Intel's upcoming Falcon Shores GPU is shaping up to be a powerhouse for AI and high-performance computing (HPC) workloads, but it will also be an extreme power hog. The processor, combining Gaudi and Ponte Vecchio successors into a single GPU, is expected to consume an astonishing 1500 W of power - more than even Nvidia's beefy B200 accelerator, which draws 1000 W. This immense power consumption will require advanced cooling solutions to ensure the Falcon Shores GPU operates efficiently and safely. Intel's partners may turn to liquid cooling or even full immersion liquid cooling, a technology Intel has been promoting for power-hungry data center hardware. The high power draw is the cost of the Falcon Shores GPU's formidable performance promises. Intel claims it will deliver 5x higher performance per watt and 5x more memory capacity and bandwidth compared to its Ponte Vecchio products.

Intel may need to develop proprietary hardware modules or a new Open Accelerator Module (OAM) spec to support such extreme power levels, as the current OAM 2.0 tops out around 1000 W. Slated for release in 2025, the Falcon Shores GPU will be Intel's GPU IP based on its next-gen Xe graphics architecture. It aims to be a major player in the AI accelerator market, backed by Intel's robust oneAPI software development ecosystem. While the 1500 W power consumption is sure to raise eyebrows, Intel is betting that the Falcon Shores GPU's supposedly impressive performance will make it an enticing option for AI and HPC customers willing to invest in robust cooling infrastructure. The ultra-high-end accelerator market is heating up, and the HPC accelerator market needs a Ponte Vecchio successor.

During the European Technology Symposium 2024, TSMC has announced its readiness to manufacture next-generation HBM4 base dies using both 12 nm and 5 nm nodes. This significant development is expected to substantially improve the performance, power consumption, and logic density of HBM4 memory, catering to the demands of high-performance computing (HPC) and artificial intelligence (AI) applications. The shift from a traditional 1024-bit interface to an ultra-wide 2048-bit interface is a key aspect of the new HBM4 standard. This change will enable the integration of more logic and higher performance while reducing power consumption. TSMC's N12FFC+ and N5 processes will be used to produce these base dies, with the N12FFC+ process offering a cost-effective solution for achieving HBM4 performance and the N5 process providing even more logic and lower power consumption at HBM4 speeds.

The company is collaborating with major HBM memory partners, including Micron, Samsung, and SK Hynix, to integrate advanced nodes for HBM4 full-stack integration. TSMC's base die, fabricated using the N12FFC+ process, will be used to install HBM4 memory stacks on a silicon interposer alongside system-on-chips (SoCs). This setup will enable the creation of 12-Hi (48 GB) and 16-Hi (64 GB) stacks with per-stack bandwidth exceeding 2 TB/s. TSMC's collaboration with EDA partners like Cadence, Synopsys, and Ansys ensures the integrity of HBM4 channel signals, thermal accuracy, and electromagnetic interference (EMI) in the new HBM4 base dies. TSMC is also optimizing CoWoS-L and CoWoS-R for HBM4 integration, meaning that massive high-performance chips are already utilizing this technology and getting ready for volume manufacturing.

According to ServeTheHome, Intel has decided to discontinue its high-performance computing (HPC) product line, Ponte Vecchio, and shift its focus towards developing its next-generation data center GPU, codenamed Falcon Shores. This decision comes as Intel aims to streamline its operations and concentrate its resources on the most promising and competitive offerings. The Ponte Vecchio GPU, released in January of 2023, was intended to be Intel's flagship product for the HPC market, competing against the likes of NVIDIA's H100 and AMD's Instinct MI series. However, despite its impressive specifications and features, Ponte Vecchio faced significant delays and challenges in its development and production cycle. Intel's decision to abandon Ponte Vecchio is pragmatic, recognizing the intense competition and rapidly evolving landscape of the data center GPU market.

By pivoting its attention to Falcon Shores, Intel aims to deliver a more competitive and cutting-edge solution that can effectively challenge the dominance of its rivals. Falcon Shores, slated for release in 2025, is expected to leverage Intel's latest process node and architectural innovations. Currently, Intel has Gaudi 2 and Gaudi 3 accelerators for AI. However, the HPC segment is left without a clear leader in the company's product offerings. Intel's Ponte Vecchio is powering Aurora exascale supercomputer, which is the latest submission to the TOP500 supercomputer lists. This is also coming after the Rialto Bridge cancellation, which was supposed to be an HPC-focused card. In the future, the company will focus only on the Falcon Shores accelerator, which will unify HPC and AI needs for high-precision FP64 and lower-precision FP16/INT8.

The 63rd edition of the TOP500 reveals that Frontier has once again claimed the top spot, despite no longer being the only exascale machine on the list. Additionally, a new system has found its way into the Top 10.

The Frontier system at Oak Ridge National Laboratory in Tennessee, USA remains the most powerful system on the list with an HPL score of 1.206 EFlop/s. The system has a total of 8,699,904 combined CPU and GPU cores, an HPE Cray EX architecture that combines 3rd Gen AMD EPYC CPUs optimized for HPC and AI with AMD Instinct MI250X accelerators, and it relies on Cray's Slingshot 11 network for data transfer. On top of that, this machine has an impressive power efficiency rating of 52.93 GFlops/Watt - putting Frontier at the No. 13 spot on the GREEN500.

MSI, a leading global server provider, brings its latest server platforms powered by AMD processors and 5th Gen Intel Xeon Scalable processors, optimized for HPC and AI markets at ISC 2024, booth #F39 in Hamburg, Germany from May 13-15. "As businesses increasingly adopt AI applications to improve customer experiences, the need for greater computing power and denser deployments has spurred significant shifts in IT infrastructure, driving a widespread adoption of liquid cooling," said Danny Hsu, General Manager of Enterprise Platform Solutions. "MSI's AI server platforms empower businesses to achieve efficiency gains while handling more compute-intensive workloads."

MSI G4201 is a 4U supercomputer designed for exceptional performance in compute-intensive tasks. It features up to eight double-wide PCIe 5.0 x16 slots optimized for high-performance GPU cards, alongside one single-wide PCIe 5.0 x16 expansion slot. Each GPU has a full PCIe 4.0 or 5.0 x16 link directly to the root port complex of a CPU socket without going through a PCIe switch, granting maximum CPU-to-GPU bandwidth. Powered by dual 5th Gen Intel Xeon Scalable Processors and equipped with 32 DDR5 DIMMs, the G4201 platform delivers outstanding heterogeneous computing capabilities for various GPU-based scientific high-performance computing, Generative AI, and inference applications. Additionally, the system includes twelve 3.5-inch drive bays for enhanced functionality.

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.

Today, in advance of ISC High Performance 2024, SpiNNcloud Systems announced the commercial availability of its SpiNNaker2 platform, a supercomputer-level hybrid AI high-performance computer system based on principles of the human brain. Pioneered by Steve Furber, designer of the original ARM and SpiNNaker1 architectures, the SpiNNaker2 supercomputing platform uses a large number of low-power processors for efficiently computing AI and other workloads.

First-generation SpiNNaker1 architecture is currently used in dozens of research groups across 23 countries worldwide. Sandia National Laboratories, Technical University of München and Universität Göttingen are among the first customers placing orders for SpiNNaker2, which was developed around commercialized IP invented in the Human Brain Project, a billion-euro research project funded by the European Union to design intelligent, efficient artificial systems.

SK hynix participated in the first-ever Compute Express Link Consortium Developers Conference (CXL DevCon) held in Santa Clara, California from April 30-May 1. Organized by a group of more than 240 global semiconductor companies known as the CXL Consortium, CXL DevCon 2024 welcomed a majority of the consortium's members to showcase their latest technologies and research results.

CXL is a technology that unifies the interfaces of different devices in a system such as semiconductor memory, storage, and logic chips. As it can increase system bandwidth and processing capacity, CXL is receiving attention as a key technology for the AI era in which high performance and capacity are essential. Under the slogan "Memory, The Power of AI," SK hynix showcased a range of CXL products at the conference that are set to strengthen the company's leadership in AI memory technology.

AMD is now a 55-year-old company. The chipmaker was founded on May Day, 1969, and traversed practically every era of digital computing to reach where it is today—a company that makes contemporary processors for PCs, servers, and consumer electronics; GPUs for gaming graphics, professional visualization, and the all important AI HPC processors that are driving the latest era of computing. As of this writing, AMD has a market capitalization of over $237 billion, presence in all market regions, and supplies hardware and services to nearly every Fortune 500 company, including every IT giant. Happy birthday, AMD!

Micron Technology, Inc. (Nasdaq: MU), today announced it is leading the industry by validating and shipping its high-capacity monolithic 32Gb DRAM die-based 128 GB DDR5 RDIMM memory in speeds up to 5,600 MT/s on all leading server platforms. Powered by Micron's industry-leading 1β (1-beta) technology, the 128 GB DDR5 RDIMM memory delivers more than 45% improved bit density, up to 22% improved energy efficiency and up to 16% lower latency over competitive 3DS through-silicon via (TSV) products.

Micron's collaboration with industry leaders and customers has yielded broad adoption of these new high-performance, large-capacity modules across high-volume server CPUs. These high-speed memory modules were engineered to meet the performance needs of a wide range of mission-critical applications in data centers, including artificial intelligence (AI) and machine learning (ML), high-performance computing (HPC), in-memory databases (IMDBs) and efficient processing for multithreaded, multicore count general compute workloads. Micron's 128 GB DDR5 RDIMM memory will be supported by a robust ecosystem including AMD, Hewlett Packard Enterprise (HPE), Intel, Supermicro, along with many others.

According to The Information, in a strategic maneuver to circumvent the constraints imposed by US sanctions, Huawei is accelerating efforts to establish domestic production capabilities for High Bandwidth Memory (HBM) within China. This move addresses the limitations that have hampered the company's advancements in AI and high-performance computing (HPC) sectors. HBM technology plays a pivotal role in enhancing the performance of AI and HPC processors by mitigating memory bandwidth bottlenecks. Recognizing its significance, Huawei has assembled a consortium comprising memory manufacturers backed by the Chinese government and prominent semiconductor companies like Fujian Jinhua Integrated Circuit. This consortium is focused on advancing HBM2 memory technology, which is crucial for Huawei's Ascend-series processors for AI applications.

Huawei's initiative comes at a time when the company faces challenges in accessing HBM from external sources, impacting the availability of its AI processors in the market. Despite facing obstacles such as international regulations restricting the sale of advanced chipmaking equipment to China, Huawei's efforts underscore China's broader push for self-sufficiency in critical technologies essential for AI and supercomputing. By investing in domestic HBM production, Huawei aims to secure a stable supply chain for these vital components, reducing reliance on external suppliers. This strategic shift not only demonstrates Huawei's resilience in navigating geopolitical challenges but also highlights China's determination to strengthen its technological independence in the face of external pressures. As the global tech landscape continues to evolve, Huawei's move to develop homegrown HBM memory could have far-reaching implications for China's AI and HPC capabilities, positioning the country as a significant player in the memory field.

TSMC today unveiled its newest semiconductor process, advanced packaging, and 3D IC technologies for powering the next generation of AI innovations with silicon leadership at the Company's 2024 North America Technology Symposium. TSMC debuted the TSMC A16 technology, featuring leading nanosheet transistors with innovative backside power rail solution for production in 2026, bringing greatly improved logic density and performance. TSMC also introduced its System-on-Wafer (TSMC-SoW) technology, an innovative solution to bring revolutionary performance to the wafer level in addressing the future AI requirements for hyperscaler datacenters.

This year marks the 30th anniversary of TSMC's North America Technology Symposium, and more than 2,000 attended the event, growing from less than 100 attendees 30 years ago. The North America Technology Symposium in Santa Clara, California kicks off TSMC Technology Symposiums around the world in the coming months. The symposium also features an "Innovation Zone," designed to highlight the technology achievements of our emerging start-up customers.

On March 29th, the United States announced another round of updates to its export controls, targeting advanced computing, supercomputers, semiconductor end-uses, and semiconductor manufacturing products. These new regulations, which took effect on April 4th, are designed to prevent certain countries and businesses from circumventing U.S. restrictions to access sensitive chip technologies and equipment. Despite these tighter controls, TrendForce believes the practical impact on the industry will be minimal.

The latest updates aim to refine the language and parameters of previous regulations, tightening the criteria for exports to Macau and D:5 countries (China, North Korea, Russia, Iran, etc.). They require a detailed examination of all technology products' Total Processing Performance (TPP) and Performance Density (PD). If a product exceeds certain computing power thresholds, it must undergo a case-by-case review. Nevertheless, a new provision, Advanced Computing Authorized (ACA), allows for specific exports and re-exports among selected countries, including the transshipment of particular products between Macau and D:5 countries.

While we are all used to having a system with a CPU, GPU, and, recently, NPU—X-Silicon Inc. (XSi), a startup founded by former Silicon Valley veterans—has unveiled an interesting RISC-V processor that can simultaneously handle CPU, GPU, and NPU workloads in a chip. This innovative chip architecture, which will be open-source, aims to provide a flexible and efficient solution for a wide range of applications, including artificial intelligence, virtual reality, automotive systems, and IoT devices. The new microprocessor combines a RISC-V CPU core with vector capabilities and GPU acceleration into a single chip, creating a versatile all-in-one processor. By integrating the functionality of a CPU and GPU into a single core, X-Silicon's design offers several advantages over traditional architectures. The chip utilizes the open-source RISC-V instruction set architecture (ISA) for both CPU and GPU operations, running a single instruction stream. This approach promises lower memory footprint execution and improved efficiency, as there is no need to copy data between separate CPU and GPU memory spaces.

Called the C-GPU architecture, X-Silicon uses RISC-V Vector Core, which has 16 32-bit FPUs and a Scaler ALU for processing regular integers as well as floating point instructions. A unified instruction decoder feeds the cores, which are connected to a thread scheduler, texture unit, rasterizer, clipping engine, neural engine, and pixel processors. All is fed into a frame buffer, which feeds the video engine for video output. The setup of the cores allows the users to program each core individually for HPC, AI, video, or graphics workloads. Without software, there is no usable chip, which prompts X-Silicon to work on OpenGL ES, Vulkan, Mesa, and OpenCL APIs. Additionally, the company plans to release a hardware abstraction layer (HAL) for direct chip programming. According to Jon Peddie Research (JPR), the industry has been seeking an open-standard GPU that is flexible and scalable enough to support various markets. X-Silicon's CPU/GPU hybrid chip aims to address this need by providing manufacturers with a single, open-chip design that can handle any desired workload. The XSi gave no timeline, but it has plans to distribute the IP to OEMs and hyperscalers, so the first silicon is still away.

Ultra Ethernet Consortium (UEC) is delighted to announce the addition of 45 new members to its thriving community since November, 2023. This remarkable influx of members underscores UEC's position as a unifying force, bringing together industry leaders to build a complete Ethernet-based communication stack architecture for high-performance networking. As a testament to UEC's commitment and the vibrant growth of its community, members shared their excitement about the recent developments. The community testimonials, accessible on our Testimonial page, reflect the positive impact UEC is having on its members. These testimonials highlight the collaborative spirit and the shared vision for the future of high-performance networking.

In the four months since November 2023, when UEC began accepting new members, the consortium has experienced an impressive growth of 450%. In October 2023, UEC boasted a distinguished membership comprising 10 steering members, marking the initial steps towards fostering collaboration in the high-performance networking sector. Now, the community is flourishing with the addition of 45 new member companies, reflecting an extraordinary expansion that demonstrates the industry's recognition of UEC's commitment. With a total of 715 industry experts actively engaged in the eight working groups, UEC is positioned at the forefront of industry collaboration, driving advancements in Ethernet-based communication technologies.

ASUS today announced its participation at the NVIDIA GTC global AI conference, where it will showcase its solutions at booth #730. On show will be the apex of ASUS GPU server innovation, ESC NM1-E1 and ESC NM2-E1, powered by the NVIDIA MGX modular reference architecture, accelerating AI supercomputing to new heights. To help meet the increasing demands for generative AI, ASUS uses the latest technologies from NVIDIA, including the B200 Tensor Core GPU, the GB200 Grace Blackwell Superchip, and H200 NVL, to help deliver optimized AI server solutions to boost AI adoption across a wide range of industries.

To better support enterprises in establishing their own generative AI environments, ASUS offers an extensive lineup of servers, from entry-level to high-end GPU server solutions, plus a comprehensive range of liquid-cooled rack solutions, to meet diverse workloads. Additionally, by leveraging its MLPerf expertise, the ASUS team is pursuing excellence by optimizing hardware and software for large-language-model (LLM) training and inferencing and seamlessly integrating total AI solutions to meet the demanding landscape of AI supercomputing.

NVIDIA today announced a new wave of networking switches, the X800 series, designed for massive-scale AI. The world's first networking platforms capable of end-to-end 800 Gb/s throughput, NVIDIA Quantum-X800 InfiniBand and NVIDIA Spectrum -X800 Ethernet push the boundaries of networking performance for computing and AI workloads. They feature software that further accelerates AI, cloud, data processing and HPC applications in every type of data center, including those that incorporate the newly released NVIDIA Blackwell architecture-based product lineup.

"NVIDIA Networking is central to the scalability of our AI supercomputing infrastructure," said Gilad Shainer, senior vice president of Networking at NVIDIA. "NVIDIA X800 switches are end-to-end networking platforms that enable us to achieve trillion-parameter-scale generative AI essential for new AI infrastructures."

Jensen Huang's opening GTC 2024 keynote is scheduled to happen tomorrow afternoon (13:00 Pacific time)—many industry experts believe that the NVIDIA boss will take the stage and formally introduce his company's B100 "Blackwell" GPU architecture. An enlightened few have been treated to preview (AI and HPC) units—including Dell's CEO, Jeff Clarke—but pre-introduction leaks have not flowed out. Team Green is likely enforcing strict conditions upon a fortunate selection of trusted evaluators, within a pool of ecosystem partners and customers.

Today, a brave soul has broken that silence—tech tipster, AGF/XpeaGPU, fears repercussions from the leather-jacketed one. They revealed a handful of technical details, a day prior to Team Green's highly anticipated unveiling: "I don't want to spoil NVIDIA B100 launch tomorrow, but this thing is a monster. 2 dies on (TSMC) CoWoS-L, 8x8-Hi HBM3E stacks for 192 GB of memory." They also crystal balled an inevitable follow-up card: "one year later, B200 goes with 12-Hi stacks and will offer a beefy 288 GB. And the performance! It's... oh no Jensen is there... me run away!" Reuters has also joined in on the fun, with some predictions and insider information: "NVIDIA is unlikely to give specific pricing, but the B100 is likely to cost more than its predecessor, which sells for upwards of $20,000." Enterprise products are expected to arrive first—possibly later this year—followed by gaming variants, maybe months later.

Samsung Electronics is all set to discuss the future of AI, alongside Jensen Huang, at NVIDIA's upcoming GTC 2024 conference. South Korean insiders have leaked the company's intentions, only days before the event's March 18 kickoff time. Their recently unveiled 36 GB HBM3E 12H DRAM product is expected to be the main focus of official presentations—additionally, a new storage subscription service is marked down for a possible live introduction. An overall "Redefining AI Infrastructure" presentation could include—according to BusinessKorea—a planned launch of: "petabyte (PB)-level SSD solution, dubbed 'PBSSD,' along with a subscription service in the US market within the second quarter (of 2024) to address the era of ultra-high-capacity data."

A Samsung statement—likely sourced from leaked material—summarized this business model: "the subscription service will help reduce initial investment costs in storage infrastructure for our customers and cut down on maintenance expenses." Under agreed upon conditions, customers are not required to purchasing ultra-high-capacity SSD solutions outright: "enterprises using the service can flexibly utilize SSD storage without the need to build separate infrastructure, while simultaneously receiving various services from Samsung Electronics related to storage management, security, and upgrades." A special session—"The Value of Storage as a Service for AI/ML and Data Analysis"—is alleged to be on the company's GTC schedule.

Two years ago, Intel Corporation and the Italian Government initiated negotiations over the "enabling" of a new state-of-the-art back-end manufacturing facility—a potential investment of up to 4.5 billion euros was mentioned at the time. Italy's chipmaking fund was put together in order to attract several big semiconductor firms, but Team Blue appeared to be the primary target. This week, Minister Adolfo Urso confirmed to media outlets that Intel had: "given up or postponed its investments in France and Italy, compared with others that it plans in Germany." Intel has not commented on this announcement according to a Reuters report—a spokesperson declined to make a statement.

Italy's Business Minister stated that he will welcome a continuation of negotiations, if Intel leadership chooses to diversify its construction portfolio outside of Germany: "if it decides to complete those projects, we are still here." His nation is set to receive further investments, following a recent announcement from Silicon Box—the Singapore-headquartered advanced semiconductor packaging company has signed an up to €3.2 billion deal. Their new Italian facility will: "enable next generation applications in artificial intelligence (AI), high performance computing (HPC)," and other segments. Urso reckons that "there will be others in coming months." He also added that a ministry task force had conducted talks with unnamed Taiwanese groups.

ZOTAC Technology Limited, a global leader in innovative technology solutions, expands its product portfolio with the GPU Server Series. The first series of products in ZOTAC's Enterprise lineup offers organizations affordable and high-performance computing solutions for a wide range of demanding applications, from core-to-edge inferencing and data visualization to model training, HPC modeling, and simulation.

The ZOTAC series of GPU Servers comes in a diverse range of form factors and configurations, featuring both Tower Workstations and Rack Mount Servers, as well as both Intel and AMD processor configurations. With support for up to 10 GPUs, modular design for easier access to internal hardware, a high space-to-performance ratio, and industry-standard features like redundant power supplies and extensive cooling options, ZOTAC's enterprise solutions can ensure optimal performance and durability, even under sustained intense workloads.

The HPC research projects DEEP-SEA, IO-SEA and RED-SEA are wrapping up this month after a three-year project term. The three projects worked together to develop key technologies for European Exascale supercomputers, based on the Modular Supercomputing Architecture (MSA), a blueprint architecture for highly efficient and scalable heterogeneous Exascale HPC systems. To achieve this, the three projects collaborated on system software and programming environments, data management and storage, as well as interconnects adapted to this architecture. The results of their joint work will be presented at a co-design workshop and poster session at the EuroHPC Summit (Antwerp, 18-21 March, www.eurohpcsummit.eu).

The latest TrendForce report reveals a notable 7.9% jump in 4Q23 revenue for the world's top ten semiconductor foundries, reaching $30.49 billion. This growth is primarily driven by sustained demand for smartphone components, such as mid and low-end smartphone APs and peripheral PMICs. The launch season for Apple's latest devices also significantly contributed, fueling shipments for the A17 chipset and associated peripheral ICs, including OLED DDIs, CIS, and PMICs. TSMC's premium 3 nm process notably enhanced its revenue contribution, pushing its global market share past the 60% threshold this quarter.

TrendForce remarks that 2023 was a challenging year for foundries, marked by high inventory levels across the supply chain, a weak global economy, and a slow recovery in the Chinese market. These factors led to a downward cycle in the industry, with the top ten foundries experiencing a 13.6% annual drop as revenue reached just $111.54 billion. Nevertheless, 2024 promises a brighter outlook, with AI-driven demand expected to boost annual revenue by 12% to $125.24 billion. TSMC, benefiting from steady advanced process orders, is poised to far exceed the industry average in growth.

MiTAC Computing Technology, a subsidiary of MiTAC Holdings Corp., proudly reveals its groundbreaking suite of server solutions that deliver unsurpassed capabilities with the 5th Gen Intel Xeon Scalable Processors. MiTAC introduces its cutting-edge signature platforms that seamlessly integrate the Intel Data Center GPUs, both Intel Max Series and Intel Flex Series, an unparalleled leap in computing performance is unleashed targeting HPC and AI applications.

MiTAC Announce its Full Array of Platforms Supporting the latest 5th Gen Intel Xeon Scalable Processors
Last year, Intel transitioned the right to manufacture and sell products based on Intel Data Center Solution Group designs to MiTAC. MiTAC confidently announces a transformative upgrade to its product offerings, unveiling advanced platforms that epitomize the future of computing. Featured with up to 64 cores, expanded shared cache, increased UPI and DDR5 support, the latest 5th Gen Intel Xeon Scalable Processors deliver remarkable performance per watt gains across various workloads. MiTAC's Intel Server M50FCP Family and Intel Server D50DNP Family fully support the latest 5th Gen Intel Xeon Scalable Processors, made possible through a quick BIOS update and easy technical resource revisions which provide unsurpassed performance to diverse computing environments.

The NVIDIA H100 Tensor Core GPU was last year's hot item for HPC and AI industry segments—the largest purchasers were reported to have acquired up to 150,000 units each. Demand grew so much that lead times of 36 to 52 weeks became the norm for H100-based server equipment. The latest rumblings indicate that things have stabilized—so much so that some organizations are "offloading chips" as the supply crunch cools off. Apparently it is more cost-effective to rent AI processing sessions through cloud service providers (CSPs)—the big three being Amazon Web Services, Google Cloud, and Microsoft Azure.

According to a mid-February Seeking Alpha report, wait times for the NVIDIA H100 80 GB GPU model have been reduced down to around three to four months. The Information believes that some companies have already reduced their order counts, while others have hardware sitting around, completely unused. Maintenance complexity and costs are reportedly cited as a main factors in "offloading" unneeded equipment, and turning to renting server time from CSPs. Despite improved supply conditions, AI GPU demand is still growing—driven mainly by organizations dealing with LLM models. A prime example being Open AI—as pointed out by The Information—insider murmurings have Sam Altman & Co. seeking out alternative solutions and production avenues.