CentOS/RHEL 7 OS GPU Installation With Yum

This is an end-to-end recipe for installing OmniSci Open Source on a CentOS/RHEL 7 machine running with NVIDIA Volta, Kepler, or Pascal series GPU cards using Yum.

Here is a short video overview of the installation process.

The installation phases are:
Important The order of these instructions is significant. To avoid problems, install each component in the order presented.

Assumptions

These instructions assume the following:
  • You are installing on a “clean” CentOS/RHEL 7 host machine with only the operating system installed.
  • Your OmniSci host only runs the daemons and services required to support OmniSci.
  • Your OmniSci host is connected to the Internet.

Preparation

Prepare your Centos/RHEL machine by updating your system, installing JDK and EPEL, creating the OmniSci user (named omnisci), installing kernel headers, and installing CUDA drivers.

Update and Reboot

Update the entire system and reboot to activate the latest kernel.

sudo yum update
sudo reboot

Install JDK

Follow these instructions to install a headless Java Development Kit and configure an environment variable with a path to the library. The headless JDK does not provide support for keyboard, mouse, or display systems. It has fewer dependencies and is best suited for a server host. For more information, see https://openjdk.java.net.

  1. Open a terminal on the host machine.
  2. Install the headless JDK using the following command: 
    sudo yum install java-1.8.0-openjdk-headless

EPEL

Install the Extra Packages for Enterprise Linux (EPEL) repository.

For CentOS, use Yum to install the epel-release package.

sudo yum install epel-release
Use the following install command for RHEL. 

yum install https://dl.fedoraproject.org/pub/epel/epel-release-latest-7.noarch.rpm

RHEL-based distributions require Dynamic Kernel Module Support (DKMS) to build the GPU driver kernel modules. For more information, see https://fedoraproject.org/wiki/EPEL.

Create the OmniSci User

Create a group called omnisci and a user named omnisci, who will be the owner of the OmniSci database. You can create the group, user, and home directory using the useradd command with the -U and -m switches.

sudo useradd -U -m omnisci

Install CUDA Drivers

CUDA is a parallel computing platform and application programming interface (API) model. It uses a CUDA-enabled graphics processing unit (GPU) for general purpose processing. The CUDA platform provides direct access to the GPU virtual instruction set and parallel computation elements. For more information on CUDA unrelated to installing OmniSci, see http://www.nvidia.com/object/cuda_home_new.html.

Install Kernel Headers

  1. Install kernel headers and development packages: 
    sudo yum install kernel-devel-$(uname -r) kernel-headers$(uname -r)
  2. Reboot your system to ensure that the kernel is up to date: 
    sudo reboot
Important If this procedure to install kernel headers does not work correctly, follow these steps instead:
  1. Identify the Linux kernel you are using by issuing the uname -r command.
  2. Use the name of the kernel (3.10.0-862.11.6.el7.x86_64 in the following code example) to install kernel headers and development packages: 
    sudo yum install kernel-devel-3.10.0-862.11.6.el7.x86_64 kernel-headers-3.10.0-862.11.6.el7.x86_64
  3. Reboot your system to ensure that the kernel is up to date: 
    sudo reboot

Install the Drivers

OmniSci requires only the CUDA drivers and not the entire CUDA package. To install the drivers:

  1. Go to https://developer.nvidia.com/cuda-downloads.
  2. Select the target platform by selecting the operating system (Linux), architecture (based on your environment), distribution (CentOS or RHEL), version (7), and installer type (OmniSci recommends rpm (network)).

    CUDA install

  3. In Download Installer..., right-click the Download button and copy the link location of the Base Installer. Do not use the installation instructions on the CUDA site:

    CUDA base installer

  4. Use one of the following methods to download the installer from the command line, using the download link you copied (https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.0.130-1.x86_64.rpm, in this example):
    • curl: 
      curl -O https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.0.130-1.x86_64.rpm
    • wget: 
      wget https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-repo-rhel7-10.0.130-1.x86_64.rpm
  5. Install the CUDA drivers using the filename you just downloaded (cuda-repo-rhel7-10.0.130-1.x86_64.rpm in the previous step): 
    sudo rpm --install <file_name>
sudo yum clean expire-cache
sudo yum install cuda-drivers
  6. Reboot your system to ensure that all changes are active. 
    sudo reboot
Note You might see a warning similar to the following:
warning: cuda-repo-rhel7-10.0.130-1.x86_64.rpm: Header V3 RSA/SHA512 Signature, key ID 7fa2af80: NOKEY
Ignore it for now; you can verify CUDA driver installation at the Checkpoint.

Checkpoint

Run nvidia-smi to verify that your drivers are installed correctly and recognize the GPUs in your environment. Depending on your environment, you should see something like this to verify that your NVIDIA GPUs and drivers are present:NVIDIA SMI

Note If you see an error like the following, the NVIDIA drivers are probably installed incorrectly: 
NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. 
Make sure that the latest NVIDIA driver is installed and running.
Review the Install CUDA Drivers section and correct any errors.

Installation

Update the repo file at \etc\yum.repos.d\CentOS-Sources.repo with the OmniSci repository specification:

[omnisci]
name='omnisci os - cuda'
baseurl=https://releases.omnisci.com/os/yum/stable/cuda
enabled=1
gpgcheck=1
repo_gpgcheck=0
gpgkey=https://releases.omnisci.com/GPG-KEY-mapd

Use yum to install OmniSci.

sudo yum install omnisci

Configuration

Follow these steps to prepare your OmniSci environment.

Set Environment Variables

For convenience, you can update .bashrc with the required environment variables.

  1. Open a terminal window.
  2. Enter cd ~/ to go to your home directory.
  3. Open .bashrc in a text editor. For example, sudo gedit .bashrc.
  4. Edit the .bashrc file. Add the following export commands under “User specific aliases and functions.” 
    # User specific aliases and functions
export OMNISCI_USER=omnisci
export OMNISCI_GROUP=omnisci
export OMNISCI_STORAGE=/var/lib/omnisci
export OMNISCI_PATH=/opt/omnisci
export OMNISCI_LOG=/var/lib/omnisci/data/mapd_log
  5. Save the .bashrc file.
  6. Open a new terminal window to use your changes.

The $OMNISCI_STORAGE directory must be dedicated to OmniSci: do not set it to a directory shared by other packages.

Initialization

Run the systemd installer. This script requires sudo access. You might be prompted for a password. 

cd $OMNISCI_PATH/systemd
sudo ./install_omnisci_systemd.sh

Accept the values provided (based on your environment variables) or make changes as needed. The script creates a data directory in $OMNISCI_STORAGE with the directories mapd_catalogs, mapd_data, and mapd_export. mapd_import and mapd_log directories are created when you insert data the first time. If you are an OmniSci administrator, the mapd_log directory is of particular interest.

Activation

Start and use OmniSci Core.

  1. Start OmniSci Core. 
    sudo systemctl start omnisci_server
  2. Enable OmniSci Core to start when the system reboots. 
    sudo systemctl enable omnisci_server

Checkpoint

To verify that everthing is working, load some sample data and perform an omnisql query.

  1. OmniSci ships with two sample datasets of airline flight information collected in 2008. To install the sample data, run the following command. 
    cd $OMNISCI_PATH
sudo ./insert_sample_data
  2. When prompted, choose whether to insert dataset 1 (7 million rows) or dataset 2 (10 thousand rows). 
    Enter dataset number to download, or 'q' to quit:
#     Dataset           Rows    Table Name          File Name
1)    Flights (2008)    7M      flights_2008_7M     flights_2008_7M.tar.gz
2)    Flights (2008)    10k     flights_2008_10k    flights_2008_10k.tar.gz
3)    NYC Tree Census (2015)    683k    nyc_trees_2015_683k    nyc_trees_2015_683k.tar.gz
  3. Connect to OmniSci Core by entering the following command in a terminal on the host machine (default password is HyperInteractive): 
    $OMNISCI_PATH/bin/omnisql
password: ••••••••••••••••
  4. Enter a SQL query such as the following, based on dataset 2 above: 
    omnisql> SELECT origin_city AS "Origin", dest_city AS "Destination", AVG(airtime) AS
"Average Airtime" FROM flights_2008_10k WHERE distance < 175 GROUP BY origin_city,
dest_city;
Origin|Destination|Average Airtime
Austin|Houston|33.055556
Norfolk|Baltimore|36.071429
Ft. Myers|Orlando|28.666667
Orlando|Ft. Myers|32.583333
Houston|Austin|29.611111
Baltimore|Norfolk|31.714286