大服务器bim-PowerEdge-R730，显卡型号：
Tesla P100-PCIE
(base) bim@bim-PowerEdge-R730:~$ conda create -n wind_paddle python==3.7 Collecting package metadata (current_repodata.json): done Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source. Collecting package metadata (repodata.json): done Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.11.0 latest version: 4.12.0 Please update conda by running $ conda update -n base -c defaults conda ## Package Plan ## environment location: /home/bim/miniconda3/envs/wind_paddle added / updated specs: - python==3.7 The following packages will be downloaded: package | build ---------------------------|----------------- libffi-3.2.1 | he1b5a44_1007 47 KB conda-forge libgcc-ng-11.2.0 | h1d223b6_14 906 KB conda-forge libgomp-11.2.0 | h1d223b6_14 429 KB conda-forge libstdcxx-ng-11.2.0 | he4da1e4_14 4.2 MB conda-forge openssl-1.0.2u | h516909a_0 3.2 MB conda-forge pip-22.0.4 | pyhd8ed1ab_0 1.5 MB conda-forge python-3.7.0 | hd21baee_1006 31.5 MB conda-forge python_abi-3.7 | 2_cp37m 4 KB conda-forge readline-7.0 | hf8c457e_1001 391 KB conda-forge setuptools-60.10.0 | py37h89c1867_0 1.2 MB conda-forge sqlite-3.28.0 | h8b20d00_0 1.9 MB conda-forge ------------------------------------------------------------ Total: 45.3 MB The following NEW packages will be INSTALLED: _libgcc_mutex conda-forge/linux-64::_libgcc_mutex-0.1-conda_forge _openmp_mutex conda-forge/linux-64::_openmp_mutex-4.5-1_gnu bzip2 conda-forge/linux-64::bzip2-1.0.8-h7f98852_4 ca-certificates conda-forge/linux-64::ca-certificates-2021.10.8-ha878542_0 libffi conda-forge/linux-64::libffi-3.2.1-he1b5a44_1007 libgcc-ng conda-forge/linux-64::libgcc-ng-11.2.0-h1d223b6_14 libgomp conda-forge/linux-64::libgomp-11.2.0-h1d223b6_14 libstdcxx-ng conda-forge/linux-64::libstdcxx-ng-11.2.0-he4da1e4_14 libzlib conda-forge/linux-64::libzlib-1.2.11-h36c2ea0_1013 ncurses conda-forge/linux-64::ncurses-6.3-h9c3ff4c_0 openssl conda-forge/linux-64::openssl-1.0.2u-h516909a_0 pip conda-forge/noarch::pip-22.0.4-pyhd8ed1ab_0 python conda-forge/linux-64::python-3.7.0-hd21baee_1006 python_abi conda-forge/linux-64::python_abi-3.7-2_cp37m readline conda-forge/linux-64::readline-7.0-hf8c457e_1001 setuptools conda-forge/linux-64::setuptools-60.10.0-py37h89c1867_0 sqlite conda-forge/linux-64::sqlite-3.28.0-h8b20d00_0 tk conda-forge/linux-64::tk-8.6.12-h27826a3_0 wheel conda-forge/noarch::wheel-0.37.1-pyhd8ed1ab_0 xz conda-forge/linux-64::xz-5.2.5-h516909a_1 zlib conda-forge/linux-64::zlib-1.2.11-h36c2ea0_1013 Proceed ([y]/n)? y Downloading and Extracting Packages python-3.7.0 | 31.5 MB | ############################################################################ | 100% libgcc-ng-11.2.0 | 906 KB | ############################################################################ | 100% sqlite-3.28.0 | 1.9 MB | ############################################################################ | 100% libgomp-11.2.0 | 429 KB | ############################################################################ | 100% setuptools-60.10.0 | 1.2 MB | ############################################################################ | 100% pip-22.0.4 | 1.5 MB | ############################################################################ | 100% python_abi-3.7 | 4 KB | ############################################################################ | 100% readline-7.0 | 391 KB | ############################################################################ | 100% openssl-1.0.2u | 3.2 MB | ############################################################################ | 100% libffi-3.2.1 | 47 KB | ############################################################################ | 100% libstdcxx-ng-11.2.0 | 4.2 MB | ############################################################################ | 100% Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # # $ conda activate wind_paddle # # To deactivate an active environment, use # # $ conda deactivate (base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$ nvidia-smi Fri Mar 25 09:00:53 2022 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 470.103.01 Driver Version: 470.103.01 CUDA Version: 11.4 | |-------------------------------+----------------------+----------------------+ | 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 Tesla P100-PCIE... Off | 00000000:04:00.0 Off | 0 | | N/A 44C P0 25W / 250W | 4MiB / 12198MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ | 1 Tesla P100-PCIE... Off | 00000000:82:00.0 Off | 0 | | N/A 39C P0 27W / 250W | 4MiB / 12198MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 1129 G /usr/lib/xorg/Xorg 4MiB | | 1 N/A N/A 1129 G /usr/lib/xorg/Xorg 4MiB | +-----------------------------------------------------------------------------+ (base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$
(base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$ lspci | grep -i nvidia 04:00.0 3D controller: NVIDIA Corporation GP100GL [Tesla P100 PCIe 12GB] (rev a1) 82:00.0 3D controller: NVIDIA Corporation GP100GL [Tesla P100 PCIe 12GB] (rev a1) (base) bim@bim-PowerEdge-R730:~$ (base) bim@bim-PowerEdge-R730:~$
python -m pip install paddlepaddle-gpu==2.2.2.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
(wind_paddle) bim@bim-PowerEdge-R730:~$ (wind_paddle) bim@bim-PowerEdge-R730:~$ python Python 3.7.0 | packaged by conda-forge | (default, Nov 12 2018, 20:15:55) [GCC 7.3.0] :: Anaconda, Inc. on linux Type "help", "copyright", "credits" or "license" for more information. >>> >>> >>> >>> >>> import paddle >>> >>> >>> paddle.utils.run_check() Running verify PaddlePaddle program ... W0325 12:26:23.599056 2118 device_context.cc:447] Please NOTE: device: 0, GPU Compute Capability: 6.0, Driver API Version: 11.4, Runtime API Version: 11.2 W0325 12:26:23.633646 2118 device_context.cc:465] device: 0, cuDNN Version: 8.1. PaddlePaddle works well on 1 GPU. W0325 12:26:30.568997 2118 parallel_executor.cc:617] Cannot enable P2P access from 0 to 1 W0325 12:26:30.569025 2118 parallel_executor.cc:617] Cannot enable P2P access from 1 to 0 W0325 12:26:32.155738 2118 dynamic_loader.cc:258] You may need to install 'nccl2' from NVIDIA official website: https://developer.nvidia.com/nccl/nccl-downloadbefore install PaddlePaddle. WARNING:root:PaddlePaddle meets some problem with 2 GPUs. This may be caused by: 1. There is not enough GPUs visible on your system 2. Some GPUs are occupied by other process now 3. NVIDIA-NCCL2 is not installed correctly on your system. Please follow instruction on https://github.com/NVIDIA/nccl-tests to test your NCCL, or reinstall it following https://docs.nvidia.com/deeplearning/sdk/nccl-install-guide/index.html WARNING:root: Original Error is: (PreconditionNotMet) The third-party dynamic library (libnccl.so) that Paddle depends on is not configured correctly. (error code is libnccl.so: cannot open shared object file: No such file or directory) Suggestions: 1. Check if the third-party dynamic library (e.g. CUDA, CUDNN) is installed correctly and its version is matched with paddlepaddle you installed. 2. Configure third-party dynamic library environment variables as follows: - Linux: set LD_LIBRARY_PATH by `export LD_LIBRARY_PATH=...` - Windows: set PATH by `set PATH=XXX; (at /paddle/paddle/fluid/platform/dynload/dynamic_loader.cc:285) PaddlePaddle is installed successfully ONLY for single GPU! Let's start deep learning with PaddlePaddle now. >>> >>>
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