Hardware

A list of the currently available hardware.

If you are looking for information on maximum resource requests, see Job Limits.

Compute Nodes¶

Your jobs will land on appropriately sized nodes automatically based on your CPU to memory ratio. For example in the Genoa partition:

A job requesting ≤ 2 GB/core will run on a 2 GB/core node, or if full, a 4 GB/core node.
A job requesting ≤ 4 GB/core will run on a 4 GB/core node, or if full, a 8 GB/core node.

And so on. You will always get the amount of memory you requested, even if running on a node with a higher ratio.

Architecture	Core	Memory		GPGPU	Nodes
2 x AMD Milan 7713 CPU └ 8 x Chiplets └ 8 x Cores	126	512GB	(4GB / Core)	-	54
		1024GB	(8GB / Core)	-	8
		1024GB	(8GB / Core)	4 x NVIDIA HGX A100	4
2 x AMD Genoa 9634 CPU └ 12 x Chiplets └ 7 x Cores	166	358GB	(1GB / Core)	-	44
		716GB	(2GB / Core)	2 x NVIDIA A100	4
		1432GB	(4GB / Core)	-	8
				2 x NVIDIA H100	4
				4 x NVIDIA L4	4

NeSI has a range of Graphical Processing Units (GPUs) to accelerate compute-intensive research and support more analysis at scale.

Depending on the type of GPU, you can access them in different ways, such as via batch scheduler (Slurm), or Virtual Machines (VMs).

For information about how to request these GPUs in a Slurm job, see Using GPUs.

Architecture	Purpose/Note	VRAM	GPUs on Node	Nodes
NVIDIA A100	Machine Learning	80GB	4	Milan	4
NVIDIA A100	Machine Learning	40GB	2	Genoa	4
NVIDIA H100	Large-scale Machine Learning	96GB	2	Genoa	4
NVIDIA L4	No fp64 double precision	24GB	4	Genoa	4
NVIDIA A40	Teaching / training	48GB	RDC		4

If you have any questions about hardware or the status of anything listed in the table, Contact our Support Team.