matsui528

# Install script of Caffe2 and Detectron on AWS EC2
#
# Tested environment:
#   - AMI: Deep Learning Base AMI (Ubuntu) Version 6.0 - ami-ce3673b6  (CUDA is already installed)
#   - Instance: p3.2xlarge (V100 * 1)
#   - Caffe2: https://github.com/pytorch/pytorch/commit/731273b8d61dfa2aa8b2909f27c8810ede103952
#   - Detectron: https://github.com/facebookresearch/Detectron/commit/cd447c77c96f5752d6b37761d30bbdacc86989a2
#
# Usage:
#   Launch a fresh EC2 instance, put this script on the /home/ubuntu/, and run the following command.

whizzzkid

# Instructions for 4.14 and cuda 9.1
# If upgrading from 4.13 and cuda 9.0
$ sudo apt-get purge --auto-remove libcud*
$ sudo apt-get purge --auto-remove cuda*
$ sudo apt-get purge --auto-remove nvidia*
# also remove the container directory direcotory at /usr/local/cuda-9.0/

# Important libs required with 4.14.x with Cuda 9.X
$ sudo apt install libelf1 libelf-dev

gocarlos

// A simple quickref for Eigen. Add anything that's missing.
// Main author: Keir Mierle

#include <Eigen/Dense>

Matrix<double, 3, 3> A;               // Fixed rows and cols. Same as Matrix3d.
Matrix<double, 3, Dynamic> B;         // Fixed rows, dynamic cols.
Matrix<double, Dynamic, Dynamic> C;   // Full dynamic. Same as MatrixXd.
Matrix<double, 3, 3, RowMajor> E;     // Row major; default is column-major.
Matrix3f P, Q, R;                     // 3x3 float matrix.

tanyuan

wangruohui

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm