GPU Cluster

The GPU cluster is optimized for workloads requiring GPU acceleration, including machine learning, molecular dynamics simulations, and large-scale data analysis. The cluster supports CUDA, TensorFlow, PyTorch, and other GPU-accelerated frameworks. Users who do not require GPU resources are strongly encouraged to leverage the MPI or SMP clusters instead.

Specifications

Partition Name	Node Count	GPU Type	GPU/Node	--constraint	Host Architecture	Core/Node	Max Core/GPU	Mem/Node	Mem/Core	Scratch	Network	Node Names
l40s	20	L40S 48GB	4	l40s,48g,intel	Intel Xeon Platinum 8462Y+	64	16	512 GB	8 GB	7 TB NVMe	10GbE	gpu-n[55-74]
a100	10	A100 40GB PCIe	4	a100,40g,amd	AMD EPYC 7742 (Rome)	64	16	512 GB	8 GB	2 TB NVMe	HDR200; 10GbE	gpu-n[35-44]
	2	A100 40GB PCIe	4	a100,40g,intel	Intel Xeon Gold 5220R (Cascade Lake)	48	12	384 GB	8 GB	1 TB NVMe	10GbE	gpu-n[33-34]
a100_multi	10	A100 40GB PCIe	4	a100,40g,amd	AMD EPYC 7742 (Rome)	64	16	512 GB	8 GB	2 TB NVMe	HDR200; 10GbE	gpu-n[45-54]
a100_nvlink	2	A100 80GB SXM	8	a100,80g,amd	AMD EPYC 7742 (Rome)	128	16	1 TB	8 GB	2 TB NVMe	HDR200; 10GbE	gpu-n[31-32]
	3	A100 40GB SXM	8	a100,40g,amd	AMD EPYC 7742 (Rome)	128	16	1 TB	8 GB	12 TB NVMe	HDR200; 10GbE	gpu-n[28-30]