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
       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
       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_DISTRIBUTOR="$(sed 's, release .*$,,g' /etc/system-release)"
GRUB_CMDLINE_LINUX="crashkernel=auto rhgb quiet nouveau.modeset=0"

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

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

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


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

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.

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

Performance Required for Deep Learning

There is this question that I wanted to find out about deep learning. What are essential System, Network, Protocol that will speed up the Training and/or Inferencing. There may not be necessary to employ the same level of requirements from Training to Inferencing and Vice Versa. I have received this information during a Nvidia Presentation


  1. Scalability requires ultra-fast networking
  2. Same hardware needs as HPC
  3. Extreme network bandwidth
  4. RDMA
  5. SHARP (Mellanox Scalable Hierarchical Aggregation and Reduction Protocol)
  6. GPUDirect (
  7. Fast Access Storage


  1. Highly Transactional
  2. Ultra-low Latency
  3. Instant Network Response
  4. RDMA
  5. PeerDirect, GPUDirect