HPC documentation
General information
To access the HPC, start a terminal session and ssh into wolfe.scem.westernsydney.edu.au
The current set up has the following partitions:
PARTITION AVAIL TIMELIMIT NODES STATE NODELIST k6000 up infinite 4 idle bd-client-[01-04] cpu* up infinite 8 idle compute-[000-007] a100-dev up 7-00:00:00 1 idle a100-dev a100 up 7-00:00:00 2 idle a100-[000-001]
Each k6000 node has 8 CPUs, cpu node has 16 CPUs, and the a100 nodes have 32 CPU each.
Both k6000 and a100 have GPUs attached. The a100 nodes are the most recent addition, and each has the full GPU capability of a A100 chip, that is 9612 cuda cores and 40GB memory. The k6000 nodes have the GTX6000 chips, each with 4600 cuda cores and 24GB memory.
other information to be filled later
Resources
GPU
To request GPU for your jobs, you need to include the line:
#SBATCH -P a100
in your bash script for submitting the jobs, to specify the a100 nodes (or the k6000 nodes). This is in addition to the gpu resource request.
Software
To use PyTorch, you'll need the following combinations:
- Python 3.7 + Torch 1.9 Cuda 11
- Python 3.9 + Torch 1.9 + cuda 11
- Python 3.10 + Torch 12.1 Cuda 11.3
There are also module load that loads all three in one go:
PyTorch/Python3.9
