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ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board

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23 Apr 2024
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Abstract

The NVIDIA H200 Tensor Core GPU supercharges generative AI and high-performance computing (HPC) workloads with game-changing performance and memory capabilities.

This product guide provides essential presales information to understand the NVIDIA H200 GPU and their key features, specifications, and compatibility. This guide is intended for technical specialists, sales specialists, sales engineers, IT architects, and other IT professionals who want to learn more about the GPUs and consider their use in IT solutions.

Introduction

The NVIDIA H200 Tensor Core GPU supercharges generative AI and high-performance computing (HPC) workloads with game-changing performance and memory capabilities. H200 is the newest addition to NVIDIA’s leading AI and high-performance data center GPU portfolio, bringing massive compute to data centers.

The NVIDIA H200 141GB 700W GPU is offered in the ThinkSystem SR680a V3 server, with eight SXM5 form factor GPU modules and NVIDIA® NVLink® Fabric to create an 8-FC (fully connected) NVLink topology per baseboard. Leveraging the power of H200 multi-precision Tensor Cores, an eight-way HGX H200 provides over 32 petaFLOPS of FP8 deep learning compute and over 1.1TB of aggregate HBM memory for the highest performance in generative AI and HPC applications.

ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board
Figure 1. ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board in the ThinkSystem SR680a V3 server

Did you know?

To maximize compute performance, H200 is the world’s first GPU with HBM3e memory with 4.8TB/s of memory bandwidth, a 1.4X increase over H100. H200 also expands GPU memory capacity nearly doubled to 141GB. The combination of faster and larger HBM memory accelerates performance of computationally intensive generative AI and HPC applications, while meeting the evolving demands of growing model sizes.

Part number information

The following table shows the part numbers for the 8-GPU board. Feature code C1HMcontains 8x H200 GPUs in the SXM form factor plus the NVLink high-speed interconnections.

Table 1. Ordering information
Part number Feature code Description
CTO only C1HM ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board

Features

The NVIDIA H200 Tensor Core GPU supercharges generative AI and HPC with game-changing performance and memory capabilities. As the first GPU with HBM3e, H200’s faster, larger memory fuels the acceleration of generative AI and LLMs while advancing scientific computing for HPC workloads.

NVIDIA HGX™ H200, the world’s leading AI computing platform, features the H200 GPU for the fastest performance. An eight-way HGX H200 provides over 32 petaflops of FP8 deep learning compute and 1.1TB of aggregate high-bandwidth memory for the highest performance in generative AI and HPC applications.

Key AI and HPC workload features:

  • Unlock Insights With High-Performance LLM Inference

    In the ever-evolving landscape of AI, businesses rely on large language models to address a diverse range of inference needs. An AI inference accelerator must deliver the highest throughput at the lowest TCO when deployed at scale for a massive user base. H200 doubles inference performance compared to H100 when handling LLMs such as Llama2 70B.

  • Optimize Generative AI Fine-Tuning Performance

    Large language models can be customized to specific business case needs with fine-tuning, low-rank adaptation (LoRA), or retrieval-augmented generation (RAG) methods. These methods bridge the gap between general pretrained results and task-specific solutions, making them essential tools for industry and research applications.

    NVIDIA H200’s Transformer Engine and fourth-generation Tensor Cores speed up fine-tuning by 5.5X over A100 GPUs. This performance increase allows enterprises and AI practitioners to quickly optimize and deploy generative AI to benefit their business. Compared to fully training foundation models from scratch, fine-tuning offers better energy efficiency and the fastest access to customized solutions needed to grow business.

  • Industry-Leading Generative AI Training

    The era of generative AI has arrived, and it requires billion-parameter models to take on the paradigm shift in business operations and customer experiences.

    NVIDIA H200 GPUs feature the Transformer Engine with FP8 precision, which provides up to 5X faster training over A100 GPUs for large language models such as GPT-3 175B. The combination of fourth-generation NVLink, which offers 900GB/s of GPU-to-GPU interconnect, PCIe Gen5, and NVIDIA Magnum IO™ software, delivers efficient scalability from small enterprise to massive unified computing clusters of GPUs. These infrastructure advances, working in tandem with the NVIDIA AI Enterprise software suite, make the NVIDIA H200 the most powerful end-to-end generative AI and HPC data center platform.

  • Supercharged High-Performance Computing

    Memory bandwidth is crucial for high-performance computing applications, as it enables faster data transfer and reduces complex processing bottlenecks. For memory-intensive HPC applications like simulations, scientific research, and artificial intelligence, H200’s higher memory bandwidth ensures that data can be accessed and manipulated efficiently, leading to up to a 110X faster time to results.

    The NVIDIA data center platform consistently delivers performance gains beyond Moore’s Law. And H200’s breakthrough AI capabilities further amplify the power of HPC+AI to accelerate time to discovery for scientists and researchers working on solving the world’s most important challenges.

  • Reduced Energy and TCO

    In a world where energy conservation and sustainability are top of mind, the concerns of business leaders and enterprises have evolved. Enter accelerated computing, a leader in energy efficiency and TCO, particularly for workloads that thrive on acceleration, such as HPC and generative AI.

    With the introduction of H200, energy efficiency and TCO reach new levels. This cutting-edge technology offers unparalleled performance, all within the same power profile as H100. AI factories and at-scale supercomputing systems that are not only faster but also more eco-friendly deliver an economic edge that propels the AI and scientific community forward. For at-scale deployments, H200 systems provide 5X more energy savings and 4X better cost of ownership savings over the NVIDIA Ampere architecture generation.

Technical specifications

The following table lists the NVIDIA H200 GPU specifications.

Table 2. GPU specifications
Specification NVIDIA H200
Form Factor SXM5
FP64 34 teraFLOPS
FP64 Tensor Core 67 teraFLOPS
FP32 67 teraFLOPS
TF32 Tensor Core 495 / 989 teraFLOPS*
BFLOAT16 Tensor 990 / 1,979 teraFLOPS*
FP16 Tensor Core 990 / 1,979 teraFLOPS*
FP8 Tensor Core 1,979 / 3,958 teraFLOPS*
INT8 Tensor Core 1,979 / 3,958 TOPS*
GPU Memory 141 GB HBM3e
GPU Memory Bandwidth 4.8 TB/s
Total Graphics Power (TGP) or Continuous Electrical Design Point (EDPc) 700W
Multi-Instance GPUs Up to 7 MIGS @ 16.5 GB
Interconnect NVLink: 900 GB/s
PCIe Gen5: 128 GB/s

* Without / with structural sparsity enabled

Server support

The following tables list the ThinkSystem servers that are compatible.

Table 3. Server support (Part 1 of 4)
Part Number Description 2S AMD V3 2S Intel V3 4S 8S Intel V3 Multi Node GPU Rich 1S V3
SR635 V3 (7D9H / 7D9G)
SR655 V3 (7D9F / 7D9E)
SR645 V3 (7D9D / 7D9C)
SR665 V3 (7D9B / 7D9A)
ST650 V3 (7D7B / 7D7A)
SR630 V3 (7D72 / 7D73)
SR650 V3 (7D75 / 7D76)
SR850 V3 (7D97 / 7D96)
SR860 V3 (7D94 / 7D93)
SR950 V3 (7DC5 / 7DC4)
SD535 V3 (7DD8 / 7DD1)
SD530 V3 (7DDA / 7DD3)
SD550 V3 (7DD9 / 7DD2)
SR670 V2 (7Z22 / 7Z23)
SR675 V3 (7D9Q / 7D9R)
SR680a V3 (7DHE)
SR685a V3 (7DHC)
ST50 V3 (7DF4 / 7DF3)
ST250 V3 (7DCF / 7DCE)
SR250 V3 (7DCM / 7DCL)
C1HM ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board N N N N N N N N N N N N N N N 11 N N N N
  1. Contains 8 separate GPUs connected via high-speed interconnects
Table 4. Server support (Part 2 of 4)
Part Number Description Edge Super Computing 1S Intel V2 2S Intel V2
SE350 (7Z46 / 7D1X)
SE350 V2 (7DA9)
SE360 V2 (7DAM)
SE450 (7D8T)
SE455 V3 (7DBY)
SD665 V3 (7D9P)
SD665-N V3 (7DAZ)
SD650 V3 (7D7M)
SD650-I V3 (7D7L)
SD650-N V3 (7D7N)
ST50 V2 (7D8K / 7D8J)
ST250 V2 (7D8G / 7D8F)
SR250 V2 (7D7R / 7D7Q)
ST650 V2 (7Z75 / 7Z74)
SR630 V2 (7Z70 / 7Z71)
SR650 V2 (7Z72 / 7Z73)
C1HM ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board N N N N N N N N N N N N N N N N
Table 5. Server support (Part 3 of 4)
Part Number Description AMD V1 Dense V2 4S V2 8S 4S V1 1S Intel V1
SR635 (7Y98 / 7Y99)
SR655 (7Y00 / 7Z01)
SR655 Client OS
SR645 (7D2Y / 7D2X)
SR665 (7D2W / 7D2V)
SD630 V2 (7D1K)
SD650 V2 (7D1M)
SD650-N V2 (7D1N)
SN550 V2 (7Z69)
SR850 V2 (7D31 / 7D32)
SR860 V2 (7Z59 / 7Z60)
SR950 (7X11 / 7X12)
SR850 (7X18 / 7X19)
SR850P (7D2F / 2D2G)
SR860 (7X69 / 7X70)
ST50 (7Y48 / 7Y50)
ST250 (7Y45 / 7Y46)
SR150 (7Y54)
SR250 (7Y52 / 7Y51)
C1HM ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board N N N N N N N N N N N N N N N N N N N
Table 6. Server support (Part 4 of 4)
Part Number Description 2S Intel V1 Dense V1
ST550 (7X09 / 7X10)
SR530 (7X07 / 7X08)
SR550 (7X03 / 7X04)
SR570 (7Y02 / 7Y03)
SR590 (7X98 / 7X99)
SR630 (7X01 / 7X02)
SR650 (7X05 / 7X06)
SR670 (7Y36 / 7Y37)
SD530 (7X21)
SD650 (7X58)
SN550 (7X16)
SN850 (7X15)
C1HM ThinkSystem NVIDIA HGX H200 141GB 700W 8-GPU Board N N N N N N N N N N N N

Operating system support

Operating system support is based on that of the supported servers. See the SR680a V3 server product guide for details: https://lenovopress.lenovo.com/lp1909-thinksystem-sr680a-v3-server

NVIDIA GPU software

NVIDIA vGPU Software (vApps, vPC, RTX vWS, and vCS)

Lenovo offers the following virtualization software for NVIDIA GPUs:

  • Virtual Applications (vApps)

    For organizations deploying Citrix XenApp, VMware Horizon RDSH or other RDSH solutions. Designed to deliver PC Windows applications at full performance. NVIDIA Virtual Applications allows users to access any Windows application at full performance on any device, anywhere. This edition is suited for users who would like to virtualize applications using XenApp or other RDSH solutions. Windows Server hosted RDSH desktops are also supported by vApps.

  • Virtual PC (vPC)

    This product is ideal for users who want a virtual desktop but need great user experience leveraging PC Windows® applications, browsers and high-definition video. NVIDIA Virtual PC delivers a native experience to users in a virtual environment, allowing them to run all their PC applications at full performance.

  • NVIDIA RTX Virtual Workstation (RTX vWS)

    NVIDIA RTX vWS is the only virtual workstation that supports NVIDIA RTX technology, bringing advanced features like ray tracing, AI-denoising, and Deep Learning Super Sampling (DLSS) to a virtual environment. Supporting the latest generation of NVIDIA GPUs unlocks the best performance possible, so designers and engineers can create their best work faster. IT can virtualize any application from the data center with an experience that is indistinguishable from a physical workstation — enabling workstation performance from any device.

  • Virtual Compute Server (vCS)

    NVIDIA Virtual Compute Server (vCS) enables data centers running on Red Hat Enterprise Linux, Red Hat Virtualization, and other supported KVM-based hypervisors to accelerate server virtualization with the latest NVIDIA data center GPUs, so that the most compute-intensive workloads, such as artificial intelligence, deep learning, and data science, can be run in a virtual machine (VM) powered by NVIDIA vGPU technology.

The following license types are offered:

  • Perpetual license

    A non-expiring, permanent software license that can be used on a perpetual basis without the need to renew. Each Lenovo part number includes a fixed number of years of Support, Upgrade and Maintenance (SUMS).

  • Annual subscription

    A software license that is active for a fixed period as defined by the terms of the subscription license, typically yearly. The subscription includes Support, Upgrade and Maintenance (SUMS) for the duration of the license term.

  • Concurrent User (CCU)

    A method of counting licenses based on active user VMs. If the VM is active and the NVIDIA vGPU software is running, then this counts as one CCU. A vGPU CCU is independent of the connection to the VM.

The following table lists the ordering part numbers and feature codes.

Table 7. NVIDIA vGPU Software
Part number Feature code
7S02CTO1WW
Description
NVIDIA vApps
7S020003WW B1MP NVIDIA vApps Perpetual License and SUMS 5Yr, 1 CCU
7S020004WW B1MQ NVIDIA vApps Subscription License 1 Year, 1 CCU
7S020005WW B1MR NVIDIA vApps Subscription License 3 Years, 1 CCU
7S02003DWW S832 NVIDIA vApps Subscription License 4 Years, 1 CCU
7S02003EWW S833 NVIDIA vApps Subscription License 5 Years, 1 CCU
NVIDIA vPC
7S020009WW B1MV NVIDIA vPC Perpetual License and SUMS 5Yr, 1 CCU
7S02000AWW B1MW NVIDIA vPC Subscription License 1 Year, 1 CCU
7S02000BWW B1MX NVIDIA vPC Subscription License 3 Years, 1 CCU
7S02003FWW S834 NVIDIA vPC Subscription License 4 Years, 1 CCU
7S02003GWW S835 NVIDIA vPC Subscription License 5 Years, 1 CCU
NVIDIA RTX vWS
7S02000FWW B1N1 NVIDIA RTX vWS Perpetual License and SUMS 5Yr, 1 CCU
7S02000GWW B1N2 NVIDIA RTX vWS Subscription License 1 Year, 1 CCU
7S02000HWW B1N3 NVIDIA RTX vWS Subscription License 3 Years, 1 CCU
7S02000XWW S6YJ NVIDIA RTX vWS Subscription License 4 Years, 1 CCU
7S02000YWW S6YK NVIDIA RTX vWS Subscription License 5 Years, 1 CCU
7S02000LWW B1N6 NVIDIA RTX vWS EDU Perpetual License and SUMS 5Yr, 1 CCU
7S02000MWW B1N7 NVIDIA RTX vWS EDU Subscription License 1 Year, 1 CCU
7S02000NWW B1N8 NVIDIA RTX vWS EDU Subscription License 3 Years, 1 CCU
7S02003BWW S830 NVIDIA RTX vWS EDU Subscription License 4 Years, 1 CCU
7S02003CWW S831 NVIDIA RTX vWS EDU Subscription License 5 Years, 1 CCU
NVIDIA vCS
7S02000ZWW S6YL NVIDIA Virtual Compute Server Subscription, 1 GPU (Max 10 CC VMs), 1 Year
7S020010WW S6YM NVIDIA Virtual Compute Server Subscription, 1 GPU (Max 10 CC VMs), 3 Years
7S020011WW S6YN NVIDIA Virtual Compute Server Subscription, 1 GPU (Max 10 CC VMs), 5 Years
7S020012WW S6YP NVIDIA Virtual Compute Server Subscription, 1 GPU (Max 10 CC VMs), EDU, 1 Year
7S020013WW S6YQ NVIDIA Virtual Compute Server Subscription, 1 GPU (Max 10 CC VMs), EDU, 3 Years
7S020014WW S6YR NVIDIA Virtual Compute Server Subscription, 1 GPU (Max 10 CC VMs), EDU, 5 Years

NVIDIA Omniverse Software (OVE)

NVIDIA Omniverse™ Enterprise is an end-to-end collaboration and simulation platform that fundamentally transforms complex design workflows, creating a more harmonious environment for creative teams.

NVIDIA and Lenovo offer a robust, scalable solution for deploying Omniverse Enterprise, accommodating a wide range of professional needs. This document details the critical components, deployment options, and support available, ensuring an efficient and effective Omniverse experience.

Deployment options cater to varying team sizes and workloads. Using Lenovo NVIDIA-Certified Systems™ and Lenovo OVX nodes which are meticulously designed to manage scale and complexity, ensures optimal performance for Omniverse tasks.

Deployment options include:

  • Workstations: NVIDIA-Certified Workstations with A5000 or A6000 Ada GPUs for desktop environments.
  • Data Center Solutions: Deployment with Lenovo OVX nodes or NVIDIA-Certified Servers equipped with L40, L40S or A40 GPUs for centralized, high-capacity needs.

NVIDIA Omniverse Enterprise includes the following components and features:

  • Platform Components: Kit, Connect, Nucleus, Simulation, RTX Renderer.
  • Foundation Applications: USD Composer, USD Presenter.
  • Omniverse Extensions: Connect Sample & SDK.
  • Integrated Development Environment (IDE)
  • Nucleus Configuration: Workstation, Enterprise Nucleus Server (supports up to 8 editors per scene); Self-Service Public Cloud Hosting using Containers.
  • Omniverse Farm: Supports batch workloads up to 8 GPUs.
  • Enterprise Services: Authentication (SSO/SSL), Navigator Microservice, Large File Transfer, User Accounts SAML/Account Directory.
  • User Interface: Workstation & IT Managed Launcher.
  • Support: NVIDIA Enterprise Support.
  • Deployment Scenarios: Desktop to Data Center: Workstation deployment for building and designing, with options for physical or virtual desktops. For batch tasks, rendering, and SDG workloads that require headless compute, Lenovo OVX nodes are recommended.

The following part numbers are for a subscription license which is active for a fixed period as noted in the description. The license is for a named user which means the license is for named authorized users who may not re-assign or share the license with any other person.

Table 8. NVIDIA Omniverse Software (OVE)
Part number Feature
7S02CTO1WW
Description
7S02003ZWW SCX0 NVIDIA Omniverse Enterprise Subscription per GPU, 1 Year
7S020042WW SCX3 NVIDIA Omniverse Enterprise Subscription per GPU, 3 Years
7S020041WW SCX2 NVIDIA Omniverse Enterprise Subscription per GPU, INC, 1 Year
7S020040WW SCX1 NVIDIA Omniverse Enterprise Subscription per GPU, EDU, 1 Year
7S020043WW SCX4 NVIDIA Omniverse Enterprise Subscription per GPU, EDU, 3 Years

NVIDIA AI Enterprise Software

Lenovo offers the NVIDIA AI Enterprise (NVAIE) cloud-native enterprise software. NVIDIA AI Enterprise is an end-to-end, cloud-native suite of  AI and data analytics software, optimized, certified, and supported by NVIDIA to run on VMware vSphere and bare-metal  with NVIDIA-Certified  Systems™.  It includes key enabling technologies from NVIDIA for rapid deployment, management, and scaling of AI workloads in the modern hybrid cloud.

NVIDIA AI Enterprise is licensed on a per-GPU basis. NVIDIA AI Enterprise products can be purchased as either a perpetual license with support services, or as an annual or multi-year subscription.

  • The perpetual license provides the right to use the NVIDIA AI Enterprise software indefinitely, with no expiration. NVIDIA AI Enterprise with perpetual licenses must be purchased in conjunction with one-year, three-year, or five-year support services. A one-year support service is also available for renewals.
  • The subscription offerings are an affordable option to allow IT departments to better manage the flexibility of license volumes. NVIDIA AI Enterprise software products with subscription includes support services for the duration of the software’s subscription license

The features of NVIDIA AI Enterprise Software are listed in the following table.

Table 9. Features of NVIDIA AI Enterprise Software (NVAIE)
Features Supported in NVIDIA AI Enterprise
Per GPU Licensing Yes
Compute Virtualization Supported
Windows Guest OS Support No support
Linux Guest OS Support Supported
Maximum Displays 1
Maximum Resolution 4096 x 2160 (4K)
OpenGL and Vulkan In-situ Graphics only
CUDA and OpenCL Support Supported
ECC and Page Retirement Supported
MIG GPU Support Supported
Multi-vGPU Supported
NVIDIA GPUDirect Supported
Peer-to-Peer over NVLink Supported
GPU Pass Through Support Supported
Baremetal Support Supported
AI and Data Science applications and Frameworks Supported
Cloud Native ready Supported

Note: Maximum 10 concurrent VMs per product license

The following table lists the ordering part numbers and feature codes.

Table 10. NVIDIA AI Enterprise Software (NVAIE)
Part number Feature code
7S02CTO1WW
Description
AI Enterprise Perpetual License
7S020019WW S6YW NVIDIA AI Enterprise Perpetual License and Support per GPU, 1 Year
7S02001AWW S6YX NVIDIA AI Enterprise Perpetual License and Support per GPU, 3 Years
7S02001BWW S6YY NVIDIA AI Enterprise Perpetual License and Support per GPU, 5 Years
7S02001CWW S6YZ NVIDIA AI Enterprise Perpetual License and Support per GPU, EDU, 1 Year
7S02001DWW S6Z0 NVIDIA AI Enterprise Perpetual License and Support per GPU, EDU, 3 Years
7S02001EWW S6Z1 NVIDIA AI Enterprise Perpetual License and Support per GPU, EDU, 5 Years
AI Enterprise Subscription License
7S02001FWW S6Z2 NVIDIA AI Enterprise Subscription License and Support per GPU, 1 Year
7S02001GWW S6Z3 NVIDIA AI Enterprise Subscription License and Support per GPU, 3 Years
7S02001HWW S6Z4 NVIDIA AI Enterprise Subscription License and Support per GPU, 5 Years
7S02001JWW S6Z5 NVIDIA AI Enterprise Subscription License and Support per GPU, EDU, 1 Year
7S02001KWW S6Z6 NVIDIA AI Enterprise Subscription License and Support per GPU, EDU, 3 Years
7S02001LWW S6Z7 NVIDIA AI Enterprise Subscription License and Support per GPU, EDU, 5 Years

Find more information in the NVIDIA AI Enterprise Sizing Guide.

NVIDIA HPC Compiler Software

Table 11. NVIDIA HPC Compiler
Part number Feature code
7S09CTO6WW
Description
HPC Compiler Support Services
7S090014WW S924 NVIDIA HPC Compiler Support Services, 1 Year
7S090015WW S925 NVIDIA HPC Compiler Support Services, 3 Years
7S09002GWW S9UQ NVIDIA HPC Compiler Support Services, 5 Years
7S090016WW S926 NVIDIA HPC Compiler Support Services, EDU, 1 Year
7S090017WW S927 NVIDIA HPC Compiler Support Services, EDU, 3 Years
7S09002HWW S9UR NVIDIA HPC Compiler Support Services, EDU, 5 Years
7S090018WW S928 NVIDIA HPC Compiler Support Services - Additional Contact, 1 Year
7S09002JWW S9US NVIDIA HPC Compiler Support Services - Additional Contact, 3 Years
7S09002KWW S9UT NVIDIA HPC Compiler Support Services - Additional Contact, 5 Years
7S090019WW S929 NVIDIA HPC Compiler Support Services - Additional Contact, EDU, 1 Year
7S09002LWW S9UU NVIDIA HPC Compiler Support Services - Additional Contact, EDU, 3 Years
7S09002MWW S9UV NVIDIA HPC Compiler Support Services - Additional Contact, EDU, 5 Years
HPC Compiler Premier Support Services
7S09001AWW S92A NVIDIA HPC Compiler Premier Support Services, 1 Year
7S09002NWW S9UW NVIDIA HPC Compiler Premier Support Services, 3 Years
7S09002PWW S9UX NVIDIA HPC Compiler Premier Support Services, 5 Years
7S09001BWW S92B NVIDIA HPC Compiler Premier Support Services, EDU, 1 Year
7S09002QWW S9UY NVIDIA HPC Compiler Premier Support Services, EDU, 3 Years
7S09002RWW S9UZ NVIDIA HPC Compiler Premier Support Services, EDU, 5 Years
7S09001CWW S92C NVIDIA HPC Compiler Premier Support Services - Additional Contact, 1 Year
7S09002SWW S9V0 NVIDIA HPC Compiler Premier Support Services - Additional Contact, 3 Years
7S09002TWW S9V1 NVIDIA HPC Compiler Premier Support Services - Additional Contact, 5 Years
7S09001DWW S92D NVIDIA HPC Compiler Premier Support Services - Additional Contact, EDU, 1 Year
7S09002UWW S9V2 NVIDIA HPC Compiler Premier Support Services - Additional Contact, EDU, 3 Years
7S09002VWW S9V3 NVIDIA HPC Compiler Premier Support Services - Additional Contact, EDU, 5 Years

Regulatory approvals

The NVIDIA H200 GPU has the following regulatory approvals:

  • RCM
  • BSMI
  • CE
  • FCC
  • ICES
  • KCC
  • cUL, UL
  • VCCI

Warranty

The NVIDIA H200 GPU assumes the server’s base warranty and any warranty upgrades.

Seller training courses

The following sales training courses are offered for employees and partners (login required). Courses are listed in date order.

  1. Think AI Weekly: Lenovo AI PCs & AI Workstations
    2024-05-23 | 60 minutes | Employees Only
    Details
    Think AI Weekly: Lenovo AI PCs & AI Workstations

    Join Mike Leach, Sr. Manager, Workstations Solutions and Pooja Sathe, Director Commercial AI PCs as they discuss why Lenovo AI Developer Workstations and AI PCs are the most powerful, where they fit into the device to cloud ecosystem, and this week’s Microsoft announcement, Copilot+PC

    Published: 2024-05-23
    Length: 60 minutes
    Employee link: Grow@Lenovo
    Course code: DTAIW105
  2. VTT Cloud Architecture: NVidia Using Cloud for GPUs and AI
    2024-05-22 | 60 minutes | Employees Only
    Details
    VTT Cloud Architecture: NVidia Using Cloud for GPUs and AI

    Join JD Dupont, NVIDIA Head of Americas Sales, Lenovo partnership and Veer Mehta, NVIDIA Solution Architect on an interactive discussion about cloud to edge, designing cloud Solutions with Nvidia GPUs and minimizing private\hybrid cloud OPEX with GPUs. Discover how you can use what is done at big public cloud providers for your customers. We will also walk through use cases and see a demo you can use to help your customers.

    Published: 2024-05-22
    Length: 60 minutes
    Employee link: Grow@Lenovo
    Course code: DVCLD212
  3. Generative AI Overview Foundational
    2024-02-16 | 17 minutes | Employees Only
    Details
    Generative AI Overview Foundational

    It seems the whole world is excited about Generative AI, and while some of it is just hype, it has become clear that Generative AI has the potential to revolutionize many aspects of our personal and professional lives. In this brief NVIDIA course, we'll explore one aspect of the Generative AI excitement, the value you get from Generative AI technology. We will discuss what Generative AI is, how it works, and how enterprises are planning to use this technology.

    By the end of this course, you will be able to discuss the Generative AI market trends and the challenges in this space with your customers. And you will be able to explain what Generative AI is and how the technology works to help enterprises unlock new opportunities for business.

    Published: 2024-02-16
    Length: 17 minutes
    Employee link: Grow@Lenovo
    Course code: DAINVD106
  4. Industry Use Cases in Modern Computing Foundational
    2024-02-16 | 9 minutes | Employees Only
    Details
    Industry Use Cases in Modern Computing Foundational

    As GPU powered computing continues to improve exponentially, applications that were once science fiction are becoming best practice. This is an introductory NVIDIA course that explores some exciting industry focused use cases that are providing companies with faster time to insight, productivity at scale and a great ROI.

    By the end of this course, you will be able to explain how companies in a few key industry verticals are benefiting from a variety of accelerated compute use cases.

    Published: 2024-02-16
    Length: 9 minutes
    Employee link: Grow@Lenovo
    Course code: DAINVD105
  5. Introduction to Artificial Intelligence Foundational
    2024-02-16 | 10 minutes | Employees Only
    Details
    Introduction to Artificial Intelligence Foundational

    This NVIDIA course aims to answer questions such as, what is AI and why are enterprises so interested in it? and how does AI happen, why are GPUs so important for it, and what does a good AI solution look like?

    By the end of this training, you should be able to describe AI and relate it to some common enterprise use cases. You'll know the difference between training and inference and be able to visualize a typical AI workflow. More importantly, you'll understand the difficulties of traditional CPU-based AI and appreciate why businesses would benefit greatly by adopting GPU-accelerated workflows. Finally, you'll also understand what features contribute to an awesome AI solution and why customers respect and enjoy NVIDIA's solutions.

    Published: 2024-02-16
    Length: 10 minutes
    Employee link: Grow@Lenovo
    Course code: DAINVD104
  6. GPU Fundamentals Foundational
    2024-02-16 | 10 minutes | Employees Only
    Details
    GPU Fundamentals Foundational

    This NVIDIA course introduces you to two devices that a computer typically uses to process information, the CPU and the GPU. We'll discuss their differences and look at how the GPU overcomes the limitations of the CPU. Once you understand the power and advantages of GPU processing, we will talk about the value GPUs bring to modern-day enterprise computing.

    By the end of this course, you should know the difference between serial and parallel processing. You will be able to explain what a GPU is in very simple terms and explain the value that GPUs bring to enterprises. Additionally, you'll become familiar with the typical GPU-accelerated enterprise workloads and list one or two use cases under them. By the time you exit this course, you should be able to target various GPU-accelerated computing opportunities with the right NVIDIA GPU.

    Published: 2024-02-16
    Length: 10 minutes
    Employee link: Grow@Lenovo
    Course code: DAINVD103
  7. Partner Technical Webinar – NVidia
    2023-12-11 | 60 minutes | Employees and Partners
    Details
    Partner Technical Webinar – NVidia

    In this 60-minute replay, Brad Davidson of Nvidia will help us recognize AI Trends, and Discuss Industry Verticals Marketing.

    Published: 2023-12-11
    Length: 60 minutes
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: 120823

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