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ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU

Product Guide

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15 Sep 2024
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LP1718
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23 pages, 532 KB

Abstract

The ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU delivers unprecedented visual computing performance for the data center and provides revolutionary neural graphics, compute, and AI capabilities to accelerate the most demanding visual computing workloads.

This product guide provides essential presales information to understand the NVIDIA L40 GPU and its 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 NVIDIA L40 GPU and consider its use in IT solutions.

Change History

Changes in the September 15, 2023 update:

Introduction

The ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU delivers unprecedented visual computing performance for the data center and provides revolutionary neural graphics, compute, and AI capabilities to accelerate the most demanding visual computing workloads. With up to twice the performance of the previous generation at the same power, the NVIDIA L40 is uniquely suited to provide the visual computing power and performance required by the modern data center.

The following figure shows the ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU.

ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU
Figure 1. ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU

Did you know?

The NVIDIA L40, based on the NVIDIA Ada Lovelace GPU architecture features new generation RT cores and Tensor cores, delivering in combination over a petaflop of inferencing performance. These new features are combined with the latest generation CUDA Cores and 48GB of graphics memory to accelerate visual computing workloads from high-performance virtual workstation instances to large-scale digital twins in NVIDIA Omniverse.

Part number information

The following table shows the part numbers for the GPU.

Table 1. Ordering information
Part number Feature code Description Controlled GPU status
4X67A84823 BT87 ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU Controlled

The NVIDIA L40 GPU is Controlled which means the GPU is not offered in certain markets, as determined by the US Government.

The option part number includes the following:

  • One NVIDIA L40 GPU with full-height (3U) adapter bracket attached
  • Documentation

Features

From virtual workstation application to large-scale modeling and simulation, modern visual computing and scientific workflows are growing in both complexity and quantity.

Enterprises need data center technology that can deliver extreme performance and scale with versatile capabilities to conquer the diverse computing demands of these increasingly complex workloads.

The NVIDIA® L40 GPU delivers unprecedented visual computing performance for the data center, providing next- generation graphics, compute, and AI capabilities. Built on the revolutionary NVIDIA Ada Lovelace architecture, the NVIDIA L40 harnesses the power of the latest generation RT, Tensor, and CUDA cores to deliver groundbreaking visualization and compute performance for the most demanding data center workloads.

Next-Generation Graphics and Compute Performance

  • 142 third-generation RT Cores and industry-leading 48 GB of GDDR6 memory: The NVIDIA L40 delivers up to twice the real-time ray-tracing performance of the previous Ampere generation to enable high-performance ray tracing of complex geometry and the creation of beautifully detailed, photorealistic models and scenes. Accelerate high-fidelity creative workflows, including real-time, full-fidelity, interactive rendering, 3D design, video streaming, and virtual
  • Faster rendering and smoother frame rates with NVIDIA Deep Learning Super Sampling 3 (DLSS 3): This breakthrough frame generation technology leverages deep learning and the latest hardware innovations within the Ada Lovelace Architecture and L40 GPU, including 4th-Generation Tensor Cores and a new Optical Flow Accelerator, to boost rendering performance, deliver higher FPS, and significantly improve
  • The NVIDIA L40 includes 18,176 Ada Lovelace GPU architecture CUDA cores delivering over 2X the single-precision floating-point (FP32) performance to accelerate 3D graphics, simulation and physics
  • Breakthrough media acceleration capabilities: The NVIDIA L40 takes streaming and video content workloads to the next level with three video encode and three video decode engines. With the addition of AV1 encoding, the L40 delivers up to twice the performance and improved TCO for broadcast streaming, video production, and transcription
  • Incredible training and inference capabilities with 90.5 TFLOPs of FP32 performance. The NVIDIA L40 includes 568 fourth-generation Tensor Cores providing up to 2X faster AI training performance than the previous generation with FP16 precision. Support for the new FP8 data format for inferencing provides more than 4X faster performance than the previous generation and reduces data memory usage by half (compared to FP16 data format)

 Data Center-Ready

  • The NVIDIA L40 is optimized for 24x7 enterprise data center operations and is designed, built, extensively tested, and supported exclusively by NVIDIA to ensure maximum
  • Secure boot with root of trust (RoT) technology within the GPU provide an additional layer of security for data centers. The NVIDIA L40 meets the latest data center standards and is NEBS Level 3
  • Passively cooled, full-height, full-length (FHFL), dual-slot design
  • The NVIDIA L40 is capable of 300W maximum board power and driven by power-efficient hardware and components selected for optimum performance, durability, and

Technical specifications

The NVIDIA L40 GPU has the following specifications:

  • Form factor
    • PCIe Full Height Full Length adapter (4.4-in x 10.5-in), Double-width (dual slot)
    • NVIDIA Form Factor 5.5
  • Host interface:
    • PCIe 4.0 x16
    • MSI-X interrupt messaging protocol (MSI not supported)
    • PCIe Lane Polarity Inversion and Lane Reversal
  • Single Root I/O Virtualization (SR-IOV) support
    • 256 virtual functions (VFs)
    • ARI Forwarding
  • Hardware Root of Trust
    • Secure boot
    • Secure firmware upgrade
    • Firmware rollback protection
    • Support for in-band firmware update disable (established after each GPU reset)
    • Secure application processor recovery

The following table lists the GPU processing specifications and performance of the NVIDIA L40.

Table 2. Specifications of the ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU
Feature Specification
GPU Architecture NVIDIA Ada Lovelace
NVIDIA CUDA Parallel Processing Cores 18,176
NVIDIA Tensor Cores (4th gen) 568
NVIDIA RT Cores (3rd Gen) 142
Peak FP32 performance (non-Tensor) 90.5 TFLOPS
Peak FP16 Tensor performance with FP16 Accumulate 181.05 TFLOPS, 362.1 TFLOPS*
Peak Tensor Float 32 (TF32) performance 90.5 TFLOPS, 181 TFLOPS*
Peak Bfloat16 (BF16) performance with FP32 Accumulate 181.05 TFLOPS, 362.1 TFLOPS*
Peak FP8 Tensor performance 362 TFLOPS, 724 TFLOPS*
Peak Integer Performance INT8: 362 TOPS, 724 TOPS*
INT4: 724 TOPS, 1448 TOPS*
RT Core performance 209 TFLOPS
GPU Memory 48 GB GDDR6
Memory Bandwidth 864 GB/s
ECC Yes
NVIDIA NVLink No support
System Interface PCIe Gen 4, x16 lanes
Form Factor PCIe full height/length, double width (10.5" x 4.4")
Multi-Instance GPU (MIG) No support
Max Power Consumption 300 W
Thermal Solution Passive
vGPU Software Support NVIDIA vPC/vApps, NVIDIA RTX Virtual Workstation (vWS)
Display connectors 4x DisplayPort 1.4a (disabled by default**)
Max Simultaneous Displays Up to four 5K Monitors at 60Hz per card or dual 8K displays @ 60Hz (requires DisplayPort 1.4 DSC); Each display port can support 4K at 120 Hz with 30-bit color
Graphics APIs DirectX 12 Ultimate, Shader Model 6.6, OpenGL 4.6, Vulkan 1.3
Compute APIs CUDA 12.0, Direct Compute, OpenCL 3.0

* With structural sparsity enabled
** To enable the DisplayPort ports, see https://developer.nvidia.com/displaymodeselector

Server support

The following tables list the ThinkSystem servers that are compatible.

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)
4X67A84823 ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU N 3 N 3 N N 3 N 2 4 N N N N N 8 8 N N N
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)
4X67A84823 ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU N N N N N N 2 2 N N N N N N N N N N N 3
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)
4X67A84823 ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU N N N N 3 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)
4X67A84823 ThinkSystem NVIDIA L40 48GB PCIe Gen4 Passive GPU 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 L40 48GB PCIe Gen4 Passive GPU, 4X67A84823
Operating systems
SE450
SE455 V3
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 N N Y Y Y N N N N N N
Microsoft Windows 11 N N N Y Y Y N N N N N N
Microsoft Windows Server 2016 N N N N N N N N N Y Y Y
Microsoft Windows Server 2019 Y Y Y Y Y Y Y Y 2 Y 2 Y Y Y
Microsoft Windows Server 2022 Y Y Y Y Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 7.9 Y N N N N N N N N Y Y Y 3
Red Hat Enterprise Linux 8.3 N N N N N N N N N Y Y Y
Red Hat Enterprise Linux 8.4 Y N N N N N N N N Y Y Y
Red Hat Enterprise Linux 8.5 Y N N N N N N N N Y Y Y
Red Hat Enterprise Linux 8.6 Y Y Y N Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 8.7 Y N Y N Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 8.8 Y Y Y Y Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 8.9 N Y Y Y Y Y N Y Y Y Y Y
Red Hat Enterprise Linux 9.0 Y Y Y N Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 9.1 Y N Y N Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 9.2 Y Y Y Y Y Y Y Y Y Y Y Y
Red Hat Enterprise Linux 9.3 Y Y Y Y Y Y N Y Y Y Y Y
SUSE Linux Enterprise Server 15 SP3 N N N N N N N N N Y Y Y
SUSE Linux Enterprise Server 15 SP4 Y Y Y N Y Y Y Y Y Y Y Y
SUSE Linux Enterprise Server 15 SP5 Y Y Y Y Y Y N Y Y Y Y Y
Ubuntu 18.04.5 LTS N N N N N N N N N Y Y N
Ubuntu 18.04.6 LTS Y N N N N N N N N N N N
Ubuntu 20.04 LTS N N N N N N N N N Y N N
Ubuntu 20.04.5 LTS Y Y N N Y Y Y Y Y N N N
Ubuntu 22.04 LTS Y N Y Y 1 Y Y Y Y Y Y Y Y
Ubuntu 22.04.2 LTS N Y N N N N N N N N N N
VMware vSphere Hypervisor (ESXi) 6.7 U3 N N N N N N N N N Y Y Y
VMware vSphere Hypervisor (ESXi) 7.0 U3 Y Y Y Y Y Y Y Y Y Y Y Y
VMware vSphere Hypervisor (ESXi) 8.0 Y N Y N Y Y N N N Y Y Y
VMware vSphere Hypervisor (ESXi) 8.0 U1 Y Y Y N Y Y Y Y Y Y Y Y
VMware vSphere Hypervisor (ESXi) 8.0 U2 Y Y Y Y Y Y Y Y Y Y Y Y

1 Ubuntu 22.04.3 LTS/Ubuntu 22.04.4 LTS

2 For limitation, please refer Support Tip TT1591

3 The OS is not supported with EPYC 7003 processors.

NVIDIA GPU software

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
Description
7S02003ZWW SCX0 NVIDIA Omniverse Enterprise Subscription per GPU, 1 Year
7S020042WW SCX3 NVIDIA Omniverse Enterprise Subscription per GPU, 3 Years
7S020044WW SD5T NVIDIA Omniverse Enterprise Subscription per GPU, 5 Year
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
7S020045WW SD5U 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 L40 option part number does not ship with auxiliary power cables. Cables are server-specific due to length requirements and the connector on the server end of the cable. 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.

Tip: The names of the cable options below may only include the H100 GPU, however these cables are also supported with the L40.

Table 13. Auxiliary power cables for NVIDIA L40
Auxiliary power cable needed with the SE455 V3 and SE450

GPU cable SBB7A74096 SC17B36330450mm 16-pin (2x6+4) cable
Option:

  • SE455 V3: 4X97A89288, ThinkEdge NVIDIA L40 GPU Power Cable Kit (contains 2 cables)
  • SE450: 4X97A89288, ThinkEdge NVIDIA L40 GPU Power Cable Kit (contains 2 cables)

Feature: BVVG
SBB: SBB7A74096
Base: SC17B36330
FRU: 03LE760

Additional components may be required when installing the GPU. See the SE455 V3 product guide for details.

Auxiliary power cable needed with the SR665, SR650 V2, SR650 V3, SR655 V3, SR665 V3

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 number is for the thermal kit and includes other components needed to install the GPU. See the respective server product guide 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 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
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

Regulatory approvals

The NVIDIA L40 GPU has the following regulatory approvals:

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

Operating environment

The NVIDIA L40 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. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD201
  2. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: SXXW2543a
  3. 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
    Employee link: Grow@Lenovo
    Course code: DVAI206
  4. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD104r2
  5. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD103r2
  6. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD108
  7. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD106r2
  8. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD107
  9. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DAINVD105r2
  10. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: 071924
  11. 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
    Employee link: Grow@Lenovo
    Partner link: Lenovo Partner Learning
    Course code: DNVIS102
  12. 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
  13. 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
  14. 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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