Topic
AI Hardware_
The AI hardware landscape is evolving at an unprecedented pace. NVIDIA releases new GPU architectures on an annual cadence, and each generation brings significant changes to infrastructure requirements: higher power per GPU, mandatory liquid cooling, new interconnect standards, and denser rack configurations. Staying current with these hardware changes is essential for any organization planning GPU infrastructure deployments.
Leviathan Systems Scope_
Leviathan Systems maintains hands-on deployment experience across multiple generations of NVIDIA GPU platforms. This hub collects our hardware-specific guides, specifications, and deployment documentation.
Articles_
Getting Ready for Rubin / VR200: Deployment-Readiness Planning NowDetails the concrete facility, power, and cooling preparation steps operators must complete before Rubin-class racks arrive, including exact sequencing, standards references, and decision criteria for upgrades.H200 Deployment Guide: What's Different from H100 on the FloorSpecifies the power and thermal deltas between H200 and H100 SXM GPUs that change rack power budgeting, liquid cooling setup, and commissioning steps for deployment crews.H100 / HGX H100 Deployment Checklist: Power, Cooling, and Cabling DemandsThis checklist specifies the exact physical-layer sequence for power distribution, cooling loop integration, copper NVLink backplane seating, and MPO-based scale-out cabling when deploying HGX H100 racks in either air-cooled or direct-liquid-cooled form factors.GH200 Grace Hopper Deployment Guide: Cabling and Cooling a Superchip NodeField procedures for integrating GH200 Grace Hopper nodes into racks, covering power feeds, internal NVLink connections, and liquid cooling loops with explicit differences from HGX baseboard layouts that change rack power sequencing and leak testing order.GB200 NVL72 Deployment Deep Dive: Liquid Loop, Busbar, and SpineDetails the physical assembly sequence for liquid cooling loops, DC busbars, and internal copper NVLink spines in GB200 NVL72 racks, including manifold connections, torque order, pressure testing, and field verification steps performed by deployment crews.B300 Deployment Guide: The Physical-Layer Step Up from B200Compares the power distribution, liquid cooling, and cabling changes required when moving from B200 to B300 racks, with explicit steps and decision criteria for field crews performing GB300-class deployments.B200 / HGX B200 Deployment Guide: Power, Thermal, and Rack DemandsDetails the rack, power distribution, and liquid-cooling prerequisites that must be verified before an HGX B200 system leaves the integration floor, including separation of NVLink copper from scale-out fiber and the validation sequence used by field crews.Air-Cooled vs Liquid-Cooled GPU Platforms: Picking the Variant for Your SiteThis article explains how to measure a site's existing CRAC/CRAH and facility water capacity against GPU rack heat loads to choose air-cooled versus liquid-cooled platforms for H100 through GB300 NVL72 deployments, including rack-level integration steps performed by field crews.NVIDIA B200 vs GB200: HGX vs Rack-Scale, and What Changes to DeployA field engineer's guide to the deployment differences between NVIDIA HGX B200 and GB200 NVL72 systems, covering rack assembly, cabling, liquid cooling, and commissioning, with emphasis on the shift from air-cooled HGX to liquid-cooled rack-scale GB200.AMD MI300X vs NVIDIA H100: Infrastructure & Deployment DifferencesA field engineer's practical comparison of AMD MI300X and NVIDIA H100 infrastructure requirements—power, cooling, fabric topology, rack density, and common deployment pitfalls—for operators building or retrofitting AI data centers.NVIDIA GB300 NVL72 Explained: Specs, Power, and What It Takes to DeployA field engineer’s guide to the NVIDIA GB300 NVL72 rack: its architecture, power/cooling specs, and the physical-layer deployment steps (rack assembly, liquid cooling, copper NVLink backplane, MPO fiber patching) that determine whether the system works at rated performance.Dell vs Supermicro vs HPE GPU Servers: A Deployment ComparisonA field engineer's practical comparison of Dell, Supermicro, and HPE GPU server platforms for AI data-center deployment, focusing on assembly, cabling, integration, and common pitfalls at scale.NVIDIA H100 vs H200 vs B200: What Changes for DeploymentA field engineer's guide to the physical deployment differences between NVIDIA H100, H200, and B200 GPU platforms, covering power, cooling, cabling, and rack density changes that affect data center build and commissioning.Google TPU vs NVIDIA GPU: What It Means for Your AI Infrastructure BuildA field engineer’s practical comparison of Google TPU pods and NVIDIA GPU clusters, covering architecture, cabling, cooling, power, and deployment differences to inform infrastructure build decisions.HGX vs DGX: What's Different When You Deploy ThemA field-level comparison of HGX and DGX deployments, detailing the practical differences in rack assembly, GPU and bridge installation, liquid cooling integration, cabling, and commissioning for AI data centers.GB300 NVL72 Deployment: Power, Cooling, and the Cable PlantA field engineer's guide to the physical-layer demands of deploying a GB300 NVL72 rack, covering power distribution, liquid cooling, and the scale-out cable plant, with emphasis on common failure modes and practical steps to avoid them. Based on field experience from Leviathan Systems and industry best practices.GB200 vs GB300 NVL72: What Changes for DeploymentA field engineer's practical guide to the deployment differences between GB200 and GB300 NVL72 racks, covering power delivery, liquid cooling, cabling, and common failure modes.
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