Version 470.256.02(Linux)/475.06(Windows)

Release notes for the Release 470 family of NVIDIA® Data Center GPU Drivers for Linux and Windows.

This edition of Release Notes describes the Release 470 family of NVIDIA® Data Center GPU Drivers for Linux and Windows. NVIDIA provides these notes to describe performance improvements, bug fixes and limitations in each documented version of the driver.

1. Version Highlights

This section provides highlights of the NVIDIA Data Center GPU R470 Driver (version 470.256.02 Linux and 475.06 Windows).

For changes related to the 470 release of the NVIDIA display driver, review the file "NVIDIA_Changelog" available in the .run installer packages.

  • Linux driver release date: 06/04/2024
  • Windows driver release date: 06/04/2024

1.1. Software Versions

For this release, the software versions are listed below.

  • CUDA Toolkit 11: 11.4

    Note that starting with CUDA 11, individual components of the toolkit are versioned independently. For a full list of the individual versioned components (for example, nvcc, CUDA libraries and so on), see the CUDA Toolkit Release Notes

  • NVIDIA Data Center GPU Driver: 470.256.02 (Linux) / 475.06 (Windows)

  • Fabric Manager: 470.256.02 (Use nv-fabricmanager -v)

  • NVFlash: 5.791

Due to a revision lock between the VBIOS and driver, VBIOS versions >= 92.00.18.00.00 must use corresponding drivers >= 450.36.01. Older VBIOS versions will work with newer drivers.

For more information on getting started with the NVIDIA Fabric Manager on NVSwitch-based systems (for example, NVIDIA HGX A100), refer to the Fabric Manager User Guide.

1.3. Known Issues

General

  • The GPU driver build system might not pick the Module.symvers file, produced when building the ofa_kernel module from MLNX_OFED, from the right subdirectory. Because of that, nvidia_peermem.ko does not have the right kernel symbol versions for the APIs exported by the IB core driver, and therefore it does not load correctly. That happens when using MLNX_OFED 5.5 or newer on a Linux Arm64 or ppc64le platform.
    To work around this issue, perform the following:
    1. Verify that nvidia_peermem.ko does not load correctly.
    2. Uninstall old MLNX_OFED if one was installed.
    3. Manually remove /usr/src/ofa_kernel/default if one exists.
    4. Install MLNX_OFED 5.5 or newer.
    5. Manually create a soft link:
       /usr/src/ofa_kernel/default -> /usr/src/ofa_kernel/$(uname -m)/$(uname -r)
    6. Reinstall the GPU driver.
  • On HGX A800 8-GPU systems, the nvswitch-audit tool will report 12 NVLinks per GPU. This is a switch configuration report and does not reflect the true number of NVLink interfaces available per-GPU, which remains 8.
  • Combining A800 and A100 SXM modules in a single server is not currently supported with this driver version.
  • Combining A800 and A100 PCIe with NVLink is not fully tested.
  • By default, Fabric Manager runs as a systemd service. If using DAEMONIZE=0 in the Fabric Manager configuration file, then the following steps may be required.
    1. Disable FM service from auto starting. (systemctl disable nvidia-fabricmanager)

    2. Once the system is booted, manually start FM process. (/usr/bin/nv-fabricmanager -c /usr/share/nvidia/nvswitch/fabricmanager.cfg). Note, since the process is not a daemon, the SSH/Shell prompt will not be returned (use another SSH shell for other activities or run FM as a background task).

  • When installing a driver on SLES15 or openSUSE15 that previously had an R515 driver installed, users need to run the following command afterwards to finalize the installation:

    sudo zypper install --force nvidia-gfxG05-kmp-default 

    Without doing this, users may see the kernel objects as missing.

  • If you encounter an error on RHEL7 when installing with cuda-drivers-fabricmanager packages, use the following alternate instructions. For example:

    If you are upgrading from a different branch, for example to driver 470.141.03:

    new_version=470.141.03
    sudo yum swap nvidia-driver-latest-dkms nvidia-driver-latest-dkms-${new_version}
    sudo yum install nvidia-fabric-manager-${new_version}

GPU Performance Counters

The use of developer tools from NVIDIA that access various performance counters requires administrator privileges. See this note for more details. For example, reading NVLink utilization metrics from nvidia-smi (nvidia-smi nvlink -g 0) would require administrator privileges.

NoScanout Mode

NoScanout mode is no longer supported on NVIDIA Data Center GPU products. If NoScanout mode was previously used, then the following line in the “screen” section of /etc/X11/xorg.conf should be removed to ensure that X server starts on data center products:

Option         "UseDisplayDevice" "None"

NVIDIA Data Center GPU products now support one display of up to 4K resolution.

Unified Memory Support

CUDA and unified memory is not supported when used with Linux power management states S3/S4.

IMPU FRU for Volta GPUs

The driver does not support the IPMI FRU multi-record information structure for NVLink. See the Design Guide for Tesla P100 and Tesla V100-SXM2 for more information.

OpenCL 3.0 Known Issues

2. Virtualization

To make use of GPU passthrough with virtual machines running Windows and Linux, the hardware platform must support the following features:

  • A CPU with hardware-assisted instruction set virtualization: Intel VT-x or AMD-V.

  • Platform support for I/O DMA remapping.

  • On Intel platforms the DMA remapper technology is called Intel VT-d.

  • On AMD platforms it is called AMD IOMMU.

Support for these features varies by processor family, product, and system, and should be verified at the manufacturer's website.

The following hypervisors are supported for virtualization:

Hypervisor Notes
Citrix XenServer Version 6.0 and later
VMware vSphere (ESX / ESXi) Version 5.1 and later.
Red Hat KVM Red Hat Enterprise Linux 7 with KVM
Microsoft Hyper-V

Windows Server 2016 Hyper-V Generation 2

Tesla products now support one display of up to 4K resolution.

The following GPUs are supported for device passthrough for virtualization:

GPU Family Boards Supported
NVIDIA Ampere GPU Architecture NVIDIA A100, A800, A40, A30, A16, A10
Turing NVIDIA T4
Volta NVIDIA V100
Pascal

Quadro: P2000, P4000, P5000, P6000, GP100

Tesla: P100, P40, P4

Maxwell

Quadro: K2200, M2000, M4000, M5000, M6000, M6000 24GB

Tesla: M60, M40, M6, M4

Kepler

Quadro: K2000, K4000, K4200, K5000, K5200, K6000

Tesla: K520, K80

Tesla: K10, K20, K20x, K20Xm, K20c, K20s, K40m, K40c, K40s, K40st, K40t, K80, K520

3. Hardware and Software Support

Support for these features varies by processor family, product, and system, and should be verified at the manufacturer's website.

Supported Operating Systems for NVIDIA Data Center GPUs

The Release 470 driver is supported on the following operating systems:

  • Windows x86_64 operating systems:

    • Microsoft Windows® Server 2022

    • Microsoft Windows® Server 2019

    • Microsoft Windows® Server 2016

    • Microsoft Windows® 11

    • Microsoft Windows® 10
  • The following table summarizes the supported Linux 64-bit distributions. For a complete list of distributions, kernel versions supported, see the CUDA Linux System Requirements documentation.

    Distribution x86_64 Arm64 Server
    OpenSUSE Leap 15.x (where y <=5) Yes No
    Red Hat Enterprise Linux 8.y (where y <= 9) Yes Yes
    Rocky Linux 8.y (where y <= 9) Yes No
    Red Hat Enterprise Linux / CentOS 7.y (where y <= 9) Yes No
    SUSE Linux Enterprise Server 15.y (where y <= 5) Yes Yes
    Ubuntu 20.04.z LTS (where z <= 6) Yes Yes
    Ubuntu 18.04.z LTS (where z <= 6) Yes No

Supported Operating Systems and CPU Configurations for NVIDIA HGX A100 and HGX A800

The Release 470 driver is validated with NVIDIA HGX A100 and HGX A800 on the following operating systems and CPU configurations:

  • Linux 64-bit distributions:

    • Red Hat Enterprise Linux 8.9 (in 4/8/16-GPU configurations)

    • Red Hat Enterprise Linux 7.9 (in 4/8/16-GPU configurations)

    • Rocky Linux 8.9 (in 4/8/16-GPU configurations)

    • CentOS Linux 7.9 (in 4/8/16-GPU configurations)

    • Ubuntu 18.04.6 LTS (in 4/8/16-GPU configurations)

    • Ubuntu 20.04.6 LTS (in 4/8/16-GPU configurations)
    • SUSE SLES 15.5 (in 4/8/16-GPU configurations)

  • Windows 64-bit distributions:
    • Windows Server 2019 (in 1/2/4/8-GPU configurations; 16-GPU configurations are currently not supported)

      Windows is supported only in shared NVSwitch virtualization configurations.

  • CPU Configurations:

    • AMD Rome in PCIe Gen4 mode

    • Intel Skylake/Cascade Lake (4-socket) in PCIe Gen3 mode

Supported Virtualization Configurations

The Release 470 driver is validated with NVIDIA HGX A100 and HGX A800 on the following configurations:

  • Passthrough (full visibility of GPUs and NVSwitches to guest VMs):

    • 8-GPU configurations with Ubuntu 18.04.4 LTS

  • Shared NVSwitch (guest VMs only have visibility of GPUs and full NVLink bandwidth between GPUs in the same guest VM):

    • 16-GPU configurations with Ubuntu 18.04.4 LTS

    • 1/2/4/8-GPU configurations with Windows x86_64 operating systems:

      • Microsoft Windows® Server 2019

      • Microsoft Windows® 10

API Support

This release supports the following APIs:

  • NVIDIA® CUDA® 11.4 for NVIDIA® KeplerTM, MaxwellTM, PascalTM, VoltaTM, TuringTM, and NVIDIA Ampere architecture GPUs

  • OpenGL® 4.6

  • Vulkan® 1.2

  • DirectX 11

  • DirectX 12 (Windows 10)

  • Open Computing Language (OpenCLTM software) 3.0

Note that for using graphics APIs on Windows (such as OpenGL, Vulkan, DirectX 11, and DirectX 12) or any WDDM 2.0+ based functionality on Data Center GPUs, vGPU is required. See the vGPU documentation for more information.

Supported NVIDIA Data Center GPUs

The NVIDIA Data Center GPU driver package is designed for systems that have one or more Data Center GPU products installed. This release of the driver supports CUDA C/C++ applications and libraries that rely on the CUDA C Runtime and/or CUDA Driver API.

Attention: Release 470 will be the last driver branch to support Data Center GPUs based on the NVIDIA Kepler architecture. This includes discontinued support for the following compute capabilities:
  • sm_30 (NVIDIA Kepler)
  • sm_32 (NVIDIA Kepler)
  • sm_35 (NVIDIA Kepler)
  • sm_37 (NVIDIA Kepler)

For more information on GPU products and compute capability, see https://developer.nvidia.com/cuda-gpus.

NVIDIA Server Platforms
Product Architecture
NVIDIA HGX A800 A800 and NVSwitch
NVIDIA HGX A100 A100 and NVSwitch
NVIDIA HGX-2 V100 and NVSwitch
RTX-Series / T-Series Products
Product GPU Architecture
NVIDIA RTX A6000 NVIDIA Ampere architecture
NVIDIA RTX A5000 NVIDIA Ampere architecture
NVIDIA RTX A4000 NVIDIA Ampere architecture
Quadro RTX 8000 NVIDIA Turing
Quadro RTX 6000 NVIDIA Turing
NVIDIA T1000 NVIDIA Turing
NVIDIA T600 NVIDIA Turing
NVIDIA T400 NVIDIA Turing
Data Center A-Series Products
Product GPU Architecture
NVIDIA A800 NVIDIA Ampere architecture
NVIDIA A100

NVIDIA A100 80 GB PCIe

NVIDIA Ampere architecture
NVIDIA A40 NVIDIA Ampere architecture
NVIDIA A30 NVIDIA Ampere architecture
NVIDA A16 NVIDIA Ampere architecture
NVIDIA A10 NVIDIA Ampere architecture
Data Center T-Series Products
Product GPU Architecture
NVIDIA T4 NVIDIA Turing
Data Center V-Series Products
Product GPU Architecture
NVIDIA V100 Volta
Data Center P-Series Products
Product GPU Architecture
NVIDIA Tesla P100 NVIDIA Pascal
NVIDIA Tesla P40 NVIDIA Pascal
NVIDIA Tesla P4 NVIDIA Pascal
Data Center K-Series Products
Product GPU Architecture
NVIDIA Tesla K520 NVIDIA Kepler
NVIDIA Tesla K80 NVIDIA Kepler
Data Center M-Class Products
Product GPU Architecture
NVIDIA Tesla M60 Maxwell
NVIDIA Tesla M40 24 GB Maxwell
NVIDIA Tesla M40 Maxwell
NVIDIA Tesla M6 Maxwell
NVIDIA Tesla M4 Maxwell

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