Henry Tang htang2012

Installing CUDA 12.1.1 + PyTorch nightly + Python 3.10 on Ubuntu 22.10

Should you keep your NVIDIA driver?

CUDA 12.1.1 toolkit is gonna offer to install Nvidia driver 530 for us. It's from New Feature branch. It's likely to be newer than the default Nvidia driver you would've installed via apt-get (apt would prefer to give you 525, i.e. Production Branch).

If you're confident that you already have a new enough Nvidia driver for CUDA 12.1.1, and you'd like to keep your driver: feel free to skip this "uninstall driver" step.

But if you're not sure, or you know your driver is too old: let's uninstall it. CUDA will install a new driver for us later.

Installing the NVIDIA driver, CUDA and cuDNN on Linux (Ubuntu 20.04)

This is a companion piece to my instructions on building TensorFlow from source. In particular, the aim is to install the following pieces of software

NVIDIA graphics card driver (v450.57)
CUDA (v11.0.2)
cuDNN (v8.0.2.39)

on an Ubuntu Linux system, in particular Ubuntu 20.04.

NOTE: This is a question I found on StackOverflow which I’ve archived here, because the answer is so effing phenomenal.

Q: How can I make a chain of function decorators in Python?

If you are not into long explanations, see [Paolo Bergantino’s answer][2].

	#!/bin/bash
	## This gist contains instructions about cuda v10.1 and cudnn 7.6 installation in Ubuntu 18.04 for Tensorflow 2.1.0

	### steps ####
	# verify the system has a cuda-capable gpu
	# download and install the nvidia cuda toolkit and cudnn
	# setup environmental variables
	# verify the installation
	###

	/*
	* This program is free software: you can redistribute it and/or modify
	* it under the terms of the GNU General Public License as published by
	* the Free Software Foundation, either version 3 of the License, or
	* (at your option) any later version.
	*/

	#include <arpa/inet.h>
	#include <linux/if_packet.h>
	#include <stdio.h>

	/*
	* This program is free software: you can redistribute it and/or modify
	* it under the terms of the GNU General Public License as published by
	* the Free Software Foundation, either version 3 of the License, or
	* (at your option) any later version.
	*/

	#include <arpa/inet.h>
	#include <linux/if_packet.h>
	#include <linux/ip.h>

	1. Execute make first. This will result in a netlinkKernel.ko output among many others.
	2. Execute $ gcc netlinkUser.c -o netlinkUser
	3. Insert kernel module by :$ sudo insmod netlinkKernel.ko
	4. Run ./netlinkUser to see message and run dmesg to see debug messages
	5. Remove module by : $ sudo rmmod netlinkKernel
	6. Finally make clean to remove output files.

	/**
	http://guochongxin.github.io/c/c/c++/linux/netlink/rj45/%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80/%E7%BD%91%E5%8D%A1/2014/12/05/tong_guo_netlink_jian_ce_wang_xian_cha_ba


	最近有个需求需要检测RJ45网卡的网线有没有接上，而最近正在了解Netlink相关资料，刚好也看下通过Netlink可以进行检测，故在此做下粗略笔记：

	1.首先要创建一个Netlink Socket，在用户层使用如下参数来调用socket()函数：

	fd = socket(AF_NETLINK, SOCK_RAW, NETLINK_ROUTE);

	#
	# STL GDB evaluators/views/utilities - 1.03
	#
	# The new GDB commands:
	# are entirely non instrumental
	# do not depend on any "inline"(s) - e.g. size(), [], etc
	# are extremely tolerant to debugger settings
	#
	# This file should be "included" in .gdbinit as following:
	# source stl-views.gdb or just paste it into your .gdbinit file