. According to UDN, the next generation NVIDIA system will be powered by the B300 GPU chip, operating at 1400 W and delivering a remarkable 1.5x improvement in FP4 performance per card compared to its B200 predecessor. One of the most notable upgrades is the memory configuration, with each GPU now sporting 288 GB of HBM3e memory, a substantial increase from the previous 192 GB of GB200. The new design implements a 12-layer stack architecture, advancing from the GB200's 8-layer configuration. The system's cooling infrastructure has been completely reimagined, incorporating advanced water cooling plates and enhanced quick disconnects in the liquid cooling system.

Networking capabilities have also seen a substantial upgrade, with the implementation of ConnectX 8 network cards replacing the previous ConnectX 7 generation, while optical modules have been upgraded from 800G to 1.6T, ensuring faster data transmission. Regarding power management and reliability, the GB300 NVL72 cabinet will standardize capacitor tray implementation, with an optional Battery Backup Unit (BBU) system. Each BBU module costs approximately $300 to manufacture, with a complete GB300 system's BBU configuration totaling around $1,500. The system's supercapacitor requirements are equally substantial, with each NVL72 rack requiring over 300 units, priced between $20-25 per unit during production due to its high-power nature. The GB300, carrying Grace CPU and Blackwell Ultra GPU, also introduces the implementation of LPCAMM on its computing boards, indicating that the LPCAMM memory standard is about to take over servers, not just laptops and desktops. We have to wait for the official launch before seeing LPCAMM memory configurations.

At SC24, NVIDIA announced its latest compute-dense AI accelerators in the form of GB200 NVL4, a single-server solution that expands the company's "Blackwell" series portfolio. The new platform features an impressive combination of four "Blackwell" GPUs and two "Grace" CPUs on a single board. The GB200 NVL4 boasts remarkable specifications for a single-server system, including 768 GB of HBM3E memory across its four Blackwell GPUs, delivering a combined memory bandwidth of 32 TB/s. The system's two Grace CPUs have 960 GB of LPDDR5X memory, making it a powerhouse for demanding AI workloads. A key feature of the NVL4 design is its NVLink interconnect technology, which enables communication between all processors on the board. This integration is important for maintaining optimal performance across the system's multiple processing units, especially during large training runs or inferencing a multi-trillion parameter model.

Performance comparisons with previous generations show significant improvements, with NVIDIA claiming the GB200 GPUs deliver 2.2x faster overall performance and 1.8x quicker training capabilities compared to their GH200 NVL4 predecessor. The system's power consumption reaches 5,400 watts, which effectively doubles the 2,700-watt requirement of the GB200 NVL2 model, its smaller sibling that features two GPUs instead of four. NVIDIA is working closely with OEM partners to bring various Blackwell solutions to market, including the DGX B200, GB200 Grace Blackwell Superchip, GB200 Grace Blackwell NVL2, GB200 Grace Blackwell NVL4, and GB200 Grace Blackwell NVL72. Fitting 5,400 W of TDP in a single server will require liquid cooling for optimal performance, and the GB200 NVL4 is expected to go inside server racks for hyperscaler customers, which usually have a custom liquid cooling systems inside their data centers.

Supermicro, Inc., a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, is announcing the highest-performing SuperCluster, an end-to-end AI data center solution featuring the NVIDIA Blackwell platform for the era of trillion-parameter-scale generative AI. The new SuperCluster will significantly increase the number of NVIDIA HGX B200 8-GPU systems in a liquid-cooled rack, resulting in a large increase in GPU compute density compared to Supermicro's current industry-leading liquid-cooled NVIDIA HGX H100 and H200-based SuperClusters. In addition, Supermicro is enhancing the portfolio of its NVIDIA Hopper systems to address the rapid adoption of accelerated computing for HPC applications and mainstream enterprise AI.

"Supermicro has the expertise, delivery speed, and capacity to deploy the largest liquid-cooled AI data center projects in the world, containing 100,000 GPUs, which Supermicro and NVIDIA contributed to and recently deployed," said Charles Liang, president and CEO of Supermicro. "These Supermicro SuperClusters reduce power needs due to DLC efficiencies. We now have solutions that use the NVIDIA Blackwell platform. Using our Building Block approach allows us to quickly design servers with NVIDIA HGX B200 8-GPU, which can be either liquid-cooled or air-cooled. Our SuperClusters provide unprecedented density, performance, and efficiency, and pave the way toward even more dense AI computing solutions in the future. The Supermicro clusters use direct liquid cooling, resulting in higher performance, lower power consumption for the entire data center, and reduced operational expenses."

Giga Computing, a subsidiary of GIGABYTE and an industry leader in generative AI servers and advanced cooling technologies, shows off at SC24 how the GIGABYTE enterprise portfolio provides solutions for all applications, from cloud computing to AI to enterprise IT, including energy-efficient liquid-cooling technologies. This portfolio is made more complete by long-term collaborations with leading technology companies and emerging industry leaders, which will be showcased at GIGABYTE booth #3123 at SC24 (Nov. 19-21) in Atlanta. The booth is sectioned to put the spotlight on strategic technology collaborations, as well as direct liquid cooling partners.

The GIGABYTE booth will showcase an array of NVIDIA platforms built to keep up with the diversity of workloads and degrees of demands in applications of AI & HPC hardware. For a rack-scale AI solution using the NVIDIA GB200 NVL72 design, GIGABYTE displays how seventy-two GPUs can be in one rack with eighteen GIGABYTE servers each housing two NVIDIA Grace CPUs and four NVIDIA Blackwell GPUs. Another platform at the GIGABYTE booth is the NVIDIA HGX H200 platform. GIGABYTE exhibits both its liquid-cooling G4L3-SD1 server and an air-cooled version, G593-SD1.

We know that NVIDIA's latest "Blackwell" GPUs are fast, but how much faster are they over the previous generation "Hopper"? Thanks to the latest MLPerf Training v4.1 results, NVIDIA's HGX B200 Blackwell platform has demonstrated massive performance gains, measuring up to 2.2x improvement per GPU compared to its HGX H200 Hopper. The latest results, verified by MLCommons, reveal impressive achievements in large language model (LLM) training. The Blackwell architecture, featuring HBM3e high-bandwidth memory and fifth-generation NVLink interconnect technology, achieved double the performance per GPU for GPT-3 pre-training and a 2.2x boost for Llama 2 70B fine-tuning compared to the previous Hopper generation. Each benchmark system incorporated eight Blackwell GPUs operating at a 1,000 W TDP, connected via NVLink Switch for scale-up.

The network infrastructure utilized NVIDIA ConnectX-7 SuperNICs and Quantum-2 InfiniBand switches, enabling high-speed node-to-node communication for distributed training workloads. While previous Hopper-based systems required 256 GPUs to optimize performance for the GPT-3 175B benchmark, Blackwell accomplished the same task with just 64 GPUs, leveraging its larger HBM3e memory capacity and bandwidth. One thing to look out for is the upcoming GB200 NVL72 system, which promises even more significant gains past the 2.2x. It features expanded NVLink domains, higher memory bandwidth, and tight integration with NVIDIA Grace CPUs, complemented by ConnectX-8 SuperNIC and Quantum-X800 switch technologies. With faster switching and better data movement with Grace-Blackwell integration, we could see even more software optimization from NVIDIA to push the performance envelope.

According to DigiTimes, NVIDIA is reportedly targeting the high-end segment for its first consumer CPU attempt. Slated to arrive in 2025, NVIDIA is partnering with MediaTek to break into the AI PC market, currently being popularized by Qualcomm, Intel, and AMD. With Microsoft and Qualcomm laying the foundation for Windows-on-Arm (WoA) development, NVIDIA plans to join and leverage its massive ecosystem of partners to design and deliver regular applications and games for its Arm-based processors. At the same time, NVIDIA is also scheduled to launch "Blackwell" GPUs for consumers, which could end up in these AI PCs with an Arm CPU at its core.

NVIDIA's partner, MediaTek, has recently launched a big core SoC for mobile called Dimensity 9400. NVIDIA could use something like that as a base for its SoC and add its Blackwell IP to the mix. This would be similar to what Apple is doing with its Apple Silicon and the recent M4 Max chip, which is apparently the fastest CPU in single-threaded and multithreaded workloads, as per recent Geekbench recordings. For NVIDIA, the company already has a team of CPU designers that delivered its Grace CPU to enterprise/server customers. Using off-the-shelf Arm Neoverse IP, the company's customers are acquiring systems with Grace CPUs as fast as they are produced. This puts a lot of hope into NVIDIA's upcoming AI PC, which could offer a selling point no other WoA device currently provides, and that is tried and tested gaming-grade GPU with AI accelerators.

MSI, a leading global provider of high-performance server solutions, proudly announced it is showcasing new AI servers powered by the NVIDIA MGX platform—designed to address the increasing demand for scalable, energy-efficient AI workloads in modern data centers—at the OCP Global Summit 2024, booth A6. This collaboration highlights MSI's continued commitment to advancing server solutions, focusing on cutting-edge AI acceleration and high-performance computing (HPC).

The NVIDIA MGX platform offers a flexible architecture that enables MSI to deliver purpose-built solutions optimized for AI, HPC, and LLMs. By leveraging this platform, MSI's AI server solutions provide exceptional scalability, efficiency, and enhanced GPU density—key factors in meeting the growing computational demands of AI workloads. Tapping into MSI's engineering expertise and NVIDIA's advanced AI technologies, these AI servers based on the MGX architecture deliver unparalleled compute power, positioning data centers to maximize performance and power efficiency while paving the way for the future of AI-driven infrastructure.

Supermicro, Inc., a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, is accelerating the industry's transition to liquid-cooled data centers with the NVIDIA Blackwell platform to deliver a new paradigm of energy-efficiency for the rapidly heightened energy demand of new AI infrastructures. Supermicro's industry-leading end-to-end liquid-cooling solutions are powered by the NVIDIA GB200 NVL72 platform for exascale computing in a single rack and have started sampling to select customers for full-scale production in late Q4. In addition, the recently announced Supermicro X14 and H14 4U liquid-cooled systems and 10U air-cooled systems are production-ready for the NVIDIA HGX B200 8-GPU system.

"We're driving the future of sustainable AI computing, and our liquid-cooled AI solutions are rapidly being adopted by some of the most ambitious AI Infrastructure projects in the world with over 2000 liquid-cooled racks shipped since June 2024," said Charles Liang, president and CEO of Supermicro. "Supermicro's end-to-end liquid-cooling solution, with the NVIDIA Blackwell platform, unlocks the computational power, cost-effectiveness, and energy-efficiency of the next generation of GPUs, such as those that are part of the NVIDIA GB200 NVL72, an exascale computer contained in a single rack. Supermicro's extensive experience in deploying liquid-cooled AI infrastructure, along with comprehensive on-site services, management software, and global manufacturing capacity, provides customers a distinct advantage in transforming data centers with the most powerful and sustainable AI solutions."

To drive the development of open, efficient and scalable data center technologies, NVIDIA today announced that it has contributed foundational elements of its NVIDIA Blackwell accelerated computing platform design to the Open Compute Project (OCP) and broadened NVIDIA Spectrum-X support for OCP standards.

At this year's OCP Global Summit, NVIDIA will be sharing key portions of the NVIDIA GB200 NVL72 system electro-mechanical design with the OCP community — including the rack architecture, compute and switch tray mechanicals, liquid-cooling and thermal environment specifications, and NVIDIA NVLink cable cartridge volumetrics — to support higher compute density and networking bandwidth.

NVIDIA and Foxconn are building Taiwan's largest supercomputer, marking a milestone in the island's AI advancement. The project, Hon Hai Kaohsiung Super Computing Center, revealed Tuesday at Hon Hai Tech Day, will be built around NVIDIA's groundbreaking Blackwell architecture and feature the GB200 NVL72 platform, which includes a total of 64 racks and 4,608 Tensor Core GPUs. With an expected performance of over 90 exaflops of AI performance, the machine would easily be considered the fastest in Taiwan.

Foxconn plans to use the supercomputer, once operational, to power breakthroughs in cancer research, large language model development and smart city innovations, positioning Taiwan as a global leader in AI-driven industries. Foxconn's "three-platform strategy" focuses on smart manufacturing, smart cities and electric vehicles. The new supercomputer will play a pivotal role in supporting Foxconn's ongoing efforts in digital twins, robotic automation and smart urban infrastructure, bringing AI-assisted services to urban areas like Kaohsiung.

NVIDIA has reportedly discontinued its dual-rack GB200 NVL36x2 GPU model, opting to focus on the single-rack GB200 NVL72 and NVL36 models. This shift, revealed by industry analyst Ming-Chi Kuo, aims to simplify NVIDIA's offerings in the AI and HPC markets. The decision was influenced by major clients like Microsoft, who prefer the NVL72's improved space efficiency and potential for enhanced inference performance. While both models perform similarly in AI large language model (LLM) training, the NVL72 is expected to excel in non-parallelizable inference tasks. As a reminder, the NVL72 features 36 Grace CPUs, delivering 2,592 Arm Neoverse V2 cores with 17 TB LPDDR5X memory with 18.4 TB/s aggregate bandwidth. Additionally, it includes 72 Blackwell GB200 SXM GPUs that have a massive 13.5 TB of HBM3e combined, running at 576 TB/s aggregate bandwidth.

However, this shift presents significant challenges. The NVL72's power consumption of around 120kW far exceeds typical data center capabilities, potentially limiting its immediate widespread adoption. The discontinuation of the NVL36x2 has also sparked concerns about NVIDIA's execution capabilities and may disrupt the supply chain for assembly and cooling solutions. Despite these hurdles, industry experts view this as a pragmatic approach to product planning in the dynamic AI landscape. While some customers may be disappointed by the dual-rack model's cancellation, NVIDIA's long-term outlook in the AI technology market remains strong. The company continues to work with clients and listen to their needs, to position itself as a leader in high-performance computing solutions.

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.

Noctua unveiled its new Ampere Altra family of CPU coolers for Ampere Altra and Altra Max Arm processors at the Computex 2024 show, as well as the upcoming NVIDIA GH200 Grace Hopper superchip cooler. In addition, it also showcased its new cooperation with Seasonic with PRIME TX-1600 Noctua Edition power supply and a rather unique Kaelo wine cooler.

In addition to the new and upcoming standard CPU coolers and fans, Noctua also unveiled the new Ampere Altra family of CPU coolers at the Computex 2024 show, aimed to be used with recently launched Ampere Altra and Altra Max Arm processors with up to 128 cores. The new Noctua Ampere Altra CPU coolers are based on the proven models for Intel Xeon and AMD Threadripper or EPYC platforms. The Noctua Ampere Altra family of CPU coolers use Noctua's SecuFirm2 mounting system for LGA4926 socket and come with pre-applied NT-H2 thermal paste. According to Noctua, these provide exceptional performance and whisper-quiet operation which are ideal for Arm based workstations in noise-sensitive environments. The Ampere Altra lineup should be already available over at Newegg. In addition, Nocuta has unveiled its new prototype of NVIDIA GH200 Grace Hopper superchip cooler, which integrates two custom NH-U12A heatsinks in order to cool both the Grace CPU and Hopper GPU. It supports up to 1,000 W of heat emissions, and aimed at noise-sensitive environments like local HPC applications and self-hosted open source LLMs. The NVIDIA GH200 cooler is expected in Q4 this year and offered to clients on pre-order basis.

Quantum computing. Drug discovery. Fusion energy. Scientific computing and physics-based simulations are poised to make giant steps across domains that benefit humanity as advances in accelerated computing and AI drive the world's next big breakthroughs. NVIDIA unveiled at GTC in March the NVIDIA Blackwell platform, which promises generative AI on trillion-parameter large language models (LLMs) at up to 25x less cost and energy consumption than the NVIDIA Hopper architecture.

Blackwell has powerful implications for AI workloads, and its technology capabilities can also help to deliver discoveries across all types of scientific computing applications, including traditional numerical simulation. By reducing energy costs, accelerated computing and AI drive sustainable computing. Many scientific computing applications already benefit. Weather can be simulated at 200x lower cost and with 300x less energy, while digital twin simulations have 65x lower cost and 58x less energy consumption versus traditional CPU-based systems and others.

Driving a fundamental shift in the high-performance computing industry toward AI-powered systems, NVIDIA today announced nine new supercomputers worldwide are using NVIDIA Grace Hopper Superchips to speed scientific research and discovery. Combined, the systems deliver 200 exaflops, or 200 quintillion calculations per second, of energy-efficient AI processing power.

New Grace Hopper-based supercomputers coming online include EXA1-HE, in France, from CEA and Eviden; Helios at Academic Computer Centre Cyfronet, in Poland, from Hewlett Packard Enterprise (HPE); Alps at the Swiss National Supercomputing Centre, from HPE; JUPITER at the Jülich Supercomputing Centre, in Germany; DeltaAI at the National Center for Supercomputing Applications at the University of Illinois Urbana-Champaign; and Miyabi at Japan's Joint Center for Advanced High Performance Computing - established between the Center for Computational Sciences at the University of Tsukuba and the Information Technology Center at the University of Tokyo.