Wiki source code of GPU Server
Last modified by Thomas Coelho (local) on 2024/10/01 13:47
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1 | {{box cssClass="floatinginfobox" title="**Contents**"}} | ||
2 | {{toc/}} | ||
3 | {{/box}} | ||
4 | |||
5 | = The GPU Server = | ||
6 | |||
7 | The GPU machine is a two socket server with AMD EPYC 7313 processors. One processor a 16 Cores, actually with SMT enabled (32 Threads). It comes with 512 GB of memory and 2 x 4 TB U.3 (NVMe) SSDs as fast storage. There are** 8 AMD Instinct Mi 50** GPU cards for computing. | ||
8 | |||
9 | Access is given by SLURM and the separate partition "gpu". | ||
10 | |||
11 | As software stack AMD ROCm is installed. This supports the ROCm and openCL interface. Current ROCm Stack is version 6.2.1. | ||
12 | |||
13 | (% class="box infomessage" %) | ||
14 | ((( | ||
15 | Because GPU computing is a new discipline, we can only provide limited information here. If you have something to share, please fell free to edit this page. | ||
16 | ))) | ||
17 | |||
18 | == Submitting == | ||
19 | |||
20 | GPUs are handled as generic resources in Slurm (gres). | ||
21 | |||
22 | Each GPU is handled as allocatable item. You can allocate up to 8 GPUs. You can do this by adding "~-~-gres=gpu:N", where N is the number of CPUs. | ||
23 | |||
24 | CPUs are handled as usual. | ||
25 | |||
26 | Example: Interative Seesion with 2 GPUs: | ||
27 | |||
28 | {{code language="bash"}} | ||
29 | srun -p gpu --gres=gpu:2 --pty bash | ||
30 | {{/code}} | ||
31 | |||
32 | == PyTorch == | ||
33 | |||
34 | A popular framework for machine learning is PyTorch. An up-to-date version with ROCm support must be installed with pip3 in a venv. | ||
35 | |||
36 | {{code language="bash"}} | ||
37 | python3 -m venv venc | ||
38 | . venv/bin/activate | ||
39 | {{/code}} | ||
40 | |||
41 | Install Pytorch: | ||
42 | |||
43 | {{code language="bash"}} | ||
44 | pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.0 | ||
45 | |||
46 | |||
47 | {{/code}} | ||
48 | |||
49 | At time of writing it's not available for 6.1. Please check the pytorch Website for updates. | ||
50 | |||
51 | You can test the installation with | ||
52 | |||
53 | {{code language="python"}} | ||
54 | import torch | ||
55 | |||
56 | print(torch.cuda.is_available()) | ||
57 | |||
58 | {{/code}} | ||
59 | |||
60 | == Links == | ||
61 | |||
62 | GPU Cards: [[https:~~/~~/www.amd.com/en/products/professional-graphics/instinct-mi50>>https://www.amd.com/en/products/professional-graphics/instinct-mi50]] | ||
63 | |||
64 | ROCm documentation: [[https:~~/~~/rocm.docs.amd.com/en/latest/rocm.html>>https://rocm.docs.amd.com/en/latest/rocm.html]] | ||
65 | |||
66 | Pytorch: [[https:~~/~~/pytorch.org/>>https://pytorch.org/]] | ||
67 | |||
68 | |||
69 |