anaconda 업데이트 및 환경 추가

[jhgoh]

lapras에서 CUDA 드라이버 호환성을 위해 pytorch 를 업데이트 해야 함.
추가로 anaconda 업데이트 작업 진행.

>>> torch.cuda.is_available()
True
>>> t = torch.FloatTensor([1,2,3,4,5,6])
>>> t = t.to('cuda')
/store/sw/anaconda3/envs/torch220_cu121/lib/python3.12/site-packages/torch/cuda/__init__.py:218: UserWarning: 
NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.
If you want to use the NVIDIA GeForce RTX 5090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/

  warnings.warn(

jhgoh@lapras:~$ nvidia-smi 
Thu Dec 18 19:50:23 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.95.05              Driver Version: 580.95.05      CUDA Version: 13.0     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 5090        Off |   00000000:01:00.0 Off |                  N/A |
|  0%   25C    P8             21W /  600W |       2MiB /  32607MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

[jhgoh]

anacoda의 base 환경 업데이트.

(base) [root@hep:~]# conda update conda
Retrieving notices: ...working... done
Channels:
 - defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done

## Package Plan ##

  environment location: /store/sw/anaconda3

  added / updated specs:
    - conda


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    archspec-0.2.5             |     pyhd3eb1b0_0          48 KB
    ca-certificates-2025.12.2  |       h06a4308_0         125 KB
    certifi-2024.8.30          |   py38h06a4308_0         162 KB
    conda-24.9.2               |   py38h06a4308_0         910 KB
    frozendict-2.4.2           |   py38h5eee18b_0          55 KB
    openssl-3.0.18             |       hd6dcaed_0         4.5 MB
    ------------------------------------------------------------
                                           Total:         5.8 MB

The following NEW packages will be INSTALLED:

  frozendict         pkgs/main/linux-64::frozendict-2.4.2-py38h5eee18b_0 

The following packages will be UPDATED:

  archspec                               0.2.1-pyhd3eb1b0_0 --> 0.2.5-pyhd3eb1b0_0 
  ca-certificates                     2023.12.12-h06a4308_0 --> 2025.12.2-h06a4308_0 
  certifi                           2024.2.2-py38h06a4308_0 --> 2024.8.30-py38h06a4308_0 
  conda                               24.1.2-py38h06a4308_0 --> 24.9.2-py38h06a4308_0 
  openssl                                 3.0.13-h7f8727e_0 --> 3.0.18-hd6dcaed_0 


Proceed ([y]/n)? y

[jhgoh]

torch 환경 신규 생성

conda create -n torch291_cu130 -c conda-forge
conda activate torch291_cu130

torch 설치

pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu130

[jhgoh]

동작 확인 완료

(torch291_cu130) jhgoh@lapras:~$ python
Python 3.14.2 | packaged by Anaconda, Inc. | (main, Dec 15 2025, 17:36:41) [GCC 14.3.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True
>>> t = torch.FloatTensor([1,2,3])
>>> t = t.to('cuda')
>>> t
tensor([1., 2., 3.], device='cuda:0')
>>> t**2
tensor([1., 4., 9.], device='cuda:0')
>>>