SBG Nodes¶
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 | 4 x NVIDIA Tesla V100 |
| 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, 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.