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SBG Nodes

SR670

We have 4 Lenovo ThinkSystem SR670 nodes for GPU jobs. Three nodes contain 4 x Nvidia Tesla V100 cards, and 1 contains 4 x Nvidia Ampere A100 cards.

SBG1-3 Lenovo ThinkSystem SR670
Processor 2 x 16 Core Intel Xeon Gold 6142 (Skylake)
Cores/Node 32
RAM 384GB
TMP Size 1.2TB
Interconnect 25Gb Ethernet
GPU 4 x NVIDIA Tesla V100
GPU architecture Volta
Form Factor PCIe
Tensor Cores 640
CUDA Cores 5,120
GPU Memory 16GiB per GPU (32GiB in sbg3)
CUDA Compute 7.0 (CUDA version 9 or greater required)
SBG5 Lenovo ThinkSystem SR670
Processor 2 x 24 Core Intel Xeon Platinum 8268
Cores/Node 48
RAM 384GB
TMP Size 1.5TB
Interconnect 25Gb Ethernet
GPU 4 x NVIDIA Tesla A100
GPU architecture Ampere
Form Factor PCIe
Tensor Cores 432 3rd Generation
CUDA Cores 6,912
GPU Memory 40GiB per GPU
CUDA Compute 8.0 (CUDA version 11 or greater required)

Accessing the GPU nodes

Access is permitted to QMUL researchers upon request. Note that access to GPU nodes is not permitted for Undergraduate and MSc students. Please raise a support ticket by emailing its-research-support@qmul.ac.uk with a brief overview of intended use, an example of a typical job submission script, and links to any software repositories, so that we can verify that the jobs will use the GPUs correctly. Please see the using GPUs section for advice on submitting GPU jobs.