Nexus/GPUs: Difference between revisions

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! [https://developer.nvidia.com/blog/accelerating-ai-training-with-tf32-tensor-cores/ TF32] Performance ([https://developer.nvidia.com/blog/accelerating-inference-with-sparsity-using-ampere-and-tensorrt Dense / Sparse TOPS])
! [https://developer.nvidia.com/blog/accelerating-ai-training-with-tf32-tensor-cores/ TF32] Performance ([https://developer.nvidia.com/blog/accelerating-inference-with-sparsity-using-ampere-and-tensorrt Dense / Sparse TOPS])
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| A100
| A100 (80GB)
| Ampere
| Ampere
| 6912
| 6912

Revision as of 19:47, 28 March 2024

There are several different types of NVIDIA GPUs in the Nexus cluster that are available to be scheduled. They are listed below in order of newest to oldest architecture, and then alphabetically.

We do not list the exact quantities of GPU here since they change frequently due to additions to or removals from the cluster or during compute node troubleshooting. To see which compute nodes have which GPUs and in what quantities, use the show_nodes command on a submission or compute node. The quantities are listed under the GRES column.

Name Architecture CUDA Cores GPU Memory Memory Bandwidth FP32 Performance (TFLOPS) TF32 Performance (Dense / Sparse TOPS)
A100 (80GB) Ampere 6912 80GB HBM2e 1935GB/s 19.5 156/312
GeForce RTX 3070 Ampere 5888 8GB GDDR6 448GB/s 20.3 20.3/40.6
GeForce RTX 3090 Ampere 10496 24GB GDDR6X 936GB/s 35.6 35.6/71
RTX A4000 Ampere 6144 16GB GDDR6 448GB/s 19.2 not officially published
RTX A5000 Ampere 8192 24GB GDDR6 768GB/s 27.8 not officially published
RTX A6000 Ampere 10752 48GB GDDR6 768GB/s 38.7 77.4/154.8
GeForce RTX 2080 Ti Turing 4352 11GB GDDR5X 616GB/s 13.4 n/a
GeForce GTX 1080 Ti Pascal 3584 11GB GDDR5X 484GB/s 11.3 n/a
Quadro P6000 Pascal 3840 24GB GDDR5X 432GB/s 12.6 n/a
Tesla P100 Pascal 3584 16GB CoWoS HBM2 732GB/s 9.3 n/a
TITAN X (Pascal) Pascal 3584 12GB GDDR5X 480GB/s 11.0 n/a
TITAN Xp Pascal 3840 12GB GDDR5X 548GB/s 12.1 n/a
GeForce GTX TITAN X Maxwell 3072 12GB GDDR5 336GB/s 6.7 n/a