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.

MSI, a leading global provider of high-performance server solutions, unveiled its AI server based on the NVIDIA MGX architecture at Supercomputing 2024 (SC24) from November 19-21 at booth 3655. Purpose-built to maximize compute density, energy efficiency, and modular flexibility, MSI's MGX-based AI server is designed to handle the intensive demands of AI, HPC, and data-heavy applications, offering the scalable performance and resilience that data centers need to stay ahead in today's high-performance computing landscape.

According to Danny Hsu, General Manager of MSI's Enterprise Platform Solutions, "MSI's latest innovations mark a significant leap in computational power and efficiency, enabling organizations to maximize performance, adapt seamlessly to evolving needs, and drive efficiency, building a robust foundation for future growth in high-performance computing."

Since its introduction, the NVIDIA Hopper architecture has transformed the AI and high-performance computing (HPC) landscape, helping enterprises, researchers and developers tackle the world's most complex challenges with higher performance and greater energy efficiency. During the Supercomputing 2024 conference, NVIDIA announced the availability of the NVIDIA H200 NVL PCIe GPU - the latest addition to the Hopper family. H200 NVL is ideal for organizations with data centers looking for lower-power, air-cooled enterprise rack designs with flexible configurations to deliver acceleration for every AI and HPC workload, regardless of size.

According to a recent survey, roughly 70% of enterprise racks are 20kW and below and use air cooling. This makes PCIe GPUs essential, as they provide granularity of node deployment, whether using one, two, four or eight GPUs - enabling data centers to pack more computing power into smaller spaces. Companies can then use their existing racks and select the number of GPUs that best suits their needs. Enterprises can use H200 NVL to accelerate AI and HPC applications, while also improving energy efficiency through reduced power consumption. With a 1.5x memory increase and 1.2x bandwidth increase over NVIDIA H100 NVL, companies can use H200 NVL to fine-tune LLMs within a few hours and deliver up to 1.7x faster inference performance. For HPC workloads, performance is boosted up to 1.3x over H100 NVL and 2.5x over the NVIDIA Ampere architecture generation.

NVIDIA's compute and AI-oriented H100 GPU is supposedly getting an upgrade. The H100 GPU is NVIDIA's most powerful offering and comes in a few different flavors: H100 PCIe, H100 SXM, and H100 NVL (a duo of two GPUs). Currently, the H100 GPU comes with 80 GB of HBM2E, both in the PCIe and SXM5 version of the card. A notable exception if the H100 NVL, which comes with 188 GB of HBM3, but that is for two cards, making it 94 GB per each. However, we could see NVIDIA enable 94 and 64 GB options for the H100 accelerator soon, as the latest PCI ID Repository shows.

According to the PCI ID Repository listing, two messages are posted: "Kindly help to add H100 SXM5 64 GB into 2337." and "Kindly help to add H100 SXM5 94 GB into 2339." These two messages indicate that NVIDIA could prepare its H100 in more variations. In September 2022, we saw NVIDIA prepare an H100 variation with 120 GB of memory, but that still isn't official. These PCIe IDs could just come from engineering samples that NVIDIA is testing in the labs, and these cards could never appear on any market. So, we have to wait and see how it plays out.

NVIDIA has killed SLI on its graphics cards, disabling the possibility of connecting two or more GPUs to harness their power for gaming and other workloads. However, SLI is making a reincarnation today in the form of a new H100 GPU model that spots higher memory capacity and higher performance. Called the H100 NVL, the GPU is a unique edition design based on the regular H100 PCIe version. What makes the H100 HVL version so special is the boost in memory capacity, now up from 80 GB in the standard model to 94 GB in the NVL edition SKU, for a total of 188 GB of HMB3 memory, running on a 6144-bit bus. Being a special edition SKU, it is sold only in pairs, as these H100 NVL GPUs are paired together and are connected by three NVLink connectors on top. Installation requires two PCIe slots, separated by dual-slot spacing.

The performance differences between the H100 PCIe version and the H100 SXM version are now matched with the new H100 NVL, as the card features a boost in the TDP with up to 400 Watts per card, which is configurable. The H100 NVL uses the same Tensor and CUDA core configuration as the SXM edition, except it is placed on a PCIe slot and connected to another card. Being sold in pairs, OEMs can outfit their systems with either two or four pairs per certified system. You can see the specification table below, with information filled out by AnandTech. As NVIDIA says, the need for this special edition SKU is the emergence of Large Language Models (LLMs) that require significant computational power to run. "Servers equipped with H100 NVL GPUs increase GPT-175B model performance up to 12X over NVIDIA DGX A100 systems while maintaining low latency in power-constrained data center environments," noted the company.