Nvidia

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Encountering shm_open permission denied issues with hpcx

If you are using Nvidia hpc-x and encountering issues like the one below during your MPI Run

shm_open(file_name=/ucx_shm_posix_77de2cf3 flags=0xc2) failed: Permission denied

The error message indicates that the shared memory has no permission to be used,  The permission of /dev/shm is found to be 755, not 777, causing the error. The issue can be resolved after the permission is changed to 777. To change and verify the changes:

% chmod 777 /dev/shm 
% ls -ld /dev/shm
drwxrwxrwx 2 root root 40 Jul  6 15:18 /dev/sh

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Cannot install the best candidate for the job for CUDA Drivers and Rocky Linux 8.5

I follow the blog Installing Nvidia Drivers on Rocky Linux 8.5. But I encountered an error that I have not encountered before

Error:
 Problem 1: package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64
 Problem 2: package cuda-drivers-515.48.07-1.x86_64 requires nvidia-kmod >= 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64
 Problem 3: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64
 Problem 4: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-modprobe-3:515.48.07-1.el8.x86_64 requires nvidia-driver(x86-64) = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64
 Problem 5: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-settings-3:515.48.07-1.el8.x86_64 requires nvidia-driver(x86-64) = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64
 Problem 6: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-xconfig-3:515.48.07-1.el8.x86_64 requires nvidia-driver(x86-64) = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - nothing provides dkms needed by kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64

The hint is that dkms is required.

nothing provides dkms needed by kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64

Enable EPEL Repository

# dnf install https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm
 # dnf config-manager --enable epel

Install dkms

 # dnf install dkms*

Install the latest Nvidia Drivers (If possible).

# dnf module install nvidia-driver:latest

If the Error pop out like this 

Last metadata expiration check: 0:01:01 ago on Mon 06 Jun 2022 08:47:40 PM EDT.
Error:
 Problem 1: package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
 Problem 2: package cuda-drivers-515.48.07-1.x86_64 requires nvidia-kmod >= 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
 Problem 3: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
 Problem 4: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-modprobe-3:515.48.07-1.el8.x86_64 requires nvidia-driver(x86-64) = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
 Problem 5: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-settings-3:515.48.07-1.el8.x86_64 requires nvidia-driver(x86-64) = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
 Problem 6: package nvidia-driver-3:515.48.07-1.el8.x86_64 requires nvidia-kmod-common = 3:515.48.07, but none of the providers can be installed
  - package nvidia-xconfig-3:515.48.07-1.el8.x86_64 requires nvidia-driver(x86-64) = 3:515.48.07, but none of the providers can be installed
  - package nvidia-kmod-common-3:515.48.07-1.el8.noarch requires nvidia-kmod = 3:515.48.07, but none of the providers can be installed
  - cannot install the best candidate for the job
  - package kmod-nvidia-latest-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering
  - package kmod-nvidia-open-dkms-3:515.48.07-1.el8.x86_64 is filtered out by modular filtering

You will notice that the dkms issues has been resolved. Try not using the nvidia-driver:latest

# dnf module install nvidia-driver
===================================================================================================================================================
 Package                                Architecture        Version                                           Repository                      Size
===================================================================================================================================================
Upgrading:
 bcc                                    x86_64              0.19.0-5.el8                                      appstream                      674 k
 bcc-tools                              x86_64              0.19.0-5.el8                                      appstream                      447 k
 bpftrace                               x86_64              0.12.1-4.el8                                      appstream                      1.3 M
 clang-libs                             x86_64              13.0.1-1.module+el8.6.0+825+7e27476a              appstream                       23 M
 clang-resource-filesystem              x86_64              13.0.1-1.module+el8.6.0+825+7e27476a              appstream                       13 k
 compiler-rt                            x86_64              13.0.1-1.module+el8.6.0+825+7e27476a              appstream                      4.2 M
 libglvnd                               x86_64              1:1.3.4-1.el8                                     appstream                      126 k
 libglvnd-egl                           x86_64              1:1.3.4-1.el8                                     appstream                       48 k
 libglvnd-gles                          x86_64              1:1.3.4-1.el8                                     appstream                       39 k
 libglvnd-glx                           x86_64              1:1.3.4-1.el8                                     appstream                      136 k
 libomp-devel                           x86_64              13.0.1-1.module+el8.6.0+825+7e27476a              appstream                       28 k
 llvm-libs                              x86_64              13.0.1-1.module+el8.6.0+825+7e27476a              appstream                       24 M
 mesa-dri-drivers                       x86_64              21.3.4-1.el8                                      appstream                       11 M
 mesa-filesystem                        x86_64              21.3.4-1.el8                                      appstream                       33 k
 mesa-libxatracker                      x86_64              21.3.4-1.el8                                      appstream                      2.0 M
 python3-bcc                            x86_64              0.19.0-5.el8                                      appstream                       89 k
Installing group/module packages:
 cuda-drivers                           x86_64              515.48.07-1                                       cuda-rhel8-x86_64              8.1 k
 kmod-nvidia-latest-dkms                x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               30 M
 nvidia-driver                          x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               23 M
 nvidia-driver-NVML                     x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64              462 k
 nvidia-driver-NvFBCOpenGL              x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               54 k
 nvidia-driver-cuda                     x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64              455 k
 nvidia-driver-cuda-libs                x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               54 M
 nvidia-driver-devel                    x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               13 k
 nvidia-driver-libs                     x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64              177 M
 nvidia-kmod-common                     noarch              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               13 k
 nvidia-libXNVCtrl                      x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               26 k
 nvidia-libXNVCtrl-devel                x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               56 k
 nvidia-modprobe                        x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               37 k
 nvidia-persistenced                    x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64               43 k
 nvidia-settings                        x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64              835 k
 nvidia-xconfig                         x86_64              3:515.48.07-1.el8                                 cuda-rhel8-x86_64              106 k
Installing dependencies:
 dnf-plugin-nvidia                      noarch              2.0-1.el8                                         cuda-rhel8-x86_64               12 k
 egl-wayland                            x86_64              1.1.9-3.el8                                       appstream                       39 k
 libX11-devel                           x86_64              1.6.8-5.el8                                       appstream                      975 k
 libXau-devel                           x86_64              1.0.9-3.el8                                       appstream                       19 k
 libglvnd-opengl                        x86_64              1:1.3.4-1.el8                                     appstream                       46 k
 libvdpau                               x86_64              1.4-2.el8                                         appstream                       40 k
 libxcb-devel                           x86_64              1.13.1-1.el8                                      appstream                      1.1 M
 mesa-vulkan-drivers                    x86_64              21.3.4-1.el8                                      appstream                      6.7 M
 ocl-icd                                x86_64              2.2.12-1.el8                                      appstream                       50 k
 opencl-filesystem                      noarch              1.0-6.el8                                         appstream                      7.3 k
 vulkan-loader                          x86_64              1.3.204.0-2.el8                                   appstream                      133 k
 xorg-x11-proto-devel                   noarch              2020.1-3.el8                                      appstream                      279 k
Installing module profiles:
 nvidia-driver/default
Enabling module streams:
 nvidia-driver                                              latest-dkms

.....
.....

Finally do a 

# nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.48.07    Driver Version: 515.48.07    CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA A100-PCI...  Off  | 00000000:A3:00.0 Off |                    0 |
| N/A   49C    P0    46W / 250W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+
|   1  NVIDIA A100-PCI...  Off  | 00000000:C3:00.0 Off |                    0 |
| N/A   53C    P0    46W / 250W |      0MiB / 40960MiB |      0%      Default |
|                               |                      |             Disabled |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
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How Synthetic Data Supercharges Vision AI Development NVIDIA Webinar

In this meetup you’ll learn how synthetic data is transforming AI development efforts:

  • Learn how to use NVIDIA’s Omniverse Replicator to quickly create synthetic data and how it can integrate with NVIDIA TAO training tools.
  • Hear from Sky Engine AI, an NVIDIA synthetic data partner, sharing how you can leverage 3rd party synthetic data services.
  • Get your questions answered in a live Q&A session with our team of experts.

Register here and select one of the following sessions:

  • Americas, Europe, Middle East: Wednesday May 18 – 8am PT | 4PM CET 
  • Asia-Pacific: Thursday May 19 – 11am SST | 12pm JST/KST | ?8:30am IST
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EOL notice for Mellanox ConnectX-5 VPI host channel adapters and Switch-IB 2 based EDR InfiniBand Switches

Nvidia Corporation has announced the EOL Notice #LCR-000906 – MELLANOX

PCN INFORMATION:
PCN Number: LCR-000906 – MELLANOX
PCN Description: EOL notice for Mellanox ConnectX-5 VPI host channel adapters and Switch-IB 2 based EDR InfiniBand Switches
Publish Date: Sun May 08 00:00:00 GMT 2022
Type: FYI

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Installing Nvidia Drivers on Rocky Linux 8.5

If you are planning to install Nvidia Drivers on Rocky Linux 8.5, you may want to use DNF to install. For a detailed explanation Streamlining NVIDIA Driver Deployment on RHEL 8 with Modularity Streams

Step 1: Add Offical Nvidia Repository to Package Managers repository list. 

# dnf config-manager --add-repo=https://developer.download.nvidia.com/compute/cuda/repos/rhel8/x86_64/cuda-rhel8.repo

Step 2: Install Kernel-Devel and Headers used by the Drivers

# dnf install kernel-devel-$(uname -r) kernel-headers-$(uname -r)

Step 3: Installing Nvidia Drivers and Settings

# dnf install nvidia-driver nvidia-settings

Step 4: Install CUDA Drivers and REboot

# dnf install cuda-driver

Once done, do a reboot,

# reboot

If after a reboot and if you do a “nvidia-smi” and receive an error like the one

# nvidia-smi
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.

You may want to take a look at https://gist.github.com/espoirMur/65cec3d67e0a96e270860c9c276ab9fa. It could be coming Secure Boot Option in your BIOS.

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Webinar – Cloud-Native Supercomputing Powers New Data Centre Architecture

Computing power becomes the service. Data center becomes the new computing unit to serve the unlimited computing resource with high performance, flexibility and security. Network as the bridge between the computing resource and storage resource, between data centers and between the user and data center,  is becoming the key to impact performance and security. The Cloud Native Supercomputing architecture is designed to leverage the advantage from both supercomputer and cloud to provide the best performance in the modern zero trust environment.

By attending this webinar, you will learn how to:

  • Use the supercomputing technologies in data center
  • Deliver the cloud flexibility with supercomputing technologies to drive the most powerful data center
  • Provide the cloud native supercomputing service in zero trust environment

Date: February 23, 2022
Time: 15:00 – 16:00 SGT
Duration: 1 hour

To Register (Cloud Native Supercomputing Powers New Data Center Architecture (nvidianews.com)

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Install Nvidia Drivers on CentOS 7

Getting Information on Nvidia GPU on CentOS 7

# lspci | grep -i --color 'vga\|3d\|2d'
02:00.0 VGA compatible controller: Matrox Electronics Systems Ltd. MGA G200e [Pilot] ServerEngines (SEP1) (rev 42)
86:00.0 VGA compatible controller: NVIDIA Corporation GP102GL [Quadro P6000] (rev a1)

# lshw -class display
 *-display
       description: VGA compatible controller
       product: MGA G200e [Pilot] ServerEngines (SEP1)
       vendor: Matrox Electronics Systems Ltd.
       physical id: 0
       bus info: pci@0000:02:00.0
       version: 42
       width: 32 bits
       clock: 33MHz
       capabilities: pm msi vga_controller bus_master cap_list rom
       configuration: driver=mgag200 latency=0
       resources: irq:16 memory:d3000000-d3ffffff memory:d4a10000-d4a13fff memory:d4000000-d47fffff memory:d4a00000-d4a0ffff
  *-display
       description: VGA compatible controller
       product: GP102GL [Quadro P6000]
       vendor: NVIDIA Corporation
       physical id: 0
       bus info: pci@0000:86:00.0
       version: a1
       width: 64 bits
       clock: 33MHz
       capabilities: pm msi pciexpress vga_controller bus_master cap_list rom
       configuration: driver=nvidia latency=0
       resources: iomemory:3df0-3def iomemory:3df0-3def irq:320 memory:ec000000-ecffffff memory:3dfe0000000-3dfefffffff memory:3dff0000000-3dff1ffffff ioport:c000(size=128) memory:ed000000-ed07ffff

Nvidia Downloads Site

From the Information, Download the Drivers from Nvidia Download Page

Yum Install Libraries and Dependencies

# yum group install "Development Tools"
# yum install kernel-devel
# yum install epel-release
# yum install dkms

Disable Noveau Drivers

Disable nouveau driver by changing the configuration /etc/default/grub file. Add the nouveau.modeset=0 into line starting with GRUB_CMDLINE_LINUX. This will disable the noveau driver after the reboot.

GRUB_TIMEOUT=5
GRUB_DISTRIBUTOR="$(sed 's, release .*$,,g' /etc/system-release)"
GRUB_DEFAULT=saved
GRUB_DISABLE_SUBMENU=true
GRUB_TERMINAL_OUTPUT="console"
GRUB_CMDLINE_LINUX="crashkernel=auto rhgb quiet nouveau.modeset=0"
GRUB_DISABLE_RECOVERY="true"

Modifying the Grub.cfg

For BIOS User,

# grub2-mkconfig -o /boot/grub2/grub.cfg
Generating grub configuration file ...
Found linux image: /boot/vmlinuz-3.10.0-957.5.1.el7.x86_64
Found initrd image: /boot/initramfs-3.10.0-957.5.1.el7.x86_64.img
Found linux image: /boot/vmlinuz-3.10.0-957.el7.x86_64
Found initrd image: /boot/initramfs-3.10.0-957.el7.x86_64.img
Found linux image: /boot/vmlinuz-0-rescue-86f557f292e5492aa7ac0bf1cb2670b0
Found initrd image: /boot/initramfs-0-rescue-86f557f292e5492aa7ac0bf1cb2670b0.img
done

For UEFI User

# grub2-mkconfig -o /boot/efi/EFI/redhat/grub.cfg

Switch CentOS from GUI to Text Mode

First switch to Text Mode

# systemctl isolate multi-user.target

Installing the Nvidia Driver on CentOS 7

# bash NVIDIA-Linux-x86_64-*

Reboot the System

# reboot

Finally, run the command nvidia-settings to check and configure

# nvidia-settings

References

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VMware-NVIDIA AI-Ready Enterprise platform

NVIDIA and VMware have formed a strategic partnership to transform the data center to bring AI and modern workloads to every enterprise.

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 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.

For more information, see NVIDIA AI Enterprise

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NVIDIA Special Address at SIGGRAPH 2021

NVIDIA and SIGGRAPH share a long history of innovation and discovery. Over the last 25 years our community has seen giant leaps forward, driven by brilliant minds and curious explorers. We are now upon the opening moments of an AI-powered revolution in computer graphics with massive advancements in rendering, AI, simulation, and compute technologies across every industry. With open standards and connected ecosystems, we are on the cusp of achieving a new way to interact and exist with graphics in shared virtual worlds.

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NVIDIA Special Address | MWC Barcelona 2021

In a special address at MWC Barcelona 2021, NVIDIA announced its partnership with Google Cloud to create the industry’s first AI-on-5G open innovation lab that will speed AI application development for 5G network operators.

Additional announcements included: ● Extending the 5G ecosystem with Arm CPU cores on NVIDIA BlueField-3 DPUs ● Launching NVIDIA CloudXR 3.0 with bidirectional audio for remote collaboration