Version 510.108.03(Linux)/513.91(Windows)

Release notes for the Release 510 family of NVIDIA® Data Center GPU Drivers for Linux and Windows.

This edition of Release Notes describes the Release 510 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 R510 Driver (version 510.108.03 Linux and 513.91 Windows).

For changes related to the 510 release of the NVIDIA display driver, review the file "NVIDIA_Changelog" available in the .run installer packages.

  • Linux driver release date: 11/22/2022
  • Windows driver release date: 11/22/2022

1.1. Software Versions

For this release, the software versions are listed below.

  • CUDA Toolkit 11: 11.6

    Note that starting with CUDA 11, individual components of the toolkit are versioned independently. For a full list of the individual versioned components (e.g. nvcc, CUDA libraries etc.), see the CUDA Toolkit Release Notes

  • NVIDIA Data Center GPU Driver: 510.108.03 (Linux) / 513.91 (Windows)

  • Fabric Manager: 510.108.02 (Use nv-fabricmanager -v)

  • GPU VBIOS:

    • 92.00.19.00.01 (NVIDIA A100 SKU200 with heatsink for HGX A100 8-way and 4-way)

    • 92.00.19.00.02 (NVIDIA A100 SKU202 w/o heatsink for HGX A100 4-way)

  • NVSwitch VBIOS: 92.10.14.00.01

  • NVFlash: 5.641

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, HGX A100), refer to the Fabric Manager User Guide.

1.2. Fixed Issues

  • CLVC - Closed Loop Voltage Controller - is a controller that periodically monitors and corrects for voltage errors. Any error (+/-) is corrected by applying a appropriate voltage offset to the VOLT/regulator. Features like droopy, thermal slowdown can cause voltage set in HW to deviate from the SW requested value In such usecases, CLVC should NOT correct for it as its not an "error" but sideeffect of droopy/slowdown. Evaluation loop of CLVC queries and calculates how long the feature like droopy/slowdown were engaged in order to check if such an event was active after the previous cycle. If droopy/slowdown was engaged we poison the sample instead of correcting the for error.

    CLFC - Closed Loop Frequency Controller - is equivalent to CLVC, however CLFC corrects for frequency errors not voltage errors. CLFC is enabled on TU10x onwards (except ampere). CLVC is enabled on GA100 onwards.

    In the earlier CLFC bug, the counter that queries THERM task for residency/engaged count time was using 32-bit counter which overflows a lot quicker than 64-bit counters. As part of the fix, engaged timers were updated to use 64-bit counter with special attention to prevent overflows.

    In the CLVC bug, whenever the engagedtime differed more than the evaluation time threshold, PMU was halted assuming it was an error condition. Instead of halting the PMU, we discard the sample by poisoning it.

    Both the bugs are in two related but separate features that use droopy/slowdown. CLFC bug updated the infra used to compute the engaged/elapsed timers from 32-bit to 64-bit. CLVC bug updated how the error case is handled in certain usecases.

  • In the L1C submodule when the clock is gated, there is a corner case where the BLCG controller was not woken up from sleep state when an external submodule wants to use L1C. This was fixed by Switching the PROD value to disable L1C BLCG will not cause the hang in the chip until some other event wakes up the BLCG FSM.
  • An issue which caused a kernel panic on A100 when using both MIG and DCGM is resolved.
  • The Access Write Protect Mode (opcode 17h) SMBPBI command resulted in an fatal access violation by reading a GPU register that is protected on certain GV100 configurations. The error is fatal for the SMBPBI server and results in a driver crash. The fix adds logic to the SMBPBI server to detect if the offending GPU register is privileged and disables opcode 17h on these configurations.
  • Resolved an issue that caused the MPS server to hang when running applications compiled under different version of gcc.

1.3. Known Issues

General

  • "Change ECC State" and "Enable Error Correction Code" do not change synchronously when ECC state changes.
  • 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.
  • nvidia-release-upgrade may report that not all updates have been installed and exit.

    When running the nvidia-release-upgrade command on DGX systems running DGX OS 4.99.x, it may exit and tell users: "Please install all available updates for your release before upgrading" even though all upgrades have been installed.

    Users who see this can run the following command:
    sudo apt install -y nvidia-fabricmanager-450/bionic-updates --allow-downgrades
    After running this, proceed with the regular upgrade steps:
    sudo apt update
    sudo apt full-upgrade -y 
    sudo apt install -y nvidia-release-upgrade 
    sudo nvidia-release-upgrade
  • 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 510.85.02:

    new_version=510.85.02
    sudo yum swap nvidia-driver-latest-dkms nvidia-driver-latest-dkms-${new_version}
    sudo yum install nvidia-fabric-manager-${new_version}
  • 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).

  • On NVSwitch systems with Windows Server 2019 in shared NVSwitch virtualization mode, the host may hang or crash when a GPU is disabled in the guest VM. This issue is under investigation.

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

Some Unified Memory APIs (for example, CPU page faults) are not supported on Windows in this version of the driver. Review the CUDA Programming Guide on the system requirements for Unified Memory

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

Device side enqueue

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.

Supported Hypervisors

The following hypervisors are supported:

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

Windows Server 2012 R2 Hyper-V

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

Supported Graphics Cards

The following GPUs are supported for device passthrough:

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

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 510 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 table below 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 POWER Arm64 Server
    OpenSUSE Leap 15.x (where y <= 4) Yes No No
    Red Hat Enterprise Linux 8.y (where y <= 6) Yes Yes Yes
    Rocky Linux 8.y (where y <= 6) Yes No No
    Red Hat Enterprise Linux / CentOS 7.y (where y <= 9) Yes No No
    SUSE Linux Enterprise Server 15.y (where y <= 4) Yes No Yes
    Ubuntu 20.04.z LTS (where z <= 5) Yes No Yes
    Ubuntu 18.04.z LTS (where z <= 6) Yes No No

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

The Release 510 driver is validated with HGX A100 and HGX A800 on the following operating systems and CPU configurations:

  • Linux 64-bit distributions:

    • Red Hat Enterprise Linux 8.6 (in 4/8/16-GPU configurations)

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

    • Rocky Linux 8.6 (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)

    • SUSE SLES 15.4 (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 510 driver is validated with HGX A100 and HGX A800 on the following configurations:

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

    • 8-GPU configurations with Ubuntu 18.04.6 LTS

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

    • 1/2/4/8/16-GPU configurations with Ubuntu 18.04.5 LTS
    • 1/2/4/8-GPU configurations with Windows Server 2019

API Support

This release supports the following APIs:

  • NVIDIA® CUDA® 11.6 for NVIDIA® MaxwellTM, PascalTM, VoltaTM, TuringTM and NVIDIA Ampere architecture GPUs

  • OpenGL® 4.6

  • Vulkan® 1.3

  • DirectX 11

  • DirectX 12 (Windows 10)

  • Open Computing Language (OpenCLTM software) 3.0

Note that for using graphics APIs on Windows (i.e. 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 was the last driver branch to support Data Center GPUs based on the Kepler architecture. This includes discontinued support for the following compute capabilities:
  • sm_30 (Kepler)
  • sm_32 (Kepler)
  • sm_35 (Kepler)
  • sm_37 (Kepler)
For more information on GPU products and compute capability, see https://developer.nvidia.com/cuda-gpus.
NVIDIA Server Platforms
Product Architecture
NVIDIA HGX A100 A100 and NVSwitch
NVIDIA HGX A800 A800 and NVSwitch
NVIDIA HGX-2 V100 and NVSwitch
RTX-Series / T-Series Products
Product GPU Architecture
NVIDIA RTX A6000 NVIDIA Ampere
NVIDIA RTX A5000 NVIDIA Ampere
NVIDIA RTX A4000 NVIDIA Ampere
Quadro RTX 8000 Turing
Quadro RTX 6000 Turing
NVIDIA T1000 Turing
NVIDIA T600 Turing
NVIDIA T400 Turing
Data Center A-Series Products
Product GPU Architecture
NVIDIA A800 NVIDIA Ampere
NVIDIA A100X NVIDIA Ampere
NVIDIA A100

NVIDIA A100 80 GB PCIe

NVIDIA Ampere
NVIDIA A40 NVIDIA Ampere
NVIDIA A30, A30X NVIDIA Ampere
NVIDIA A16 NVIDIA Ampere
NVIDIA A10, A10M NVIDIA Ampere
Data Center T-Series Products
Product GPU Architecture
NVIDIA T4 Turing
Data Center V-Series Products
Product GPU Architecture
NVIDIA V100 Volta
Data Center P-Series Products
Product GPU Architecture
NVIDIA Tesla P100 Pascal
NVIDIA Tesla P40 Pascal
NVIDIA Tesla P4 Pascal
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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