This page is currently being updated to include examples of submission and configuration commands that can be used on CTBP resources.

It should be noted that this example assumes the use of only one GPU per task and requests an equal amount of memory and CPU resources based on the total resources of each node. The amount of CPU and RAM memory utilized can be increased or decreased based on the user's experience with their system.

NOTS (commons)

This partition includes 16 volta GPU nodes, each equipped with 80 CPUs and 182GB of RAM. In addition, each node includes 2 NVIDIA GPUs.

#SBATCH --account=commons
#SBATCH --partition=commons
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=40
#SBATCH --mem=90G
#SBATCH --gres=gpu:1

NOTS (ctbp-common)

This partition includes two ampere GPU nodes, each equipped with an AMD EPYC chip featuring 16 CPUs and 512GB of RAM. In addition, each node includes 8 NVIDIA A40 GPUs with 48GB of memory.

#SBATCH --account=ctbp-common
#SBATCH --partition=ctbp-common
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=2
#SBATCH --mem=64G
#SBATCH --gres=gpu:1

NOTS (ctbp-onuchic)

This partition includes one GPU node, equipped with an AMD EPYC chip featuring 16 CPUs and 512GB of RAM. In addition, each node includes 8 NVIDIA A40 GPUs with 48GB of memory.

#SBATCH --account=ctbp-onuchic
#SBATCH --partition=ctbp-onuchic
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=2
#SBATCH --mem=64G
#SBATCH --gres=gpu:1

ARIES

This partition includes 19 GPU nodes, each equipped with an AMD EPYC chip featuring 48 CPUs and 512GB of RAM. In addition, each node includes 8 AMD MI50 GPUs with 32 GB of memory each. To submit a job to this queue, it is necessary to launch 8 processes in parallel, each with a similar runtime to minimize waiting time. This ensures that all of the GPUs are used efficiently.

#SBATCH --account=commons
#SBATCH --partition=commons
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --export=ALL
#SBATCH --gres=gpu:8

*Alternative if running 8 jobs in parallel

#SBATCH --account=commons
#SBATCH --partition=commons
#SBATCH --ntasks=8
#SBATCH --cpus-per-task=6
#SBATCH --threads-per-core=1
#SBATCH --mem-per-cpu=3G
#SBATCH --gres=gpu:8
#SBATCH --time=24:00:00
#SBATCH --export=ALL

PODS

This partition includes 80 GPU nodes, each equipped with an AMD EPYC chip featuring 48 CPUs and 512GB of RAM. In addition, each node includes 8 AMD MI50 GPUs with 32 GB of memory each.

#SBATCH --account=commons
#SBATCH --partition=commons
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --export=ALL
#SBATCH --gres=gpu

Accessing the cluster

To access the servers from outside of Rice it is recommended to connect to them through the gw.crc.rice.edu server. Here we will show how to create a passwordless ssh tunnel that will allow you to securely connect to a remote machine without having to enter a password everytime you connect.

Generate the keys

First generate a pair of public and private keys on your local machine. Open a terminal and enter the following command:

ssh-keygen -t rsa

This will generate a pair of public and private keys, with the default file names id_rsa and id_rsa.pub. Don't share or expose your private key.

Copy the keys to the gateway server

Copy the public key to the remote machine (The gw.crc.rice.edu server). Enter the following command in your terminal, replacing user with the correct rice user id:

ssh-copy-id user@gw.crc.rice.edu

This will copy your public key, id_rsa.pub, to the remote machine and add it to the authorized_keys file on the remote machine.

Test the connection. Enter the following command in your terminal to connect to the remote machine:

ssh user@gw.crc.rice.edu

You should be able to connect to the remote machine without being prompted for a password. Exit to your local machine using Ctrl+D

Create a ssh config file

To make it easier to connect to the remote machine in the future, you can create an ssh config file. This file allows you to specify connection settings and aliases for different remote machines. To create an ssh config file, open a text editor and enter the following information, replacing user_id with your username on the remote machine:

Host crc
    User user_id
    HostName gw.crc.rice.edu
    IdentityFile ~/.ssh/id_rsa

Host aries
    User user_id
    HostName aries.rice.edu
    ProxyJump crc
    Port 22
    IdentityFile ~/.ssh/id_rsa

Host nots
    User user_id
    HostName nots.rice.edu
    ProxyJump crc
    Port 22
    IdentityFile ~/.ssh/id_rsa

Save the file as ~/.ssh/config.

Connect to the remote machine using the alias. To connect to the remote machine using the alias, enter the following command in your terminal:

ssh crc

This will connect you to the remote machine using the settings and alias specified in the ssh config file. The gateway will be accessible without a password. Exit and try connecting to the compute servers:

ssh nots

The compute server will still ask for a password. To connect to them without a password we will need to copy the keys to them too.

Copy the keys to the compute servers

Copy the public key to the compute servers Enter the following commands in your terminal, replacing user with the correct rice user id:

ssh-copy-id aries
ssh-copy-id nots