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从APNIC获取中国IP地址列表 关于APNIC 全球IP地址块被IANA(Internet Assigned Numbers Authority)分配给全球三大地区性IP地址分配机构，它们分别是：ARIN (American Registry for Internet Numbers) 负责北美、南美、加勒比以及非洲撒哈啦部分的IP地址分配。同时还要给全球NSP(Network Service Providers)分配地址。RIPE (Reseaux IP Europeens) 负责欧洲、中东、北非、西亚部分地区(前苏联)APNIC (Asia Pacific Network Information Center) 负责亚洲、太平洋地区APNIC IP地址分配信息总表的获取：APNIC提供了每日更新的亚太地区IPv4，IPv6，AS号分配的信息表：http://ftp.apnic.net/apnic/stats/apnic/delegated-apnic-latest该文件的格式与具体内容参见：ftp://ftp.apnic.net/pub/apnic/stats/apnic/README.TXT通过该文件我们能够得到APNIC辖下IPv4地址空间的分配情况。脚本获取IP地址#!/bin/bash wget -c http://ftp.apnic.net/stats/apnic/delegated-apnic-latest cat delegated-apnic-latest | awk -F '|' '/CN/&&/ipv4/ {print $4 "/" 32-log($5)/log(2)}' | cat > ipv4.txt cat delegated-apnic-latest | awk -F '|' '/CN/&&/ipv6/ {print $4 "/" 32-log($5)/log(2)}' | cat > ipv6.txt cat delegated-apnic-latest | awk -F '|' '/HK/&&/ipv4/ {print $4 "/" 32-log($5)/log(2)}' | cat > ipv4-hk.txt cat delegated-apnic-latest | awk -F '|' '/HK/&&/ipv6/ {print $4 "/" 32-log($5)/log(2)}' | cat > ipv6-hk.txt执行脚本：[root@cby cby]# ./ip.sh --2021-04-29 12:17:13-- http://ftp.apnic.net/stats/apnic/delegated-apnic-latest Resolving ftp.apnic.net (ftp.apnic.net)... 203.119.102.40, 2001:dd8:8:701::40 Connecting to ftp.apnic.net (ftp.apnic.net)|203.119.102.40|:80... connected. HTTP request sent, awaiting response... 200 OK Length: 3352151 (3.2M) [text/plain] Saving to: ‘delegated-apnic-latest’ delegated-apnic-latest 100%[=============================================================>] 3.20M 61.3KB/s in 44s 2021-04-29 12:17:58 (74.0 KB/s) - ‘delegated-apnic-latest’ saved [3352151/3352151] [root@cby cby]# ls delegated-apnic-latest index.html ip.sh ipv4-hk.txt ipv4.txt ipv6-hk.txt ipv6.txt 每日凌晨十二点十分会进行同步，若需要IP地址，可以访问如下地址：http://aliyun.chenby.cn/定时任务：[root@cby cby]# crontab -l 10 0 * * * /www/server/cron/3ab48c27ec99cb9787749c362afae517 >> /www/server/cron/3ab48c27ec99cb9787749c362afae517.log 2>&1 10 0 * * * rm -rf /www/wwwroot/www.chenby.cn/cby/ipv4.txt /www/wwwroot/www.chenby.cn/cby/ipv4-hk.txt /www/wwwroot/www.chenby.cn/cby/ipv6.txt /www/wwwroot/www.chenby.cn/cby/ipv6-hk.txt /www/wwwroot/www.chenby.cn/cby/delegated-apnic-latest 11 0 * * * /www/wwwroot/www.chenby.cn/cby/ip.sh >> /home/ip.txt本文使用 文章同步助手 同步 -
华为人工智能atlasA800-9000物理服务器离线安装及CANN安装和MindSpore安装和Tensorflow安装 目录华为人工智能atlas A800-9000 物理服务器全程离线安装驱动以及CANN安装部署和MindSpore安装部署和Tensorflow安装部署A800-9000 物理服务器安装驱动使用镜像配置本地apt源创建普通用户并设置密码安装驱动以及固件验证是否安装成功CANN开发环境部署安装安装环境以及依赖安装完成后查看版本安装Python3.7.5使用Python3.7.5环境安装pip依赖包安装开发套件包CANN训练环境部署安装说明安装训练软件包安装MindSpore安装whl包配置环境变量测试是否可行安装mindinsight安装whl包配置环境变量启动及使用安装Tensorflow编译hdf5配置环境变量及软连接安装whl包安装Pytorch华为人工智能atlas A800-9000 物理服务器全程离线安装驱动以及CANN安装部署和MindSpore安装部署和Tensorflow安装部署背景Atlas 800 训练服务器（型号：9000）是基于华为鲲鹏920+昇腾910处理器的AI训练服务器，具有最强算力密度、超高能效与高速网络带宽等特点。该服务器广泛应用于深度学习模型开发和训练，适用于智慧城市、智慧医疗、天文探索、石油勘探等需要大算力的行业领域。链接：https://e.huawei.com/cn/products/cloud-computing-dc/atlas/atlas-800-training-9000CANN (Compute Architecture for Neural Networks)是华为公司针对AI场景推出的异构计算架构，通过提供多层次的编程接口，支持用户快速构建基于昇腾平台的AI应用和业务。链接：https://e.huawei.com/cn/products/cloud-computing-dc/atlas/cannMindSpore，新一代AI开源计算框架。创新编程范式，AI科学家和工程师更易使用，便于开放式创新；该计算框架可满足终端、边缘计算、云全场景需求，能更好保护数据隐私；可开源，形成广阔应用生态。链接：https://www.mindspore.cn/TensorFlow最初由谷歌大脑团队开发，用于Google的研究和生产，于2015年11月9日在Apache 2.0开源许可证下发布。 链接： https://www.tensorflow.org/A800-9000物理服务器安装驱动使用镜像配置本地apt源root@ubuntu:/etc/apt# mkdir/media/cdrom root@ubuntu:/etc/apt# mount/home/cby/ubuntu-18.04.5-server-arm64.iso /media/cdrom mount: /media/chrom: WARNING:device write-protected, mounted read-only. root@ubuntu:/etc/apt# apt-cdrom-m -d=/media/cdrom/ add root@ubuntu:/etc/apt# cat/etc/apt/sources.list创建普通用户并设置密码root@ubuntu:~#groupadd HwHiAiUser root@ubuntu:~#useradd -g HwHiAiUser -d /home/HwHiAiUser -m HwHiAiUser root@ubuntu:~#passwd HwHiAiUser Enter newUNIX password: Retype newUNIX password: passwd:password updated successfully安装驱动以及固件root@ubuntu:~# cd /home/cby/ root@ubuntu:/home/cby# ll total 98324 drwxr-xr-x 4 cby cby 4096 Apr 21 21:41 ./ drwxr-xr-x 4 root root 4096 Apr 21 21:44 ../ -rw-r--r-- 1 cby cby 99728721 Apr 21 21:41A800-9000-npu-driver\_20.2.0\_ubuntu18.04-aarch64.run -rw-r--r-- 1 cby cby 912335 Apr 21 21:41 A800-9000-npu-firmware\_1.76.22.3.220.run root@ubuntu:/home/cby# chmod +x\*.run root@ubuntu:/home/cby# ll total 98324 drwxr-xr-x 4 cby cby 4096 Apr 21 21:41 ./ drwxr-xr-x 4 root root 4096 Apr 21 21:44 ../ -rwxr-xr-x 1 cby cby 99728721 Apr 21 21:41 A800-9000-npu-driver\_20.2.0\_ubuntu18.04-aarch64.run\* -rwxr-xr-x 1 cby cby 912335 Apr 21 21:41 A800-9000-npu-firmware\_1.76.22.3.220.run\* root@ubuntu:/home/cby# aptinstall gcc root@ubuntu:/home/cby# aptinstall make root@ubuntu:/home/cby#./A800-9000-npu-driver\_20.2.0\_ubuntu18.04-aarch64.run –run root@ubuntu:/home/cby#./A800-9000-npu-firmware\_1.76.22.3.220.run –run*注意：安装完成后需要重启服务器验证是否安装成功root@ubuntu:/home/cby#npu-smi infoCANN开发环境部署安装 安装环境以及依赖root@ubuntu:/home/cby# apt install g++ root@ubuntu:/home/cby# cd cmake/ root@ubuntu:/home/cby/cmake# ll total 4356 drwxr-xr-x 2 root root 4096 Apr 21 23:48 ./ drwxr-xr-x 7 cby cby 4096 Apr 21 23:48 ../ -rw-r--r-- 1 cby cby 2971248 Apr 21 23:45 cmake\_3.10.2-1ubuntu2.18.04.1\_arm64.deb -rw-r--r-- 1 cby cby 1331524 Apr 21 23:45 cmake-data\_3.10.2-1ubuntu2.18.04.1\_all.deb -rw-r--r-- 1 cby cby 69166 Apr 21 23:47 libjsoncpp1\_1.7.4-3\_arm64.deb -rw-r--r-- 1 cby cby 71788 Apr 21 23:48 librhash0\_1.3.6-2\_arm64.deb root@ubuntu:/home/cby/cmake# apt install./\* root@ubuntu:/home/cby/cmake# make–versionroot@ubuntu:/home/cby# apt install./zlib1g-dev\_1%3a1.2.11.dfsg-0ubuntu2\_arm64.deb root@ubuntu:/home/cby# apt install./libbz2-dev\_1.0.6-8.1ubuntu0.2\_arm64.deb root@ubuntu:/home/cby# apt install ./libsqlite3-dev\_3.22.0-1ubuntu0.4\_arm64.debroot@ubuntu:/home/cby# cd libssl-dev/ root@ubuntu:/home/cby/libssl-dev#apt install ./\*root@ubuntu:/home/cby# cd libxslt1-dev/ root@ubuntu:/home/cby/libxslt1-dev#ll total 13596 drwxr-xr-x 2 root root 4096 Apr 22 00:37 ./ drwxr-xr-x 10 cby cby 4096 Apr 22 00:37 ../ -rw-r--r-- 1 cby cby 18528 Apr 22 00:30gir1.2-harfbuzz-0.0\_1.7.2-1ubuntu1\_arm64.deb -rw-r--r-- 1 cby cby 170204 Apr 22 00:27icu-devtools\_60.2-3ubuntu3.1\_arm64.deb -rw-r--r-- 1 cby cby 983364 Apr 22 00:37libglib2.0-0\_2.56.4-0ubuntu0.18.04.8\_arm64.deb -rw-r--r-- 1 cby cby 61832 Apr 22 00:33libglib2.0-bin\_2.56.4-0ubuntu0.18.04.8\_arm64.deb -rw-r--r-- 1 cby cby 1297600 Apr 22 00:31libglib2.0-dev\_2.56.4-0ubuntu0.18.04.8\_arm64.deb -rw-r--r-- 1 cby cby 99676 Apr 22 00:31libglib2.0-dev-bin\_2.56.4-0ubuntu0.18.04.8\_arm64.deb -rw-r--r-- 1 cby cby 14528 Apr 22 00:32libgraphite2-dev\_1.3.11-2\_arm64.deb -rw-r--r-- 1 cby cby 280584 Apr 22 00:28libharfbuzz-dev\_1.7.2-1ubuntu1\_arm64.deb -rw-r--r-- 1 cby cby 12556 Apr 22 00:30libharfbuzz-gobject0\_1.7.2-1ubuntu1\_arm64.deb -rw-r--r-- 1 cby cby 5348 Apr 22 00:29libharfbuzz-icu0\_1.7.2-1ubuntu1\_arm64.deb -rw-r--r-- 1 cby cby 8890124 Apr 22 00:26libicu-dev\_60.2-3ubuntu3.1\_arm64.deb -rw-r--r-- 1 cby cby 14412 Apr 22 00:28libicu-le-hb0\_1.0.3+git161113-4\_arm64.deb -rw-r--r-- 1 cby cby 29760 Apr 22 00:27libicu-le-hb-dev\_1.0.3+git161113-4\_arm64.deb -rw-r--r-- 1 cby cby 18756 Apr 22 00:26libiculx60\_60.2-3ubuntu3.1\_arm64.deb -rw-r--r-- 1 cby cby 120696 Apr 22 00:35libpcre16-3\_2%3a8.39-9\_arm64.deb -rw-r--r-- 1 cby cby 113240 Apr 22 00:35libpcre32-3\_2%3a8.39-9\_arm64.deb -rw-r--r-- 1 cby cby 459316 Apr 22 00:33libpcre3-dev\_2%3a8.39-9\_arm64.deb -rw-r--r-- 1 cby cby 15124 Apr 22 00:35libpcrecpp0v5\_2%3a8.39-9\_arm64.deb -rw-r--r-- 1 cby cby 673384 Apr 22 00:25libxml2-dev\_2.9.4+dfsg1-6.1ubuntu1.3\_arm64.deb -rw-r--r-- 1 cby cby 395564 Apr 22 00:24libxslt1-dev\_1.1.29-5ubuntu0.2\_arm64.deb -rw-r--r-- 1 cby cby 42802 Apr 22 00:33pkg-config\_0.29.1-0ubuntu2\_arm64.deb -rw-r--r-- 1 cby cby 144176 Apr 22 00:37python3-distutils\_3.6.9-1~18.04\_all.deb root@ubuntu:/home/cby/libxslt1-dev#apt install ./\*root@ubuntu:/home/cby# cd libffi-dev/ root@ubuntu:/home/cby/libffi-dev#ls libffi-dev\_3.2.1-8\_arm64.deb root@ubuntu:/home/cby/libffi-dev#apt install ./\*root@ubuntu:/home/cby#apt install unzip root@ubuntu:/home/cby# apt install./libblas-dev\_3.7.1-4ubuntu1\_arm64.debroot@ubuntu:/home/cby# cd gfortran/ root@ubuntu:/home/cby/gfortran#ll total 7844 drwxr-xr-x 2 root root 4096 Apr 22 00:50 ./ drwxr-xr-x 12cby cby 4096 Apr 22 00:50 ../ -rw-r--r-- 1 cby cby 1344 Apr 22 00:48gfortran\_4%3a7.4.0-1ubuntu2.3\_arm64.deb -rw-r--r-- 1 cby cby 7464740 Apr 22 00:48gfortran-7\_7.5.0-3ubuntu1~18.04\_arm64.deb -rw-r--r-- 1 cby cby 248176 Apr 22 00:50libgfortran4\_7.5.0-3ubuntu1~18.04\_arm64.deb -rw-r--r-- 1 cby cby 300500 Apr 22 00:49libgfortran-7-dev\_7.5.0-3ubuntu1~18.04\_arm64.deb root@ubuntu:/home/cby/gfortran#apt install ./\*root@ubuntu:/home/cby# cd libblas3/ root@ubuntu:/home/cby/libblas3#apt install ./libblas3\_3.7.1-4ubuntu1\_arm64.debroot@ubuntu:/home/cby# cdlibopenblas-dev/ root@ubuntu:/home/cby/libopenblas-dev#ll total 3412 drwxr-xr-x 2 root root 4096 Apr 22 00:56 ./ drwxr-xr-x 14cby cby 4096 Apr 22 00:56 ../ -rw-r--r-- 1 cby cby 1813748 Apr 22 00:55libopenblas-base\_0.2.20+ds-4\_arm64.deb -rw-r--r-- 1 cby cby 1668126 Apr 22 00:54libopenblas-dev\_0.2.20+ds-4\_arm64.deb root@ubuntu:/home/cby/libopenblas-dev#apt install ./\*安装完成后查看版本gcc --version g++ --version make --version cmake --version dpkg -l zlib1g| grepzlib1g| grep ii dpkg -l zlib1g-dev|grep zlib1g-dev| grep ii dpkg -l libbz2-dev|grep libbz2-dev| grep ii dpkg -llibsqlite3-dev| grep libsqlite3-dev| grep ii dpkg -l openssl| grepopenssl| grep ii dpkg -l libssl-dev|grep libssl-dev| grep ii dpkg -l libxslt1-dev|grep libxslt1-dev| grep ii dpkg -l libffi-dev|grep libffi-dev| grep ii dpkg -l unzip| grepunzip| grep ii dpkg -l pciutils|grep pciutils| grep ii dpkg -l net-tools|grep net-tools| grep ii dpkg -l libblas-dev|grep libblas-dev| grep ii dpkg -l gfortran|grep gfortran| grep ii dpkg -l libblas3|grep libblas3| grep ii dpkg -llibopenblas-dev| grep libopenblas-dev| grep ii安装Python3.7.5root@ubuntu:/home/cby/python#tar xvf Python3.7.5.tar root@ubuntu:/home/cby/python# cdPython-3.7.5/ root@ubuntu:/home/cby/python/Python-3.7.5#./configure --prefix=/usr/local/python3.7.5 --enable-loadable-sqlite-extensions--enable-shared root@ubuntu:/home/cby/python/Python-3.7.5#make root@ubuntu:/home/cby/python/Python-3.7.5#make install root@ubuntu:/home/cby# sudo ln -s/usr/local/python3.7.5/bin/pip3 /usr/local/bin/pip3.7.5 root@ubuntu:/home/cby# sudo ln-s /usr/local/python3.7.5/bin/python3 /usr/local/bin/python3.7.5 root@ubuntu:/home/cby/cann\_xunlian#sudo ln -s /usr/local/python3.7.5/bin/python3 /usr/local/bin/python3.7 root@ubuntu:/home/cby/cann\_xunlian#sudo ln -s /usr/local/python3.7.5/bin/pip3 /usr/local/bin/pip3.7 root@ubuntu:/home/cby# vim ~/.bashrc exportLD\_LIBRARY\_PATH=/usr/local/python3.7.5/lib:$LD\_LIBRARY\_PATH root@ubuntu:/home/cby#python3.7.5 --version Python 3.7.5 root@ubuntu:/home/cby# pip3.7.5--version pip 19.2.3 from /usr/local/python3.7.5/lib/python3.7/site-packages/pip(python 3.7)使用Python3.7.5环境安装pip依赖包root@ubuntu:/home/cby/pip-pack# tar xvfpip\_pack.tar root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./attrs-20.3.0-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./numpy-1.17.2-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./decorator-5.0.6-py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./mpmath-1.2.1-py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./sympy-1.4-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./pycparser-2.20-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./cffi-1.12.3.tar.gz root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./PyYAML-5.3.1.tar.gz root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./six-1.15.0-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./pathlib2-2.3.5-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./psutil-5.8.0.tar.gz root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./protobuf-3.15.8-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./scipy-1.6.0-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./chardet-3.0.4-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./idna-2.10-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./urllib3-1.25.10-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./certifi-2020.6.20-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./certifi-2020.6.20-py2.py3-none-any.whl root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./requests-2.24.0-py2.py3-none-any.wh root@ubuntu:/home/cby/pip-pack/pip\_pack#pip3.7.5 install ./xlrd-1.2.0-py2.py3-none-any.whl *注意：以上pip包的安装必须以该顺序依次进行安装安装开发套件包root@ubuntu:/home/cby/cann#./Ascend-cann-tfplugin\_20.2.rc1\_linux-aarch64.run –install root@ubuntu:/home/cby/cann#./Ascend-cann-toolkit\_20.2.rc1\_linux-aarch64.run –install 出现install success后表示安装成功。 CANN训练环境部署安装说明 训练环境的Python3.7.5和环境以及依赖，和开发环境下的安装方式一样，可参考《CANN开发环境部署安装》文档进行安装。在已经搭建好的开发环境中，进行安装训练环境仅需安装一下训练软件包和实用工具包即可。安装训练软件包root@ubuntu:/home/cby/cann\_xunlian# chmod+x ./\*.run root@ubuntu:/home/cby/cann\_xunlian# ./Ascend-cann-nnae\_20.2.rc1\_linux-aarch64.run–install root@ubuntu:/home/cby/cann\_xunlian#./Ascend-cann-toolbox\_20.2.rc1\_linux-aarch64.run –install 出现install success后表示安装成功。安装MindSpore安装whl包 安装Ascend 910 AI处理器配套软件包提供的whl包，whl包随配套软件包发布，升级配套软件包之后需要重新安装。root@ubuntu:/home/cby/mindspore\_ascend#pip3.7.5 install /usr/local/Ascend/ascend-toolkit/latest/fwkacllib/lib64/hccl-0.1.0-py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend#pip3.7.5 install /usr/local/Ascend/ascend-toolkit/latest/fwkacllib/lib64/te-0.4.0-py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend#pip3.7.5 install /usr/local/Ascend/ascend-toolkit/latest/fwkacllib/lib64/topi-0.4.0-py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install easydict-1.9.tar.gz root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./wheel-0.36.2-py2.py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./astunparse-1.6.3-py2.py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./Pillow-8.2.0-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./asttokens-2.0.4-py2.py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./cffi-1.14.5-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./pyparsing-2.4.7-py2.py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ./packaging-20.9-py2.py3-none-any.whl root@ubuntu:/home/cby/mindspore\_ascend/pip#pip3.7.5 install ../mindspore\_ascend-1.1.1-cp37-cp37m-linux\_aarch64.whl*注意：安装时必须以此顺序进行安装配置环境变量\# control log level.0-DEBUG, 1-INFO, 2-WARNING, 3-ERROR, default level is WARNING. export GLOG\_v=2 # Conda environmentaloptions LOCAL\_ASCEND=/usr/local/Ascend # the root directoryof run package # lib libraries thatthe run package depends on exportLD\_LIBRARY\_PATH=${LOCAL\_ASCEND}/add-ons/:${LOCAL\_ASCEND}/ascend-toolkit/latest/fwkacllib/lib64:${LOCAL\_ASCEND}/driver/lib64:${LOCAL\_ASCEND}/opp/op\_impl/built-in/ai\_core/tbe/op\_tiling:${LD\_LIBRARY\_PATH} # Environmentvariables that must be configured exportTBE\_IMPL\_PATH=${LOCAL\_ASCEND}/ascend-toolkit/latest/opp/op\_impl/built-in/ai\_core/tbe # TBE operatorimplementation tool path exportASCEND\_OPP\_PATH=${LOCAL\_ASCEND}/ascend-toolkit/latest/opp # OPP path exportPATH=${LOCAL\_ASCEND}/ascend-toolkit/latest/fwkacllib/ccec\_compiler/bin/:${PATH} # TBE operatorcompilation tool path exportPYTHONPATH=${TBE\_IMPL\_PATH}:${PYTHONPATH} # Python library thatTBE implementation depends on测试是否可行Python代码内容：import numpy as np from mindspore importTensor import mindspore.opsas ops importmindspore.context as context context.set\_context(device\_target="Ascend") x =Tensor(np.ones(\[1,3,3,4\]).astype(np.float32)) y =Tensor(np.ones(\[1,3,3,4\]).astype(np.float32)) print(ops.tensor\_add(x,y))出现此结果即是安装部署完成\[\[\[\[2. 2. 2. 2.\] \[2. 2. 2. 2.\] \[2. 2. 2. 2.\]\] \[\[2. 2. 2. 2.\] \[2. 2. 2. 2.\] \[2. 2. 2. 2.\]\] \[\[2. 2. 2. 2.\] \[2. 2. 2. 2.\] \[2. 2. 2. 2.\]\]\]\]安装mindinsight安装whl包root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./itsdangerous-1.1.0-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./Werkzeug-1.0.1-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./MarkupSafe-1.1.1-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./Jinja2-2.11.3-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./click-7.1.2-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./Flask-1.1.2-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./Flask\_Cors-3.0.10-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./yapf-0.31.0-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./future-0.18.2.tar.gz root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./treelib-1.6.1.tar.gz root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./grpcio-1.37.0-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./google\_pasta-0.2.0-py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./pytz-2021.1-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./python\_dateutil-2.8.1-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./pandas-1.2.3-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./gunicorn-20.1.0.tar.gz root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./marshmallow-3.11.1-py2.py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./threadpoolctl-2.1.0-py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./joblib-1.0.1-py3-none-any.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./scikit\_learn-0.24.1-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/mindinsight/Mindinsight#pip3.7.5 install ./mindinsight-1.1.1-cp37-cp37m-linux\_aarch64.whl*注意：安装必须以此顺序进安装配置环境变量在配置文件中配置如下变量PATH=$PATH:/usr/local/python3.7.5/bin/root@ubuntu:/home/cby#source /etc/profile启动及使用root@ubuntu:/home/cby#mindinsight start Workspace:/root/mindinsight Webaddress: http://127.0.0.1:8080 servicestart state: success 出现该消息后，说明可视化已经启动成功，若需要外机访问的话，需要进行反向代理到0.0.0.0上面即可，比如frp工具即可实现该操作 在训练完成的Python代码目录下，使以下命令即可启动并展示该目录下的训练数据，debugger的参数可使用false或者truemindinsightstart --summary-base-dir . --port 8080 --enable-debugger True --debugger-port50051使用如下命令即可启动训练root@ubuntu:/home/cby/lenet/lenet#python3.7.5 lenet.py --device_target=Ascend安装Tensorflow编译hdf5root@ubuntu:/home/cby/Tensorflow/Tensorflow#cd hdf5-1.10.5/ root@ubuntu:/home/cby/Tensorflow/Tensorflow/hdf5-1.10.5#./configure --prefix=/usr/include/hdf5 root@ubuntu:/home/cby/Tensorflow/Tensorflow/hdf5-1.10.5#make root@ubuntu:/home/cby/Tensorflow/Tensorflow/hdf5-1.10.5#make install配置环境变量及软连接exportCPATH="/usr/include/hdf5/include/:/usr/include/hdf5/lib/" root@ubuntu:/home/cby/Tensorflow/Tensorflow/hdf5-1.10.5#ln -s /usr/include/hdf5/lib/libhdf5.so /usr/lib/libhdf5.so root@ubuntu:/home/cby/Tensorflow/Tensorflow/hdf5-1.10.5#ln -s /usr/include/hdf5/lib/libhdf5\_hl.so /usr/lib/libhdf5\_hl.so安装whl包root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./Cython-0.29.21-py2.py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./h5py-2.10.0-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./grpcio-1.30.0.tar.gz root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./gast-0.2.2.tar.gz root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./opt\_einsum-3.3.0-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./Keras\_Applications-1.0.8-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./Keras\_Preprocessing-1.1.2-py2.py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./astor-0.8.1-py2.py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./typing\_extensions-3.7.4.3-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./zipp-3.4.1-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./importlib\_metadata-3.10.1-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./Markdown-3.2.2-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./tensorboard-1.15.0-py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./wrapt-1.12.1.tar.gz root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./tensorflow\_estimator-1.15.1-py2.py3-none-any.whl root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./termcolor-1.1.0.tar.gz root@ubuntu:/home/cby/Tensorflow/Tensorflow#pip3.7.5 install ./tensorflow-1.15.0-cp37-cp37m-linux\_aarch64.whl注意：必须依次安装安装Pytorchroot@ubuntu:/home/cby/pytorch/Pytorch#pip3.7.5 install ./apex-0.1+ascend-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/pytorch/Pytorch#pip3.7.5 install ./torch-1.5.0+ascend.post2-cp37-cp37m-linux\_aarch64.whl root@ubuntu:/home/cby/pytorch/Pytorch#pip3.7.5 install ./future-0.18.2.tar.gz该文章所配套的软件包关注微信公众号回复 ai 即可获取所需要的所有软件包 Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。20篇原创内容公众号
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Linux文件系统故障，Input/output error 事情是这样的，在启动某一个应用程序的时候，出现 Input/output error 的报错，磁盘以及目录无法使用的情况下，进行了重启，重启完成后是可以正常使用的，过一段时间后就会再次出现这个问题，一番Google之后怀疑是磁盘出现问题，根据网友的解决方案尝试之后发现，这个方法可行，下文是命令及回显： 使用ls命令查看的时候出现这个报错[root@webc ~]# ls /data/ ls: 无法访问/data/: 输入/输出错误 [root@webc ~]# 这个是xfs的文件系统，所以使用如下命令进行修复[root@webc ~]# xfs_repair /dev/sdc1 xfs_repair: cannot open /dev/sdc1: 设备或资源忙 这时这个问题，不要慌，先把磁盘卸载了在进行修复[root@webc ~]# umount /dev/sdc1 [root@webc ~]# xfs_repair /dev/sdc1 Phase 1 - find and verify superblock... Phase 2 - using internal log - zero log... ERROR: The filesystem has valuable metadata changes in a log which needs to be replayed. Mount the filesystem to replay the log, and unmount it before re-running xfs_repair. If you are unable to mount the filesystem, then use the -L option to destroy the log and attempt a repair. Note that destroying the log may cause corruption -- please attempt a mount of the filesystem before doing this. [root@webc ~]# [root@webc ~]# [root@webc ~]# xfs_repair /dev/sdc1 Phase 1 - find and verify superblock... Phase 2 - using internal log - zero log... ERROR: The filesystem has valuable metadata changes in a log which needs to be replayed. Mount the filesystem to replay the log, and unmount it before re-running xfs_repair. If you are unable to mount the filesystem, then use the -L option to destroy the log and attempt a repair. Note that destroying the log may cause corruption -- please attempt a mount of the filesystem before doing this. [root@webc ~]# xfs_repair /dev/sdc1 -L Phase 1 - find and verify superblock... Phase 2 - using internal log - zero log... ALERT: The filesystem has valuable metadata changes in a log which is being destroyed because the -L option was used. - scan filesystem freespace and inode maps... agi unlinked bucket 31 is 7620063 in ag 5 (inode=10745038303) sb_icount 533632, counted 533568 sb_ifree 617, counted 614 sb_fdblocks 2852137932, counted 2860186916 - found root inode chunk Phase 3 - for each AG... - scan and clear agi unlinked lists... - process known inodes and perform inode discovery... - agno = 0 - agno = 1 - agno = 2 - agno = 3 - agno = 4 - agno = 5 correcting bt key (was 91997, now 92001) in inode 10745038303 data fork, btree block 1343129285 correcting bt key (was 226254, now 226257) in inode 10745038303 data fork, btree block 1345535075 correcting bt key (was 241554, now 241557) in inode 10745038303 data fork, btree block 1345535075 correcting bt key (was 795517, now 795515) in inode 10745038303 data fork, btree block 1343659983 data fork in regular inode 10745038303 claims used block 1353137709 correcting nextents for inode 10745038303 bad data fork in inode 10745038303 cleared inode 10745038303 - agno = 6 - agno = 7 - agno = 8 correcting nextents for inode 17197661037, was 870903 - counted 870911 - agno = 9 - agno = 10 correcting bt key (was 1923723, now 1923730) in inode 21481716216 data fork, btree block 2687659655 correcting bt key (was 1997785, now 1997794) in inode 21481716216 data fork, btree block 2687659655 correcting nextents for inode 21481716216, was 918874 - counted 918898 - process newly discovered inodes... Phase 4 - check for duplicate blocks... - setting up duplicate extent list... - check for inodes claiming duplicate blocks... - agno = 0 - agno = 3 - agno = 4 - agno = 2 - agno = 5 - agno = 6 - agno = 1 - agno = 7 - agno = 9 - agno = 8 - agno = 10 Phase 5 - rebuild AG headers and trees... - reset superblock... Phase 6 - check inode connectivity... - resetting contents of realtime bitmap and summary inodes - traversing filesystem ... - traversal finished ... - moving disconnected inodes to lost+found ... Phase 7 - verify and correct link counts... Maximum metadata LSN (15:166217) is ahead of log (1:2). Format log to cycle 18. done [root@webc ~]# 修复完成后在把磁盘挂上，即可生效[root@webc ~]# mount /dev/sdc1 /data/ 查看一下这个磁盘是否可以正常使用[root@webc ~]# cd /data/vm/ [root@webc vm]# ls CentOS7-Clone-1 CentOS7-Clone-3 CentOS7-Clone-4 CentOS7-Clone-5 CentOS8 Ubuntu此刻文件系统已修复完毕 注意： 修复其他文件系统使用fsck命令进行修复 例如ext4文件系统fsck -t ext4 -y /dev/sda1不同的文件系统，命令会有些许不同，灵活变通一下Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。28篇原创内容公众号本文使用 文章同步助手 同步
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华为 A800-9000 服务器 离线安装MindX DL MindX DL（昇腾深度学习组件）是支持 Atlas 800 训练服务器、Atlas 800 推理服务器的深度学习组件参考设计，提供昇腾 AI 处理器资源管理和监控、昇腾 AI 处理器优化调度、分布式训练集合通信配置生成等基础功能，快速使能合作伙伴进行深度学习平台开发。 操作系统使用的是Ubuntu-1804，CPU是华为自研ARM架构。一、安装前准备配置apt网络源hello@ubuntu:/etc/apt$ sudo cp sources.list~ sources.list hello@ubuntu:/etc/apt$ cat sources.list # # deb cdrom:[Ubuntu-Server 18.04.5 LTS _Bionic Beaver_ - Release arm64 (20200810)]/ bionic main restricted #deb cdrom:[Ubuntu-Server 18.04.5 LTS _Bionic Beaver_ - Release arm64 (20200810)]/ bionic main restricted # See http://help.ubuntu.com/community/UpgradeNotes for how to upgrade to # newer versions of the distribution. deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic main restricted # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic main restricted ## Major bug fix updates produced after the final release of the ## distribution. deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-updates main restricted # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-updates main restricted ## N.B. software from this repository is ENTIRELY UNSUPPORTED by the Ubuntu ## team. Also, please note that software in universe WILL NOT receive any ## review or updates from the Ubuntu security team. deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic universe # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic universe deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-updates universe # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-updates universe ## N.B. software from this repository is ENTIRELY UNSUPPORTED by the Ubuntu ## team, and may not be under a free licence. Please satisfy yourself as to ## your rights to use the software. Also, please note that software in ## multiverse WILL NOT receive any review or updates from the Ubuntu ## security team. deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic multiverse # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic multiverse deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-updates multiverse # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-updates multiverse ## N.B. software from this repository may not have been tested as ## extensively as that contained in the main release, although it includes ## newer versions of some applications which may provide useful features. ## Also, please note that software in backports WILL NOT receive any review ## or updates from the Ubuntu security team. deb http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-backports main restricted universe multiverse # deb-src http://cn.ports.ubuntu.com/ubuntu-ports/ bionic-backports main restricted universe multiverse ## Uncomment the following two lines to add software from Canonical's ## 'partner' repository. ## This software is not part of Ubuntu, but is offered by Canonical and the ## respective vendors as a service to Ubuntu users. # deb http://archive.canonical.com/ubuntu bionic partner # deb-src http://archive.canonical.com/ubuntu bionic partner deb http://ports.ubuntu.com/ubuntu-ports bionic-security main restricted # deb-src http://ports.ubuntu.com/ubuntu-ports bionic-security main restricted deb http://ports.ubuntu.com/ubuntu-ports bionic-security universe # deb-src http://ports.ubuntu.com/ubuntu-ports bionic-security universe deb http://ports.ubuntu.com/ubuntu-ports bionic-security multiverse # deb-src http://ports.ubuntu.com/ubuntu-ports bionic-security multiverse 2.配置kubernetes网络源root@ubuntu:~/123/offline-pkg-arm64# cat <<EOF >/etc/apt/sources.list.d/kubernetes.list > deb https://mirrors.aliyun.com/kubernetes/apt/ kubernetes-xenial main > EOF 3.创建目录并下载基础包root@ubuntu:~/123# mkdir offline-pkg-arm64 root@ubuntu:~/123# cd offline-pkg-arm64/ root@ubuntu:~/123/offline-pkg-arm64# sudo apt update root@ubuntu:~/123/offline-pkg-arm64# apt-get download conntrack cri-tools haveged keyutils libhavege1 libltdl7 libnfsidmap2 libtirpc-dev libtirpc1 nfs-common nfs-kernel-server rpcbind socat sshpass root@ubuntu:~/123/offline-pkg-arm64# wget --no-check-certificate https://download.docker.com/linux/ubuntu/dists/bionic/pool/stable/arm64/docker-ce_18.06.3~ce~3-0~ubuntu_arm64.deb root@ubuntu:~/123/offline-pkg-arm64# apt-get download kubelet=1.17.3-00 kubeadm=1.17.3-00 kubectl=1.17.3-00 kubernetes-cni=0.8.6-00 4.下载docker镜像并导出保存root@ubuntu:~/123# mkdir docker_images root@ubuntu:~/123# cd docker_images/ root@ubuntu:~/123/docker_images# docker pull calico/node:v3.11.3 root@ubuntu:~/123/docker_images# docker save -o calico-node_arm64.tar.gz calico/node:v3.11.3 root@ubuntu:~/123/docker_images# docker pull calico/pod2daemon-flexvol:v3.11.3 root@ubuntu:~/123/docker_images# docker save -o calico-pod2daemon-flexvol_arm64.tar.gz calico/pod2daemon-flexvol:v3.11.3 root@ubuntu:~/123/docker_images# docker pull calico/cni:v3.11.3 root@ubuntu:~/123/docker_images# docker save -o calico-cni_arm64.tar.gz calico/cni:v3.11.3 root@ubuntu:~/123/docker_images# docker pull calico/kube-controllers:v3.11.3 root@ubuntu:~/123/docker_images# docker save -o calico-kube-controllers_arm64.tar.gz calico/kube-controllers:v3.11.3 root@ubuntu:~/123/docker_images# docker pull coredns/coredns:1.6.5 root@ubuntu:~/123/docker_images# docker save -o coredns_arm64.tar.gz coredns/coredns:1.6.5 root@ubuntu:~/123/docker_images# docker pull cruse/etcd-arm64:3.4.3-0 root@ubuntu:~/123/docker_images# docker save -o etcd_arm64.tar.gz cruse/etcd-arm64:3.4.3-0 root@ubuntu:~/123/docker_images# docker pull cruse/kube-apiserver-arm64:v1.17.3 root@ubuntu:~/123/docker_images# docker save -o kube-apiserver_arm64.tar.gz cruse/kube-apiserver-arm64:v1.17.3 root@ubuntu:~/123/docker_images# docker pull cruse/kube-controller-manager-arm64:v1.17.3 root@ubuntu:~/123/docker_images# docker save -o kube-controller-manager_arm64.tar.gz cruse/kube-controller-manager-arm64:v1.17.3 root@ubuntu:~/123/docker_images# docker pull cruse/kube-proxy-arm64:v1.17.3-beta.0 root@ubuntu:~/123/docker_images# docker save -o kube-proxy_arm64.tar.gz cruse/kube-proxy-arm64:v1.17.3-beta.0 root@ubuntu:~/123/docker_images# docker pull cruse/kube-scheduler-arm64:v1.17.3-beta.0 root@ubuntu:~/123/docker_images# docker save -o kube-scheduler_arm64.tar.gz cruse/kube-scheduler-arm64:v1.17.3-beta.0 root@ubuntu:~/123/docker_images# docker pull cruse/pause-arm64:3.1 root@ubuntu:~/123/docker_images# docker save -o pause_arm64.tar.gz cruse/pause-arm64:3.1 root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# docker login -u 15648907522 -p RtZOXgmpYAQd5cj93uFCabNXUWB7wOftGw4pFdcal4XZH4bf06hvFxTOrYtr1nRao ascendhub.huawei.com root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/vc-controller-manager_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/vc-scheduler_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/vc-webhook-manager_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/vc-webhook-manager-base_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/hccl-controller_arm64:v20.2.0 root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/ascend-k8sdeviceplugin_arm64:v20.2.0 root@ubuntu:~/123/docker_images# docker pull ascendhub.huawei.com/public-ascendhub/cadvisor_arm64:v0.34.0-r40 root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/vc-controller-manager_arm64:v1.0.1-r40 volcanosh/vc-controller-manager:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/vc-scheduler_arm64:v1.0.1-r40 volcanosh/vc-scheduler:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/vc-webhook-manager_arm64:v1.0.1-r40 volcanosh/vc-webhook-manager:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/vc-webhook-manager-base_arm64:v1.0.1-r40 volcanosh/vc-webhook-manager-base:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/hccl-controller_arm64:v20.2.0 hccl-controller:v20.2.0 root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/ascend-k8sdeviceplugin_arm64:v20.2.0 ascend-k8sdeviceplugin:v20.2.0 root@ubuntu:~/123/docker_images# docker tag ascendhub.huawei.com/public-ascendhub/cadvisor_arm64:v0.34.0-r40 google/cadvisor:v0.34.0-r40 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/vc-controller-manager_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/vc-scheduler_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/vc-webhook-manager_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/vc-webhook-manager-base_arm64:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/hccl-controller_arm64:v20.2.0 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/ascend-k8sdeviceplugin_arm64:v20.2.0 root@ubuntu:~/123/docker_images# docker rmi ascendhub.huawei.com/public-ascendhub/cadvisor_arm64:v0.34.0-r40 root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# root@ubuntu:~/123/docker_images# docker save -o Ascend-K8sDevicePlugin-v20.2.0-arm64-Docker.tar.gz ascend-k8sdeviceplugin:v20.2.0 root@ubuntu:~/123/docker_images# docker save -o hccl-controller-v20.2.0-arm64.tar.gz hccl-controller:v20.2.0 root@ubuntu:~/123/docker_images# docker save -o huawei-cadvisor-v0.34.0-r40-arm64.tar.gz google/cadvisor:v0.34.0-r40 root@ubuntu:~/123/docker_images# docker save -o vc-controller-manager-v1.0.1-r40-arm64.tar.gz volcanosh/vc-controller-manager:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker save -o vc-scheduler-v1.0.1-r40-arm64.tar.gz volcanosh/vc-scheduler:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker save -o vc-webhook-manager-base-v1.0.1-r40-arm64.tar.gz volcanosh/vc-webhook-manager-base:v1.0.1-r40 root@ubuntu:~/123/docker_images# docker save -o vc-webhook-manager-v1.0.1-r40-arm64.tar.gz volcanosh/vc-webhook-manager:v1.0.1-r40 注* 其中部分镜像是需要在华为hub里面进行获取权限后进行下载 https://support.huaweicloud.com/usermanual-mindxdl202/atlasmindx_03_0047.html 5.完成后的目录root@ubuntu:~/123# tree . ├── docker_images │ ├── Ascend-K8sDevicePlugin-v20.2.0-arm64-Docker.tar.gz │ ├── calico-cni_arm64.tar.gz │ ├── calico-kube-controllers_arm64.tar.gz │ ├── calico-node_arm64.tar.gz │ ├── calico-pod2daemon-flexvol_arm64.tar.gz │ ├── coredns_arm64.tar.gz │ ├── etcd_arm64.tar.gz │ ├── hccl-controller-v20.2.0-arm64.tar.gz │ ├── huawei-cadvisor-v0.34.0-r40-arm64.tar.gz │ ├── kube-apiserver_arm64.tar.gz │ ├── kube-controller-manager_arm64.tar.gz │ ├── kube-proxy_arm64.tar.gz │ ├── kube-scheduler_arm64.tar.gz │ ├── pause_arm64.tar.gz │ ├── vc-controller-manager-v1.0.1-r40-arm64.tar.gz │ ├── vc-scheduler-v1.0.1-r40-arm64.tar.gz │ ├── vc-webhook-manager-base-v1.0.1-r40-arm64.tar.gz │ └── vc-webhook-manager-v1.0.1-r40-arm64.tar.gz ├── offline-pkg-arm64 │ ├── conntrack_1%3a1.4.4+snapshot20161117-6ubuntu2_arm64.deb │ ├── cri-tools_1.13.0-01_arm64.deb │ ├── docker-ce_18.06.3~ce~3-0~ubuntu_arm64.deb │ ├── haveged_1.9.1-6_arm64.deb │ ├── keyutils_1.5.9-9.2ubuntu2_arm64.deb │ ├── kubeadm_1.17.3-00_arm64.deb │ ├── kubectl_1.17.3-00_arm64.deb │ ├── kubelet_1.17.3-00_arm64.deb │ ├── kubernetes-cni_0.8.6-00_arm64.deb │ ├── libhavege1_1.9.1-6_arm64.deb │ ├── libltdl7_2.4.6-2_arm64.deb │ ├── libnfsidmap2_0.25-5.1_arm64.deb │ ├── libtirpc1_0.2.5-1.2ubuntu0.1_arm64.deb │ ├── libtirpc-dev_0.2.5-1.2ubuntu0.1_arm64.deb │ ├── nfs-common_1%3a1.3.4-2.1ubuntu5.5_arm64.deb │ ├── nfs-kernel-server_1%3a1.3.4-2.1ubuntu5.5_arm64.deb │ ├── rpcbind_0.2.3-0.6ubuntu0.18.04.4_arm64.deb │ ├── socat_1.7.3.2-2ubuntu2_arm64.deb │ └── sshpass_1.06-1_arm64.deb ├── offline-pkg-arm64.zip └── yamls ├── ascendplugin-310-v20.2.0.yaml ├── ascendplugin-volcano-v20.2.0.yaml ├── cadvisor-v0.34.0-r40.yaml ├── calico.yaml ├── hccl-controller-v20.2.0.yaml ├── npu-exporter-v20.2.0.yaml └── volcano-v1.0.1-r40.yaml 3 directories, 46 files root@ubuntu:~/123#注* 其中yamls文件在下方链接中下载 https://gitee.com/ascend/mindxdl-deploy/tree/20201230-V20.2.0/ 6.配置免密登陆root@ubuntu:~# ssh-keygen Generating public/private rsa key pair. Enter file in which to save the key (/root/.ssh/id_rsa): Created directory '/root/.ssh'. Enter passphrase (empty for no passphrase): Enter same passphrase again: Your identification has been saved in /root/.ssh/id_rsa. Your public key has been saved in /root/.ssh/id_rsa.pub. The key fingerprint is: SHA256:07dTbsAycQqT2w7HdCwjIyJig5T20FQ/eHZGxWg7pbY root@ubuntu The key's randomart image is: +---[RSA 2048]----+ | .+... .+. | |o+ . o .+ + | |+o+ ...=BoO + | |...o .o.+/ O | | S @ + . | | E + = | | . o o | | o | | | +----[SHA256]-----+ root@ubuntu:~# root@ubuntu:~# ssh-copy-id -i 127.0.0.1 7.配置安装ansibleroot@ubuntu:~# root@ubuntu:~# apt install ansible root@ubuntu:~# vim /etc/ansible/hosts #配置内容如下 [all:vars] # default shared directory, you can change it as yours nfs_shared_dir=/data/atlas_dls # NFS service IP nfs_service_ip=192.168.1.110 # Master IP master_ip=192.168.1.110 # dls install package dir dls_root_dir=/root/123 # set proxy proxy="" # Command for logging in to the Asend hub ascendhub_login_command="login_command" # Generally, you do not need to change the value or delete it. ascendhub_prefix="ascendhub.huawei.com/public-ascendhub" # versions deviceplugin_version="v20.2.0" cadvisor_version="v0.34.0-r40" volcano_version="v1.0.1-r40" hccl_version="v20.2.0" [nfs_server] ubuntu ansible_host=192.168.1.110 ansible_ssh_user="root" ansible_ssh_pass="123123" [localnode] ubuntu ansible_host=192.168.1.110 ansible_ssh_user="root" ansible_ssh_pass="123123" [training_node] ubuntu ansible_host=192.168.1.110 ansible_ssh_user="root" ansible_ssh_pass="123123" [inference_node] [A300T_node] [arm] ubuntu ansible_host=192.168.1.110 ansible_ssh_user="root" ansible_ssh_pass="123123" [x86] [workers:children] training_node inference_node A300T_node root@ubuntu:~/mindxdl/deploy/offline/steps# vim /etc/ansible/ansible.cfg log_path = /var/log/ansible.log host_key_checking = False deprecation_warnings = False 注* 参数说明，请根据实际写入：nfs-host-ip：NFS节点服务器IP地址，即服务器IP地址，如果不安装NFS可设置为空字符串，如：""。 master-host-ip：管理节点服务器IP地址，即服务器IP地址。 install_dir：基础软件包、镜像包和yamls文件夹的上传目录。 proxy_address：代理地址，请根据实际情况配置，如果不需要代理，设置为空字符串，如：""。 login_command：从Ascend Hub中心获取镜像需要使用的登录命令，仅在线安装需要配置，如："docker login -u xxxxxx@xxxxxx -p xxxxxxxx ascendhub.huawei.com"，注意不要遗漏命令前后的引号，获取方式请参见获取MindX DL镜像中1~2。离线安装可设置为空字符串，如：""。 single-node-host-name：请使用单节点主机名，可通过hostname命令查看。 IP：服务器IP地址。 username：登录服务器的用户名。建议使用root用户，避免权限不足。 passwd：登录服务器的用户密码。 二、一键安装root@ubuntu:~/sshpass# apt install sshpass root@ubuntu:~/mindxdl/deploy/offline/steps# dos2unix * root@ubuntu:~/mindxdl/deploy/offline/steps# chmod 500 entry.sh root@ubuntu:~/mindxdl/deploy/offline/steps# bash -x entry.sh三、安装后进行验证 1.docker信息查看root@ubuntu:~# docker info Containers: 35 Running: 30 Paused: 0 Stopped: 5 Images: 18 Server Version: 18.06.3-ce Storage Driver: overlay2 Backing Filesystem: extfs Supports d_type: true Native Overlay Diff: true Logging Driver: json-file Cgroup Driver: systemd Plugins: Volume: local Network: bridge host macvlan null overlay Log: awslogs fluentd gcplogs gelf journald json-file logentries splunk syslog Swarm: inactive Runtimes: ascend runc Default Runtime: ascend Init Binary: docker-init containerd version: 468a545b9edcd5932818eb9de8e72413e616e86e runc version: a592beb5bc4c4092b1b1bac971afed27687340c5 init version: fec3683 Security Options: apparmor seccomp Profile: default Kernel Version: 4.15.0-112-generic Operating System: Ubuntu 18.04.5 LTS OSType: linux Architecture: aarch64 CPUs: 192 Total Memory: 503.6GiB Name: ubuntu ID: MUTU:QOYU:2P6F:P2QB:4JKZ:QNKE:PPMQ:PQLL:3PDG:QEYU:LMDK:KNMF Docker Root Dir: /var/lib/docker Debug Mode (client): false Debug Mode (server): false Registry: https://index.docker.io/v1/ Labels: Experimental: false Insecure Registries: docker.mirrors.ustc.edu.cn 127.0.0.0/8 Registry Mirrors: https://dockerhub.azk8s.cn/ https://docker.mirrors.ustc.edu.cn/ http://hub-mirror.c.163.com/ Live Restore Enabled: false WARNING: No swap limit support 2. kubectl的pod信息查看root@ubuntu:~# kubectl get pod --all-namespaces NAMESPACE NAME READY STATUS RESTARTS AGE cadvisor cadvisor-nsn4r 1/1 Running 0 5m23s default hccl-controller-645bb466f-5fqq6 1/1 Running 0 5m34s kube-system ascend-device-plugin-daemonset-vxj8s 1/1 Running 0 5m23s kube-system calico-kube-controllers-8464785d6b-bnjdn 1/1 Running 0 5m50s kube-system calico-node-blshl 1/1 Running 0 5m51s kube-system coredns-6955765f44-5jr59 1/1 Running 0 5m50s kube-system coredns-6955765f44-wbzvz 1/1 Running 0 5m50s kube-system etcd-ubuntu 1/1 Running 0 5m43s kube-system kube-apiserver-ubuntu 1/1 Running 0 5m43s kube-system kube-controller-manager-ubuntu 1/1 Running 0 5m43s kube-system kube-proxy-b78fm 1/1 Running 0 5m51s kube-system kube-scheduler-ubuntu 1/1 Running 0 5m43s volcano-system volcano-admission-74776688c8-g9p9q 1/1 Running 0 5m31s volcano-system volcano-admission-init-sbktn 0/1 Completed 0 5m31s volcano-system volcano-controllers-6786db54f-vn797 1/1 Running 0 5m31s volcano-system volcano-scheduler-844f9b547b-xxjm7 1/1 Running 0 5m31s root@ubuntu:~# root@ubuntu:~# kubectl describe node ubuntu Name: ubuntu Roles: master,worker Labels: accelerator=huawei-Ascend910 beta.kubernetes.io/arch=arm64 beta.kubernetes.io/os=linux host-arch=huawei-arm kubernetes.io/arch=arm64 kubernetes.io/hostname=ubuntu kubernetes.io/os=linux masterselector=dls-master-node node-role.kubernetes.io/master= node-role.kubernetes.io/worker=worker workerselector=dls-worker-node Annotations: huawei.com/Ascend910: Ascend910-1,Ascend910-2,Ascend910-3,Ascend910-0 kubeadm.alpha.kubernetes.io/cri-socket: /var/run/dockershim.sock node.alpha.kubernetes.io/ttl: 0 projectcalico.org/IPv4Address: 192.168.1.110/24 projectcalico.org/IPv4IPIPTunnelAddr: 10.30.243.192 volumes.kubernetes.io/controller-managed-attach-detach: true CreationTimestamp: Thu, 05 Aug 2021 16:34:33 +0800 Taints: <none> Unschedulable: false Lease: HolderIdentity: ubuntu AcquireTime: <unset> RenewTime: Thu, 05 Aug 2021 16:41:29 +0800 Conditions: Type Status LastHeartbeatTime LastTransitionTime Reason Message ---- ------ ----------------- ------------------ ------ ------- NetworkUnavailable False Thu, 05 Aug 2021 16:35:06 +0800 Thu, 05 Aug 2021 16:35:06 +0800 CalicoIsUp Calico is running on this node MemoryPressure False Thu, 05 Aug 2021 16:40:30 +0800 Thu, 05 Aug 2021 16:34:27 +0800 KubeletHasSufficientMemory kubelet has sufficient memory available DiskPressure False Thu, 05 Aug 2021 16:40:30 +0800 Thu, 05 Aug 2021 16:34:27 +0800 KubeletHasNoDiskPressure kubelet has no disk pressure PIDPressure False Thu, 05 Aug 2021 16:40:30 +0800 Thu, 05 Aug 2021 16:34:27 +0800 KubeletHasSufficientPID kubelet has sufficient PID available Ready True Thu, 05 Aug 2021 16:40:30 +0800 Thu, 05 Aug 2021 16:35:19 +0800 KubeletReady kubelet is posting ready status. AppArmor enabled Addresses: InternalIP: 192.168.1.110 Hostname: ubuntu Capacity: cpu: 192 ephemeral-storage: 920422204Ki huawei.com/Ascend910: 4 hugepages-2Mi: 0 memory: 528101392Ki pods: 110 Allocatable: cpu: 192 ephemeral-storage: 848261101802 huawei.com/Ascend910: 4 hugepages-2Mi: 0 memory: 527998992Ki pods: 110 System Info: Machine ID: 3996e745414f461b9e0e990f6d0b597e System UUID: CD56756C-607E-BD02-EB11-5292EAFB068C Boot ID: adb96127-7fdc-4d84-8867-a13005f9b535 Kernel Version: 4.15.0-112-generic OS Image: Ubuntu 18.04.5 LTS Operating System: linux Architecture: arm64 Container Runtime Version: docker://18.6.3 Kubelet Version: v1.17.3 Kube-Proxy Version: v1.17.3 PodCIDR: 10.30.0.0/24 PodCIDRs: 10.30.0.0/24 Non-terminated Pods: (15 in total) Namespace Name CPU Requests CPU Limits Memory Requests Memory Limits AGE --------- ---- ------------ ---------- --------------- ------------- --- cadvisor cadvisor-nsn4r 500m (0%) 1 (0%) 300Mi (0%) 2000Mi (0%) 6m17s default hccl-controller-645bb466f-5fqq6 500m (0%) 500m (0%) 300Mi (0%) 300Mi (0%) 6m28s kube-system ascend-device-plugin-daemonset-vxj8s 500m (0%) 500m (0%) 500Mi (0%) 500Mi (0%) 6m17s kube-system calico-kube-controllers-8464785d6b-bnjdn 0 (0%) 0 (0%) 0 (0%) 0 (0%) 6m44s kube-system calico-node-blshl 250m (0%) 0 (0%) 0 (0%) 0 (0%) 6m45s kube-system coredns-6955765f44-5jr59 100m (0%) 0 (0%) 70Mi (0%) 170Mi (0%) 6m44s kube-system coredns-6955765f44-wbzvz 100m (0%) 0 (0%) 70Mi (0%) 170Mi (0%) 6m44s kube-system etcd-ubuntu 0 (0%) 0 (0%) 0 (0%) 0 (0%) 6m37s kube-system kube-apiserver-ubuntu 250m (0%) 0 (0%) 0 (0%) 0 (0%) 6m37s kube-system kube-controller-manager-ubuntu 200m (0%) 0 (0%) 0 (0%) 0 (0%) 6m37s kube-system kube-proxy-b78fm 0 (0%) 0 (0%) 0 (0%) 0 (0%) 6m45s kube-system kube-scheduler-ubuntu 100m (0%) 0 (0%) 0 (0%) 0 (0%) 6m37s volcano-system volcano-admission-74776688c8-g9p9q 500m (0%) 500m (0%) 300Mi (0%) 300Mi (0%) 6m25s volcano-system volcano-controllers-6786db54f-vn797 500m (0%) 500m (0%) 300Mi (0%) 300Mi (0%) 6m25s volcano-system volcano-scheduler-844f9b547b-xxjm7 500m (0%) 500m (0%) 300Mi (0%) 300Mi (0%) 6m25s Allocated resources: (Total limits may be over 100 percent, i.e., overcommitted.) Resource Requests Limits -------- -------- ------ cpu 4 (2%) 3500m (1%) memory 2140Mi (0%) 4040Mi (0%) ephemeral-storage 0 (0%) 0 (0%) huawei.com/Ascend910 0 0 Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal NodeHasSufficientMemory 7m10s (x8 over 7m11s) kubelet, ubuntu Node ubuntu status is now: NodeHasSufficientMemory Normal NodeHasNoDiskPressure 7m10s (x7 over 7m11s) kubelet, ubuntu Node ubuntu status is now: NodeHasNoDiskPressure Normal NodeHasSufficientPID 7m10s (x6 over 7m11s) kubelet, ubuntu Node ubuntu status is now: NodeHasSufficientPID Normal Starting 6m37s kubelet, ubuntu Starting kubelet. Normal NodeHasSufficientMemory 6m37s kubelet, ubuntu Node ubuntu status is now: NodeHasSufficientMemory Normal NodeHasNoDiskPressure 6m37s kubelet, ubuntu Node ubuntu status is now: NodeHasNoDiskPressure Normal NodeHasSufficientPID 6m37s kubelet, ubuntu Node ubuntu status is now: NodeHasSufficientPID Normal NodeAllocatableEnforced 6m37s kubelet, ubuntu Updated Node Allocatable limit across pods Normal Starting 6m33s kube-proxy, ubuntu Starting kube-proxy. Normal NodeReady 6m17s kubelet, ubuntu Node ubuntu status is now: NodeReady root@ubuntu:~#注* 再此信息中可以看到CPU和加速卡的信息Capacity: cpu: 192 ephemeral-storage: 920422204Ki huawei.com/Ascend910: 4 hugepages-2Mi: 0 memory: 528101392Ki pods: 110 Allocatable: cpu: 192 ephemeral-storage: 848261101802 huawei.com/Ascend910: 4 hugepages-2Mi: 0 memory: 527998992Ki pods: 110**详情可以查看华为官方文档： **https://support.huaweicloud.com/mindxdl201/Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。30篇原创内容公众号本文使用 文章同步助手 同步
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人工智能NVIDIA显卡计算（CUDA+CUDNN）平台搭建 NVIDIA是GPU（图形处理器）的发明者，也是人工智能计算的引领者。我们创建了世界上最大的游戏平台和世界上最快的超级计算机。 第一步，首先安装N卡驱动。cby@cby-Inspiron-7577:~$ sudo add-apt-repository ppa:graphics-drivers/ppa [sudo] cby 的密码： PPA publishes dbgsym, you may need to include 'main/debug' component Repository: 'deb http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu/ hirsute main' Description: Fresh drivers from upstream, currently shipping Nvidia. ## Current Status Current long-lived branch release: `nvidia-430` (430.40) Dropped support for Fermi series (https://nvidia.custhelp.com/app/answers/detail/a_id/4656) Old long-lived branch release: `nvidia-390` (390.129) For GF1xx GPUs use `nvidia-390` (390.129) For G8x, G9x and GT2xx GPUs use `nvidia-340` (340.107) For NV4x and G7x GPUs use `nvidia-304` (304.137) End-Of-Life! Support timeframes for Unix legacy GPU releases: https://nvidia.custhelp.com/app/answers/detail/a_id/3142 ## What we're working on right now: - Normal driver updates - Help Wanted: Mesa Updates for Intel/AMD users, ping us if you want to help do this work, we're shorthanded. ## WARNINGS: This PPA is currently in testing, you should be experienced with packaging before you dive in here: Volunteers welcome! ### How you can help: ## Install PTS and benchmark your gear: sudo apt-get install phoronix-test-suite Run the benchmark: phoronix-test-suite default-benchmark openarena xonotic tesseract gputest unigine-valley and then say yes when it asks you to submit your results to openbechmarking.org. Then grab a cup of coffee, it takes a bit for the benchmarks to run. Depending on the version of Ubuntu you're using it might preferable for you to grabs PTS from upstream directly: http://www.phoronix-test-suite.com/?k=downloads ## Share your results with the community: Post a link to your results (or any other feedback to): https://launchpad.net/~graphics-drivers-testers Remember to rerun and resubmit the benchmarks after driver upgrades, this will allow us to gather a bunch of data on performance that we can share with everybody. If you run into old documentation referring to other PPAs, you can help us by consolidating references to this PPA. If someone wants to go ahead and start prototyping on `software-properties-gtk` on what the GUI should look like, please start hacking! ## Help us Help You! We use the donation funds to get the developers hardware to test and upload these drivers, please consider donating to the "community" slider on the donation page if you're loving this PPA: http://www.ubuntu.com/download/desktop/contribute More info: https://launchpad.net/~graphics-drivers/+archive/ubuntu/ppa Adding repository. Press [ENTER] to continue or Ctrl-c to cancel. Adding deb entry to /etc/apt/sources.list.d/graphics-drivers-ubuntu-ppa-hirsute.list Adding disabled deb-src entry to /etc/apt/sources.list.d/graphics-drivers-ubuntu-ppa-hirsute.list Adding key to /etc/apt/trusted.gpg.d/graphics-drivers-ubuntu-ppa.gpg with fingerprint 2388FF3BE10A76F638F80723FCAE110B1118213C 命中:1 http://security.ubuntu.com/ubuntu hirsute-security InRelease 命中:3 http://dl.google.com/linux/chrome/deb stable InRelease 获取:4 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu hirsute InRelease [24.4 kB] 命中:5 http://cn.archive.ubuntu.com/ubuntu hirsute InRelease 获取:6 http://cn.archive.ubuntu.com/ubuntu hirsute-updates InRelease [109 kB] 获取:7 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu hirsute/main amd64 Packages [23.4 kB] 命中:8 http://cn.archive.ubuntu.com/ubuntu hirsute-backports InRelease 获取:9 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu hirsute/main i386 Packages [10.6 kB] 获取:10 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu hirsute/main Translation-en [5,880 B] 忽略:2 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1604/x86_64 InRelease 命中:11 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1604/x86_64 Release 已下载 173 kB，耗时 21秒 (8,156 B/s) 正在读取软件包列表... 完成 cby@cby-Inspiron-7577:~$ 第二步，更新源同时查看可安装的驱动cby@cby-Inspiron-7577:~$ sudo apt update 命中:1 http://dl.google.com/linux/chrome/deb stable InRelease 命中:2 http://cn.archive.ubuntu.com/ubuntu hirsute InRelease 获取:4 http://cn.archive.ubuntu.com/ubuntu hirsute-updates InRelease [109 kB] 命中:5 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu hirsute InRelease 命中:6 http://security.ubuntu.com/ubuntu hirsute-security InRelease 忽略:3 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1604/x86_64 InRelease 命中:7 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1604/x86_64 Release 命中:8 http://cn.archive.ubuntu.com/ubuntu hirsute-backports InRelease 已下载 109 kB，耗时 2秒 (64.2 kB/s) 正在读取软件包列表... 完成 正在分析软件包的依赖关系树... 完成 正在读取状态信息... 完成 有 4 个软件包可以升级。请执行 ‘apt list --upgradable’ 来查看它们。 cby@cby-Inspiron-7577:~$ ubuntu-drivers devices WARNING:root:_pkg_get_support nvidia-driver-390: package has invalid Support Legacyheader, cannot determine support level == /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 == modalias : pci:v000010DEd00001C8Csv00001028sd000007FAbc03sc02i00 vendor : NVIDIA Corporation model : GP107M [GeForce GTX 1050 Ti Mobile] manual_install: True driver : nvidia-driver-460 - distro non-free recommended driver : nvidia-driver-450-server - distro non-free driver : nvidia-driver-390 - distro non-free driver : nvidia-driver-465 - distro non-free driver : nvidia-driver-460-server - distro non-free driver : nvidia-driver-418-server - distro non-free driver : xserver-xorg-video-nouveau - distro free builtin cby@cby-Inspiron-7577:~$ sudo apt install nvidia-driver-465 ...略... 第三步，查看显卡信息cby@cby-Inspiron-7577:~$ nvidia-smi Sun Jun 6 21:58:45 2021 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 465.27 Driver Version: 465.27 CUDA Version: 11.3 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 NVIDIA GeForce ... Off | 00000000:01:00.0 Off | N/A | | N/A 59C P3 N/A / N/A | 919MiB / 4042MiB | 6% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | 0 N/A N/A 1976 G /usr/lib/xorg/Xorg 351MiB | | 0 N/A N/A 2620 G /usr/bin/gnome-shell 213MiB | | 0 N/A N/A 4020 G gnome-control-center 1MiB | | 0 N/A N/A 4258 G ...AAAAAAAAA= --shared-files 349MiB | | 0 N/A N/A 6333 G /usr/bin/nvidia-settings 1MiB | +-----------------------------------------------------------------------------+ cby@cby-Inspiron-7577:~$ 第四步，安装 CUDA Toolkit Archivehttps://developer.nvidia.com/cuda-toolkit-archive在如上官网中下载安装CUDA 第五步，根据官方教程进行安装cby@cby-Inspiron-7577:~$ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin --2021-06-06 21:59:36-- https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin 正在解析主机 developer.download.nvidia.com (developer.download.nvidia.com)... 192.254.94.202, 45.43.32.210, 45.43.32.211, ... 正在连接 developer.download.nvidia.com (developer.download.nvidia.com)|192.254.94.202|:443... 已连接。 已发出 HTTP 请求，正在等待回应... 301 Moved Permanently 位置：https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin [跟随至新的 URL] --2021-06-06 21:59:37-- https://developer.download.nvidia.cn/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin 正在解析主机 developer.download.nvidia.cn (developer.download.nvidia.cn)... 124.132.138.66, 124.132.138.73, 124.132.138.69 正在连接 developer.download.nvidia.cn (developer.download.nvidia.cn)|124.132.138.66|:443... 已连接。 已发出 HTTP 请求，正在等待回应... 200 OK 长度：190 [application/octet-stream] 正在保存至: ‘cuda-ubuntu2004.pin’ cuda-ubuntu2004.pin 100%[==================>] 190 --.-KB/s 用时 0s 2021-06-06 21:59:37 (26.1 MB/s) - 已保存 ‘cuda-ubuntu2004.pin’ [190/190]) cby@cby-Inspiron-7577:~$ sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600 cby@cby-Inspiron-7577:~$ wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb --2021-06-06 21:59:48-- https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb 正在解析主机 developer.download.nvidia.com (developer.download.nvidia.com)... 45.43.32.210, 192.254.94.203, 45.43.32.211, ... 正在连接 developer.download.nvidia.com (developer.download.nvidia.com)|45.43.32.210|:443... 已连接。 已发出 HTTP 请求，正在等待回应... 301 Moved Permanently 位置：https://developer.download.nvidia.cn/compute/cuda/11.3.1/local_installers/cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb [跟随至新的 URL] --2021-06-06 21:59:48-- https://developer.download.nvidia.cn/compute/cuda/11.3.1/local_installers/cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb 正在解析主机 developer.download.nvidia.cn (developer.download.nvidia.cn)... 124.132.138.66, 124.132.138.73, 124.132.138.69 正在连接 developer.download.nvidia.cn (developer.download.nvidia.cn)|124.132.138.66|:443... 已连接。 已发出 HTTP 请求，正在等待回应... 200 OK 长度：2374574280 (2.2G) [application/x-deb] 正在保存至: ‘cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb’ cuda-repo-ubuntu200 100%[==================>] 2.21G 44.0MB/s 用时 51s 2021-06-06 22:00:40 (44.3 MB/s) - 已保存 ‘cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb’ [2374574280/2374574280]) cby@cby-Inspiron-7577:~$ sudo dpkg -i cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb 正在选中未选择的软件包 cuda-repo-ubuntu2004-11-3-local。 (正在读取数据库 ... 系统当前共安装有 209119 个文件和目录。) 准备解压 cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb ... 正在解压 cuda-repo-ubuntu2004-11-3-local (11.3.1-465.19.01-1) ... 正在设置 cuda-repo-ubuntu2004-11-3-local (11.3.1-465.19.01-1) ... cby@cby-Inspiron-7577:~$ sudo apt-key add /var/cuda-repo-ubuntu2004-11-3-local/7fa2af80.pub Warning: apt-key is deprecated. Manage keyring files in trusted.gpg.d instead (see apt-key(8)). OK cby@cby-Inspiron-7577:~$ sudo apt-get update 获取:1 file:/var/cuda-repo-ubuntu2004-11-3-local InRelease 忽略:1 file:/var/cuda-repo-ubuntu2004-11-3-local InRelease 获取:2 file:/var/cuda-repo-ubuntu2004-11-3-local Release [564 B] 获取:2 file:/var/cuda-repo-ubuntu2004-11-3-local Release [564 B] 获取:3 file:/var/cuda-repo-ubuntu2004-11-3-local Release.gpg [836 B] 获取:3 file:/var/cuda-repo-ubuntu2004-11-3-local Release.gpg [836 B] 获取:4 file:/var/cuda-repo-ubuntu2004-11-3-local Packages [30.4 kB] 命中:5 http://cn.archive.ubuntu.com/ubuntu hirsute InRelease 获取:7 http://cn.archive.ubuntu.com/ubuntu hirsute-updates InRelease [109 kB] 命中:8 http://dl.google.com/linux/chrome/deb stable InRelease 命中:9 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu hirsute InRelease 命中:10 http://security.ubuntu.com/ubuntu hirsute-security InRelease 忽略:6 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1604/x86_64 InRelease 命中:11 https://developer.download.nvidia.cn/compute/machine-learning/repos/ubuntu1604/x86_64 Release 命中:13 http://cn.archive.ubuntu.com/ubuntu hirsute-backports InRelease 已下载 109 kB，耗时 2秒 (52.6 kB/s) 正在读取软件包列表... 完成 cby@cby-Inspiron-7577:~$ cby@cby-Inspiron-7577:~$ cby@cby-Inspiron-7577:~$ sudo apt-get -y 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... 完成 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： libaccinj64-11.2 libcub-dev libcublas11 libcublaslt11 libcudart11.0 libcufft10 libcufftw10 libcuinj64-11.2 libcupti-dev libcupti-doc libcupti11.2 libcurand10 libcusolver11 libcusolvermg11 libcusparse11 libegl-dev libgl-dev libgl1-mesa-dev libgles-dev libgles1 libglvnd-dev libglx-dev libnppc11 libnppial11 libnppicc11 libnppidei11 libnppif11 libnppig11 libnppim11 libnppist11 libnppisu11 libnppitc11 libnpps11 libnvblas11 libnvjpeg11 libnvrtc11.2 libnvtoolsext1 libnvvm4 libopengl-dev libopengl0 libpthread-stubs0-dev libthrust-dev libvdpau-dev libx11-dev libxau-dev libxcb1-dev libxdmcp-dev node-html5shiv nsight-compute nsight-compute-target nsight-systems nsight-systems-target nvidia-cuda-gdb nvidia-cuda-toolkit-doc nvidia-opencl-dev nvidia-profiler nvidia-visual-profiler ocl-icd-opencl-dev opencl-c-headers opencl-clhpp-headers x11proto-dev xorg-sgml-doctools xtrans-dev 使用'sudo apt autoremove'来卸载它(它们)。 将会同时安装下列软件： cuda-11-3 cuda-command-line-tools-11-3 cuda-compiler-11-3 cuda-cudart-11-3 cuda-cudart-dev-11-3 cuda-cuobjdump-11-3 cuda-cupti-11-3 cuda-cupti-dev-11-3 cuda-cuxxfilt-11-3 cuda-demo-suite-11-3 cuda-documentation-11-3 cuda-driver-dev-11-3 cuda-drivers cuda-drivers-465 cuda-gdb-11-3 cuda-libraries-11-3 cuda-libraries-dev-11-3 cuda-memcheck-11-3 cuda-nsight-11-3 cuda-nsight-compute-11-3 cuda-nsight-systems-11-3 cuda-nvcc-11-3 cuda-nvdisasm-11-3 cuda-nvml-dev-11-3 cuda-nvprof-11-3 cuda-nvprune-11-3 cuda-nvrtc-11-3 cuda-nvrtc-dev-11-3 cuda-nvtx-11-3 cuda-nvvp-11-3 cuda-runtime-11-3 cuda-samples-11-3 cuda-sanitizer-11-3 cuda-thrust-11-3 cuda-toolkit-11-3 cuda-toolkit-11-3-config-common cuda-toolkit-11-config-common cuda-toolkit-config-common cuda-tools-11-3 cuda-visual-tools-11-3 default-jre default-jre-headless libcublas-11-3 libcublas-dev-11-3 libcufft-11-3 libcufft-dev-11-3 libcurand-11-3 libcurand-dev-11-3 libcusolver-11-3 libcusolver-dev-11-3 libcusparse-11-3 libcusparse-dev-11-3 libnpp-11-3 libnpp-dev-11-3 libnvjpeg-11-3 libnvjpeg-dev-11-3 nsight-compute-2021.1.1 nsight-systems-2021.1.3 nvidia-modprobe nvidia-settings openjdk-11-jre openjdk-11-jre-headless 建议安装： fonts-ipafont-gothic fonts-ipafont-mincho fonts-wqy-microhei | fonts-wqy-zenhei 下列【新】软件包将被安装： cuda cuda-11-3 cuda-command-line-tools-11-3 cuda-compiler-11-3 cuda-cudart-11-3 cuda-cudart-dev-11-3 cuda-cuobjdump-11-3 cuda-cupti-11-3 cuda-cupti-dev-11-3 cuda-cuxxfilt-11-3 cuda-demo-suite-11-3 cuda-documentation-11-3 cuda-driver-dev-11-3 cuda-drivers cuda-drivers-465 cuda-gdb-11-3 cuda-libraries-11-3 cuda-libraries-dev-11-3 cuda-memcheck-11-3 cuda-nsight-11-3 cuda-nsight-compute-11-3 cuda-nsight-systems-11-3 cuda-nvcc-11-3 cuda-nvdisasm-11-3 cuda-nvml-dev-11-3 cuda-nvprof-11-3 cuda-nvprune-11-3 cuda-nvrtc-11-3 cuda-nvrtc-dev-11-3 cuda-nvtx-11-3 cuda-nvvp-11-3 cuda-runtime-11-3 cuda-samples-11-3 cuda-sanitizer-11-3 cuda-thrust-11-3 cuda-toolkit-11-3 cuda-toolkit-11-3-config-common cuda-toolkit-11-config-common cuda-toolkit-config-common cuda-tools-11-3 cuda-visual-tools-11-3 default-jre default-jre-headless libcublas-11-3 libcublas-dev-11-3 libcufft-11-3 libcufft-dev-11-3 libcurand-11-3 libcurand-dev-11-3 libcusolver-11-3 libcusolver-dev-11-3 libcusparse-11-3 libcusparse-dev-11-3 libnpp-11-3 libnpp-dev-11-3 libnvjpeg-11-3 libnvjpeg-dev-11-3 nsight-compute-2021.1.1 nsight-systems-2021.1.3 nvidia-modprobe openjdk-11-jre openjdk-11-jre-headless 下列软件包将被升级： nvidia-settings 升级了 1 个软件包，新安装了 62 个软件包，要卸载 0 个软件包，有 5 个软件包未被升级。 需要下载 37.4 MB/2,162 MB 的归档。 解压缩后会消耗 4,934 MB 的额外空间。 获取:1 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-toolkit-config-common 11.3.109-1 [16.1 kB] 获取:2 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-toolkit-11-config-common 11.3.109-1 [16.1 kB] 获取:3 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-toolkit-11-3-config-common 11.3.109-1 [16.1 kB] 获取:4 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-cudart-11-3 11.3.109-1 [157 kB] 获取:5 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-nvrtc-11-3 11.3.109-1 [26.1 MB] 获取:6 http://cn.archive.ubuntu.com/ubuntu hirsute-updates/main amd64 openjdk-11-jre-headless amd64 11.0.11+9-0ubuntu2 [37.2 MB] 获取:7 file:/var/cuda-repo-ubuntu2004-11-3-local libcublas-11-3 11.5.1.109-1 [168 MB] 获取:8 file:/var/cuda-repo-ubuntu2004-11-3-local libcufft-11-3 10.4.2.109-1 [108 MB] 获取:9 file:/var/cuda-repo-ubuntu2004-11-3-local libcurand-11-3 10.2.4.109-1 [39.4 MB] 获取:10 file:/var/cuda-repo-ubuntu2004-11-3-local libcusolver-11-3 11.1.2.109-1 [85.5 MB] 获取:11 file:/var/cuda-repo-ubuntu2004-11-3-local libcusparse-11-3 11.6.0.109-1 [104 MB] 获取:12 file:/var/cuda-repo-ubuntu2004-11-3-local libnpp-11-3 11.3.3.95-1 [75.1 MB] 获取:13 file:/var/cuda-repo-ubuntu2004-11-3-local libnvjpeg-11-3 11.5.0.109-1 [1,742 kB] 获取:14 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-libraries-11-3 11.3.1-1 [2,498 B] 获取:15 file:/var/cuda-repo-ubuntu2004-11-3-local nvidia-modprobe 465.19.01-0ubuntu1 [19.9 kB] 获取:16 file:/var/cuda-repo-ubuntu2004-11-3-local nvidia-settings 465.19.01-0ubuntu1 [928 kB] 获取:17 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-drivers-465 465.19.01-1 [2,628 B] 获取:18 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-drivers 465.19.01-1 [2,504 B] 获取:19 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-runtime-11-3 11.3.1-1 [2,424 B] 获取:20 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-cuobjdump-11-3 11.3.58-1 [112 kB] 获取:21 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-cuxxfilt-11-3 11.3.58-1 [44.1 kB] 获取:22 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-thrust-11-3 11.3.109-1 [981 kB] 获取:23 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-driver-dev-11-3 11.3.109-1 [26.2 kB] 获取:24 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-cudart-dev-11-3 11.3.109-1 [737 kB] 获取:25 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-nvcc-11-3 11.3.109-1 [46.5 MB] 获取:26 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-nvprune-11-3 11.3.58-1 [54.9 kB] 获取:27 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-compiler-11-3 11.3.1-1 [2,430 B] 获取:28 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-nvrtc-dev-11-3 11.3.109-1 [23.4 kB] 获取:29 http://cn.archive.ubuntu.com/ubuntu hirsute/main amd64 default-jre-headless amd64 2:1.11-72 [3,192 B] 获取:30 http://cn.archive.ubuntu.com/ubuntu hirsute-updates/main amd64 openjdk-11-jre amd64 11.0.11+9-0ubuntu2 [177 kB] 获取:31 http://cn.archive.ubuntu.com/ubuntu hirsute/main amd64 default-jre amd64 2:1.11-72 [1,084 B] 获取:32 file:/var/cuda-repo-ubuntu2004-11-3-local libcublas-dev-11-3 11.5.1.109-1 [171 MB] 获取:33 file:/var/cuda-repo-ubuntu2004-11-3-local libcufft-dev-11-3 10.4.2.109-1 [181 MB] 获取:34 file:/var/cuda-repo-ubuntu2004-11-3-local libcurand-dev-11-3 10.2.4.109-1 [39.9 MB] 获取:35 file:/var/cuda-repo-ubuntu2004-11-3-local libcusolver-dev-11-3 11.1.2.109-1 [22.2 MB] 获取:36 file:/var/cuda-repo-ubuntu2004-11-3-local libcusparse-dev-11-3 11.6.0.109-1 [104 MB] 获取:37 file:/var/cuda-repo-ubuntu2004-11-3-local libnpp-dev-11-3 11.3.3.95-1 [71.7 MB] 获取:38 file:/var/cuda-repo-ubuntu2004-11-3-local libnvjpeg-dev-11-3 11.5.0.109-1 [1,435 kB] 获取:39 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-libraries-dev-11-3 11.3.1-1 [2,526 B] 获取:40 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-cupti-11-3 11.3.111-1 [11.7 MB] 获取:41 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-cupti-dev-11-3 11.3.111-1 [2,404 kB] 获取:42 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-nvdisasm-11-3 11.3.58-1 [32.9 MB] 获取:43 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-gdb-11-3 11.3.109-1 [3,622 kB] 获取:44 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-memcheck-11-3 11.3.109-1 [145 kB] 获取:45 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-nvprof-11-3 11.3.111-1 [1,925 kB] 获取:46 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file:/var/cuda-repo-ubuntu2004-11-3-local cuda-tools-11-3 11.3.1-1 [2,378 B] 获取:58 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-samples-11-3 11.3.58-1 [59.2 MB] 获取:59 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-documentation-11-3 11.3.111-1 [48.1 kB] 获取:60 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-toolkit-11-3 11.3.1-1 [3,300 B] 获取:61 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-demo-suite-11-3 11.3.58-1 [3,978 kB] 获取:62 file:/var/cuda-repo-ubuntu2004-11-3-local cuda-11-3 11.3.1-1 [2,450 B] 获取:63 file:/var/cuda-repo-ubuntu2004-11-3-local cuda 11.3.1-1 [2,396 B] 已下载 37.4 MB，耗时 15秒 (2,527 kB/s) Requesting to save current system state Successfully saved as "autozsys_el84cc" 正在从软件包中解出模板：100% 正在选中未选择的软件包 cuda-toolkit-config-common。 (正在读取数据库 ... 系统当前共安装有 209232 个文件和目录。) 准备解压 .../00-cuda-toolkit-config-common_11.3.109-1_all.deb ... 正在解压 cuda-toolkit-config-common (11.3.109-1) ... 正在选中未选择的软件包 cuda-toolkit-11-config-common。 准备解压 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cuda-nvvp-11-3 (11.3.111-1) ... 正在选中未选择的软件包 cuda-visual-tools-11-3。 准备解压 .../55-cuda-visual-tools-11-3_11.3.1-1_amd64.deb ... 正在解压 cuda-visual-tools-11-3 (11.3.1-1) ... 正在选中未选择的软件包 cuda-tools-11-3。 准备解压 .../56-cuda-tools-11-3_11.3.1-1_amd64.deb ... 正在解压 cuda-tools-11-3 (11.3.1-1) ... 正在选中未选择的软件包 cuda-samples-11-3。 准备解压 .../57-cuda-samples-11-3_11.3.58-1_amd64.deb ... 正在解压 cuda-samples-11-3 (11.3.58-1) ... 正在选中未选择的软件包 cuda-documentation-11-3。 准备解压 .../58-cuda-documentation-11-3_11.3.111-1_amd64.deb ... 正在解压 cuda-documentation-11-3 (11.3.111-1) ... 正在选中未选择的软件包 cuda-toolkit-11-3。 准备解压 .../59-cuda-toolkit-11-3_11.3.1-1_amd64.deb ... 正在解压 cuda-toolkit-11-3 (11.3.1-1) ... 正在选中未选择的软件包 cuda-demo-suite-11-3。 准备解压 .../60-cuda-demo-suite-11-3_11.3.58-1_amd64.deb ... 正在解压 cuda-demo-suite-11-3 (11.3.58-1) ... 正在选中未选择的软件包 cuda-11-3。 准备解压 .../61-cuda-11-3_11.3.1-1_amd64.deb ... 正在解压 cuda-11-3 (11.3.1-1) ... 正在选中未选择的软件包 cuda。 准备解压 .../62-cuda_11.3.1-1_amd64.deb ... 正在解压 cuda (11.3.1-1) ... 正在设置 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Setting alternatives update-alternatives: 使用 /usr/local/cuda-11.3 来在自动模式中提供 /usr/local/cuda (cuda) update-alternatives: 使用 /usr/local/cuda-11.3 来在自动模式中提供 /usr/local/cuda-11 (cuda-11) 正在设置 cuda-toolkit-11-config-common (11.3.109-1) ... 正在设置 cuda-nvtx-11-3 (11.3.109-1) ... 正在设置 cuda-memcheck-11-3 (11.3.109-1) ... 正在设置 cuda-nvprune-11-3 (11.3.58-1) ... 正在设置 cuda-driver-dev-11-3 (11.3.109-1) ... 正在设置 openjdk-11-jre-headless:amd64 (11.0.11+9-0ubuntu2) ... update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/java 来在自动模式中提供 /usr/bin/java (java) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/jjs 来在自动模式中提供 /usr/bin/jjs (jjs) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/keytool 来在自动模式中提供 /usr/bin/keytool (keytool) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/rmid 来在自动模式中提供 /usr/bin/rmid (rmid) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/rmiregistry 来在自动模式中提供 /usr/bin/rmiregistry (rmiregistry) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/pack200 来在自动模式中提供 /usr/bin/pack200 (pack200) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/bin/unpack200 来在自动模式中提供 /usr/bin/unpack200 (unpack200) update-alternatives: 使用 /usr/lib/jvm/java-11-openjdk-amd64/lib/jexec 来在自动模式中提供 /usr/bin/jexec (jexec) 正在设置 openjdk-11-jre:amd64 (11.0.11+9-0ubuntu2) ... 正在设置 libnvjpeg-11-3 (11.5.0.109-1) ... 正在设置 cuda-nvprof-11-3 (11.3.111-1) ... 正在设置 nvidia-modprobe (465.19.01-0ubuntu1) ... 正在设置 cuda-thrust-11-3 (11.3.109-1) ... 正在设置 cuda-nvml-dev-11-3 (11.3.58-1) ... 正在设置 libnvjpeg-dev-11-3 (11.5.0.109-1) ... 正在设置 cuda-cudart-11-3 (11.3.109-1) ... 正在设置 cuda-cudart-dev-11-3 (11.3.109-1) ... 正在设置 nsight-compute-2021.1.1 (2021.1.1.5-1) ... 正在设置 libnpp-11-3 (11.3.3.95-1) ... 正在设置 libcusparse-11-3 (11.6.0.109-1) ... 正在设置 nsight-systems-2021.1.3 (2021.1.3.14-b695ea9) ... update-alternatives: 使用 /opt/nvidia/nsight-systems/2021.1.3/target-linux-x64/nsys 来在自动模式中提供 /usr/local/bin/nsys (nsys) update-alternatives: 错误: alternative path /opt/nvidia/nsight-systems/2021.1.3/host-linux-x64/nsight-sys doesn't exist update-alternatives: 错误: 无 nsight-sys 的候选项 update-alternatives: 使用 /opt/nvidia/nsight-systems/2021.1.3/host-linux-x64/nsys-ui 来在自动模式中提供 /usr/local/bin/nsys-ui (nsys-ui) 正在设置 cuda-nvdisasm-11-3 (11.3.58-1) ... 正在设置 nvidia-settings (465.19.01-0ubuntu1) ... 正在设置 libcurand-11-3 (10.2.4.109-1) ... 正在设置 cuda-cuobjdump-11-3 (11.3.58-1) ... 正在设置 libcufft-11-3 (10.4.2.109-1) ... 正在设置 libcusparse-dev-11-3 (11.6.0.109-1) ... 正在设置 cuda-nvrtc-11-3 (11.3.109-1) ... 正在设置 cuda-sanitizer-11-3 (11.3.111-1) ... 正在设置 libcusolver-11-3 (11.1.2.109-1) ... 正在设置 libcublas-11-3 (11.5.1.109-1) ... 正在设置 cuda-nsight-systems-11-3 (11.3.1-1) ... 正在设置 cuda-nvrtc-dev-11-3 (11.3.109-1) ... 正在设置 libcurand-dev-11-3 (10.2.4.109-1) ... 正在设置 default-jre-headless (2:1.11-72) ... 正在设置 libcublas-dev-11-3 (11.5.1.109-1) ... 正在设置 cuda-nsight-compute-11-3 (11.3.1-1) ... 正在设置 cuda-nvcc-11-3 (11.3.109-1) ... 正在设置 cuda-drivers-465 (465.19.01-1) ... 正在设置 libnpp-dev-11-3 (11.3.3.95-1) ... 正在设置 cuda-libraries-11-3 (11.3.1-1) ... 正在设置 cuda-gdb-11-3 (11.3.109-1) ... 正在设置 default-jre (2:1.11-72) ... 正在设置 cuda-compiler-11-3 (11.3.1-1) ... 正在设置 cuda-drivers (465.19.01-1) ... 正在设置 libcufft-dev-11-3 (10.4.2.109-1) ... 正在设置 cuda-nvvp-11-3 (11.3.111-1) ... 正在设置 libcusolver-dev-11-3 (11.1.2.109-1) ... 正在设置 cuda-runtime-11-3 (11.3.1-1) ... 正在设置 cuda-cupti-11-3 (11.3.111-1) ... 正在设置 cuda-nsight-11-3 (11.3.109-1) ... 正在设置 cuda-demo-suite-11-3 (11.3.58-1) ... 正在设置 cuda-cupti-dev-11-3 (11.3.111-1) ... 正在设置 cuda-libraries-dev-11-3 (11.3.1-1) ... 正在设置 cuda-visual-tools-11-3 (11.3.1-1) ... 正在设置 cuda-samples-11-3 (11.3.58-1) ... 正在设置 cuda-command-line-tools-11-3 (11.3.1-1) ... 正在设置 cuda-documentation-11-3 (11.3.111-1) ... 正在设置 cuda-tools-11-3 (11.3.1-1) ... 正在设置 cuda-toolkit-11-3 (11.3.1-1) ... Setting alternatives 正在设置 cuda-11-3 (11.3.1-1) ... 正在设置 cuda (11.3.1-1) ... 正在处理用于 libc-bin (2.33-0ubuntu5) 的触发器 ... 正在处理用于 man-db (2.9.4-2) 的触发器 ... 正在处理用于 mailcap (3.68ubuntu1) 的触发器 ... 正在处理用于 desktop-file-utils (0.26-1ubuntu1) 的触发器 ... 正在处理用于 hicolor-icon-theme (0.17-2) 的触发器 ... 正在处理用于 gnome-menus (3.36.0-1ubuntu1) 的触发器 ... ZSys is adding automatic system snapshot to GRUB menu 第六步，配置环境变量cby@cby-Inspiron-7577:~$ vim ~/.bashrc cby@cby-Inspiron-7577:~$ cat ~/.bashrc # ...略... export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-11.3/lib64 export PATH=$PATH:/usr/local/cuda-11.3/bin export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-11.3 cby@cby-Inspiron-7577:~$ source ~/.bashrc第七步，下载安装CUDNNhttps://developer.nvidia.com/cudnn访问如向连接，进行注册英伟达开发者，注册完成后下载安装包第八步，下载完成后进入目录后进行安装刚刚下载的安装包cby@cby-Inspiron-7577:~/Downloads$ ls libcudnn8_8.2.0.53-1+cuda11.3_amd64.deb libcudnn8-dev_8.2.0.53-1+cuda11.3_amd64.deb libcudnn8-samples_8.2.0.53-1+cuda11.3_amd64.deb pycharm-community-2021.1.2.tar.gz cby@cby-Inspiron-7577:~/Downloads$ sudo apt install ./libcudnn8* 正在读取软件包列表... 完成 正在分析软件包的依赖关系树... 完成 正在读取状态信息... 完成 注意，选中 'libcudnn8' 而非 './libcudnn8_8.2.0.53-1+cuda11.3_amd64.deb' 注意，选中 'libcudnn8-dev' 而非 './libcudnn8-dev_8.2.0.53-1+cuda11.3_amd64.deb' 注意，选中 'libcudnn8-samples' 而非 './libcudnn8-samples_8.2.0.53-1+cuda11.3_amd64.deb' 下列软件包是自动安装的并且现在不需要了： libaccinj64-11.2 libcub-dev libcublas11 libcublaslt11 libcudart11.0 libcufft10 libcufftw10 libcuinj64-11.2 libcupti-dev libcupti-doc libcupti11.2 libcurand10 libcusolver11 libcusolvermg11 libcusparse11 libegl-dev libgl-dev libgl1-mesa-dev libgles-dev libgles1 libglvnd-dev libglx-dev libnppc11 libnppial11 libnppicc11 libnppidei11 libnppif11 libnppig11 libnppim11 libnppist11 libnppisu11 libnppitc11 libnpps11 libnvblas11 libnvjpeg11 libnvrtc11.2 libnvtoolsext1 libnvvm4 libopengl-dev libopengl0 libpthread-stubs0-dev libthrust-dev libvdpau-dev libx11-dev libxau-dev libxcb1-dev libxdmcp-dev node-html5shiv nsight-compute nsight-compute-target nsight-systems nsight-systems-target nvidia-cuda-gdb nvidia-cuda-toolkit-doc nvidia-opencl-dev nvidia-profiler nvidia-visual-profiler ocl-icd-opencl-dev opencl-c-headers opencl-clhpp-headers x11proto-dev xorg-sgml-doctools xtrans-dev 使用'sudo apt autoremove'来卸载它(它们)。 下列【新】软件包将被安装： libcudnn8 libcudnn8-dev libcudnn8-samples 升级了 0 个软件包，新安装了 3 个软件包，要卸载 0 个软件包，有 5 个软件包未被升级。 需要下载 0 B/823 MB 的归档。 解压缩后会消耗 2,899 MB 的额外空间。 获取:1 /home/cby/Downloads/libcudnn8_8.2.0.53-1+cuda11.3_amd64.deb libcudnn8 amd64 8.2.0.53-1+cuda11.3 [454 MB] 获取:2 /home/cby/Downloads/libcudnn8-dev_8.2.0.53-1+cuda11.3_amd64.deb libcudnn8-dev amd64 8.2.0.53-1+cuda11.3 [366 MB] 获取:3 /home/cby/Downloads/libcudnn8-samples_8.2.0.53-1+cuda11.3_amd64.deb libcudnn8-samples amd64 8.2.0.53-1+cuda11.3 [1,672 kB] Requesting to save current system state Successfully saved as "autozsys_mptxg3" 正在选中未选择的软件包 libcudnn8。 (正在读取数据库 ... 系统当前共安装有 216273 个文件和目录。) 准备解压 .../libcudnn8_8.2.0.53-1+cuda11.3_amd64.deb ... 正在解压 libcudnn8 (8.2.0.53-1+cuda11.3) ... 正在选中未选择的软件包 libcudnn8-dev。 准备解压 .../libcudnn8-dev_8.2.0.53-1+cuda11.3_amd64.deb ... 正在解压 libcudnn8-dev (8.2.0.53-1+cuda11.3) ... 正在选中未选择的软件包 libcudnn8-samples。 准备解压 .../libcudnn8-samples_8.2.0.53-1+cuda11.3_amd64.deb ... 正在解压 libcudnn8-samples (8.2.0.53-1+cuda11.3) ... 正在设置 libcudnn8 (8.2.0.53-1+cuda11.3) ... 正在设置 libcudnn8-dev (8.2.0.53-1+cuda11.3) ... update-alternatives: 使用 /usr/include/x86_64-linux-gnu/cudnn_v8.h 来在自动模 式中提供 /usr/include/cudnn.h (libcudnn) 正在设置 libcudnn8-samples (8.2.0.53-1+cuda11.3) ... 正在处理用于 libc-bin (2.33-0ubuntu5) 的触发器 ... ZSys is adding automatic system snapshot to GRUB menu N: 由于文件'/home/cby/Downloads/libcudnn8_8.2.0.53-1+cuda11.3_amd64.deb'无法被用户'_apt'访问，已脱离沙盒并提权为根用户来进行下载。- pkgAcquire::Run (13: 权限不够) cby@cby-Inspiron-7577:~/Downloads$ 第九步，进行验证cby@cby-Inspiron-7577:~/Downloads$ python Python 3.9.5 (default, May 11 2021, 08:20:37) [GCC 10.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import paddle >>> paddle.utils.run_check() Running verify PaddlePaddle program ... W0606 22:39:35.543371 63149 device_context.cc:404] Please NOTE: device: 0, GPU Compute Capability: 6.1, Driver API Version: 11.3, Runtime API Version: 10.2 W0606 22:39:35.572693 63149 device_context.cc:422] device: 0, cuDNN Version: 8.2. PaddlePaddle works well on 1 GPU. PaddlePaddle works well on 1 GPUs. PaddlePaddle is installed successfully! Let's start deep learning with PaddlePaddle now. >>> 第十步，运行情感训练模型，查看结果 至此，已完成安装，需要注意的是：在windows下安装及其困难，部分工具无法安装，导致无法正常运行AMD的显卡是无法使用GPU进行人工智能计算的特别注意IDE开发环境中的PYTHON和系统中的环境Linux运维交流社区Linux运维交流社区，互联网新闻以及技术交流。27篇原创内容公众号本文使用 文章同步助手 同步