GPU Cluster Overview

The GPU cluster is optimized for computational tasks requiring GPU acceleration, such as artificial intelligence and machine learning workflows, molecular dynamics simulations, and large-scale data analysis.

Key Features

  • Designed for high-performance GPU workloads.
  • Supports CUDA, TensorFlow, PyTorch, and other GPU-accelerated frameworks.

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]

Partition Details

l40s: This partition is appropriate for AI, simulations, 3D modeling workloads that require up to 4x gpus on a single node and rely on single or mixed precision operations (Note: This partition does not support double precision - FP64).

a100: This is the default partition in the gpu cluster and is appropriate for workflows that require up to 4x gpus on a single node. To request a particular feature (such as an Intel host CPU), add the following directive to your job script:

#SBATCH --constraint=intel

Multiple features can be specified in a comma-separated string.

a100_multi: This partition supports multi-node GPU workflows. Your job must request a minimum of 2 nodes and 4 GPUs on each node.

a100_nvlink: This partition supports multi-GPU computation on an Nvidia HGX platform with 8x A100 that are tightly coupled through an NVLink switch. To request a particular feature (such as an A100 with 80GB of GPU memory), add the the following directive to your job script:

#SBATCH --constraint=80g
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