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SBG Nodes

SR670

We have 2 Lenovo ThinkSystem SR670 nodes containing Nvidia Tesla V100 cards for GPU jobs.

SBG Lenovo ThinkSystem SR670
Count 2
Processor 2 x 16 Core Intel Xeon Gold 6142 (Skylake)
Cores/Node 32
RAM 384GB
TMP Size 1.2TB
Interconnect 25Gb Ethernet
GPU 2 x NVIDIA Tesla V100 (up to maximum of 4)
GPU architecture Volta
Tensor Cores 640
CUDA Cores 5,120
GPU Memory 16GiB per GPU
CUDA Compute 7.0 (CUDA version 9 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, so that we can verify that the jobs will use the GPUs correctly. More detail is on the using GPUs section.

Half-node jobs

Please ensure that you specify system (as opposed to GPU) RAM carefully when requesting a "half-node job" (i.e. to make use of a single GPU). Remember that CPU memory is per core, so if you are using 1 GPU and 16 CPU cores, setting -l h_vmem=11.5G, will request 184GB of system RAM.