*Qs 1: How do I cite or mention the cluster in papers? or what is the preferred method?

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You could try a trace.
cmake --trace . 2>&1 | tee /tmp/cmakeOut.txt

You may have to explicitly mention the path, For example:
cmake . -DLAPACK_LIBRARIES=/sw/library/lapack/lapack-3.6.0/3.6.0/lib64/liblapack.so -DBLAS_LIBRARIES=/sw/library/blas/CBLAS/lib/cblas_LINUX.so
 
OR:
 cmake . -DLAPACK_LIBRARIES=/sw/library/lapack/lapack-3.6.0/3.6.0/lib64/liblapack.so -DBLAS_LIBRARIES=/sw/library/blas/CBLAS/lib/cblas_LINUX.so -DCMAKE_INSTALL_PREFIX=/sw/simbody/353

Qs28:  How do I check number of CPUs my job is using

You can find out on which compute node your job is running:
qstat -1an|grep snumber
>>>>>>>>>>>>>>>>>>>
e.g:
qstat -1an|grep s2761086
4598354.pbsserv s2761086 workq    DT_k-e_04   21795   1   1   10gb 99999 R 523:2 n010/0
Here you see it is running on n010
Then you can do this:
ssh nodename -t "htop"  or ssh nodename -t "htop -u username" 
e.g.ssh n010 -t "htop -u s2761086"
Press <F2> key, go to "Columns", and add PROCESSOR under "Available Columns".
The currently used CPU ID of each process will appear under "CPU" column.

Qs29:   How to customize an environmental variable using modules

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Qs 31: Multi Cores are requested and allocated by PBs but job runs only on 1 core. Why is that?

This contribution is from Nicholas Dhal and is acknowledged. Nick is an active Grifith HPC user.

>>>>>>>>>

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goo.gl/koYII3

>>>>>>>>>>

Qs 32: How to check the remaining licenses on the license server

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e.g scp -r /export/home/s5284664/folder n061:/lscratch/s5284664/

Qs.56: NCMAS process and application

NCMAS facilities overview and who should apply
https://youtu.be/7ZZVk4HtdDY

NCMAS process and application 2021
https://youtu.be/hmV_j5GFgI0

Qs 57: What kind of storage and compute is available on Griffith HPC

...

Additionally and in parallel, you can also apply directly when the application opens

https://my.nci.org.au/mancini/ncmas/2022/

Please note that projects will be given a fixed allocation which is given per quarter on a use it or loose it basis. Allocations cannot be carried forward or backward into other quarters. Standard disk space per project is 75GB in /scratch and if a project needs more you will need to contact help@nci.org.au.

Students cannot be a lead CI on an NCI project however, for the QCIF share postdocs can be. For NCMAS the lead CI is required to have an ARC or NHMRC grant or equivalent which is why larger groups apply for NCMAS. A grant is not required for a project under QCIF. However, the QCIF allocations are small, around 20-50 thousand per quarter. Larger allocations are only available through NCMAS.

Some applications like Mathematica and Matlab are licensed software. Mathematica is only available to ANU researchers on NCI. For Matlab, Griffith will need to get in contact with NCI to set up their institutional license. At the moment this is not available so one cannot use it. Unless you have your own license. But also in that case you would need to get in touch with NCI first to see if you can use Matlab on Gadi or not.

In general, allocations are given in service units SUs. 1 core hour is charged at 2 SUs. So if you have a calculation running using 4 cores and taking 48 hours then you will be charged 4*48*2=384 SUs for that calculation.

If a larger disk space (e.g 300GB) is needed, you would need to talk to NCI to increase the space in /scratch to accommodate this. If a larger RAM (e.g 400GB ), then you would need to make sure you run in a queue that supports that ram request. They could be charged more than 2 SUs per core hour though, so you would need to factor that in.

But talk to NCI, help@nci.org.au, first to see if you could use the application (e.g Matlab) onNCI before you even consider applying for an allocation on NCI.

Qs69: How to install bioinformatics software in your home directory

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Reference: https://kb.hlrs.de/platforms/index.php/Batch_System_PBSPro_(vulcan)#DISPLAY:_X11_applications_on_interactive_batch_jobs

The login or head node of each cluster is a resource that is shared by many users. Running a GUI job on the login node is prohibited and may adversely affect other users. X11 Forwarding is only possible for interactive jobs.

Please note that there is a performance penalty when running a GUI job on the compute nodes using the method outlined below. 

Set up X11 forwarding

To use X11 port forwarding, Install Xming X Server on Windows laptop/desktop first. Install the xming fonts package as well.
See instructions here: https://griffith.atlassian.net/wiki/spaces/GHCD/pages/4035477/xming

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1. http://mobaxterm.mobatek.net/download-home-edition.html
2. putty
3. Filezillia
4. Windows WSL system lets you run the linux versions of ssh under windows.
      wsl --install
   This should get you command line:  ssh,  scp,  and sftp; 

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To transfer from remote to locally: scp -r remotehostname:/export/home/snumber/FolderName ~/ 

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We do not recommend installing miniconda as we provide conda as a module.
module load anaconda3/2024.02 

If you have installed it, comment out the miniconda section from ~./bashrc which can mess with other non-miniconda env. 
After commenting it out re-log back in.

Here is how you can test pytorch on your home dir for cuda availability:

To test this, please do this;
cd ~/slurm 
There are a couple of sample scripts to run slurm jobs

We will run an interactive job to troubleshoot this problem:
For example:
srun --export=PATH,TERM,HOME,LANG  --job-name=hello_word --cpus-per-task=1 --mem-per-cpu=50GB --time=1:00:00 --qos=work --gres=gpu:a100:1 --pty /bin/bash -l

it would put you inside a job.

squeue
             JOBID PARTITION     NAME     USER ST       TIME  NODES NODELIST(REASON)
            <snip>
              1718    LocalQ    myrun s5284664  R    4:17:59      1 dgxlogin


Once inside a job, check if it detects gpu in pytorch app. (if already installed)

module load anaconda3/2024.02 
conda info --envs
# conda environments:
#
base                  *  /export/home/s5305964/miniconda3
PHDenv                   /export/home/s5305964/miniconda3/envs/PHDenv

Unfortunately, you have installed it in miniconda. So leaving aside that, I would build a new env

To install new env and packages, do this:

source /usr/local/bin/s3proxy.sh  (need to get access the internet within a slurm job)
conda create --name pytorchCuda121 pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia

(See Qs 90 : https://griffith.atlassian.net/wiki/spaces/GHCD/pages/4030751/FAQ+-+Griffith+HPC+Cluster#FAQ-GriffithHPCCluster-Qs90%3AHowtorunthepytorch(containermethodandcondaenvmethod)ontheICTcluster)

source activate pytorchCuda121
 python ~/isCuda.py 
CUDA AVILABLE
>>>>>>>>>isCuda.py>>>>>>>>>>>>>
import torch
if torch.cuda.is_available():
    print('CUDA AVILABLE')
else:
    print('NO CUDA')

>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>

PS: Comment out the miniconda install from ~./bashrc which can mess with this env.

If you ever need to use the miniconda env, you can do this:

source deactivate
module purge

__conda_setup="$('~/miniconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)"
eval "$__conda_setup"
source activate PHDenv
python isCuda.py 
CUDA AVILABLE

Qs92: dgxA100 gpu node : group reservation - dedicated gpus in slurm

A group named "alan" has 2 A100 gpus reserved.

scontrol show res
ReservationName=alan100 StartTime=2024-07-01T10:33:01 EndTime=2024-08-02T10:33:01 Duration=32-00:00:00
   Nodes=dgxlogin NodeCnt=1 CoreCnt=32 Features=(null) PartitionName=LocalQ Flags=FLEX,MAGNETIC
     NodeName=dgxlogin CoreIDs=0-10,13,40-43,64-79
   TRES=cpu=64,gres/gpu:a100=2,gres/gpu=2
   Users=(null) Groups=alan Accounts=(null) Licenses=(null) State=ACTIVE BurstBuffer=(null) Watts=n/a
   MaxStartDelay=(null)


This is reservation is automated (using cron) so that it is deleted every 30 days and recreated. Which means , these 2 gpus are permanently reserved for alan group. 

Usage is as follows:
For batch runs
==============
Add this inside the slurm script:
#SBATCH --reservation=alan100 
OR
sbatch  --reservation=alan100 <job script>
e.g:   sbatch  --reservation=alan1g10gb slurm.res
Make sure the job script has resource request covered by the reservation (This command will list that: scontrol show res)

For interactive runs
=================
srun --reservation=alan100 --export=PATH,TERM,HOME,LANG  --job-name=myTestRun --cpus-per-task=1 --mem-per-cpu=15GB --time=00:02:00 --qos=work --gres=gpu:a100:1 --pty /bin/bash -l