There’s a new GPU node in the gpu partition!

It’s notable for a list of reasons. This is the first node on Sherlock to feature both:

1. the latest generation of Intel CPUs (Skylake),
2. the latest generation of computing-optimized NVIDIA GPUs,

and it’s also the first node on Sherlock with 32GB GPUs, which is particularly interesting for a lot of Deep-Learning oriented workloads.

Specs

This compute node features:

• 24x Intel Skylake CPU cores (2x Xeon 5118, 2.30GHz),
• 192GB of memory (RAM),
• 4x NVIDIA Tesla V100 GPUs with 32GB of GPU memory each.

Details

Nodes in the gpu partition are now available to everyone on Sherlock, and the new node can be requested by adding the following flag to your job submission options: -C "GPU_SKU:V100_SXM2&GPU_MEM:32GB"

To request an interactive session on a Tesla V100 GPU with 32GB of memory, you can run:

$ srun -p gpu --gres gpu:1 -C "GPU_SKU:V100_SXM2&GPU_MEM:32GB" --pty bash

To see the list of all the available GPU features and characteristics that can be requested in the gpu partition:

$ sh_node_feat -p gpu | grep GPU
GPU_BRD:GEFORCE
GPU_BRD:TESLA
GPU_CC:3.5
GPU_CC:3.7
GPU_CC:5.2
GPU_CC:6.0
GPU_CC:6.1
GPU_CC:7.0
GPU_GEN:KPL
GPU_GEN:MXW
GPU_GEN:PSC
GPU_GEN:VLT
GPU_MEM:12GB
GPU_MEM:16GB
GPU_MEM:24GB
GPU_MEM:32GB
GPU_MEM:6GB
GPU_SKU:K20X
GPU_SKU:K80
GPU_SKU:P100_PCIE
GPU_SKU:P100_SXM2
GPU_SKU:P40
GPU_SKU:TITAN_BLACK
GPU_SKU:TITAN_X
GPU_SKU:TITAN_Xp
GPU_SKU:V100_SXM2

For more details about GPUs on Sherlock, see the GPU user guide.

If you have any question, feel free to send us a note at [email protected].