各种教学视频或文档资料 +QQ:635992897
一、基础环境配置
0、apt-get update
1、sshd安装
sudo apt-get install openssh-server
2、Vi重装
apt-get install vim
3、Samba 安装及配置
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
这些下面加
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用户
sudo smbpasswd -a smbuser
这里一定要保证在linux系统中也有smbuser用户,名称可以自己定
3.4 错误处理
ubuntu14.04中文版装好samba后,报各种错,查看/var/log/samba日志,发现也是报各种错,最后处理发现linux 下使用smbclient 访问正常,Windows下访问报如下:
"无法访问。您可能没有权限使用网络资源,请与这台服务器的管理员联系以查明您是否有访问权限。指定的网络名不再可用。"
日志中有如下错误:
[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]
处理方式:
sudo apt-get install libtalloc2 升级 libtalloc2,参考:http://blog.csdn.net/merlinholland/article/details/52822501
4、sudo自动切换
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 是你想支持用户
5、安装nvidia 驱动,这里是安装Tesla k20c的驱动,也支持k40c 、k80,具体如下:
Tesla K80, Tesla K40c, Tesla K40m, Tesla K40s, Tesla K40st, Tesla K40t, Tesla K20Xm, Tesla K20m, Tesla K20s, Tesla K20c, Tesla K10
5.1 安装 bumblebee
sudo add-apt-repository ppa:bumblebee/stable
sudo apt-get update
sudo apt-get install bumblebee bumblebee-nvidia
5.2 安装nvidia驱动
参考:http://blog.csdn.net/TriLoo/article/details/52678033?locationNum=14
备用: http://blog.163.com/zhao_en_peng/blog/static/12740422420131202110539/
5.2.1.查看电脑的显卡信息以及正在使用的显卡驱动
查看电脑显卡信息命令:lspci | grep VGA
lspci会显示所有的PCI接口设备,然后从中提取处显示相关的设备(VGA)。
执行命令会得到类似下面的信息:
01:00.0 VGA compatible controller: NVIDIA Corporation GM107 [GeForce GTX 745] (rev a2)
从上面的信息可以看出:显卡型号为GTX745。显卡型号会在后面下载显卡驱动时用到。
得到显卡型号后,可以利用下面的命令查看关于显卡的更详细信息:
lspci -v -s 01:00.01
-v : 显示详细信息
-s : 后面接PCI设备的ID
执行命令会得到类似下面的信息:
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
其中在最后一行显示正在使用的驱动是nvidias。这是安装Nvidia显卡后的显示,最开始会显示nouveau。
在倒数第二行显示access denied,是因为权限问题,可以sudo解决。
好了现在我们知道了显卡型号以及显卡驱动信息了下一步是去Nvidia官网下载相应的显卡驱动程序。
1.下载驱动
Nvidia驱动下载链接: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
在打开的界面中(界面如下图),建议选用手动根据自己的系统、显卡型号等选择相关的驱动。
5.2.2.禁止nouveau驱动
通过网上的相关信息,如果之前显卡驱动是用的nouveau,那么在安装自己下载的驱动的时候会显示错误。
所以在安装驱动之前,需要先在/etc/modprobe.d/blacklist.conf文件中加入下面内容:
blacklist nouveau
然后重新启动。
sudo reboot
5.2.3.安装显卡
重启后,在登陆界面时同时按下:Ctrl + Alt + F1~F6进入字符界面。
也可以在登陆界面登陆后,在终端输入init 3来改变run level.
需要说明的是,重启后,会发现字体变大,这属于正常显现。
登陆tt1终端,然后关闭Ubuntu的Unity:
sudo service lightdm stop
其中lightdm根据自己使用的桌面做相应的调整:
[KDM(KDE),GDM(GNOME)
然后进入之前下载的驱动文件所在的目录,运行下载的脚本文件即可:
sudo sh NVIDIA-Linux-x86_64-346.96.run
#sudo dpkg -i nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb 错误
后面根据程序的提示操作即可。
5.2.4.重启
安装完成后,重启即可。
sudo service lightdm start
问题处理:
(1) 安装完成后重启可能会出现循环登录的情况,解决方法是重启前先按照下面教程安装一个管理软件:
http://blog.csdn.net/triloo/article/details/52767412
见5.1安装 bumblebee
(2)错误信息:
软件包的体系架构(ppc64el)与本机系统的架构(amd64)不符
在处理时有错误发生:
nvidia-driver-repo-ubuntu1404_7.0-346.96_ppc64el.deb
下载安装包错误,重新下载适合你机器的安装包即可
安装检查工具
sudo apt-get install mesa-utils
6、安装CUDA7.0
下载CUDA7.0
6.1安装 cuda
6.1.1安装依赖库
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安装CUDA7.0 参考: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.
(正在读取数据库 ... 系统当前共安装有 171979 个文件和目录。)
Preparing to unpack cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb ...
Unpacking cuda-repo-ubuntu1404-7-0-local (7.0-28) ...
正在设置 cuda-repo-ubuntu1404-7-0-local (7.0-28) ...
OK
(1.5) sudo apt-get update
(2)sudo apt-get install cuda
正在读取软件包列表... 完成
正在分析软件包的依赖关系树
正在读取状态信息... 完成
下列软件包是自动安装的并且现在不需要了:
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.
将会安装下列额外的软件包:
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
下列软件包将被【卸载】:
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】软件包将被安装:
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
下列软件包将被升级:
nvidia-settings
升级了 1 个软件包,新安装了 44 个软件包,要卸载 8 个软件包,有 590 个软件包未被升级。
需要下载 75.5 MB/1,042 MB 的软件包。
解压缩后会消耗掉 1,556 MB 的额外空间。
您希望继续执行吗? [Y/n] y
获取:1 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-352 amd64 367.57-0ubuntu0.14.04.1 [4,802 B]
获取:2 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346 amd64 352.63-0ubuntu0.14.04.1 [4,802 B]
获取:3 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-367 amd64 367.57-0ubuntu0.14.04.1 [69.8 MB]
获取:4 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-367 amd64 367.57-0ubuntu0.14.04.1 [2,708 kB]
获取:5 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346-uvm amd64 346.96-0ubuntu0.0.1 [4,762 B]
获取:6 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-367-dev amd64 367.57-0ubuntu0.14.04.1 [80.8 kB]
获取:7 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-352-dev amd64 367.57-0ubuntu0.14.04.1 [4,806 B]
获取:8 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-346-dev amd64 352.63-0ubuntu0.14.04.1 [4,812 B]
获取:9 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-352 amd64 367.57-0ubuntu0.14.04.1 [4,814 B]
获取:10 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted libcuda1-346 amd64 352.63-0ubuntu0.14.04.1 [4,810 B]
获取:11 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-367 amd64 367.57-0ubuntu0.14.04.1 [2,901 kB]
获取:12 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-352 amd64 367.57-0ubuntu0.14.04.1 [4,818 B]
获取:13 http://cn.archive.ubuntu.com/ubuntu/ trusty-updates/restricted nvidia-opencl-icd-346 amd64 352.63-0ubuntu0.14.04.1 [4,822 B]
下载 75.5 MB,耗时 13分 13秒 (95.2 kB/s)
正在从软件包中解出模板:100%
Selecting previously unselected package nvidia-352.
(正在读取数据库 ... 系统当前共安装有 179276 个文件和目录。)
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) ...
(正在读取数据库 ... 系统当前共安装有 179281 个文件和目录。)
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 依赖于 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:没有发现操作
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.
(正在读取数据库 ... 系统当前共安装有 178942 个文件和目录。)
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 依赖于 libcuda-5.5-1;然而:
未安装软件包 libcuda-5.5-1。
提供了 libcuda-5.5-1 的软件包 libcuda1-340 即将被删除。
nvidia-profiler 依赖于 libcuda-5.5-1;然而:
未安装软件包 libcuda-5.5-1。
提供了 libcuda-5.5-1 的软件包 libcuda1-340 即将被删除。
(正在读取数据库 ... 系统当前共安装有 179508 个文件和目录。)
Removing libcuda1-340 (340.98-0ubuntu0.14.04.1) ...
Processing triggers for libc-bin (2.19-0ubuntu6) ...
Selecting previously unselected package libcuda1-367.
(正在读取数据库 ... 系统当前共安装有 179500 个文件和目录。)
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) ...
Selecting previously unselected package cuda-cudart-7-0.
Preparing to unpack .../cuda-cudart-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cudart-7-0 (7.0-28) ...
Selecting previously unselected package cuda-driver-dev-7-0.
Preparing to unpack .../cuda-driver-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-driver-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cudart-dev-7-0.
Preparing to unpack .../cuda-cudart-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cudart-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-command-line-tools-7-0.
Preparing to unpack .../cuda-command-line-tools-7-0_7.0-28_amd64.deb ...
Unpacking cuda-command-line-tools-7-0 (7.0-28) ...
Selecting previously unselected package cuda-nvrtc-7-0.
Preparing to unpack .../cuda-nvrtc-7-0_7.0-28_amd64.deb ...
Unpacking cuda-nvrtc-7-0 (7.0-28) ...
Selecting previously unselected package cuda-nvrtc-dev-7-0.
Preparing to unpack .../cuda-nvrtc-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-nvrtc-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cusolver-7-0.
Preparing to unpack .../cuda-cusolver-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cusolver-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cusolver-dev-7-0.
Preparing to unpack .../cuda-cusolver-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cusolver-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cublas-7-0.
Preparing to unpack .../cuda-cublas-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cublas-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cublas-dev-7-0.
Preparing to unpack .../cuda-cublas-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cublas-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cufft-7-0.
Preparing to unpack .../cuda-cufft-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cufft-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cufft-dev-7-0.
Preparing to unpack .../cuda-cufft-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cufft-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-curand-7-0.
Preparing to unpack .../cuda-curand-7-0_7.0-28_amd64.deb ...
Unpacking cuda-curand-7-0 (7.0-28) ...
Selecting previously unselected package cuda-curand-dev-7-0.
Preparing to unpack .../cuda-curand-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-curand-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cusparse-7-0.
Preparing to unpack .../cuda-cusparse-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cusparse-7-0 (7.0-28) ...
Selecting previously unselected package cuda-cusparse-dev-7-0.
Preparing to unpack .../cuda-cusparse-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-cusparse-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-npp-7-0.
Preparing to unpack .../cuda-npp-7-0_7.0-28_amd64.deb ...
Unpacking cuda-npp-7-0 (7.0-28) ...
Selecting previously unselected package cuda-npp-dev-7-0.
Preparing to unpack .../cuda-npp-dev-7-0_7.0-28_amd64.deb ...
Unpacking cuda-npp-dev-7-0 (7.0-28) ...
Selecting previously unselected package cuda-samples-7-0.
Preparing to unpack .../cuda-samples-7-0_7.0-28_amd64.deb ...
Unpacking cuda-samples-7-0 (7.0-28) ...
Selecting previously unselected package cuda-documentation-7-0.
Preparing to unpack .../cuda-documentation-7-0_7.0-28_amd64.deb ...
Unpacking cuda-documentation-7-0 (7.0-28) ...
Selecting previously unselected package cuda-visual-tools-7-0.
Preparing to unpack .../cuda-visual-tools-7-0_7.0-28_amd64.deb ...
Unpacking cuda-visual-tools-7-0 (7.0-28) ...
Selecting previously unselected package cuda-toolkit-7-0.
Preparing to unpack .../cuda-toolkit-7-0_7.0-28_amd64.deb ...
Unpacking cuda-toolkit-7-0 (7.0-28) ...
Selecting previously unselected package nvidia-346-uvm.
Preparing to unpack .../nvidia-346-uvm_346.96-0ubuntu0.0.1_amd64.deb ...
Unpacking nvidia-346-uvm (346.96-0ubuntu0.0.1) ...
Selecting previously unselected package nvidia-367-dev.
Preparing to unpack .../nvidia-367-dev_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-367-dev (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-352-dev.
Preparing to unpack .../nvidia-352-dev_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-352-dev (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-346-dev.
Preparing to unpack .../nvidia-346-dev_352.63-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-346-dev (352.63-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-modprobe.
Preparing to unpack .../nvidia-modprobe_346.46-0ubuntu1_amd64.deb ...
Unpacking nvidia-modprobe (346.46-0ubuntu1) ...
Preparing to unpack .../nvidia-settings_346.46-0ubuntu1_amd64.deb ...
Unpacking nvidia-settings (346.46-0ubuntu1) over (331.20-0ubuntu8) ...
Selecting previously unselected package libcuda1-352.
Preparing to unpack .../libcuda1-352_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking libcuda1-352 (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package libcuda1-346.
Preparing to unpack .../libcuda1-346_352.63-0ubuntu0.14.04.1_amd64.deb ...
Unpacking libcuda1-346 (352.63-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-opencl-icd-367.
Preparing to unpack .../nvidia-opencl-icd-367_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-opencl-icd-367 (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-opencl-icd-352.
Preparing to unpack .../nvidia-opencl-icd-352_367.57-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-opencl-icd-352 (367.57-0ubuntu0.14.04.1) ...
Selecting previously unselected package nvidia-opencl-icd-346.
Preparing to unpack .../nvidia-opencl-icd-346_352.63-0ubuntu0.14.04.1_amd64.deb ...
Unpacking nvidia-opencl-icd-346 (352.63-0ubuntu0.14.04.1) ...
Selecting previously unselected package cuda-drivers.
Preparing to unpack .../cuda-drivers_346.46-1_amd64.deb ...
Unpacking cuda-drivers (346.46-1) ...
Selecting previously unselected package cuda-runtime-7-0.
Preparing to unpack .../cuda-runtime-7-0_7.0-28_amd64.deb ...
Unpacking cuda-runtime-7-0 (7.0-28) ...
Selecting previously unselected package cuda-7-0.
Preparing to unpack ..././cuda-7-0_7.0-28_amd64.deb ...
Unpacking cuda-7-0 (7.0-28) ...
Selecting previously unselected package cuda.
Preparing to unpack ..././cuda_7.0-28_amd64.deb ...
Unpacking cuda (7.0-28) ...
Processing triggers for man-db (2.6.7.1-1) ...
Processing triggers for doc-base (0.10.5) ...
Processing 1 added doc-base file...
Processing triggers for gnome-menus (3.10.1-0ubuntu2) ...
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) ...
正在设置 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 自动模式
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 自动模式
update-alternatives: using /usr/share/nvidia-367/glamor.conf to provide /usr/share/X11/xorg.conf.d/glamoregl.conf (glamor_conf) in 自动模式
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
正在添加系统用户"nvidia-persistenced" (UID 117)...
正在添加新组"nvidia-persistenced" (GID 125)...
正在将新用户"nvidia-persistenced" (UID 117)添加到组"nvidia-persistenced"...
无法创建主目录"/"
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.
正在设置 nvidia-352 (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-346 (352.63-0ubuntu0.14.04.1) ...
正在设置 libcuda1-367 (367.57-0ubuntu0.14.04.1) ...
正在设置 ocl-icd-libopencl1:amd64 (2.1.3-4) ...
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 cuda-samples-7-0 (7.0-28) ...
正在设置 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.
正在设置 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.
正在设置 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.
正在设置 nvidia-346-uvm (346.96-0ubuntu0.0.1) ...
正在设置 nvidia-367-dev (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-352-dev (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-346-dev (352.63-0ubuntu0.14.04.1) ...
正在设置 nvidia-modprobe (346.46-0ubuntu1) ...
正在设置 nvidia-settings (346.46-0ubuntu1) ...
正在设置 libcuda1-352 (367.57-0ubuntu0.14.04.1) ...
正在设置 libcuda1-346 (352.63-0ubuntu0.14.04.1) ...
正在设置 nvidia-opencl-icd-367 (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-opencl-icd-352 (367.57-0ubuntu0.14.04.1) ...
正在设置 nvidia-opencl-icd-346 (352.63-0ubuntu0.14.04.1) ...
正在设置 cuda-drivers (346.46-1) ...
正在设置 cuda-runtime-7-0 (7.0-28) ...
正在设置 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. ***
*****************************************************************************************
正在设置 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 安装 cuda-toolkit
好像没装,装了toolkit,检查一下
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,否则执行:
sudo apt-get install nvidia-cuda-toolkit
安装失败,nvidia-cuda-toolkit : 依赖: nvidia-opencl-dev (= 5.5.22-3ubuntu1) 但是它将不
重新执行一下, 6.3.1 问题处理,执行 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 安装sample(如果安装的是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
这样,就将cuda的sample拷贝到dir文件夹下了。该命令只是一个拷贝操作。
我的执行如下:
$ cuda-install-samples-7.0.sh /home/cudaSamples/
cd /home/cudaSamples/
$ make
然后进入该文件夹,执行make命令进行编译,编译时间较长,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 ./`
执行成功再次make 完成
执行 /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
重启发现,系统不能正常显示,只出现log界面,崩溃!!!!
6.3.1 问题处理如下:
首先,之前使用bumblebee解决双显卡问题的需要卸载bumblebee。
(1) sudo apt-get purge bumblebee*
安装nvidia-367驱动和nvidia prime,这里先不管驱动的版本问题
(2). sudo stop lightdm
(3). sudo apt-get install nvidia-367 nvidia-prime 重装驱动 因该是
切换到nvidia独显下安装CUDA
(3.5). sudo prime-select nvidia 应该是这步起作用了
(3.8).sudo dpkg -i cuda-repo-ubuntu1404-7-0-local_7.0-28_amd64.deb 这步估计没用
(4).sudo reboot 重启,
(5).系统启动还报错,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
先看驱动检测
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,安装cuDNN
下载 cudnn-7.0-linux-x64-v3.0-prod.tgz,官网申请不到,网上自己找的,就不给地址了。
[plain] view plain copy print?在CODE上查看代码片派生到我的代码片
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
同时需要添加lib库路径: 在 /etc/ld.so.conf.d/加入文件 cuda.conf, 内容如下
/usr/local/cuda/lib64
保存后,执行下列命令使之立刻生效
sudo ldconfig
7、安装python
7.1 不再安装python管理工具pyenv,跳过##错误##
(1)安装git
sudo apt-get install git
###### (2)安装python管理工具pyenv,这里我假设用用户system安装
###### sudo git clone git://github.com/yyuu/pyenv.git ~/.pyenv
###### 切换到root用户
###### 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 编译安装
(1)安装依赖库
安装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)编译python
pyenv install 2.7.12 -v 下载失败
拷贝下载的源码安装
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
所以通常我们./configure的时候,默认是--prefix=/usr,这样的话,本程序的配置文件就会装到/usr/etc,应用文件就会安装到/usr/bin,本程序的私有库也会安装到/usr/lib等等,,我们也不用设置PATH就可以直接用了,,
sudo make install
(2.5)修改链接
sudo mv /usr/bin/python /usr/bin/python2.7.6
sudo ln -s /usr/local/bin/python2.7 /usr/bin/python
a.需要编辑/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文件配置完毕后,我们需要执行如下命令:
sudo /sbin/ldconfig
sudo /sbin/ldconfig -v
c. 然后再执行python -V命令,查看python版本如下
Python 2.7.12
(3)安装python的pip和easy_install(工具包 setuptools-32.3.0.zip ),方便安装软件包
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)安装其他包
a. numpy 安装
tar -xzvf numpy-1.12.0b1.tar.gz
cd numpy-1.12.0b1
sudo python setup.py install
b. mock安装
tar -xzvf mock-2.0.0.tar.gz
cd mock-2.0.0/
sudo python setup.py install
c. six安装
tar -xvzf six-1.10.0.tar.gz
cd six-1.10.0/
sudo python setup.py install
d. pbr.version安装
tar -xzvf pbr-1.10.0.tar.gz
cd pbr-1.10.0/
sudo python setup.py install
e. funcsigs 安装
tar -xvzf funcsigs-1.0.2.tar.gz
cd funcsigs-1.0.2/
sudo python setup.py install
f. atlas3 安装(没装)
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
**************************************************
编译过程出错,提示be due to shut off throttling ,放弃安装,可以通过进入bois修改对应选项再安装
g. boost_1_57_0 安装
#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 在最后面加上一行“using mpi ;”(注意mpi后面有个空格,然后一个分号 )
sudo ./b2
sudo ./b2 install --prefix=/usr
h. dask安装
tar -xzvf dask-0.12.0.tar.gz
cd dask-0.12.0/
sudo python setup.py install
i. easydict 安装
unzip easydict-1.6.zip
cd easydict-1.6/
sudo python setup.py install
j. Cython 安装
tar -xzvf Cython-0.25.1.tar.gz
cd Cython-0.25.1/
sudo python setup.py install
k. h5py 安装
tar -xvzf h5py-2.6.0.tar.gz
cd h5py-2.6.0/
sudo python setup.py install
缺少 hdf5.h 文件,下载 anaconda 安装
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安装
tar -xvzf ipython-5.1.0.tar.gz
cd ipython-5.1.0/
sudo python setup.py install
n. lapack安装
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/
编辑Makefile 文件内容, 把
lib: lapacklib tmglib
#lib: blaslib variants lapacklib tmglib
改为:
#lib: lapacklib tmglib
lib: blaslib variants lapacklib tmglib
将生成的liblapack.a,librefblas.a,libtmglib.a 三个库拷贝到/usr/lib
sudo cp liblapack.a /usr/lib
sudo cp librefblas.a /usr/lib
sudo cp libtmglib.a /usr/lib
o. leveldb安装
tar -xvzf leveldb-0.194.tar.gz
cd leveldb-0.194/
sudo python setup.py install
p. matplotlib安装 ..... Math跳过去没装
tar -xzvf matplotlib-1.4.2.tar.gz
cd matplotlib-1.4.2/
sudo python setup.py install
报如下错误:
* The following required packages can not be built:
* freetype, png
采用如下方法安装:
安装 :sudo apt-get install libpng-dev
下载 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
再次执行:
sudo python setup.py install , 另一种安装方式: sudo pip install matplotlib
测试安装成功 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
修改为:backend : Qt4Agg
在Ubuntu系统上安装PySide
sudo add-apt-repository ppa:pyside
sudo apt-get update
sudo apt-get install python-pyside
如果想只装某个模块:
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/
使用下面的方法测试是否安装成功:
>>> from PySide.QtCore import *
>>> print QT_VERSION_STR 运行错误,忽略
4.7.0
q. networkx 安装
tar -xzvf networkx-1.11.tar.gz
cd networkx-1.11/
sudo python setup.py install
自动安装了decorator库
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 安装
tar -xvzf nose-1.3.7.tar.gz
cd nose-1.3.7/
sudo python setup.py install
s. pandas 安装
tar -xzvf pandas-0.19.1.tar.gz
cd pandas-0.19.1/
sudo python setup.py install
t. pip 安装
tar -xzvf pip-9.0.1.tar.gz
cd pip-9.0.1/
sudo python setup.py install
u. pkgconfig安装
tar -xvzf pkgconfig-1.1.0.tar.gz
cd pkgconfig-1.1.0/
sudo python setup.py install
v. protobuf安装
unzip protobuf-2.5.0.zip
cd protobuf-2.5.0/
sudo ./configure --prefix=/usr #漏掉了 --prefix 安装到/usr/local/lib有报错,将前一次安装的/usr/local/lib下的文件拷贝到/usr/lib****************************
************************************
sudo make
sudo make check
sudo make install
sudo ldconfig
安装protobuf的Python支持
cd python # 位于protobuf下
python setup.py build
sudo python setup.py test
sudo python setup.py install
验证 protoc --version
#python
>>>import google.protobuf
w. pyparsing安装
tar -xzvf pyparsing-2.1.10.tar.gz
cd pyparsing-2.1.10/
sudo python setup.py install
x. python-dateutil安装
tar -xvf python-dateutil-1.4.tar
cd python-dateutil-1.4/
sudo python setup.py install
y. python-gflags安装
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 报错,采用下面方式安装
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 安装
sudo pip install opencv-python
也可直接执行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
测试安装
python
>>> import cv2
d1. Wx图形库安装
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 ./
如果有报错,记得安装以下包:
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
错误的步骤,安装2.8.12.1,好像编译后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
该报错网上提示是自带bug,改为安装3.0.2.0,但是由于安装了2.8,所以需要删除原有2.8,折腾了
下面的安装包错误:
tar -xzvf wx-3.0.3.tar.gz
cd wxPython_Phoenix-3.0.3
以下不对
tar -xzvf wxWidgets-2.8.12.tar.gz
cd wxWidgets-2.8.12/
sudo ./configure --prefix=/usr --with-gtk
sudo make
sudo make install
安装出错:
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
删除所有与gtk2-unicode-2.8有关的文件和文件夹,重新安装 sudo make install
其他错误处理
configure: error: GStreamer not available
ubuntu14.04安装GStreamer插件
sudo apt-get install libghc-gstreamer-dev
以下不对,记录下走错的路:
sudo add-apt-repository ppa:mc3man/trusty-media
sudo apt-get update
sudo apt-get install gstreamer0.10-ffmpeg
e1. mysql-connector-python安装
也折腾了一下,不知道怎么搞的以前pip install mysql-connector-python-rf==2.1.3和deb包安装都可以,没办法下载一个2.1.4安装
unzip mysql-connector-2.1.4.zip
cd mysql-connector-2.1.4/
sudo python setup.py install
测试:
python
>>>
import mysql.connector
f1. 安装yaml
前面包安装中,已经安装
(5)更改环境变量
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
错误: ImportError: No module named _io
sudo pip install virtualenv --upgrade
这次还会报错首先会报一个PIC的错误还有/usr/local/lib/libboost_python.so: undefined reference to `PyUnicodeUCS4_AsWideChar'
这时因为caffe需要用UCS4编码格式,但是我们的Python环境是UCS2的所以需要卸载掉我们环境里的所有Python,sudo apt-get remove Python(如果卸载失败需要手动删除比较麻烦),然后手动下载Python的源码包进行编译安装
进入源码目录
./configure --enable-unicode=ucs4 --enable-shared cxxflags=-fPIC cflags=-fPIC
Make;sudo make install
进入Python环境 >>>import sys >>>print(sys.maxunicode)看下打印是不是1114111
(6)安装完Python我们还需要重装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 在最后面加上一行“using mpi ;”(注意mpi后面有个空格,然后一个分号 )
sudo ./b2
mock安装
matplotlib安装
sudo python setup.py install
python删除
sudo apt-get remove Python 卸载的是2.7.6
python3.4删除
sudo rm -rf /usr/local/lib/python3.4/
sudo rm -rf /usr/lib/python3*
sudo rm -rf /usr/bin/python*
如上操作后,报 /usr/bin/python3: 坏的解释器: 没有那个文件或目录
残暴处理
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 报错,说没安装 ,放弃
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安装 Tkinter
sudo easy_install Tkinter
sudo pip install Tkinter
sudo apt-get install aptitude
sudo apt-get install python-tk
8、安装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
我参考网址:https://www.zybuluo.com/hanxiaoyang/note/364737
8.1 安装依赖包
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* #本人忘记按这个了
8.2下载
git clone https://github.com/BVLC/caffe
8.3 安装python依赖(路径根据自己的目录可能要调一下)
切换到root用户下执行,否则可能出现类似如下错误:
IOError: [Errno 13] 权限不够: '/usr/local/lib/python2.7/site-packages/cython.py'的错误,当然也可以对 /usr/local/lib/python2.7/site-packages权限进行调整
cd caffe/python
执行
for req in $(cat requirements.txt); do pip install $req; done
这步安装也有点慢,别急,等会儿,先去干点别的 ^_^
8.4编辑caffe所需的Makefile文件
cd caffe
cp Makefile.config.example Makefile.config
vim Makefile.config
Makefile.config里面有依赖库的路径,及各种编译配置,如果是没有GPU的情况下,可以参照我下面帮你改的配置文件内容:
## 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 编译caffe
make -j8
报如下错误
/usr/bin/ld: cannot find -lcblas /usr/bin/ld: cannot find -latlas。
这是由于atlas安装在/usr/lib和/usr/include里面,cd到这个路径下,如果发现只有libblas.so,没有libatlas.so和libcblas.so,那就需要输入以下命令手动建立链接:
sudo ln -sf ./libblas.so.3 ./libatlas.so
sudo ln -sf ./libblas.so.3 ./libcblas.so
?测试一下编译结果
sudo make test -j16
sudo make runtest -j16
[----------] 1 test from HDF5OutputLayerTest/0, where TypeParam = caffe::CPUDevice
[ 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.编译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 # 下载数据
/home/system/caffe/examples/mnist/train_lenet.sh
注意下载数据
8.6 安装fast-rcnn
参考
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
下载Fast RCNN检测器
./data/scripts/fetch_fast_rcnn_models.sh
9、安装mysql-connetor(连接mysql 数据库使用,可以不安装)
1、使用pip install mysql-connector-python-rf==2.1.3进行安装
2、使用下载的离线文件(本次使用该方法安装失败,建议使用方法1,应该是python不认)
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
离线安装完成后,执行如下命令:
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 文件夹
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、解决ubuntu新建用户后,tab键不能使用的问题
时间:2015-11-12来源:linux网站 作者:期待一片自己的蓝天
一、新建用户 support
adduser 新建用户的名字
passwd 新建用户的名字即可添加新用户
二、创建家目录
# cd /home
1.创建家目录:
# mkdir 新建用户的名字
2.拷贝环境变量模板文件:
# cp /etc/skel/.b* support
# cp /etc/skel/.p* support
3.修改权限
# chown -R support:support support
# chmod 770 support
三、赋予ROOT权限
方法一: 修改 /etc/sudoers 文件,找到下面一行,把前面的注释(#)去掉
## Allows people in group wheel to run all commands
%wheel ALL=(ALL) ALL
然后修改用户,使其属于root组(wheel),命令如下:
#usermod -g root 用户名
修改完毕,现在可以用新建的用户名帐号登录,然后用命令 su - ,即可获得root权限进行操作。
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
新建用户的名字 ALL=(ALL) ALL
修改完毕,现在可以用新建的用户名字帐号登录,然后用命令 sudo su -,即可获得root权限进行操作。
四、不能使用TAB键、上下键,命令行不显示当前路径的解决
因默认ubuntu创建的普通帐号,默认shell为/bin/sh,而这不支持tab等键的,所以将「指定用户」帐号的shell改为/bin/bash就可以了。
1.查看当前的shell:
# echo $SHELL
/bin/sh
2.修改shell为/bin/bash:
# usermod -s /bin/bash 用户名
11、查看系统驱动和信息
11.1显卡驱动
lspci | grep -i nvidia
11.2系统信息
uname -m && cat /etc/*release
12.ubuntu开机只有桌面,没有菜单栏和任务栏,只有壁纸
sudo apt-get install unity --fix-missing
13、修改IP地址和机器名称
修改机器名和IP地址
1、gedit /etc/hostname
2、gedit /etc/hosts
3、gedit /etc/network/interfaces
添加内容如下(根据自己的需要修改):
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