Turing

You can use SSH login. Since turing.ce.pdn.ac.lk is not a public IP you shoud either (a) use a computer in the Peradeniya network or (b) SSH to a public IP server like tesla.ce.pdn.ac.lk or aiken.ce.pdn.ac.lk and SSH to turing.ce.pdn.ac.lk from there.

NVIDIA GeForce RTX 3090 Ti

Ubuntu 22.04

• Ubuntu 22.04
• NVIDIA-Driver Version: 530.41.03
• CUDA Version: 12.1 (You can update this using conda)

We store frequently used datasets inside the turing.ce.pdn.ac.lk local storage for easy access. You can access these by the following commands

ls /storage/datasets/

These datasets are in the read only mode. You can use these datsets as the input for your tasks but you have to output the results to your home directory. The following datasets are stored at the moment.

• THIS LIST WILL BE POPULATED SOON

If you have suggestions for what datasets should be made available on this server, please send a request via email available in https://www.cs.umd.edu/~gihan/contact/ address.

Use https://anaconda.org/anaconda/cudatoolkit

Please request through any CO staff member. Please note that the server admin has no authority to install something unless it is requested by a staff memeber.

Ask via email

Ask headce[at]eng.pdn.ac.lk.

Contact server admin</a>

1. Send a request to the server admin via the server admin contact page to run this command:

   sudo singularity config fakeroot --add eXXYYY

2. Download the sample def file:

   eyyxxx@turing:~$ wget https://raw.githubusercontent.com/cepdnaclk/singularity-deployment/main/base.def

3. Build the container:

   eyyxxx@turing:~$ singularity build --fakeroot base.sif base.def

4. Run commands using the container:

   eyyxxx@turing:~$ singularity exec base.sif <your-command>

If you need to learn more, go to: https://github.com/cepdnaclk/singularity-deployment