Why Should I Care (For Developers)
"Docker interests me because it allows simple environment isolation and repeatability. I can create a run-time environment once, package it up, then run it again on any other machine. Furthermore, everything that runs in that environment is isolated from the underlying host (much like a virtual machine). And best of all, everything is fast and simple."
| # Copyright 2012 Erlware, LLC. All Rights Reserved. | |
| # | |
| # This file is provided to you under the Apache License, | |
| # Version 2.0 (the "License"); you may not use this file | |
| # except in compliance with the License. You may obtain | |
| # a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, |
| #!/bin/bash | |
| sudo apt-get update | |
| sudo apt-get -y install linux-image-extra-$(uname -r) | |
| sudo sh -c "wget -qO- https://get.docker.io/gpg | apt-key add -" | |
| sudo sh -c "echo deb http://get.docker.io/ubuntu docker main\ > /etc/apt/sources.list.d/docker.list" | |
| sudo apt-get update | |
| sudo apt-get -y install lxc-docker |
This is a collection of information on PostgreSQL and PostGIS for what I tend to use most often.
The PostgreSQL native FDW (foreign data wrapper), postgres_fdw allows you to access tables from remote PostgreSQL servers very transparently, even doing thoughtful things like pushing restrictions to the remote server to reduce the amount of data transferred and ensure work is done close to the data.
Out of the box, the standard PostgreSQL FDW also allows PostGIS geometry to transit from remote to local hosts, which is pretty cool.
However, it will not push spatial restrictions from the local host to the remote host, only restrictions that relate to built-in types. I've done a rough and ready patch to the 9.4 branch to allow spatial restrictions to pass over FDW, and it is available here:
| #!/usr/bin/env bash | |
| set -e | |
| # Installation script for Cuda and drivers on Ubuntu 14.04, by Roelof Pieters (@graphific) | |
| # BSD License | |
| if [ "$(whoami)" == "root" ]; then | |
| echo "running as root, please run as user you want to have stuff installed as" | |
| exit 1 | |
| fi |
| #!/usr/bin/env bash | |
| set -e | |
| # Test script for checking if Cuda and Drivers correctly installed on Ubuntu 14.04, by Roelof Pieters (@graphific) | |
| # BSD License | |
| if [ "$(whoami)" == "root" ]; then | |
| echo "running as root, please run as user you want to have stuff installed as" | |
| exit 1 |
| #!/usr/bin/env bash | |
| # Installation script for Deep Learning Libraries on Ubuntu 14.04, by Roelof Pieters (@graphific) | |
| # BSD License | |
| orig_executor="$(whoami)" | |
| if [ "$(whoami)" == "root" ]; then | |
| echo "running as root, please run as user you want to have stuff installed as" | |
| exit 1 | |
| fi | |
| ################################### |
| #!/usr/bin/env python | |
| # gpu_stat.py [DELAY [COUNT]] | |
| # dump gpu stats as a line of json | |
| # {"time": 1474168378.146957, "pci_tx": 146000, "pci_rx": 1508000, | |
| # "gpu_util": 42, "mem_util": 24, "mem_used": 11710, | |
| # "temp": 76, "fan_speed": 44 } |
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.