https://blog.csdn.net/nwpushuai/article/details/79935740https://blog.csdn.net/qq_43030766/article/details/91513501https://blog.csdn.net/zhqh100/article/details/77646497https://www.cnblogs.com/zixuan-L/p/11023051.htmlhttps://blog.csdn.net/huangfei711/article/details/79230446https://www.cnblogs.com/yjlch1016/p/8641910.html
CPU I7-7700,8M,3.6GHZ,4核
RAM DDR4 16G
ハードディスクSSD500G
システムUbuntu16.04デスクトップ版（画像インターフェースが必要）
グラフィックカードNVDIAGeForce GTX1050Ti 4G
1. デュアルネットワークカードバインディング
root@mec03:~# cat /etc/modules
# /etc/modules: kernel modules to load at boot time.
#
# This file contains the names of kernel modules that should be loaded
# at boot time, one per line. Lines beginning with"#" are ignored.
bonding mode=0 miimon=100
root@mec03:/etc/network# cat /etc/network/interfaces
auto bond0
iface bond0 inet static
address 172.30.10.249
netmask 255.255.255.0
gateway 172.30.10.254
post-up ifenslave bond0 enp2s0 enp3s0
pre-down ifenslave -d bond0 enp2s0 enp3s0
rcで起動.ローカル内
root@mec03:/etc/network# modprobe bonding
ネットワークカード管理を閉じると、ボンディングと競合します
root@mec03:/etc/network# systemctl disable network-manager.service
2. apt-listソースを設定
root@mec03:~# cat /etc/apt/sources.list
deb http://mirrors.163.com/ubuntu/ xenial main restricted universe multiverse
deb http://mirrors.163.com/ubuntu/ xenial-security main restricted universe multiverse
deb http://mirrors.163.com/ubuntu/ xenial-updates main restricted universe multiverse
deb http://mirrors.163.com/ubuntu/ xenial-proposed main restricted universe multiverse
deb http://mirrors.163.com/ubuntu/ xenial-backports main restricted universe multiverse
deb-src http://mirrors.163.com/ubuntu/ xenial main restricted universe multiverse
deb-src http://mirrors.163.com/ubuntu/ xenial-security main restricted universe multiverse
deb-src http://mirrors.163.com/ubuntu/ xenial-updates main restricted universe multiverse
deb-src http://mirrors.163.com/ubuntu/ xenial-proposed main restricted universe multiverse
deb-src http://mirrors.163.com/ubuntu/ xenial-backports main restricted universe multiverse
3. デフォルトの言語設定
root@mec03:~# cat /etc/default/locale
# File generated by update-locale
# LANG="zh_CN.UTF-8"
# LANGUAGE="zh_CN:zh"
LANG="en_US.UTF-8"
LANGUAGE="en_US:en"
1. システムのデフォルトの組み込みnvidiaドライバーを無効にする
root@mec03:~# lsmod | grep nouveau
nouveau 17244161
mxm_wmi 163841 nouveau
wmi 245762 mxm_wmi,nouveau
i2c_algo_bit 163841 nouveau
ttm 1064961 nouveau
drm_kms_helper 1720321 nouveau
drm 4014084 drm_kms_helper,ttm,nouveau
video 450561 nouveau
2. モジュールを無効にする
root@mec03:~# vim /etc/modprobe.d/blacklist.conf
ファイルの最後に次の行を追加します。
blacklist vga16fb
blacklist nouveau
blacklist rivafb
blacklist rivatv
blacklist nvidiafb
3. カーネルの更新
root@mec03:~# update-initramfs -u
update-initramfs: Generating /boot/initrd.img-4.15.0-45-generic
4. 再起動
root@mec03:~# reboot
5. cudnn_cudn.zipパッケージをアップロード
root@mec03:~# rz
root@mec03:~# ls
cudnn_cuda cudnn_cuda.zip
root@mec03:~# cd cudnn_cuda/
root@mec03:~/cudnn_cuda# ls
cuda_10.0.130.1_linux.run libcudnn7-dev_7.6.3.30-1+cuda10.0_amd64.deb
cuda_10.0.130_410.48_linux.run libcudnn7-doc_7.6.3.30-1+cuda10.0_amd64.deb
libcudnn7_7.6.3.30-1+cuda10.0_amd64.deb NVIDIA-Linux-x86_64-435.21.run
6. ドライバをインストール
root@mec03:~/cudnn_cuda# systemctl stop lightdm.service
root@mec03:~/cudnn_cuda# sh NVIDIA-Linux-x86_64-435.21.run
Verifying archive integrity... OK
Uncompressing NVIDIA Accelerated Graphics Driver for Linux-x86_64 435.21........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
root@mec03:~/cudnn_cuda# lsmod | grep nvi
nvidia_drm 450560
nvidia_modeset 11182081 nvidia_drm
nvidia 194723841 nvidia_modeset
drm_kms_helper 1720321 nvidia_drm
drm 4014083 drm_kms_helper,nvidia_drm
ipmi_msghandler 532482 ipmi_devintf,nvidia
root@mec03:~/cudnn_cuda# sh cuda_10.0.130_410.48_linux.run
Do you accept the previously read EULA?
accept/decline/quit: accept
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 410.48?(y)es/(n)o/(q)uit: n
Install the CUDA 10.0 Toolkit?(y)es/(n)o/(q)uit: y
Enter Toolkit Location
[ default is /usr/local/cuda-10.0]:
Do you want to install a symbolic link at /usr/local/cuda?(y)es/(n)o/(q)uit: y
Install the CUDA 10.0 Samples?(y)es/(n)o/(q)uit: y
Enter CUDA Samples Location
[ default is /root ]:
Installing the CUDA Toolkit in/usr/local/cuda-10.0...
Installing the CUDA Toolkit in/usr/local/cuda-10.0...
Missing recommended library: libGLU.so
Missing recommended library: libX11.so
Missing recommended library: libXi.so
Missing recommended library: libXmu.so
Installing the CUDA Samples in/root ...
Copying samples to /root/NVIDIA_CUDA-10.0_Samples now...
Finished copying samples.============ Summary ============
Driver: Not Selected
Toolkit: Installed in/usr/local/cuda-10.0
Samples: Installed in/root, but missing recommended libraries
Please make sure that
- PATH includes /usr/local/cuda-10.0/bin
- LD_LIBRARY_PATH includes /usr/local/cuda-10.0/lib64, or, add /usr/local/cuda-10.0/lib64 to /etc/ld.so.conf and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in/usr/local/cuda-10.0/bin
Please see CUDA_Installation_Guide_Linux.pdf in/usr/local/cuda-10.0/doc/pdf for detailed information on setting up CUDA.***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 10.0 functionality to work.
To install the driver using this installer, run the following command, replacing <CudaInstaller>with the name ofthis run file:
sudo <CudaInstaller>.run -silent -driver
Logfile is /tmp/cuda_install_9752.log
root@mec03:~/cudnn_cuda# vim /etc/ld.so.conf
root@mec03:~/cudnn_cuda# ldconfig
root@mec03:~# cat /etc/profile
export PATH=/usr/local/cuda-10.0/bin${PATH:+:${PATH}}export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}export CUDA_HOME=/usr/local/cuda
root@mec03:~# nvcc --version
nvcc:NVIDIA(R) Cuda compiler driver
Copyright(c)2005-2018 NVIDIA Corporation
Built on Sat_Aug_25_21:08:01_CDT_2018
Cuda compilation tools, release 10.0, V10.0.130
root@mec03:~/cudnn_cuda# dpkg -i libcudnn7_7.6.3.30-1+cuda10.0_amd64.deb
Selecting previously unselected package libcudnn7.(Reading database ...184057 files and directories currently installed.)
Preparing to unpack libcudnn7_7.6.3.30-1+cuda10.0_amd64.deb ...
Unpacking libcudnn7(7.6.3.30-1+cuda10.0)...
Setting up libcudnn7(7.6.3.30-1+cuda10.0)...
Processing triggers for libc-bin(2.23-0ubuntu11)...
root@mec03:~/cudnn_cuda# dpkg -i libcudnn7-dev_7.6.3.30-1+cuda10.0_amd64.deb
Selecting previously unselected package libcudnn7-dev.(Reading database ...184063 files and directories currently installed.)
Preparing to unpack libcudnn7-dev_7.6.3.30-1+cuda10.0_amd64.deb ...
Unpacking libcudnn7-dev(7.6.3.30-1+cuda10.0)...
Setting up libcudnn7-dev(7.6.3.30-1+cuda10.0)...
update-alternatives: using /usr/include/x86_64-linux-gnu/cudnn_v7.h to provide /usr/include/cudnn.h(libcudnn)in auto mode
root@mec03:~/cudnn_cuda# dpkg -i libcudnn7-doc_7.6.3.30-1+cuda10.0_amd64.deb
Selecting previously unselected package libcudnn7-doc.(Reading database ...184069 files and directories currently installed.)
Preparing to unpack libcudnn7-doc_7.6.3.30-1+cuda10.0_amd64.deb ...
Unpacking libcudnn7-doc(7.6.3.30-1+cuda10.0)...
Setting up libcudnn7-doc(7.6.3.30-1+cuda10.0)...
root@mec03:~/cudnn_cuda# cp /usr/include/cudnn.h /usr/local/cuda/include
root@mec03:~/cudnn_cuda# cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
# define CUDNN_MAJOR 7
# define CUDNN_MINOR 6
# define CUDNN_PATCHLEVEL 3--
# define CUDNN_VERSION(CUDNN_MAJOR *1000+ CUDNN_MINOR *100+ CUDNN_PATCHLEVEL)
# include "driver_types.h"
**1. python3.6 **をインストールします
root@mec03:~# add-apt-repository ppa:jonathonf/python-3.6
A plain backport of*just* Python 3.6. System extensions/Python libraries may or may not work.
Don't remove Python 3.5from your system - it will break.
More info: https://launchpad.net/~jonathonf/+archive/ubuntu/python-3.6
Press [ENTER] to continue or ctrl-c to cancel adding it
gpg: keyring `/tmp/tmpec5st1dk/secring.gpg' created
gpg: keyring `/tmp/tmpec5st1dk/pubring.gpg' created
gpg: requesting key F06FC659 from hkp server keyserver.ubuntu.com
gpg:/tmp/tmpec5st1dk/trustdb.gpg: trustdb created
gpg: key F06FC659:public key "Launchpad PPA for J Fernyhough" imported
gpg: Total number processed:1
gpg: imported:1(RSA:1)
OK
root@mec03:~# update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.51
update-alternatives: using /usr/bin/python3.5 to provide /usr/bin/python3(python3)in auto mode
root@mec03:~# update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.62
update-alternatives: using /usr/bin/python3.6 to provide /usr/bin/python3(python3)in auto mode
root@mec03:~# update-alternatives --install /usr/bin/python python /usr/bin/python2 100
update-alternatives: using /usr/bin/python2 to provide /usr/bin/python(python)in auto mode
root@mec03:~# update-alternatives --install /usr/bin/python python /usr/bin/python3 150
update-alternatives: using /usr/bin/python3 to provide /usr/bin/python(python)in auto mode
root@mec03:~# python3
Python 3.6.8(default, May 72019,14:58:50)[GCC 5.4.020160609] on linux
Type "help","copyright","credits" or "license"for more information.>>>
**2. pip3 **をインストールします
root@mec03:~# apt install python3-pip
3. tensorflowをインストールします
root@mec03:~# pip3 install tensorflow-gpu==1.13.1-i https://pypi.tuna.tsinghua.edu.cn/simple
Collecting tensorflow-gpu==1.13.1
4. gpuをテスト
pythonステートメントをテストする
import numpy
import tensorflow as tf
a = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[2, 3], name='a')
b = tf.constant([1.0, 2.0, 3.0, 4.0, 5.0, 6.0], shape=[3, 2], name='b')
c = tf.matmul(a, b)
sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
print(sess.run(c))
root@mec03:~# python3
Python 3.6.8(default, May 72019,14:58:50)[GCC 5.4.020160609] on linux
Type "help","copyright","credits" or "license"for more information.>>>import numpy
ement=True))print(sess.run(c))>>>import tensorflow as tf
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:526: FutureWarning:Passing(type,1) or '1type'as a synonym of type is deprecated;in a future version of numpy, it will be understood as(type,(1,))/'(1,)type'.
_ np_qint8 = np.dtype([("qint8", np.int8,1)])/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:527: FutureWarning:Passing(type,1) or '1type'as a synonym of type is deprecated;in a future version of numpy, it will be understood as(type,(1,))/'(1,)type'.
_ np_quint8 = np.dtype([("quint8", np.uint8,1)])/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:528: FutureWarning:Passing(type,1) or '1type'as a synonym of type is deprecated;in a future version of numpy, it will be understood as(type,(1,))/'(1,)type'.
_ np_qint16 = np.dtype([("qint16", np.int16,1)])/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:529: FutureWarning:Passing(type,1) or '1type'as a synonym of type is deprecated;in a future version of numpy, it will be understood as(type,(1,))/'(1,)type'.
_ np_quint16 = np.dtype([("quint16", np.uint16,1)])/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:530: FutureWarning:Passing(type,1) or '1type'as a synonym of type is deprecated;in a future version of numpy, it will be understood as(type,(1,))/'(1,)type'.
_ np_qint32 = np.dtype([("qint32", np.int32,1)])/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/dtypes.py:535: FutureWarning:Passing(type,1) or '1type'as a synonym of type is deprecated;in a future version of numpy, it will be understood as(type,(1,))/'(1,)type'.
np_resource = np.dtype([("resource", np.ubyte,1)])>>> a = tf.constant([1.0,2.0,3.0,4.0,5.0,6.0], shape=[2,3], name='a')>>> b = tf.constant([1.0,2.0,3.0,4.0,5.0,6.0], shape=[3,2], name='b')>>> c = tf.matmul(a, b)>>> sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))2019-09-1412:27:18.309361: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019- 09- 1412:27:18.360212: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:998] successful NUMA node read from SysFS had negative value(-1), but there must be at least one NUMA node, so returning NUMA node zero
2019- 09- 1412:27:18.360498: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x3bb3a20 executing computations on platform CUDA. Devices:2019-09-1412:27:18.360512: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device(0): GeForce GTX 1050 Ti, Compute Capability 6.12019-09-1412:27:18.379184: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:3600000000 Hz
2019- 09- 1412:27:18.380446: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x3ccb2f0 executing computations on platform Host. Devices:2019-09-1412:27:18.380503: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device(0):<undefined>,<undefined>2019-09-1412:27:18.380792: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1433] Found device 0with properties:
name: GeForce GTX 1050 Ti major:6 minor:1memoryClockRate(GHz):1.392
pciBusID:0000:01:00.0
totalMemory:3.94GiB freeMemory:3.66GiB
2019- 09- 1412:27:18.380852: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1512] Adding visible gpu devices:02019-09-1412:27:18.382037: I tensorflow/core/common_runtime/gpu/gpu_device.cc:984] Device interconnect StreamExecutor with strength 1 edge matrix:2019-09-1412:27:18.382075: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990]02019-09-1412:27:18.382090: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1003]0: N
2019- 09- 1412:27:18.382242: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1115] Created TensorFlow device(/job:localhost/replica:0/task:0/device:GPU:0with3452 MB memory)-> physical GPU(device:0, name: GeForce GTX 1050 Ti, pci bus id:0000:01:00.0, compute capability:6.1)
Device mapping:/job:localhost/replica:0/task:0/device:XLA_GPU:0-> device: XLA_GPU device
/job:localhost/replica:0/task:0/device:XLA_CPU:0-> device: XLA_CPU device
/job:localhost/replica:0/task:0/device:GPU:0-> device:0, name: GeForce GTX 1050 Ti, pci bus id:0000:01:00.0, compute capability:6.12019-09-1412:27:18.384493: I tensorflow/core/common_runtime/direct_session.cc:317] Device mapping:/job:localhost/replica:0/task:0/device:XLA_GPU:0-> device: XLA_GPU device
/job:localhost/replica:0/task:0/device:XLA_CPU:0-> device: XLA_CPU device
/job:localhost/replica:0/task:0/device:GPU:0-> device:0, name: GeForce GTX 1050 Ti, pci bus id:0000:01:00.0, compute capability:6.1>>>print(sess.run(c))
MatMul:(MatMul):/job:localhost/replica:0/task:0/device:GPU:02019-09-1412:27:20.118473: I tensorflow/core/common_runtime/placer.cc:1059] MatMul:(MatMul)/job:localhost/replica:0/task:0/device:GPU:0
a:(Const):/job:localhost/replica:0/task:0/device:GPU:02019-09-1412:27:20.118492: I tensorflow/core/common_runtime/placer.cc:1059] a:(Const)/job:localhost/replica:0/task:0/device:GPU:0
b:(Const):/job:localhost/replica:0/task:0/device:GPU:02019-09-1412:27:20.118502: I tensorflow/core/common_runtime/placer.cc:1059] b:(Const)/job:localhost/replica:0/task:0/device:GPU:0[[22.28.][49.64.]]>>>
5. GPUの使用状況を表示
root@mec03:~# nvidia-smi
Fri Sep 619:42:422019+-----------------------------------------------------------------------------+| Processes: GPU Memory || GPU PID Type Process name Usage ||=============================================================================||09558 C python3 3865MiB ||012510 G /usr/lib/xorg/Xorg 39MiB ||012608 G gnome-shell 38MiB |+-----------------------------------------------------------------------------+
Fri Sep 600:22:272019+-----------------------------------------------------------------------------+| NVIDIA-SMI 435.21 Driver Version:435.21 CUDA Version:10.1||-------------------------------+----------------------+----------------------+| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC || Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M.||===============================+======================+======================||0 GeForce GTX 105... Off |00000000:01:00.0 On | N/A ||31% 62C P0 N/A / 80W | 3955MiB / 4038MiB |97% Default |+-------------------------------+----------------------+----------------------++-----------------------------------------------------------------------------+| Processes: GPU Memory || GPU PID Type Process name Usage ||=============================================================================||09558 C python3 3865MiB ||012510 G /usr/lib/xorg/Xorg 39MiB ||012608 G gnome-shell 38MiB |+-----------------------------------------------------------------------------+
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