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ThinkSystem NVIDIA H100 PCIe Gen5 GPUs

Product Guide

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Updated
9 Aug 2024
Form Number
LP1732
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27 pages, 707 KB

Abstract

The ThinkSystem NVIDIA H100 GPU delivers unprecedented performance, scalability, and security for every workload. The GPUs use breakthrough innovations in the NVIDIA Hopper™ architecture to deliver industry-leading conversational AI, speeding up large language models by 30X over the previous generation.

This product guide provides essential presales information to understand the NVIDIA H100 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.

Change History

Changes in the August 9, 2024 update:

  • The following GPU is withdrawn from marketing:
    • ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU, 4X67A82257

Introduction

The ThinkSystem NVIDIA H100 GPU delivers unprecedented performance, scalability, and security for every workload. The GPUs use breakthrough innovations in the NVIDIA Hopper™ architecture to deliver industry-leading conversational AI, speeding up large language models by 30X over the previous generation.

The NVIDIA H100 GPU features fourth-generation Tensor Cores and the Transformer Engine with FP8 precision, further extending NVIDIA’s market-leading AI leadership with up to 9X faster training and an incredible 30X inference speedup on large language models. For high-performance computing (HPC) applications, The GPUs triple the floating-point operations per second (FLOPS) of FP64 and add dynamic programming (DPX) instructions to deliver up to 7X higher performance.

The following figure shows the ThinkSystem NVIDIA H100 GPU in the double-width PCIe adapter form factor.

ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU
Figure 1. ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU

Did you know?

The NVIDIA H100 family is available in both double-wide PCIe adapter form factor and in SXM form factor. The latter is used in Lenovo's Neptune direct-water-cooled ThinkSystem SD665-N V3 server for the ultimate in GPU performance and heat management.

The NVIDIA H100 NVL Tensor Core GPU is optimized for Large Language Model (LLM) Inferences, with its high compute density, high memory bandwidth, high energy efficiency, and unique NVLink architecture.

Part number information

The following table shows the part numbers for the ThinkSystem NVIDIA H100 GPU.

Not available in China, Hong Kong and Macau: The H100 GPUs are not available in China, Hong Kong and Macau. For these markets, the H800 is avalable. See the NVIDIA H800 product guide for details, https://lenovopress.lenovo.com/LP1814.

Table 1. Ordering information
Part number Feature code Description
Double-wide PCIe adapter form factor
4X67A89325 BXAK ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU
4X67A82257 BR9U ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU
SXM form factor
CTO only C1HL ThinkSystem NVIDIA HGX H100 80GB 700W 8-GPU Board
CTO only BQQV ThinkSystem NVIDIA H100 SXM5 700W 80G GPU Board
CTO only BUBB ThinkSystem NVIDIA H100 SXM5 700W 94G HBM2e GPU Board
NVLink bridge (for PCIe adapters only, not SXM)
4X67A71309 BG3F ThinkSystem NVIDIA Ampere NVLink 2-Slot Bridge (3 required per pair of GPUs)

The PCIe option part numbers includes the following:

  • One GPU with full-height (3U) adapter bracket attached
  • Documentation

The following figure shows the NVIDIA H100 SXM5 8-GPU Board with heatsinks installed in the ThinkSystem SR680a V3 and ThinkSystem SR685a V3 servers.

NVIDIA H100 SXM5 8-GPU Board in the ThinkSystem SR680a V3 and SR685a V3 servers
Figure 2. NVIDIA H100 SXM5 8-GPU Board in the ThinkSystem SR680a V3 and SR685a V3 servers

Features

The ThinkSystem NVIDIA H100 GPU delivers high performance, scalability, and security for every workload. The GPU uses breakthrough innovations in the NVIDIA Hopper™ architecture to deliver industry-leading conversational AI, speeding up large language models (LLMs) by 30X over the previous generation.

The PCIe versions of the NVIDIA H100 GPUs include a five-year software subscription, with enterprise support, to the NVIDIA AI Enterprise software suite, simplifying AI adoption with the highest performance. This ensures organizations have access to the AI frameworks and tools they need to build accelerated AI workflows such as AI chatbots, recommendation engines, vision AI, and more.

The NVIDIA H100 GPU features fourth-generation Tensor Cores and the Transformer Engine with FP8 precision, further extending NVIDIA’s market-leading AI leadership with up to 9X faster training and an incredible 30X inference speedup on large language models. For high-performance computing (HPC) applications, the GPU triples the floating-point operations per second (FLOPS) of FP64 and adds dynamic programming (DPX) instructions to deliver up to 7X higher performance. With second-generation Multi-Instance GPU (MIG), built-in NVIDIA confidential computing, and NVIDIA NVLink Switch System, the NVIDIA H100 GPU securely accelerates all workloads for every data center from enterprise to exascale.

Key features of the NVIDIA H100 GPU:

  • NVIDIA H100 Tensor Core GPU

    Built with 80 billion transistors using a cutting-edge TSMC 4N process custom tailored for NVIDIA’s accelerated compute needs, H100 is the world’s most advanced chip ever built. It features major advances to accelerate AI, HPC, memory bandwidth, interconnect, and communication at data center scale.

  • Transformer Engine

    The Transformer Engine uses software and Hopper Tensor Core technology designed to accelerate training for models built from the world’s most important AI   model building block, the transformer. Hopper Tensor Cores can apply mixed FP8 and FP16 precisions to dramatically accelerate AI calculations  for transformers.

  • NVLink Switch System

    The NVLink Switch System enables the scaling of multi-GPU input/output (IO) across multiple servers. The system delivers up to 9X higher bandwidth than InfiniBand HDR on the NVIDIA Ampere architecture.

  • NVIDIA Confidential Computing

    NVIDIA Confidential Computing is a built-in security feature of Hopper that makes NVIDIA H100 the world’s first accelerator with confidential computing capabilities. Users can protect the confidentiality and integrity of their data and applications in use while accessing the unsurpassed acceleration of H100 GPUs.

  • Second-Generation Multi-Instance GPU (MIG)

    The Hopper architecture’s second-generation MIG supports  multi-tenant, multi-user configurations in virtualized environments, securely partitioning the GPU into isolated, right-size instances to maximize quality of service (QoS) for 7X more secured tenants.

  • DPX Instructions

    Hopper’s DPX instructions accelerate dynamic programming algorithms by 40X compared to CPUs and 7X compared to NVIDIA Ampere architecture GPUs. This leads to dramatically faster times in disease diagnosis, real-time routing optimizations, and graph analytics.

The following figure shows the NVIDIA H100 SXM5 4-GPU Board installed in the ThinkSystem SD665-N V3 server

NVIDIA H100 SXM5 4-GPU Board in the ThinkSystem SD665-N V3 server
Figure 3. NVIDIA H100 SXM5 4-GPU Board in the ThinkSystem SD665-N V3 server

Technical specifications

The following table lists the GPU processing specifications and performance of the NVIDIA H100 GPU.

Table 2. Specifications of the NVIDIA H100 GPU
Feature H100 NVL 94GB PCIe adapter H100 80GB PCIe adapter H100 80GB SXM board H100 94GB SXM board
GPU Architecture NVIDIA Hopper NVIDIA Hopper NVIDIA Hopper NVIDIA Hopper
Part number 4X67A89325 4X67A82257 BQQV or C1HL BUBB
GPUs per part number 1 1 BQQV: 4
C1HL: 8
4
NVIDIA Tensor Cores 456 fourth-generation Tensor Cores 456 fourth-generation Tensor Cores 528 fourth-generation Tensor Cores 528 fourth-generation Tensor Cores
NVIDIA CUDA Cores (shading units) 14,592 FP32 CUDA Cores 14,592 FP32 CUDA Cores 16,896 FP32 CUDA Cores 16,896 FP32 CUDA Cores
Peak FP64 performance 34 TFLOPS 26 TFLOPS 34 TFLOPS 34 TFLOPS
Peak FP64 Tensor Core performance 67 TFLOPS 51 TFLOPS 67 TFLOPS 67 TFLOPS
Peak FP32 performance 67 TFLOPS 51 TFLOPS 67 TFLOPS 67 TFLOPS
Peak Tensor Float 32 (TF32) performance 990 TFLOPS* 756 TFLOPS* 989 TFLOPS* 989 TFLOPS*
Peak FP16 performance 1,980 TFOPS* 1,513 TFLOPS* 1,979 TFLOPS* 1,979 TFLOPS*
Peak Bfloat16 (BF16) performance 1,980 TFOPS* 1,513 TFLOPS* 1,979 TFLOPS* 1,979 TFLOPS*
Peak FP8 performance 3,960 TFOPS* 3,026 TFLOPS*    
INT8 Integer Performance 3,960 TOPS* 3,026 TOPS* 3,958 TOPS* 3,958 TOPS*
GPU Memory 94 GB HBM3 80 GB HBM2e 80GB board (feature BQQV): 80 GB HBM3 94GB board (feature BUBB): 90GB HBM2e
Memory Bandwidth 3.9 TB/s 2 TB/sec 80GB board (feature BQQV): 3.35 TB/sec 94GB board (feature BUBB): 2.4 TB/sec
ECC Yes Yes Yes Yes
Interconnect Bandwidth NVLink: 600 GB/sec
PCIe Gen5: 128 GB/sec
NVLink: 600 GB/sec
PCIe Gen5: 128 GB/sec
NVLink: 900 GB/sec
PCIe Gen5: 128 GB/sec
NVLink: 900 GB/sec
PCIe Gen5: 128 GB/sec
System Interface PCIe Gen 5.0, x16 lanes PCIe Gen 5.0, x16 lanes PCIe Gen 5.0, x16 lanes PCIe Gen 5.0, x16 lanes
Form Factor PCIe full height/length, double width PCIe full height/length, double width SXM5 SXM5
NVLink support Yes; 3 NVLink Bridge supported per pair of GPUs (all 3 required) Yes; 3 NVLink Bridge supported per pair of GPUs (all 3 required) Yes, integrated Yes, integrated
Multi-Instance GPU (MIG) Up to 7 GPU instances, 12GB each Up to 7 GPU instances, 10GB each Up to 7 GPU instances, 10GB each Up to 7 GPU instances, 10GB each
Max Power Consumption 400 W 350 W 700 W 700 W
Thermal Solution Passive Passive Water cooled Water cooled
Compute APIs CUDA, DirectCompute, OpenCL, OpenACC CUDA, DirectCompute, OpenCL, OpenACC CUDA, DirectCompute, OpenCL, OpenACC CUDA, DirectCompute, OpenCL, OpenACC

* With structural sparsity enabled

Server support

The following tables list the ThinkSystem servers that are compatible.

NVLink server support: The NVLink Ampere bridge is supported with additional NVIDIA A-series and H-series GPUs. As a result, there are additional servers listed as supporting the bridge that don't support the H100 GPU.

Table 3. Server support (Part 1 of 4)
Part Number Description AMD V3 2S Intel V3/V4 4S 8S Intel V3 Multi Node V3/V4 GPU Rich
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)
SR630 V4 (7DG8 / 7DG9)
SR850 V3 (7D97 / 7D96)
SR860 V3 (7D94 / 7D93)
SR950 V3 (7DC5 / 7DC4)
SD535 V3 (7DD8 / 7DD1)
SD530 V3 (7DDA / 7DD3)
SD550 V3 (7DD9 / 7DD2)
SD520 V4 (7DFZ / 7DFY)
SR670 V2 (7Z22 / 7Z23)
SR675 V3 (7D9Q / 7D9R)
SR680a V3 (7DHE)
SR685a V3 (7DHC)
SR780a V3 (7DJ5)
Double-wide PCIe adapter form factor
4X67A89325 ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU N 3 N 3 N N 3 N N N N N N N N N 8 N N N
4X67A82257 ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU N 3 N 3 N N 3 N 2 4 N N N N N 8 8 N N N
SXM form factor
C1HL ThinkSystem NVIDIA HGX H100 80GB 700W 8-GPU Board N N N N N N N N N N N N N N N N N 11 11 N
BQQV ThinkSystem NVIDIA H100 SXM5 700W 80G HBM3 GPU Board N N N N N N N N N N N N N N N N 12 N N N
BUBB ThinkSystem NVIDIA H100 SXM5 700W 94G HBM2e GPU Board N N N N N N N N N N N N N N N N N N N N
NVLink bridge (for PCIe adapters only, not SXM; order 3 per pair of GPUs)
4X67A71309 ThinkSystem NVIDIA Ampere NVLink 2-Slot Bridge N N N N N N N N N N N N N N N Y Y N N N
  1. Contains 8 separate GPUs connected via high-speed interconnects
  2. Contains 4 separate GPUs connected via high-speed interconnects
Table 4. Server support (Part 2 of 4)
Part Number Description 1S V3 Edge Super Computing 1S Intel V2 2S Intel V2
ST50 V3 (7DF4 / 7DF3)
ST250 V3 (7DCF / 7DCE)
SR250 V3 (7DCM / 7DCL)
SE350 (7Z46 / 7D1X)
SE350 V2 (7DA9)
SE360 V2 (7DAM)
SE450 (7D8T)
SE455 V3 (7DBY)
SC750 V4 (7DDJ)
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)
Double-wide PCIe adapter form factor
4X67A89325 ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU N N N N N N N N N N N N N N N N N N N N
4X67A82257 ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU N N N N N N N N N N N N N N N N N N N 3
SXM form factor
C1HL ThinkSystem NVIDIA HGX H100 80GB 700W 8-GPU Board N N N N N N N N N N N N N N N N N N N N
BQQV ThinkSystem NVIDIA H100 SXM5 700W 80G HBM3 GPU Board N N N N N N N N N N 11 N N 11 N N N N N N
BUBB ThinkSystem NVIDIA H100 SXM5 700W 94G HBM2e GPU Board N N N N N N N N N N 11 N N 11 N N N N N N
NVLink bridge (for PCIe adapters only, not SXM; order 3 per pair of GPUs)
4X67A71309 ThinkSystem NVIDIA Ampere NVLink 2-Slot Bridge N N N N N N N N N N N N N N N N N N N N
  1. Contains 4 separate GPUs connected via high-speed interconnects
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)
Double-wide PCIe adapter form factor
4X67A89325 ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU N N N N N N N N N N N N N N N N N N N
4X67A82257 ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU N N N N 3 N N N N N N N N N N N N N N
SXM form factor
C1HL ThinkSystem NVIDIA HGX H100 80GB 700W 8-GPU Board N N N N N N N N N N N N N N N N N N N
BQQV ThinkSystem NVIDIA H100 SXM5 700W 80G HBM3 GPU Board N N N N N N N N N N N N N N N N N N N
BUBB ThinkSystem NVIDIA H100 SXM5 700W 94G HBM2e GPU Board N N N N N N N N N N N N N N N N N N N
NVLink bridge (for PCIe adapters only, not SXM; order 3 per pair of GPUs)
4X67A71309 ThinkSystem NVIDIA Ampere NVLink 2-Slot Bridge 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)
Double-wide PCIe adapter form factor
4X67A89325 ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU N N N N N N N N N N N N
4X67A82257 ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU N N N N N N N N N N N N
SXM form factor
C1HL ThinkSystem NVIDIA HGX H100 80GB 700W 8-GPU Board N N N N N N N N N N N N
BQQV ThinkSystem NVIDIA H100 SXM5 700W 80G HBM3 GPU Board N N N N N N N N N N N N
BUBB ThinkSystem NVIDIA H100 SXM5 700W 94G HBM2e GPU Board N N N N N N N N N N N N
NVLink bridge (for PCIe adapters only, not SXM; order 3 per pair of GPUs)
4X67A71309 ThinkSystem NVIDIA Ampere NVLink 2-Slot Bridge N N N N N N N N N N N N

Operating system support

The following table lists the supported operating systems.

Tip: These tables are automatically generated based on data from Lenovo ServerProven.

Table 7. Operating system support for ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU, 4X67A82257
Operating systems
SR650 V3 (4th Gen Xeon)
SR650 V3 (5th Gen Xeon)
SR655 V3
SR665 V3
SR675 V3
SR850 V3
SR860 V3
SR650 V2
SR670 V2
SR665
Microsoft Windows 10 N Y Y Y N N N N N N
Microsoft Windows 11 N Y Y Y N N N N N N
Microsoft Windows Server 2019 Y Y Y Y Y Y 3 Y 3 Y Y Y 4
Microsoft Windows Server 2022 Y Y Y 2 Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 7.9 N N N N N N N Y Y N
Red Hat Enterprise Linux 8.3 N N N N N N N Y Y Y 4
Red Hat Enterprise Linux 8.4 N N N N N N N Y Y Y 4
Red Hat Enterprise Linux 8.5 N N N N N N N Y Y Y 4
Red Hat Enterprise Linux 8.6 Y N Y Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 8.7 Y N Y Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 8.8 Y Y Y Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 8.9 Y Y Y Y N Y Y Y Y Y
Red Hat Enterprise Linux 9.0 Y N Y Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 9.1 Y N Y Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 9.2 Y Y Y Y Y Y Y Y Y Y 4
Red Hat Enterprise Linux 9.3 Y Y Y Y N Y Y Y Y Y
SUSE Linux Enterprise Server 15 SP3 N N N N N N N Y Y Y 4
SUSE Linux Enterprise Server 15 SP4 Y N Y 2 Y Y Y Y Y Y Y 4
SUSE Linux Enterprise Server 15 SP5 Y Y Y Y N Y Y Y Y Y 4
Ubuntu 18.04.5 LTS N N N N N N N Y Y N
Ubuntu 20.04 LTS N N N N N N N Y N N
Ubuntu 20.04.5 LTS N N Y Y Y Y Y N N N
Ubuntu 22.04 LTS Y Y 1 Y 2 Y Y Y Y Y Y Y 4
VMware vSphere Hypervisor (ESXi) 7.0 U3 Y Y Y Y Y Y Y Y Y Y 4
VMware vSphere Hypervisor (ESXi) 8.0 Y N Y 2 Y N N N Y Y Y 4
VMware vSphere Hypervisor (ESXi) 8.0 U1 Y N Y Y Y Y Y Y Y Y 4
VMware vSphere Hypervisor (ESXi) 8.0 U2 Y Y Y Y Y Y Y Y Y Y 4

1 Ubuntu 22.04.3 LTS/Ubuntu 22.04.4 LTS

2 For limitation, please refer Support Tip TT1064

3 For limitation, please refer Support Tip TT1591

4 HW is not supported with EPYC 7002 processors.

NVIDIA GPU software

This section lists the NVIDIA software that is available from Lenovo.

The PCIe adapter H100 GPUs include a five-year software subscription, including enterprise support, to the NVIDIA AI Enterprise software suite:

  • ThinkSystem NVIDIA H100 NVL 94GB PCIe Gen5 Passive GPU, 4X67A89325
  • ThinkSystem NVIDIA H100 80GB PCIe Gen5 Passive GPU, 4X67A82257

This license is equivalent to part number 7S02001HWW listed in the NVIDIA AI Enterprise Software section below.

To activate the NVIDIA AI Enterprise license, see the following page:
https://www.nvidia.com/en-us/data-center/activate-license/

SXM GPUs: The NVIDIA AI Enterprise software suite is not included with the SXM H100 GPUs and will need to ordered separately if needed.

NVIDIA vGPU Software (vApps, vPC, RTX vWS)

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.

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 8. NVIDIA vGPU Software
Part number Feature code
7S02CTO1WW
Description
NVIDIA vApps
7S020003WW B1MP NVIDIA vApps SUMS ONLY 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 SUMS 5Yr ONLY, 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 SUMS ONLY 5Yr, 1 CCU
7S02000GWW B1N2 NVIDIA RTX vWS Subsc Lic 1Yr 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 SUMS ONLY 5Y, 1CCU
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 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 RTX 6000 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 9. NVIDIA Omniverse Software (OVE)
Part number Feature
7S02CTO1WW
NVIDIA part number Description
7S02003ZWW SCX0 721-OV7006+P3CMI12 NVIDIA Omniverse Enterprise Subscription per GPU, 1 Year
7S020042WW SCX3 721-OV7006+P3CMI36 NVIDIA Omniverse Enterprise Subscription per GPU, 3 Years
7S020044WW SD5T 721-OV7006+P3CMI60 NVIDIA Omniverse Enterprise Subscription per GPU, 5 Year
7S020041WW SCX2 721-OV7006+P3INI12 NVIDIA Omniverse Enterprise Subscription per GPU, INC, 1 Year
7S020040WW SCX1 721-OV7006+P3EDI12 NVIDIA Omniverse Enterprise Subscription per GPU, EDU, 1 Year
7S020043WW SCX4 721-OV7006+P3EDI36 NVIDIA Omniverse Enterprise Subscription per GPU, EDU, 3 Years
7S020045WW SD5U 721-OV7006+P3EDI60 NVIDIA Omniverse Enterprise Subscription per GPU EDU, 5 Year

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 10. 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 11. 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 12. 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

Auxiliary power cables

The power cables needed for the H100 SXM GPUs are included with the supported servers.

The H100 PCIe GPU option part number does not ship with auxiliary power cables. Cables are server-specific due to length requirements. For CTO orders, auxiliary power cables are derived by the configurator. For field upgrades, cables will need to be ordered separately as listed in the table below.

Table 13. Auxiliary power cables for H100
Auxiliary power cable needed with the SR650 V3, SR655 V3, SR665 V3, SR665, SR650 V2

SBB7A66338400mm 16-pin (2x6+4) cable
Option:
SR665: 4X97A85028, ThinkSystem 400mm 2x6+4 GPU Power Cable
SR650 V2: 4X97A85028, ThinkSystem 400mm 2x6+4 GPU Power Cable
SR650 V3: 4X67A82883, ThinkSystem SR650 V3 GPU Full Length Thermal Option Kit*
SR655 V3: 4X67A86438, ThinkSystem SR655 V3 GPU Enablement Kit*
SR665 V3: 4X67A85856, ThinkSystem SR665 V3 GPU Full Length Thermal Option Kit*
Feature: BRWK
SBB: SBB7A66338
Base: SC17B33047
FRU: 03KM846

* The option part numbers are for thermal kits and include other components needed to install the GPU. See the SR650 V3 product guide or SR655 V3 product guide or SR665 V3 product guide for details.

Auxiliary power cable needed with the SR675 V3
SBB7A65299235mm 16-pin (2x6+4) cable
Option
: 4X97A84510, ThinkSystem SR675 V3 Supplemental Power Cable for H100 GPU Option
Feature: BSD2
SBB: SBB7A65299
Base: SC17B39301
FRU: 03LE554
Auxiliary power cable needed with the SR850 V3, SR860 V3
SBB7A72759200mm 16-pin (2x6+4) cable
Option: 4X97A88016, ThinkSystem SR850 V3/SR860 V3 H100 GPU Power Cable Option Kit
Feature: BW28
SBB: SBB7A72759
Base: SC17B40604
FRU: 03LF915
Auxiliary power cable needed with the SR670 V2
SBB7A66339215mm 16-pin (2x6+4) cable
Option
: 4X97A85027, ThinkSystem SR670 V2 H100/L40 GPU Option Power Cable
Feature: BRWL
SBB: SBB7A66339
Base: SC17B33046
FRU: 03KM845

Regulatory approvals

The NVIDIA H100 GPU has the following regulatory approvals:

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

Operating environment

The NVIDIA H100 GPU has the following operating characteristics:

  • Ambient temperature
    • Operational: 0°C to 50°C (-5°C to 55°C for short term*)
    • Storage: -40°C to 75°C
  • Relative humidity:
    • Operational: 5-85% (5-93% short term*)
    • Storage: 5-95%

* A period not more than 96 hours consecutive, not to exceed 15 days per year.

Warranty

One year limited warranty. When installed in a Lenovo server, the 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. Partner Technical Webinar - NVIDIA Portfolio
    2024-11-06 | 60 minutes | Employees and Partners
    Details
    Partner Technical Webinar - NVIDIA Portfolio

    in this 60-minute replay, Jason Knudsen of NVIDIA presented the NVIDIA Computing Platform. Jason talked about the full portfolio from GPUs to Networking to AI Enterprise and NIMs.

    Published: 2024-11-06
    Length: 60 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: 110124
  2. NVIDIA Data Center GPU Portfolio
    2024-09-26 | 11 minutes | Employees and Partners
    Details
    NVIDIA Data Center GPU Portfolio

    This course equips Lenovo and partner technical sellers with the knowledge to effectively communicate the positioning of NVIDIA's data center GPU portfolio, enhancing your ability to showcase its key advantages to clients.

    Upon completion of this training, you will be familiar with the following:
    • Data Center GPUs for AI and HPC
    • Data Center GPUs for Graphics
    • GPU comparisons

    Published: 2024-09-26
    Length: 11 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD201
  3. Q2 Solutions Launch TruScale GPU Next Generation Management in the AI Era Quick Hit
    2024-09-10 | 6 minutes | Employees and Partners
    Details
    Q2 Solutions Launch TruScale GPU Next Generation Management in the AI Era Quick Hit

    This Quick Hit focuses on Lenovo announcing additional ways to help you build, scale, and evolve your customer’s private AI faster for improved ROI with TruScale GPU as a Service, AI-driven systems management, and infrastructure transformation services.

    Published: 2024-09-10
    Length: 6 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: SXXW2543a
  4. VTT AI: The NetApp AIPod with Lenovo for NVIDIA OVX
    2024-08-13 | 38 minutes | Employees Only
    Details
    VTT AI: The NetApp AIPod with Lenovo for NVIDIA OVX

    AI, for some organizations, is out of reach, due to cost, integration complexity, and time to deployment. Previously, organizations relied on frequently retraining their LLMs with the latest data, a costly and time-consuming process. The NetApp AIPod with Lenovo for NVIDIA OVX combines NVIDIA-Certified OVX Lenovo ThinkSystem SR675 V3 servers with validated NetApp storage to create a converged infrastructure specifically designed for AI workloads. Using this solution, customers will be able to conduct AI RAG and inferencing operations for use cases like chatbots, knowledge management, and object recognition.

    Topics covered in this VTT session include:
    •  Where Lenovo fits in the solution
    •  NetApp AIPod with Lenovo for NVIDIA OVX Solution Overview
    •  Challenges/pain points that this solution solves for enterprises deploying AI
    •  Solution value/benefits of the combined NetApp, Lenovo, and NVIDIA OVX-Certified Solution

    Published: 2024-08-13
    Length: 38 minutes

    Start the training:
    Employee link: Grow@Lenovo

    Course code: DVAI206
  5. Introduction to Artificial Intelligence
    2024-08-02 | 11 minutes | Employees and Partners
    Details
    Introduction to Artificial Intelligence

    IMPORTANT: If you receive the following error message:
    "There is an issue with this slide content. Please contact your administrator”, please change your VPN location setting and try again. We are actively working on fixing this issue. Thank you for your understanding!


    This NVIDIA course aims to answer questions such as:

    • What is AI?
    • Why are enterprises so interested in it?
    • How does AI happen?
    • Why are GPUs so important for it?
    • What does a good AI solution look like?


    Course Objectives:

    By the end of this training, you should be able to:
    1. Describe AI on a high level and list a few common enterprise use cases
    2. List how enterprises benefit from AI
    3. Distinguish between Training and Inference
    4. Say how GPUs address known bottlenecks in a typical AI pipeline
    5. Tell a customer why NVIDIA’s AI solutions are well-respected in the market

    Published: 2024-08-02
    Length: 11 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD104r2
  6. GPU Fundamentals
    2024-08-02 | 10 minutes | Employees and Partners
    Details
    GPU Fundamentals

    IMPORTANT: If you receive the following error message:
    "There is an issue with this slide content. Please contact your administrator”,
    please change your VPN location setting and try again. We are actively working on fixing this issue. Thank you for your understanding.

    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. We will also talk about the value GPUs bring to modern-day enterprise computing.

    Course Objectives:

    By the end of this training, you should be able to:
    1. Distinguish between serial and parallel processing
    2. Explain what a GPU is and what it does at a high level
    3. Articulate the value of GPU computing for enterprises
    4. List three typical GPU-accelerated workloads and a few uses cases
    5. Recommend the appropriate NVIDIA GPU for its corresponding enterprise computing workloads

    Published: 2024-08-02
    Length: 10 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD103r2
  7. Key NVIDIA Use Cases for Industry Verticals
    2024-08-02 | 32 minutes | Employees and Partners
    Details
    Key NVIDIA Use Cases for Industry Verticals

    IMPORTANT: If you receive the following error message:
    "There is an issue with this slide content. Please contact your administrator”,
    please change your VPN location setting and try again. We are actively working on fixing this issue. Thank you for your understanding.

    In this NVIDIA course, you will learn about key AI use cases driving innovation and change across Automotive, Financial Services, Energy, Healthcare, Higher Education, Manufacturing, Retail and Telco industries.


    Course Objectives:
    By the end of this training, you should be able to:
    1. Discuss common AI use cases across a broad range of industry verticals
    2. Explain how NVIDIA’s AI software stack speeds up time to production for AI projects in multiple industry verticals

    Published: 2024-08-02
    Length: 32 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD108
  8. Generative AI Overview
    2024-08-02 | 17 minutes | Employees and Partners
    Details
    Generative AI Overview

    IMPORTANT: If you receive the following error message:
    "There is an issue with this slide content. Please contact your administrator”, please change your VPN location setting and try again. We are actively working on fixing this issue. Thank you for your understanding!


    Since ChatGPTs debut in November of 2022, it has become clear that Generative AI has the potential to revolutionize many aspects of our personal and professional lives. This NVIDIA course aims to answer questions such as:

    • What are the Generative AI market trends?
    • What is generative AI and how does it work?


    Course Objectives:

    By the end of this training, you should be able to:
    1. Discuss the Generative AI market trends and the challenges in this space with your customers.
    2. Explain what Generative AI is and how the technology works to help enterprises to unlock new opportunities for the business.
    3. Present a high-level overview of the steps involved in building a Generative AI application.

    Published: 2024-08-02
    Length: 17 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD106r2
  9. Retrieval Augmented Generation
    2024-08-02 | 15 minutes | Employees and Partners
    Details
    Retrieval Augmented Generation

    IMPORTANT: If you receive the following error message:
    "There is an issue with this slide content. Please contact your administrator”, please change your VPN location setting and try again. We are actively working on fixing this issue. Thank you for your understanding!


    In this NVIDIA course, Dave Barry, Senior Solutions Architect, talks about a technique known as Retrieval Augmented Generation (RAG). It is a powerful tool for enhancing the accuracy and reliability of Generative AI models with facts fetched from external sources.

    This course requires prior knowledge of Generative AI concepts, such as the difference between model training and inference. Please refer to relevant courses within this curriculum.


    Course Objectives:

    By the end of this training, you should be able to:
    1. Explain the limitations of large language models to customers
    2. Articulate the value of RAG to enterprises
    3. Demo an NVIDIA RAG workflow with a video
    4. Drive TCO conversations using an authentic use case

    Published: 2024-08-02
    Length: 15 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD107
  10. AI Industry Use Cases & Solutions
    2024-08-02 | 25 minutes | Employees and Partners
    Details
    AI Industry Use Cases & Solutions

    IMPORTANT: If you receive the following error message:
    "There is an issue with this slide content. Please contact your administrator”, please change your VPN location setting and try again. We are actively working on fixing this issue. Thank you for your understanding!


    This NVIDIA course aims to answer the question:

    • How does NVIDIA bring AI solutions to market with and through the partner ecosystem?


    Course Objectives:

    By the end of this training, you should be able to:
    1. Think of solutions in terms of an industry and use case approach
    2. Develop solutions that address the industry-specific challenges (with FSI as the illustrative model)
    3. Engage customers with their conversations and advance deals with stakeholder’s concerns in mind
    4. Replicate NVIDIA’s best practices and ecosystem engagement strategies appropriately

    Published: 2024-08-02
    Length: 25 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DAINVD105r2
  11. Partner Technical Webinar - NVIDIA Smart Spaces
    2024-07-24 | 60 minutes | Employees and Partners
    Details
    Partner Technical Webinar - NVIDIA Smart Spaces

    In this 60-minute replay, Alex Pazos, NVIDIA BDM for Smart Spaces, reviewed the NVIDIA AI for Smart Spaces framework and use cases. Alex reviewed the Metropolus Framework and the Smart Spaces ecosystem. Then he reviewed several use cases including sports stadiums, warehouses, airports, and roadways.

    Published: 2024-07-24
    Length: 60 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: 071924
  12. Guidance for Selling NVIDIA Products at Lenovo for ISG
    2024-07-01 | 25 minutes | Employees and Partners
    Details
    Guidance for Selling NVIDIA Products at Lenovo for ISG

    This course gives key talking points about the Lenovo and NVIDIA partnership in the Data Center. Details are included on where to find the products that are included in the partnership and what to do if NVIDIA products are needed that are not included in the partnership. Contact information is included if help is needed in choosing which product is best for your customer. At the end of this session sellers should be able to explain the Lenovo and NVIDIA partnership, describe the products Lenovo can sell through the partnership with NVIDIA, help a customer purchase other NVIDIA product, and get assistance with choosing NVIDIA products to fit customer needs.

    Published: 2024-07-01
    Length: 25 minutes

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: DNVIS102
  13. 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

    Start the training:
    Employee link: Grow@Lenovo

    Course code: DTAIW105
  14. 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

    Start the training:
    Employee link: Grow@Lenovo

    Course code: DVCLD212
  15. 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

    Start the training:
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning

    Course code: 120823

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