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NVIDIA GeForce RTX 4060 Laptop GPU CUDA Conda Windows 가상환경 설치
hwpform
2024. 5. 15. 11:20
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- PC환경 정보
o Windows 11에서 conda 가상환경에서 GPU 인식하기
o Windows 환경정보 ( DXDIAG 명령어로 확인)
-Windows 11 Pro 64-bit (10.0, Build 22631) (22621.ni_release.220506-1250)
13th Gen Intel(R) Core(TM) i7-13620H (16 CPUs), ~2.4GHz
- NVIDIA GeForce RTX 4060 Laptop GPU\
o Windows 에 NVIDIA 설치 정보
- NVIDIA CUDA Version : 12.4
- NVIDIA Cunna Version : 8.9
- Windows Conda 가상환경에서 GPU를 사용하려면 다음과 같은 제약조건이 인터넷 검색결과로 나옴
o NVIDIA CUDA Version : 11.x 이하일것
o NVIDIA Cunna Version : 8.x 이하일것
o Python : 3.10.x 이하일것
o Tensorflow 2.10.x 이하일것
위의 제약조건에 맞게 Conda 가상환경을 만들어 보고 가상환경에서 GPU가 인식되는지 테스트 해봄
- Cuda-SDK 다운로드 사이트 https://developer.nvidia.com/cuda-toolkit-archive
CUDA Toolkit Archive
Previous releases of the CUDA Toolkit, GPU Computing SDK, documentation and developer drivers can be found using the links below. Please select the release you want from the list below, and be sure to check www.nvidia.com/drivers for more recent production
developer.nvidia.com
- cuda cudnn archive 사이트 https://developer.nvidia.com/rdp/cudnn-archive
cuDNN Archive
Download releases from the GPU-accelerated primitive library for deep neural networks.
developer.nvidia.com
- NVIDIA 그래픽카드 지원 확인 사이트 https://en.wikipedia.org/wiki/CUDA#GPUs_supported
CUDA - Wikipedia
From Wikipedia, the free encyclopedia Parallel computing platform and programming model Compute Unified Device Architecture (CUDA) is a proprietary[1] parallel computing platform and application programming interface (API) that allows software to use certa
en.wikipedia.org
- NVIDIA Drive 확인 Nvidia-smi
# C:\Users\shim>nvidia-smi
Wed May 15 12:16:12 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 552.44 Driver Version: 552.44 CUDA Version: 12.4 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name TCC/WDDM | 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 4060 ... WDDM | 00000000:01:00.0 Off | N/A |
| N/A 44C P8 1W / 80W | 0MiB / 8188MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
- NVIDIA Cuda 확인 nvcc -V
# C:\Users\shim>nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2024 NVIDIA Corporation
Built on Thu_Mar_28_02:30:10_Pacific_Daylight_Time_2024
Cuda compilation tools, release 12.4, V12.4.131
Build cuda_12.4.r12.4/compiler.34097967_0
conda를 통한 가상환경 생성 및 GPU 확인
- conda에서 가상환경 설치하기
# 설치요약
1. 가상환경 디렉토리를 cuda 로 설정
2. python 3.10 설치
3. cudatoolkit 11.2 설치
4. cudnn=8.1.0 설치
5. Tensorflow 2.10 설치
# (base) C:\Users\shim>conda create -n cuda python=3.10
Channels:
- defaults
Platform: win-64
Collecting package metadata (repodata.json): done
Solving environment: done
<< Package Plan >>
environment location: C:\Users\shim\anaconda3\envs\cuda
added / updated specs:
- python=3.10
The following packages will be downloaded:
package | build
---------------------------|-----------------
pip-24.0 | py310haa95532_0 2.9 MB
python-3.10.14 | he1021f5_1 15.9 MB
setuptools-69.5.1 | py310haa95532_0 1013 KB
wheel-0.43.0 | py310haa95532_0 136 KB
------------------------------------------------------------
Total: 20.0 MB
The following NEW packages will be INSTALLED:
bzip2 pkgs/main/win-64::bzip2-1.0.8-h2bbff1b_6
ca-certificates pkgs/main/win-64::ca-certificates-2024.3.11-haa95532_0
libffi pkgs/main/win-64::libffi-3.4.4-hd77b12b_1
openssl pkgs/main/win-64::openssl-3.0.13-h2bbff1b_1
pip pkgs/main/win-64::pip-24.0-py310haa95532_0
python pkgs/main/win-64::python-3.10.14-he1021f5_1
setuptools pkgs/main/win-64::setuptools-69.5.1-py310haa95532_0
sqlite pkgs/main/win-64::sqlite-3.45.3-h2bbff1b_0
tk pkgs/main/win-64::tk-8.6.14-h0416ee5_0
tzdata pkgs/main/noarch::tzdata-2024a-h04d1e81_0
vc pkgs/main/win-64::vc-14.2-h21ff451_1
vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.27.29016-h5e58377_2
wheel pkgs/main/win-64::wheel-0.43.0-py310haa95532_0
xz pkgs/main/win-64::xz-5.4.6-h8cc25b3_1
zlib pkgs/main/win-64::zlib-1.2.13-h8cc25b3_1
Proceed ([y]/n)? y
Downloading and Extracting Packages:
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
To activate this environment, use
$ conda activate cuda
To deactivate an active environment, use
$ conda deactivate
# (base) C:\Users\shim>conda env list
conda environments:
base * C:\Users\shim\anaconda3
cuda C:\Users\shim\anaconda3\envs\cuda
llm C:\Users\shim\anaconda3\envs\llm
textgen2 C:\Users\shim\anaconda3\envs\textgen2
# (base) C:\Users\shim>conda activate cuda
# (cuda) C:\Users\shim>conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0
Channels:
- conda-forge
- defaults
Platform: win-64
Collecting package metadata (repodata.json): done
Solving environment: done
<< Package Plan >>
environment location: C:\Users\shim\anaconda3\envs\cuda
added / updated specs:
- cudatoolkit=11.2
- cudnn=8.1.0
The following packages will be downloaded:
package | build
---------------------------|-----------------
cudatoolkit-11.2.2 | h7d7167e_13 634.5 MB conda-forge
cudnn-8.1.0.77 | h3e0f4f4_0 610.8 MB conda-forge
"By downloading and using the cuDNN conda packages, you accept the terms and conditions of the NVID
done
# (cuda) C:\Users\shim>python -m pip install "tensorflow<2.11"
Collecting tensorflow<2.11
Downloading tensorflow-2.10.1-cp310-cp310-win_amd64.whl.metadata (3.1 kB)
Collecting absl-py>=1.0.0 (from tensorflow<2.11)
Using cached absl_py-2.1.0-py3-none-any.whl.metadata (2.3 kB)
... 중간 생략
Downloading pyasn1_modules-0.4.0-py3-none-any.whl (181 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 181.2/181.2 kB 5.5 MB/s eta 0:00:00
Using cached urllib3-2.2.1-py3-none-any.whl (121 kB)
Downloading oauthlib-3.2.2-py3-none-any.whl (151 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 151.7/151.7 kB 4.6 MB/s eta 0:00:00
Downloading pyasn1-0.6.0-py2.py3-none-any.whl (85 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 85.3/85.3 kB ? eta 0:00:00
Installing collected packages: tensorboard-plugin-wit, libclang, keras, flatbuffers, wrapt, urllib3, typing-extensions, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, six, pyasn1, protobuf, packaging, oauthlib, numpy, MarkupSafe, markdown, idna, grpcio, gast, charset-normalizer, certifi, cachetools, absl-py, werkzeug, rsa, requests, pyasn1-modules, opt-einsum, keras-preprocessing, h5py, google-pasta, astunparse, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow
Successfully installed MarkupSafe-2.1.5 absl-py-2.1.0 astunparse-1.6.3 cachetools-5.3.3 certifi-2024.2.2 charset-normalizer-3.3.2 flatbuffers-24.3.25 gast-0.4.0 google-auth-2.29.0 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 grpcio-1.63.0 h5py-3.11.0 idna-3.7 keras-2.10.0 keras-preprocessing-1.1.2 libclang-18.1.1 markdown-3.6 numpy-1.26.4 oauthlib-3.2.2 opt-einsum-3.3.0 packaging-24.0 protobuf-3.19.6 pyasn1-0.6.0 pyasn1-modules-0.4.0 requests-2.31.0 requests-oauthlib-2.0.0 rsa-4.9 six-1.16.0 tensorboard-2.10.1 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.10.1 tensorflow-estimator-2.10.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.4.0 typing-extensions-4.11.0 urllib3-2.2.1 werkzeug-3.0.3 wrapt-1.16.0
- conda 가상환경 GPU 확인 실행 테스트 및 결과
# (cuda) C:\Users\shim>python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
# (cuda) C:\Users\shim>python
Python 3.10.14 | packaged by Anaconda, Inc. | (main, May 6 2024, 19:44:50) [MSC v.1916 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
# >>> from tensorflow.python.client import device_lib
# >>> device_lib.list_local_devices()
2024-05-15 11:54:20.473703: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /device:GPU:0 with 5449 MB memory: -> device: 0, name: NVIDIA GeForce RTX 4060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.9
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 11119453684472034767
xla_global_id: -1
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 5713690624
locality {
bus_id: 1
links {
}
}
incarnation: 4304763808021192206
physical_device_desc: "device: 0, name: NVIDIA GeForce RTX 4060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.9"
xla_global_id: 416903419
]
# >>> gpus = tf.config.experimental.list_physical_devices('GPU')
# >>> for gpu in gpus:
... print(gpu)
...
PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')
# >>> import tensorflow as tf
# >>> print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices('GPU')))
Num GPUs Available: 1
- Vitual Studio Code 에서 실행결과
# 파이선 코드
import tensorflow as tf
from tensorflow.python.client import device_lib
print(device_lib.list_local_devices())
print("Num GPUs AVAILABLE: ", len(tf.config.list_physical_devices('GPU')))
# 실행결과
PS C:\Users\shim\anaconda3\envs\cuda> & c:/Users/shim/anaconda3/envs/cuda/python.exe c:/Users/shim/anaconda3/envs/cuda/cuda_gpu_test.py
2024-05-15 12:53:21.191667: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-05-15 12:53:21.806525: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1616] Created device /device:GPU:0 with 5449 MB memory: -> device: 0, name: NVIDIA GeForce RTX 4060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.9
[name: "/device:CPU:0"
device_type: "CPU"
memory_limit: 268435456
locality {
}
incarnation: 18426872582674291349
xla_global_id: -1
, name: "/device:GPU:0"
device_type: "GPU"
memory_limit: 5713690624
locality {
bus_id: 1
links {
}
}
incarnation: 3688180905390782346
physical_device_desc: "device: 0, name: NVIDIA GeForce RTX 4060 Laptop GPU, pci bus id: 0000:01:00.0, compute capability: 8.9"
xla_global_id: 416903419
]
Num GPUs AVAILABLE: 1
- conda 가상환경 패키지 설치 정보 확인
# conda 환경에 cudatoolkit 11.2.2, cudnn 8.1.0.77, python 3.10.14, tensorflow 2.10.1이
설치되어 있는것을 확인할수 있다.
#(cuda) C:\Users\shim\anaconda3\envs\cuda>conda list
packages in environment at C:\Users\shim\anaconda3\envs\cuda:
$ Name Version Build Channel
absl-py 2.1.0 pypi_0 pypi
astunparse 1.6.3 pypi_0 pypi
bzip2 1.0.8 h2bbff1b_6
ca-certificates 2024.3.11 haa95532_0
cachetools 5.3.3 pypi_0 pypi
certifi 2024.2.2 pypi_0 pypi
charset-normalizer 3.3.2 pypi_0 pypi
cudatoolkit 11.2.2 h7d7167e_13 conda-forge
cudnn 8.1.0.77 h3e0f4f4_0 conda-forge
flatbuffers 24.3.25 pypi_0 pypi
gast 0.4.0 pypi_0 pypi
google-auth 2.29.0 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.63.0 pypi_0 pypi
h5py 3.11.0 pypi_0 pypi
idna 3.7 pypi_0 pypi
keras 2.10.0 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
libclang 18.1.1 pypi_0 pypi
libffi 3.4.4 hd77b12b_1
markdown 3.6 pypi_0 pypi
markupsafe 2.1.5 pypi_0 pypi
numpy 1.26.4 pypi_0 pypi
oauthlib 3.2.2 pypi_0 pypi
openssl 3.3.0 hcfcfb64_0 conda-forge
opt-einsum 3.3.0 pypi_0 pypi
packaging 24.0 pypi_0 pypi
pip 24.0 py310haa95532_0
protobuf 3.19.6 pypi_0 pypi
pyasn1 0.6.0 pypi_0 pypi
pyasn1-modules 0.4.0 pypi_0 pypi
python 3.10.14 he1021f5_1
requests 2.31.0 pypi_0 pypi
requests-oauthlib 2.0.0 pypi_0 pypi
rsa 4.9 pypi_0 pypi
setuptools 69.5.1 py310haa95532_0
six 1.16.0 pypi_0 pypi
sqlite 3.45.3 h2bbff1b_0
tensorboard 2.10.1 pypi_0 pypi
tensorboard-data-server 0.6.1 pypi_0 pypi
tensorboard-plugin-wit 1.8.1 pypi_0 pypi
tensorflow 2.10.1 pypi_0 pypi
tensorflow-estimator 2.10.0 pypi_0 pypi
tensorflow-io-gcs-filesystem 0.31.0 pypi_0 pypi
termcolor 2.4.0 pypi_0 pypi
tk 8.6.14 h0416ee5_0
typing-extensions 4.11.0 pypi_0 pypi
tzdata 2024a h04d1e81_0
ucrt 10.0.22621.0 h57928b3_0 conda-forge
urllib3 2.2.1 pypi_0 pypi
vc 14.2 h21ff451_1
vc14_runtime 14.38.33130 h82b7239_18 conda-forge
vs2015_runtime 14.38.33130 hcb4865c_18 conda-forge
werkzeug 3.0.3 pypi_0 pypi
wheel 0.43.0 py310haa95532_0
wrapt 1.16.0 pypi_0 pypi
xz 5.4.6 h8cc25b3_1
zlib 1.2.13 h8cc25b3_1
(cuda) C:\Users\shim\anaconda3\envs\cuda>
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