各種教學視頻或文檔資料 +QQ：635992897
一、基礎環境配置
0、apt-get update
1、sshd安裝
sudo apt-get install openssh-server
2、Vi重裝
apt-get install vim
3、Samba 安裝及配置
3.1 sudo apt-get install samba samba-common
3.2 配置如下：
# Cap the size of the individual log files (in KiB).
max log size = 1000
這些下面加
security = user
配置文件最下面加
[myshare]
comment = this is Linux share directory
path = /home/share
# public = yes
browseable = yes
writable = yes
user = system,ubuntu
create mask = 0755
force create mode = 0755
directory mask = 0755
force directory mode = 0755
available = yes
3.3.添加smb用戶
sudo smbpasswd -a smbuser
這裏一定要保證在linux系統中也有smbuser用戶，名稱可以自己定
3.4 錯誤處理
ubuntu14.04中文版裝好samba後，報各種錯，查看/var/log/samba日誌，發現也是報各種錯，最後處理髮現linux 下使用smbclient 訪問正常，Windows下訪問報如下：
"無法訪問。您可能沒有權限使用網絡資源，請與這臺服務器的管理員聯繫以查明您是否有訪問權限。指定的網絡名不再可用。"
日誌中有如下錯誤：
[2016/12/21 08:43:18.450576, 0] ../source3/lib/dumpcore.c:303(dump_core)
dumping core in /var/log/samba/cores/smbd
[2016/12/21 08:43:18.614643, 0] ../source3/lib/popt_common.c:68(popt_s3_talloc_log_fn)
talloc: access after free error - first free may be at ../source3/smbd/open.c:3715
[2016/12/21 08:43:18.614690, 0] ../source3/lib/popt_common.c:68(popt_s3_talloc_log_fn)
Bad talloc magic value - access after free
[2016/12/21 08:43:18.614710, 0] ../source3/lib/util.c:789(smb_panic_s3)
PANIC (pid 5348): Bad talloc magic value - access after free
[2016/12/21 08:43:18.615376, 0] ../source3/lib/util.c:900(log_stack_trace)
BACKTRACE: 26 stack frames:
#0 /usr/lib/x86_64-linux-gnu/samba/libsmbregistry.so.0(log_stack_trace+0x1a) [0x7f24d91e914a]
處理方式：
sudo apt-get install libtalloc2 升級 libtalloc2，參考：http://blog.csdn.net/merlinholland/article/details/52822501
4、sudo自動切換
visudo
插入如下信息：
## Allows people in group wheel to run all commands
# %wheel ALL=(ALL) ALL
## Same thing without a password
%wheel ALL=(ALL) NOPASSWD: ALL
system ALL=(ALL) NOPASSWD: ALL
ubuntu ALL=(ALL) NOPASSWD: ALL
其中 system ubuntu 是你想支持用戶
5、安裝nvidia 驅動，這裏是安裝Tesla k20c的驅動，也支持k40c 、k80，具體如下：
Tesla K80, Tesla K40c, Tesla K40m, Tesla K40s, Tesla K40st, Tesla K40t, Tesla K20Xm, Tesla K20m, Tesla K20s, Tesla K20c, Tesla K10
5.1 安裝 bumblebee
sudo add-apt-repository ppa:bumblebee/stable
sudo apt-get update
sudo apt-get install bumblebee bumblebee-nvidia
5.2 安裝nvidia驅動
參考：http://blog.csdn.net/TriLoo/article/details/52678033?locationNum=14
備用： http://blog.163.com/zhao_en_peng/blog/static/12740422420131202110539/
5.2.1.查看電腦的顯卡信息以及正在使用的顯卡驅動
查看電腦顯卡信息命令：lspci | grep VGA
lspci會顯示所有的PCI接口設備，然後從中提取處顯示相關的設備（VGA）。
執行命令會得到類似下面的信息：
01:00.0 VGA compatible controller: NVIDIA Corporation GM107 [GeForce GTX 745] (rev a2)
從上面的信息可以看出：顯卡型號爲GTX745。顯卡型號會在後面下載顯卡驅動時用到。
得到顯卡型號後，可以利用下面的命令查看關於顯卡的更詳細信息：
lspci -v -s 01:00.01
-v ： 顯示詳細信息
-s ： 後面接PCI設備的ID
執行命令會得到類似下面的信息：
01:00.0 VGA compatible controller: NVIDIA Corporation GM107 [GeForce GTX 745] (rev a2) (prog-if 00 [VGA controller])
Subsystem: NVIDIA Corporation Device 1065
Flags: bus master, fast devsel, latency 0, IRQ 34
Memory at f6000000 (32-bit, non-prefetchable) [size=16M]
Memory at e0000000 (64-bit, prefetchable) [size=256M]
Memory at f0000000 (64-bit, prefetchable) [size=32M]
I/O ports at e000 [size=128]
[virtual] Expansion ROM at f7000000 [disabled] [size=512K]
Capabilities:
Kernel driver in use: nvidias
其中在最後一行顯示正在使用的驅動是nvidias。這是安裝Nvidia顯卡後的顯示，最開始會顯示nouveau。
在倒數第二行顯示access denied，是因爲權限問題，可以sudo解決。
好了現在我們知道了顯卡型號以及顯卡驅動信息了下一步是去Nvidia官網下載相應的顯卡驅動程序。
1.下載驅動
Nvidia驅動下載鏈接：Nvidia。
http://cn.download.nvidia.com/XFree86/Linux-x86_64/346.96/NVIDIA-Linux-x86_64-346.96.run
#http://cn.download.nvidia.com/Ubuntu/346.96/nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb
在打開的界面中（界面如下圖），建議選用手動根據自己的系統、顯卡型號等選擇相關的驅動。
5.2.2.禁止nouveau驅動
通過網上的相關信息，如果之前顯卡驅動是用的nouveau，那麼在安裝自己下載的驅動的時候會顯示錯誤。
所以在安裝驅動之前，需要先在/etc/modprobe.d/blacklist.conf文件中加入下面內容：
blacklist nouveau
然後重新啓動。
sudo reboot
5.2.3.安裝顯卡
重啓後，在登陸界面時同時按下：Ctrl + Alt + F1~F6進入字符界面。
也可以在登陸界面登陸後，在終端輸入init 3來改變run level.
需要說明的是，重啓後，會發現字體變大，這屬於正常顯現。
登陸tt1終端，然後關閉Ubuntu的Unity：
sudo service lightdm stop
其中lightdm根據自己使用的桌面做相應的調整：
[KDM（KDE），GDM（GNOME）
然後進入之前下載的驅動文件所在的目錄，運行下載的腳本文件即可：
sudo sh NVIDIA-Linux-x86_64-346.96.run
#sudo dpkg -i nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb 錯誤
後面根據程序的提示操作即可。
5.2.4.重啓
安裝完成後，重啓即可。
sudo service lightdm start
問題處理：
（1） 安裝完成後重啓可能會出現循環登錄的情況，解決方法是重啓前先按照下面教程安裝一個管理軟件：
http://blog.csdn.net/triloo/article/details/52767412
見5.1安裝 bumblebee
（2）錯誤信息：
軟件包的體系架構(ppc64el)與本機系統的架構(amd64)不符
在處理時有錯誤發生：
nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb
下載安裝包錯誤，重新下載適合你機器的安裝包即可
安裝檢查工具
sudo apt-get install mesa-utils
6、安裝CUDA7.0
下載CUDA7.0
6.1安裝 cuda
6.1.1安裝依賴庫
sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
6.1.2安裝CUDA7.0 參考：http://blog.csdn.net/a350203223/article/details/50262535
(1) sudo dpkg -i cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb
Selecting previously unselected package cuda-repo-ubuntu1404-7-0-local.
(正在讀取數據庫 ... 系統當前共安裝有 171979 個文件和目錄。)
Preparing to unpack cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb ...
Unpacking cuda-repo-ubuntu1404-7-0-local (7.0-28) ...
正在設置 cuda-repo-ubuntu1404-7-0-local (7.0-28) ...
OK
(1.5) sudo apt-get update
(2)sudo apt-get install cuda
正在讀取軟件包列表... 完成
正在分析軟件包的依賴關係樹
正在讀取狀態信息... 完成
下列軟件包是自動安裝的並且現在不需要了：
libcublas5.5 libcudart5.5 libcufft5.5 libcufftw5.5 libcuinj64-5.5
libcurand5.5 libcusparse5.5 libnppc5.5 libnppi5.5 libnpps5.5 libnvtoolsext1
libnvvm2 libthrust-dev libvdpau-dev nvidia-cuda-dev nvidia-cuda-doc
nvidia-cuda-gdb nvidia-profiler nvidia-visual-profiler opencl-headers
Use 'apt-get autoremove' to remove them.
將會安裝下列額外的軟件包：
cuda-7-0 cuda-command-line-tools-7-0 cuda-core-7-0 cuda-cublas-7-0
cuda-cublas-dev-7-0 cuda-cudart-7-0 cuda-cudart-dev-7-0 cuda-cufft-7-0
cuda-cufft-dev-7-0 cuda-curand-7-0 cuda-curand-dev-7-0 cuda-cusolver-7-0
cuda-cusolver-dev-7-0 cuda-cusparse-7-0 cuda-cusparse-dev-7-0
cuda-documentation-7-0 cuda-driver-dev-7-0 cuda-drivers cuda-license-7-0
cuda-misc-headers-7-0 cuda-npp-7-0 cuda-npp-dev-7-0 cuda-nvrtc-7-0
cuda-nvrtc-dev-7-0 cuda-runtime-7-0 cuda-samples-7-0 cuda-toolkit-7-0
cuda-visual-tools-7-0 libcuda1-346 libcuda1-352 libcuda1-367 nvidia-346
nvidia-346-dev nvidia-346-uvm nvidia-352 nvidia-352-dev nvidia-367
nvidia-367-dev nvidia-modprobe nvidia-opencl-icd-346 nvidia-opencl-icd-352
nvidia-opencl-icd-367 nvidia-settings ocl-icd-libopencl1
下列軟件包將被【卸載】：
libcuda1-340 nvidia-340 nvidia-340-uvm nvidia-cuda-toolkit
nvidia-libopencl1-331 nvidia-libopencl1-340 nvidia-opencl-dev
nvidia-opencl-icd-340
下列【新】軟件包將被安裝：
cuda cuda-7-0 cuda-command-line-tools-7-0 cuda-core-7-0 cuda-cublas-7-0
cuda-cublas-dev-7-0 cuda-cudart-7-0 cuda-cudart-dev-7-0 cuda-cufft-7-0
cuda-cufft-dev-7-0 cuda-curand-7-0 cuda-curand-dev-7-0 cuda-cusolver-7-0
cuda-cusolver-dev-7-0 cuda-cusparse-7-0 cuda-cusparse-dev-7-0
cuda-documentation-7-0 cuda-driver-dev-7-0 cuda-drivers cuda-license-7-0
cuda-misc-headers-7-0 cuda-npp-7-0 cuda-npp-dev-7-0 cuda-nvrtc-7-0
cuda-nvrtc-dev-7-0 cuda-runtime-7-0 cuda-samples-7-0 cuda-toolkit-7-0
cuda-visual-tools-7-0 libcuda1-346 libcuda1-352 libcuda1-367 nvidia-346
nvidia-346-dev nvidia-346-uvm nvidia-352 nvidia-352-dev nvidia-367
nvidia-367-dev nvidia-modprobe nvidia-opencl-icd-346 nvidia-opencl-icd-352
nvidia-opencl-icd-367 ocl-icd-libopencl1
下列軟件包將被升級：
nvidia-settings
升級了 1 個軟件包，新安裝了 44 個軟件包，要卸載 8 個軟件包，有 590 個軟件包未被升級。
需要下載 75.5 MB/1,042 MB 的軟件包。
解壓縮後會消耗掉 1,556 MB 的額外空間。
您希望繼續執行嗎？ [Y/n] y
獲取：1 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-352 amd64 367.57-0ubuntu0.14.04.1 [4,802 B]
獲取：2 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346 amd64 352.63-0ubuntu0.14.04.1 [4,802 B]
獲取：3 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-367 amd64 367.57-0ubuntu0.14.04.1 [69.8 MB]
獲取：4 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-367 amd64 367.57-0ubuntu0.14.04.1 [2,708 kB]
獲取：5 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346-uvm amd64 346.96-0ubuntu0.0.1 [4,762 B]
獲取：6 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-367-dev amd64 367.57-0ubuntu0.14.04.1 [80.8 kB]
獲取：7 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-352-dev amd64 367.57-0ubuntu0.14.04.1 [4,806 B]
獲取：8 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346-dev amd64 352.63-0ubuntu0.14.04.1 [4,812 B]
獲取：9 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-352 amd64 367.57-0ubuntu0.14.04.1 [4,814 B]
獲取：10 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-346 amd64 352.63-0ubuntu0.14.04.1 [4,810 B]
獲取：11 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-367 amd64 367.57-0ubuntu0.14.04.1 [2,901 kB]
獲取：12 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-352 amd64 367.57-0ubuntu0.14.04.1 [4,818 B]
獲取：13 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-346 amd64 352.63-0ubuntu0.14.04.1 [4,822 B]
下載 75.5 MB，耗時 13分 13秒 (95.2 kB/s)
正在從軟件包中解出模板：100%
Selecting previously unselected package nvidia-352.
(正在讀取數據庫 ... 系統當前共安裝有 179276 個文件和目錄。)
Preparing to unpack .../nvidia-352_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-352 (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-346.
Preparing to unpack .../nvidia-346_352.63-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-346 (352.63-0ubuntu0.14.04.1) ...
(正在讀取數據庫 ... 系統當前共安裝有 179281 個文件和目錄。)
Removing nvidia-opencl-icd-340 (340.98-0ubuntu0.14.04.1) ...
Removing nvidia-cuda-toolkit (5.5.22-3ubuntu1) ...
Removing nvidia-opencl-dev:amd64 (5.5.22-3ubuntu1) ...
Removing nvidia-libopencl1-331 (340.98-0ubuntu0.14.04.1) ...
Removing nvidia-libopencl1-340 (340.98-0ubuntu0.14.04.1) ...
Removing nvidia-340-uvm (340.98-0ubuntu0.14.04.1) ...
dpkg: nvidia-340: dependency problems, but removing anyway as you requested:
bumblebee-nvidia 依賴於 nvidia-driver | nvidia-glx | nvidia-kernel-dkms | nvidia-kernel-amd64 | nvidia-kernel-686-pae | nvidia-kernel-486 | nvidia | nvidia-current | nvidia-current-updates | nvidia-driver-binary | nvidia-304 | nvidia-304-updates | nvidia-experimental-304 | nvidia-310 | nvidia-310-updates | nvidia-experimental-310 | nvidia-313 | nvidia-313-updates | nvidia-experimental-313 | nvidia-319 | nvidia-319-updates | nvidia-experimental-319 | nvidia-325 | nvidia-325-updates | nvidia-experimental-325 | nvidia-331 | nvidia-331-updates | nvidia-experimental-331 | nvidia-334 | nvidia-334-updates | nvidia-experimental-334 | nvidia-337 | nvidia-337-updates | nvidia-experimental-337 | nvidia-340 | nvidia-340-updates | nvidia-experimental-340 | nvidia-343 | nvidia-343-updates | nvidia-experimental-343 | nvidia-346 | nvidia-346-updates | nvidia-experimental-346 | nvidia-349 | nvidia-349-updates | nvidia-experimental-349 | nvidia-352 | n
Removing nvidia-340 (340.98-0ubuntu0.14.04.1) ...
Stopping nvidia-persistenced
nvidia-persistenced：沒有發現操作
Done.
Removing all DKMS Modules
Done.
INFO:Disable nvidia-340
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
update-initramfs: deferring update (trigger activated)
Processing triggers for libc-bin (2.19-0ubuntu6) ...
Processing triggers for man-db (2.6.7.1-1) ...
Processing triggers for initramfs-tools (0.103ubuntu4.2) ...
update-initramfs: Generating /boot/initrd.img-3.13.0-32-generic
Selecting previously unselected package nvidia-367.
(正在讀取數據庫 ... 系統當前共安裝有 178942 個文件和目錄。)
Preparing to unpack .../nvidia-367_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-367 (367.57-0ubuntu0.14.04.1) ...
Processing triggers for ureadahead (0.100.0-16) ...
Processing triggers for man-db (2.6.7.1-1) ...
dpkg: libcuda1-340: dependency problems, but removing anyway as you requested:
libcuinj64-5.5:amd64 依賴於 libcuda-5.5-1；然而：
未安裝軟件包 libcuda-5.5-1。
提供了 libcuda-5.5-1 的軟件包 libcuda1-340 即將被刪除。
nvidia-profiler 依賴於 libcuda-5.5-1；然而：
未安裝軟件包 libcuda-5.5-1。
提供了 libcuda-5.5-1 的軟件包 libcuda1-340 即將被刪除。
(正在讀取數據庫 ... 系統當前共安裝有 179508 個文件和目錄。)
Removing libcuda1-340 (340.98-0ubuntu0.14.04.1) ...
Processing triggers for libc-bin (2.19-0ubuntu6) ...
Selecting previously unselected package libcuda1-367.
(正在讀取數據庫 ... 系統當前共安裝有 179500 個文件和目錄。)
Preparing to unpack .../libcuda1-367_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking libcuda1-367 (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package ocl-icd-libopencl1:amd64.
Preparing to unpack .../ocl-icd-libopencl1_2.1.3-4_amd64.deb ...
Unpacking ocl-icd-libopencl1:amd64 (2.1.3-4) ...
Selecting previously unselected package cuda-license-7-0.
Preparing to unpack .../cuda-license-7-0_7.0-28_amd64.deb ...
Unpacking cuda-license-7-0 (7.0-28) ...
Selecting previously unselected package cuda-misc-headers-7-0.
Preparing to unpack .../cuda-misc-headers-7-0_7.0-28_amd64.deb ...
Unpacking cuda-misc-headers-7-0 (7.0-28) ...
Selecting previously unselected package cuda-core-7-0.
Preparing to unpack .../cuda-core-7-0_7.0-28_amd64.deb ...
Unpacking cuda-core-7-0 (7.0-28) ...
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Preparing to unpack .../cuda-cudart-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cudart-7-0 (7.0-28) ...
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Unpacking cuda-nvrtc-7-0 (7.0-28) ...
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Unpacking cuda-nvrtc-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cusolver-7-0.
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Unpacking cuda-cusolver-7-0 (7.0-28) ...
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Processing triggers for man-db (2.6.7.1-1) ...
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Processing 1 added doc-base file...
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Processing triggers for desktop-file-utils (0.22-1ubuntu1) ...
Processing triggers for bamfdaemon (0.5.1+14.04.20140409-0ubuntu1) ...
Rebuilding /usr/share/applications/bamf-2.index...
Processing triggers for mime-support (3.54ubuntu1) ...
正在設置 nvidia-367 (367.57-0ubuntu0.14.04.1) ...
update-alternatives: using /usr/lib/nvidia-367/ld.so.conf to provide /etc/ld.so.conf.d/x86_64-linux-gnu_EGL.conf (x86_64-linux-gnu_egl_conf) in 自動模式
update-alternatives: using /usr/lib/nvidia-367/alt_ld.so.conf to provide /etc/ld.so.conf.d/i386-linux-gnu_EGL.conf (i386-linux-gnu_egl_conf) in 自動模式
update-alternatives: using /usr/share/nvidia-367/glamor.conf to provide /usr/share/X11/xorg.conf.d/glamoregl.conf (glamor_conf) in 自動模式
INFO:Enable nvidia-367
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/put_your_quirks_here
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/dell_latitude
DEBUG:Parsing /usr/share/ubuntu-drivers-common/quirks/lenovo_thinkpad
正在添加系統用戶"nvidia-persistenced" (UID 117)...
正在添加新組"nvidia-persistenced" (GID 125)...
正在將新用戶"nvidia-persistenced" (UID 117)添加到組"nvidia-persistenced"...
無法創建主目錄"/"
Loading new nvidia-367-367.57 DKMS files...
First Installation: checking all kernels...
Building only for 3.13.0-32-generic
Building for architecture x86_64
Building initial module for 3.13.0-32-generic
Done.
nvidia_367:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
nvidia_367_modeset.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
nvidia_367_drm.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
nvidia_367_uvm.ko:
Running module version sanity check.
- Original module
- No original module exists within this kernel
- Installation
- Installing to /lib/modules/3.13.0-32-generic/updates/dkms/
depmod....
DKMS: install completed.
正在設置 nvidia-352 (367.57-0ubuntu0.14.04.1) ...
正在設置 nvidia-346 (352.63-0ubuntu0.14.04.1) ...
正在設置 libcuda1-367 (367.57-0ubuntu0.14.04.1) ...
正在設置 ocl-icd-libopencl1:amd64 (2.1.3-4) ...
正在設置 cuda-license-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-misc-headers-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-core-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cudart-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-driver-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cudart-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-command-line-tools-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-nvrtc-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-nvrtc-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cusolver-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cusolver-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cublas-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cublas-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cufft-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cufft-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-curand-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-curand-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cusparse-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-cusparse-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-npp-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-npp-dev-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-samples-7-0 (7.0-28) ...
正在設置 cuda-documentation-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-visual-tools-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 cuda-toolkit-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
正在設置 nvidia-346-uvm (346.96-0ubuntu0.0.1) ...
正在設置 nvidia-367-dev (367.57-0ubuntu0.14.04.1) ...
正在設置 nvidia-352-dev (367.57-0ubuntu0.14.04.1) ...
正在設置 nvidia-346-dev (352.63-0ubuntu0.14.04.1) ...
正在設置 nvidia-modprobe (346.46-0ubuntu1) ...
正在設置 nvidia-settings (346.46-0ubuntu1) ...
正在設置 libcuda1-352 (367.57-0ubuntu0.14.04.1) ...
正在設置 libcuda1-346 (352.63-0ubuntu0.14.04.1) ...
正在設置 nvidia-opencl-icd-367 (367.57-0ubuntu0.14.04.1) ...
正在設置 nvidia-opencl-icd-352 (367.57-0ubuntu0.14.04.1) ...
正在設置 nvidia-opencl-icd-346 (352.63-0ubuntu0.14.04.1) ...
正在設置 cuda-drivers (346.46-1) ...
正在設置 cuda-runtime-7-0 (7.0-28) ...
正在設置 cuda-7-0 (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
*****************************************************************************************
*** Please reboot your computer and verify that the nvidia graphics driver is loaded. ***
*** If the driver fails to load, please use the NVIDIA graphics driver .run installer ***
*** to get into a stable state. ***
*****************************************************************************************
正在設置 cuda (7.0-28) ...
*** LICENSE AGREEMENT ***
By using this software you agree to fully comply with the terms and conditions of the EULA (End User License Agreement). The EULA is located at /usr/local/cuda-7.0/doc/EULA.txt. The EULA can also be found at http://docs.nvidia.com/cuda/eula/index.html. If you do not agree to the terms and conditions of the EULA, do not use the software.
Processing triggers for libc-bin (2.19-0ubuntu6) ...
(3) 配置CUDA
sudo vi /etc/profile 添加
export PATH=/usr/local/cuda-7.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-7.0/lib64:$LD_LIBRARY_PATH
添加cuda.conf
sudo vim /etc/ld.so.conf.d/cuda.conf
/usr/local/cuda/lib64
/lib
6.2 安裝 cuda-toolkit
好像沒裝，裝了toolkit，檢查一下
nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Mon_Feb_16_22:59:02_CST_2015
Cuda compilation tools, release 7.0, V7.0.27
如果有上述信息不用操做，否則執行：
sudo apt-get install nvidia-cuda-toolkit
安裝失敗，nvidia-cuda-toolkit : 依賴: nvidia-opencl-dev (= 5.5.22-3ubuntu1) 但是它將不
重新執行一下， 6.3.1 問題處理，執行 nvcc --version，
system@ubunt:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Mon_Feb_16_22:59:02_CST_2015
Cuda compilation tools, release 7.0, V7.0.27
一切正常
6.3 安裝sample(如果安裝的是8.0需要先sudo apt-get remove --purge nvidia-375 nvidia-modprobe nvidia-settings 再sudo ./cuda_8.0.61_375.26_linux.run)
cd /usr/local/cuda-7.0/bin
$ cuda-install-samples-7.0.sh <dir>
這樣，就將cuda的sample拷貝到dir文件夾下了。該命令只是一個拷貝操作。
我的執行如下:
$ cuda-install-samples-7.0.sh /home/cudaSamples/
cd /home/cudaSamples/
$ make
然後進入該文件夾，執行make命令進行編譯，編譯時間較長，需要等待。
/usr/bin/ld: cannot find -lnvcuvid
collect2: error: ld returned 1 exit status
sudo sed -i "s/nvidia-346/nvidia-367/g" `grep nvidia-346 -rl ./`
執行成功再次make 完成
執行 /home/cuda7_sample/NVIDIA_CUDA-7.0_Samples/bin/x86_64/linux/release下的
./deviceQuery
CUDA Device Query (Runtime API) version (CUDART static linking)
modprobe: FATAL: Module nvidia-uvm not found.
cudaGetDeviceCount returned 30
-> unknown error
Result = FAIL
重啓發現，系統不能正常顯示，只出現log界面，崩潰！！！！
6.3.1 問題處理如下：
首先，之前使用bumblebee解決雙顯卡問題的需要卸載bumblebee。
(1) sudo apt-get purge bumblebee*
安裝nvidia-367驅動和nvidia prime，這裏先不管驅動的版本問題
(2). sudo stop lightdm
(3). sudo apt-get install nvidia-367 nvidia-prime 重裝驅動 因該是
切換到nvidia獨顯下安裝CUDA
(3.5). sudo prime-select nvidia 應該是這步起作用了
(3.8).sudo dpkg -i cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb 這步估計沒用
(4).sudo reboot 重啓，
(5).系統啓動還報錯，忽略
./deviceQuery
./deviceQuery Starting...
CUDA Device Query (Runtime API) version (CUDART static linking)
Detected 2 CUDA Capable device(s)
Device 0: "Tesla K20c"
CUDA Driver Version / Runtime Version 8.0 / 7.0
CUDA Capability Major/Minor version number: 3.5
Total amount of global memory: 4742 MBytes (4972412928 bytes)
(13) Multiprocessors, (192) CUDA Cores/MP: 2496 CUDA Cores
GPU Max Clock rate: 706 MHz (0.71 GHz)
Memory Clock rate: 2600 Mhz
Memory Bus Width: 320-bit
L2 Cache Size: 1310720 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 2 copy engine(s)
Run time limit on kernels: No
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Enabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 4 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
Device 1: "Quadro K420"
CUDA Driver Version / Runtime Version 8.0 / 7.0
CUDA Capability Major/Minor version number: 3.0
Total amount of global memory: 972 MBytes (1019215872 bytes)
( 1) Multiprocessors, (192) CUDA Cores/MP: 192 CUDA Cores
GPU Max Clock rate: 876 MHz (0.88 GHz)
Memory Clock rate: 891 Mhz
Memory Bus Width: 128-bit
L2 Cache Size: 262144 bytes
Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096)
Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers
Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers
Total amount of constant memory: 65536 bytes
Total amount of shared memory per block: 49152 bytes
Total number of registers available per block: 65536
Warp size: 32
Maximum number of threads per multiprocessor: 2048
Maximum number of threads per block: 1024
Max dimension size of a thread block (x,y,z): (1024, 1024, 64)
Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535)
Maximum memory pitch: 2147483647 bytes
Texture alignment: 512 bytes
Concurrent copy and kernel execution: Yes with 1 copy engine(s)
Run time limit on kernels: Yes
Integrated GPU sharing Host Memory: No
Support host page-locked memory mapping: Yes
Alignment requirement for Surfaces: Yes
Device has ECC support: Disabled
Device supports Unified Addressing (UVA): Yes
Device PCI Domain ID / Bus ID / location ID: 0 / 3 / 0
Compute Mode:
< Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
> Peer access from Tesla K20c (GPU0) -> Quadro K420 (GPU1) : No
> Peer access from Quadro K420 (GPU1) -> Tesla K20c (GPU0) : No
deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 8.0, CUDA Runtime Version = 7.0, NumDevs = 2, Device0 = Tesla K20c, Device1 = Quadro K420
Result = PASS
先看驅動檢測
system@Ubuntu14:/var/cache/apt/archives$ nvidia-smi
Mon Dec 26 16:36:52 2016
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 367.57 Driver Version: 367.57 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 Quadro K420 Off | 0000:03:00.0 On | N/A |
| 25% 43C P8 N/A / N/A | 220MiB / 972MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
| 1 Tesla K20c Off | 0000:04:00.0 Off | 0 |
| 30% 33C P8 17W / 225W | 0MiB / 4742MiB | 0% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
| 0 1457 G /usr/bin/X 132MiB |
| 0 2696 G compiz 86MiB |
+-----------------------------------------------------------------------------+
6.43，安裝cuDNN
下載 cudnn-7.0-linux-x64-v3.0-prod.tgz，官網申請不到，網上自己找的，就不給地址了。
[plain] view plain copy print?在CODE上查看代碼片派生到我的代碼片
tar -zxvf cudnn-7.0-linux-x64-v3.0-prod.tgz
cd cuda
sudo cp lib64/lib* /usr/local/cuda/lib64/
sudo cp include/cudnn.h /usr/local/cuda/include/
不用操作以下：
sudo chmod u=rwx,g=rx,o=rx libcudnn.so.7.0.64
sudo ln -s libcudnn.so.7.0.64 libcudnn.so.7.0
sudo ln -s libcudnn.so.7.0 libcudnn.so
同時需要添加lib庫路徑： 在 /etc/ld.so.conf.d/加入文件 cuda.conf, 內容如下
/usr/local/cuda/lib64
保存後，執行下列命令使之立刻生效
sudo ldconfig
7、安裝python
7.1 不再安裝python管理工具pyenv，跳過##錯誤##
(1)安裝git
sudo apt-get install git
###### (2)安裝python管理工具pyenv,這裏我假設用用戶system安裝
###### sudo git clone git://github.com/yyuu/pyenv.git ~/.pyenv
###### 切換到root用戶
###### echo 'export PYENV_ROOT="/home/system/.pyenv"' >> /etc/profile
###### echo 'export PATH="/home/system/.pyenv/bin:$PATH"' >> /etc/profile
###### echo 'eval "$(pyenv init -)"' >> /etc/profile
###### source /etc/profile
7.2python 編譯安裝
(1)安裝依賴庫
安裝git
sudo apt-get install git
sudo apt-get install -y make build-essential libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm
sudo apt-get install libc6-dev gcc
(2)編譯python
pyenv install 2.7.12 -v 下載失敗
拷貝下載的源碼安裝
XX sudo ./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC --prefix=/usr/local/python
XX sudo ./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC --prefix=/usr
sudo ./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC
所以通常我們./configure的時候，默認是--prefix=/usr，這樣的話，本程序的配置文件就會裝到/usr/etc,應用文件就會安裝到/usr/bin,本程序的私有庫也會安裝到/usr/lib等等，，我們也不用設置PATH就可以直接用了，，
sudo make install
(2.5)修改鏈接
sudo mv /usr/bin/python /usr/bin/python2.7.6
sudo ln -s /usr/local/bin/python2.7 /usr/bin/python
a.需要編輯/etc/ld.so.conf增加一行/usr/local/lib
sudo vim /etc/ld.so.conf
include ld.so.conf.d/*.conf #原有的
/usr/local/lib
b. ld.so.conf文件配置完畢後，我們需要執行如下命令：
sudo /sbin/ldconfig
sudo /sbin/ldconfig -v
c. 然後再執行python -V命令，查看python版本如下
Python 2.7.12
(3)安裝python的pip和easy_install（工具包 setuptools-32.3.0.zip ），方便安裝軟件包
wget --no-check-certificate https://bootstrap.pypa.io/ez_setup.py
python ez_setup.py --insecure
wget https://bootstrap.pypa.io/get-pip.py
sudo python get-pip.py
(4)安裝其他包
a. numpy 安裝
tar -xzvf numpy-1.12.0b1.tar.gz
cd numpy-1.12.0b1
sudo python setup.py install
b. mock安裝
tar -xzvf mock-2.0.0.tar.gz
cd mock-2.0.0/
sudo python setup.py install
c. six安裝
tar -xvzf six-1.10.0.tar.gz
cd six-1.10.0/
sudo python setup.py install
d. pbr.version安裝
tar -xzvf pbr-1.10.0.tar.gz
cd pbr-1.10.0/
sudo python setup.py install
e. funcsigs 安裝
tar -xvzf funcsigs-1.0.2.tar.gz
cd funcsigs-1.0.2/
sudo python setup.py install
f. atlas3 安裝(沒裝)
tar -jxvf
tar -jxvf atlas3.10.3.tar.bz2
cd ATLAS/
**************************************************
mkdir build ; cd build
./ATLAS/configure [flags]
make ! tune and compile library
make check ! perform sanity tests
make ptcheck ! checks of threaded code for multiprocessor systems
make time ! provide performance summary as % of clock rate
make install ! Copy library and include files to other directories
**************************************************
編譯過程出錯，提示be due to shut off throttling ,放棄安裝，可以通過進入bois修改對應選項再安裝
g. boost_1_57_0 安裝
#sudo apt-get remove libboost-dev
tar -jxvf boost_1_57_0.tar.bz2
cd boost_1_57_0/
sudo ./bootstrap.sh
修改tools/build/boost-build.jam 在最後面加上一行“using mpi ;”(注意mpi後面有個空格，然後一個分號 )
sudo ./b2
sudo ./b2 install --prefix=/usr
h. dask安裝
tar -xzvf dask-0.12.0.tar.gz
cd dask-0.12.0/
sudo python setup.py install
i. easydict 安裝
unzip easydict-1.6.zip
cd easydict-1.6/
sudo python setup.py install
j. Cython 安裝
tar -xzvf Cython-0.25.1.tar.gz
cd Cython-0.25.1/
sudo python setup.py install
k. h5py 安裝
tar -xvzf h5py-2.6.0.tar.gz
cd h5py-2.6.0/
sudo python setup.py install
缺少 hdf5.h 文件，下載 anaconda 安裝
bash Anaconda-2.1.0-Linux-x86_64.sh
chmod +x Anaconda-2.1.0-Linux-x86_64.sh
./Anaconda-2.1.0-Linux-x86_64.sh
m. ipython安裝
tar -xvzf ipython-5.1.0.tar.gz
cd ipython-5.1.0/
sudo python setup.py install
n. lapack安裝
sudo apt-get install gfortran
tar -xzvf lapack-3.5.0.tgz
cd lapack-3.5.0/
cp make.inc.example make.inc
cd lapack-3.5.0/
編輯Makefile 文件內容， 把
lib: lapacklib tmglib
#lib: blaslib variants lapacklib tmglib
改爲：
#lib: lapacklib tmglib
lib: blaslib variants lapacklib tmglib
將生成的liblapack.a，librefblas.a，libtmglib.a 三個庫拷貝到/usr/lib
sudo cp liblapack.a /usr/lib
sudo cp librefblas.a /usr/lib
sudo cp libtmglib.a /usr/lib
o. leveldb安裝
tar -xvzf leveldb-0.194.tar.gz
cd leveldb-0.194/
sudo python setup.py install
p. matplotlib安裝 ..... Math跳過去沒裝
tar -xzvf matplotlib-1.4.2.tar.gz
cd matplotlib-1.4.2/
sudo python setup.py install
報如下錯誤：
* The following required packages can not be built:
* freetype, png
採用如下方法安裝：
安裝 ：sudo apt-get install libpng-dev
下載 freetype-2.3.10.tar.bz2
tar -xjvf freetype-2.3.10.tar.bz2
cd freetype-2.3.10
sudo ./configure --prefix=/usr
sudo make
sudo make install
再次執行:
sudo python setup.py install , 另一種安裝方式: sudo pip install matplotlib
測試安裝成功 import matplotlib.pyplot as plt
配置matploatlib
cd /usr/local/lib/python2.7/site-packages/matplotlib-1.4.2-py2.7-linux-x86_64.egg/matplotlib/mpl-data
vi matplotlibrc
#### CONFIGURATION BEGINS HERE
# The default backend; one of GTK GTKAgg GTKCairo GTK3Agg GTK3Cairo
# CocoaAgg MacOSX Qt4Agg Qt5Agg TkAgg WX WXAgg Agg Cairo GDK PS PDF SVG
# Template.
# You can also deploy your own backend outside of matplotlib by
# referring to the module name (which must be in the PYTHONPATH) as
# 'module://my_backend'.
backend : agg
修改爲：backend : Qt4Agg
在Ubuntu系統上安裝PySide
sudo add-apt-repository ppa:pyside
sudo apt-get update
sudo apt-get install python-pyside
如果想只裝某個模塊：
sudo apt-get install python-pyside.qtgui
cd /usr/lib/python2.7/dist-packages
sudo cp -rf PyQt4 /usr/local/lib/python2.7/site-packages/
sudo cp -rf PySide/ /usr/local/lib/python2.7/site-packages/
使用下面的方法測試是否安裝成功：
>>> from PySide.QtCore import *
>>> print QT_VERSION_STR 運行錯誤，忽略
4.7.0
q. networkx 安裝
tar -xzvf networkx-1.11.tar.gz
cd networkx-1.11/
sudo python setup.py install
自動安裝了decorator庫
Best match: decorator 4.0.11
Processing decorator-4.0.11.tar.gz
Writing /tmp/easy_install-kCHNjB/decorator-4.0.11/setup.cfg
Running decorator-4.0.11/setup.py -q bdist_egg --dist-dir /tmp/easy_install-kCHNjB/decorator-4.0.11/egg-dist-tmp-5NBa3d
creating /usr/local/lib/python2.7/site-packages/decorator-4.0.11-py2.7.egg
Extracting decorator-4.0.11-py2.7.egg to /usr/local/lib/python2.7/site-packages
Adding decorator 4.0.11 to easy-install.pth file
Installed /usr/local/lib/python2.7/site-packages/decorator-4.0.11-py2.7.egg
Finished processing dependencies for networkx==1.11
r. nose 安裝
tar -xvzf nose-1.3.7.tar.gz
cd nose-1.3.7/
sudo python setup.py install
s. pandas 安裝
tar -xzvf pandas-0.19.1.tar.gz
cd pandas-0.19.1/
sudo python setup.py install
t. pip 安裝
tar -xzvf pip-9.0.1.tar.gz
cd pip-9.0.1/
sudo python setup.py install
u. pkgconfig安裝
tar -xvzf pkgconfig-1.1.0.tar.gz
cd pkgconfig-1.1.0/
sudo python setup.py install
v. protobuf安裝
unzip protobuf-2.5.0.zip
cd protobuf-2.5.0/
sudo ./configure --prefix=/usr #漏掉了 --prefix 安裝到/usr/local/lib有報錯，將前一次安裝的/usr/local/lib下的文件拷貝到/usr/lib****************************
************************************
sudo make
sudo make check
sudo make install
sudo ldconfig
安裝protobuf的Python支持
cd python # 位於protobuf下
python setup.py build
sudo python setup.py test
sudo python setup.py install
驗證 protoc --version
#python
>>>import google.protobuf
w. pyparsing安裝
tar -xzvf pyparsing-2.1.10.tar.gz
cd pyparsing-2.1.10/
sudo python setup.py install
x. python-dateutil安裝
tar -xvf python-dateutil-1.4.tar
cd python-dateutil-1.4/
sudo python setup.py install
y. python-gflags安裝
tar -xzvf python-gflags-3.1.0.tar.gz
cd python-gflags-3.1.0/
sudo python setup.py install
z. pytz
tar -xvzf pytz-2016.7.tar.gz
cd pytz-2016.7/
sudo python setup.py install
a1. scikit-image
tar -xvzf scikit-image-0.12.3.tar.gz
cd scikit-image-0.12.3/
sudo python setup.py install
b1. scipy
tar -xvzf scipy-0.14.0.tar.gz
cd scipy-0.14.0/
#sudo python setup.py install #LD_LIBRARY_PATH 報錯，採用下面方式安裝
sudo apt-get install -y python-scipy
cd /usr/lib/python2.7/dist-packages
sudo cp -rf scipy* /usr/local/lib/python2.7/site-packages/
python
>>> from scipy import *
c1. opencv 安裝
sudo pip install opencv-python
也可直接執行opencv_python-3.2.0.6-cp27-cp27mu-manylinux1_x86_64.whl，注意是cp27mu而不是m
sudo pip install opencv_python-3.2.0.6-cp27-cp27mu-manylinux1_x86_64.whl
測試安裝
python
>>> import cv2
d1. Wx圖形庫安裝
tar -jxvf wxPython-src-3.0.2.0.tar.bz2
cd wxPython-src-3.0.2.0/
sudo ./configure --prefix=/usr --with-gtk
sudo make
sudo make install
sudo vi /etc/profile
修改或添加上/home/system/source/wxPython-src-3.0.2.0
PATH=$PATH:/home/system/source/wxPython-src-3.0.2.0
LD_LIBRARY_PATH=/home/system/source/wxPython-src-3.0.2.0/lib:$LD_LIBRARY_PATH
cd /usr/lib
sudo ln -s /usr/local/lib/libwx_gtk2u_core-3.0.so.0.2.0
cd wxPython
sudo python setup.py build
sudo python setup.py install
cd /usr/include
cp /home/system/source/wxPython-src-3.0.2.0/lib/wx/include/gtk2-unicode-3.0/wx/setup.h ./wx
sudo cp -rf wx-3.0/wx ./
如果有報錯，記得安裝以下包：
sudo python setup.py install
sudo apt-get install libghc-gstreamer-dev
gtk2，gtk2-devel，python-devel，tk，tk-devel，gstreamer，gstreamer-devel，mesa-libGL-devel，
mesa-libGLU-devel，mesa-libGLU，mesa-libGL，libSM，libSM-devel，gstreamer-plugins-base-devel
錯誤的步驟，安裝2.8.12.1，好像編譯後ansi，不是unicode的
tar -jxvf wxPython-src-2.8.12.1.tar.bz2
cd wxPython-src-2.8.12.1/
sudo ./configure --prefix=/usr --with-gtk --unicode=yes
sudo make
sudo make install
cd wxPython
sudo python setup.py build
sudo python setup.py install
sudo apt-get install python-wxtools
checking for GST... configure: WARNING: GStreamer 0.10 not available, falling back to 0.8
checking for GST... configure: WARNING: GStreamer 0.8/0.10 not available.
configure: error: GStreamer not available
Error running configure
ERROR: failed building wxWidgets
Traceback (most recent call last):
File "build.py", line 1184, in cmd_build_wx
wxbuild.main(wxDir(), build_options)
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 368, in main
"Error running configure")
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 85, in exitIfError
raise builder.BuildError(msg)
BuildError
/usr/include/wx/gtk/clipbrd.h:59:5: error: ‘GtkWidget’ does not name a type
該報錯網上提示是自帶bug，改爲安裝3.0.2.0，但是由於安裝了2.8，所以需要刪除原有2.8，折騰了
下面的安裝包錯誤：
tar -xzvf wx-3.0.3.tar.gz
cd wxPython_Phoenix-3.0.3
以下不對
tar -xzvf wxWidgets-2.8.12.tar.gz
cd wxWidgets-2.8.12/
sudo ./configure --prefix=/usr --with-gtk
sudo make
sudo make install
安裝出錯：
checking for GST... configure: WARNING: GStreamer 0.10 not available, falling back to 0.8
checking for GST... configure: WARNING: GStreamer 0.8/0.10 not available.
configure: error: GStreamer not available
Error running configure
ERROR: failed building wxWidgets
Traceback (most recent call last):
File "build.py", line 1184, in cmd_build_wx
wxbuild.main(wxDir(), build_options)
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 368, in main
"Error running configure")
File "/home/system/source/wxPython_Phoenix-3.0.3/buildtools/build_wxwidgets.py", line 85, in exitIfError
raise builder.BuildError(msg)
BuildError
wx-config --list
Default config is gtk2-unicode-2.8
Default config will be used for output
Also available in /usr:
wx-config
刪除所有與gtk2-unicode-2.8有關的文件和文件夾，重新安裝 sudo make install
其他錯誤處理
configure: error: GStreamer not available
ubuntu14.04安裝GStreamer插件
sudo apt-get install libghc-gstreamer-dev
以下不對，記錄下走錯的路：
sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install gstreamer0.10-ffmpeg
e1. mysql-connector-python安裝
也折騰了一下，不知道怎麼搞的以前pip install mysql-connector-python-rf==2.1.3和deb包安裝都可以，沒辦法下載一個2.1.4安裝
unzip mysql-connector-2.1.4.zip
cd mysql-connector-2.1.4/
sudo python setup.py install
測試：
python
>>>
import mysql.connector
f1. 安裝yaml
前面包安裝中，已經安裝
(5)更改環境變量
export PYTHONPATH=/usr/local/lib/python2.7:/usr/local/lib/python2.7/site-packages:/usr/local/lib/python2.7/plat-linux2:/usr/local/lib/python2.7/lib-tk:/usr/local/lib/python2.7/lib-dynload
export PYTHONHOME=/usr/local/lib/python2.7
錯誤： ImportError: No module named _io
sudo pip install virtualenv --upgrade
這次還會報錯首先會報一個PIC的錯誤還有/usr/local/lib/libboost_python.so: undefined reference to `PyUnicodeUCS4_AsWideChar'
這時因爲caffe需要用UCS4編碼格式，但是我們的Python環境是UCS2的所以需要卸載掉我們環境裏的所有Python，sudo apt-get remove Python（如果卸載失敗需要手動刪除比較麻煩），然後手動下載Python的源碼包進行編譯安裝
進入源碼目錄
./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC
Make;sudo make install
進入Python環境 >>>import sys >>>print(sys.maxunicode)看下打印是不是1114111
（6）安裝完Python我們還需要重裝boost
sudo apt-get remove libboost-dev
tar -jxvf boost_1_57_0.tar.bz2
sudo ./bootstrap.sh
修改tools/build/boost-build.jam 在最後面加上一行“using mpi ;”(注意mpi後面有個空格，然後一個分號 )
sudo ./b2
mock安裝
matplotlib安裝
sudo python setup.py install
python刪除
sudo apt-get remove Python 卸載的是2.7.6
python3.4刪除
sudo rm -rf /usr/local/lib/python3.4/
sudo rm -rf /usr/lib/python3*
sudo rm -rf /usr/bin/python*
如上操作後，報 /usr/bin/python3: 壞的解釋器: 沒有那個文件或目錄
殘暴處理
mkdir /usr/bin/bakpython
sudo mv -rf /usr/bin/python /usr/bin/bakpython
sudo cp -rf /usr/local/bin/python* /usr/bin/
sudo ln -s /usr/bin/python2.7 /usr/bin/python3
pyenv global 2.7.12 報錯，說沒安裝 ,放棄
Fatal Python error: Py_Initialize: Unable to get the locale encoding
File "/usr/local/lib/python2.7/encodings/__init__.py", line 123
raise CodecRegistryError,\
^
SyntaxError: invalid syntax
vi /etc/grub.d10_linux
linux ${rel_dirname}/${basename} root=${LINUX_HOST_DEVICE} loop=${loop_file_relative} ro ${args} //修改前
linux ${rel_dirname}/${basename} root=${LINUX_HOST_DEVICE} loop=${loop_file_relative} rw ${args}
sudo update-grub
7.3安裝 Tkinter
sudo easy_install Tkinter
sudo pip install Tkinter
sudo apt-get install aptitude
sudo apt-get install python-tk
8、安裝caffe
http://www.cnblogs.com/kunyuanjushi/p/5947066.html
http://blog.csdn.net/lu597203933/article/details/46742199
http://www.cnblogs.com/CarryPotMan/p/5392284.html
我參考網址：https://www.zybuluo.com/hanxiaoyang/note/364737
8.1 安裝依賴包
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
sudo apt-get install OpenBLAS* #本人忘記按這個了
8.2下載
git clone https://github.com/BVLC/caffe
8.3 安裝python依賴(路徑根據自己的目錄可能要調一下)
切換到root用戶下執行，否則可能出現類似如下錯誤：
IOError: [Errno 13] 權限不夠: '/usr/local/lib/python2.7/site-packages/cython.py'的錯誤，當然也可以對 /usr/local/lib/python2.7/site-packages權限進行調整
cd caffe/python
執行
for req in $(cat requirements.txt); do pip install $req; done
這步安裝也有點慢，別急，等會兒，先去幹點別的 ^_^
8.4編輯caffe所需的Makefile文件
cd caffe
cp Makefile.config.example Makefile.config
vim Makefile.config
Makefile.config裏面有依賴庫的路徑，及各種編譯配置，如果是沒有GPU的情況下，可以參照我下面幫你改的配置文件內容:
## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!
# cuDNN acceleration switch (uncomment to build with cuDNN).
# USE_CUDNN := 1
# CPU-only switch (uncomment to build without GPU support).
CPU_ONLY := 1
# uncomment to disable IO dependencies and corresponding data layers
# USE_OPENCV := 0
# USE_LEVELDB := 0
# USE_LMDB := 0
# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)
# You should not set this flag if you will be reading LMDBs with any
# possibility of simultaneous read and write
# ALLOW_LMDB_NOLOCK := 1
# Uncomment if you're using OpenCV 3
# OPENCV_VERSION := 3
# To customize your choice of compiler, uncomment and set the following.
# N.B. the default for Linux is g++ and the default for OSX is clang++
# CUSTOM_CXX := g++
# CUDA directory contains bin/ and lib/ directories that we need.
CUDA_DIR := /usr/local/cuda
# On Ubuntu 14.04, if cuda tools are installed via
# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
# CUDA_DIR := /usr
# CUDA architecture setting: going with all of them.
# For CUDA < 6.0, comment the *_50 lines for compatibility.
CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
-gencode arch=compute_20,code=sm_21 \
-gencode arch=compute_30,code=sm_30 \
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=sm_50 \
-gencode arch=compute_50,code=compute_50
# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
#BLAS := atlas
BLAS := open
# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
# Leave commented to accept the defaults for your choice of BLAS
# (which should work)!
# BLAS_INCLUDE := /path/to/your/blas
# BLAS_LIB := /path/to/your/blas
# Homebrew puts openblas in a directory that is not on the standard search path
# BLAS_INCLUDE := $(shell brew --prefix openblas)/include
# BLAS_LIB := $(shell brew --prefix openblas)/lib
BLAS_INCLUDE := /usr/include/openblas
# This is required only if you will compile the matlab interface.
# MATLAB directory should contain the mex binary in /bin.
# MATLAB_DIR := /usr/local
# MATLAB_DIR := /Applications/MATLAB_R2012b.app
# NOTE: this is required only if you will compile the python interface.
# We need to be able to find Python.h and numpy/arrayobject.h.
PYTHON_INCLUDE := /usr/include/python2.7 \
/usr/lib/python2.7/dist-packages/numpy/core/include
# Anaconda Python distribution is quite popular. Include path:
# Verify anaconda location, sometimes it's in root.
# ANACONDA_HOME := $(HOME)/anaconda
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
# $(ANACONDA_HOME)/include/python2.7 \
# $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \
# We need to be able to find libpythonX.X.so or .dylib.
PYTHON_LIB := /usr/lib
# PYTHON_LIB := $(ANACONDA_HOME)/lib
# Homebrew installs numpy in a non standard path (keg only)
# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
# PYTHON_LIB += $(shell brew --prefix numpy)/lib
# Uncomment to support layers written in Python (will link against Python libs)
WITH_PYTHON_LAYER := 1
# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
# INCLUDE_DIRS += $(shell brew --prefix)/include
# LIBRARY_DIRS += $(shell brew --prefix)/lib
# Uncomment to use `pkg-config` to specify OpenCV library paths.
# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1
BUILD_DIR := build
DISTRIBUTE_DIR := distribute
# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
# DEBUG := 1
# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0
# enable pretty build (comment to see full commands)
Q ?= @
8.4 編譯caffe
make -j8
報如下錯誤
/usr/bin/ld: cannot find -lcblas /usr/bin/ld: cannot find -latlas。
這是由於atlas安裝在/usr/lib和/usr/include裏面，cd到這個路徑下，如果發現只有libblas.so，沒有libatlas.so和libcblas.so，那就需要輸入以下命令手動建立鏈接：
sudo ln -sf ./libblas.so.3 ./libatlas.so
sudo ln -sf ./libblas.so.3 ./libcblas.so
?測試一下編譯結果
sudo make test -j16
sudo make runtest -j16
[----------] 1 test from HDF5OutputLayerTest/0, where TypeParam = caffe::CPUDevice<float>
[ RUN ] HDF5OutputLayerTest/0.TestForward
[ OK ] HDF5OutputLayerTest/0.TestForward (1 ms)
[----------] 1 test from HDF5OutputLayerTest/0 (1 ms total)
[----------] Global test environment tear-down
[==========] 2037 tests from 267 test cases ran. (596193 ms total)
[ PASSED ] 2037 tests.
8.5.編譯pycaffe
sudo make pycaffe -j16
/home/caffe/build/tools/caffe train \
--solver=/home//mnist_solver.prototxt 2>&1 | tee ./mnist_model/cy.txt
/home/system/caffe/build/tools/caffe train --solver=/home/mnist_solver.prototxt 2>&1 | tee ./mnist_model/cy.txt
cd /home/system/caffe/
./data/mnist/get_mnist.sh # 下載數據
/home/system/caffe/examples/mnist/train_lenet.sh
注意下載數據
8.6 安裝fast-rcnn
參考
http://blog.csdn.net/u014696921/article/details/52703586
git clone --recursive https://github.com/rbgirshick/fast-rcnn.git
'bcd9b4eadc7d8fbc433aeefd564e82ec63aaf69c'
‘0dcd397b29507b8314e252e850518c5695efbb83’
~/source/caffe-fast-rcnn
cp Makefile.config.example Makefile.config
sudo make -j8 2>&1|tee make.log
sudo make pycaffe 2>&1|tee make.log
下載Fast RCNN檢測器
./data/scripts/fetch_fast_rcnn_models.sh
9、安裝mysql-connetor（連接mysql 數據庫使用，可以不安裝）
1、使用pip install mysql-connector-python-rf==2.1.3進行安裝
2、使用下載的離線文件（本次使用該方法安裝失敗，建議使用方法1，應該是python不認）
mysql-connector-python_2.2.0-1ubuntu14.04_all.deb
dpkg -i mysql-connector-python_2.2.0-1ubuntu14.04_all.deb
或
mysql-connector-python-2.1.3-1.el6.x86_64.rpm
rpm -ivh mysql-connector-python-2.1.3-1.el6.x86_64.rpm
離線安裝完成後,執行如下命令：
cp -r /usr/lib/python2.7/dist-packages/*mysql* /usr/local/lib/python2.7/site-packages/
cd /usr/local/lib/python2.7/site-packages/
ls -l *mysq*
一定要有如下信息，mysql 和 mysql_connector_python_rf-2.1.3.dist-info 文件夾
mysql:
total 8
drwxr-sr-x 5 root staff 4096 Aug 25 16:20 connector
-rw-r--r-- 1 root staff 0 Aug 25 16:20 __init__.py
-rw-r--r-- 1 root staff 197 Aug 25 16:20 __init__.pyc
mysql_connector_python_rf-2.1.3.dist-info:
total 32
-rw-r--r-- 1 root staff 139 Aug 25 16:20 DESCRIPTION.rst
-rw-r--r-- 1 root staff 4 Aug 25 16:20 INSTALLER
-rw-r--r-- 1 root staff 1466 Aug 25 16:20 METADATA
-rw-r--r-- 1 root staff 1363 Aug 25 16:20 metadata.json
-rw-r--r-- 1 root staff 5568 Aug 25 16:20 RECORD
-rw-r--r-- 1 root staff 6 Aug 25 16:20 top_level.txt
-rw-r--r-- 1 root staff 104 Aug 25 16:20 WHEEL
10、解決ubuntu新建用戶後，tab鍵不能使用的問題
時間:2015-11-12來源:linux網站 作者:期待一片自己的藍天
一、新建用戶 support
adduser 新建用戶的名字
passwd 新建用戶的名字即可添加新用戶
二、創建家目錄
# cd /home
1.創建家目錄：
# mkdir 新建用戶的名字
2.拷貝環境變量模板文件：
# cp /etc/skel/.b* support
# cp /etc/skel/.p* support
3.修改權限
# chown -R support:support support
# chmod 770 support
三、賦予ROOT權限
方法一： 修改 /etc/sudoers 文件，找到下面一行，把前面的註釋（#）去掉
## Allows people in group wheel to run all commands
%wheel ALL=(ALL) ALL
然後修改用戶，使其屬於root組（wheel），命令如下：
#usermod -g root 用戶名
修改完畢，現在可以用新建的用戶名帳號登錄，然後用命令 su - ，即可獲得root權限進行操作。
方法二： 修改 /etc/sudoers 文件，找到下面一行，在root下面添加一行，如下所示：
## Allow root to run any commands anywhere
root ALL=(ALL) ALL
新建用戶的名字 ALL=(ALL) ALL
修改完畢，現在可以用新建的用戶名字帳號登錄，然後用命令 sudo su -，即可獲得root權限進行操作。
四、不能使用TAB鍵、上下鍵，命令行不顯示當前路徑的解決
因默認ubuntu創建的普通帳號，默認shell爲/bin/sh，而這不支持tab等鍵的，所以將「指定用戶」帳號的shell改爲/bin/bash就可以了。
1.查看當前的shell：
# echo $SHELL
/bin/sh
2.修改shell爲/bin/bash：
# usermod -s /bin/bash 用戶名
11、查看系統驅動和信息
11.1顯卡驅動
lspci | grep -i nvidia
11.2系統信息
uname -m && cat /etc/*release
12.ubuntu開機只有桌面，沒有菜單欄和任務欄，只有壁紙
sudo apt-get install unity --fix-missing
13、修改IP地址和機器名稱
修改機器名和IP地址
1、gedit /etc/hostname
2、gedit /etc/hosts
3、gedit /etc/network/interfaces
添加內容如下（根據自己的需要修改）：
auto lo
iface lo inet loopback
auto eth0
iface eth0 inet static
address 10.1.132.233
netmask 255.255.255.0
gateway 10.1.132.1
dns-nameservers 10.36.8.40 10.36.8.41