What do we have so far? That’s an instance running inside the server and our ability to remotely control the instance by using ssh tool. It’s time do something more fascinating on that instance, we’re going to make it become a web server to provide a blog service. Let do our first move by ssh to that instance, and make sure that the following commands are executed on the instance.
$sudo apt-get install lamp-server^：lamp here stands for (Linux, Apache, MySQL, PHP), the password of root is set to wp-admin. Never forget the ^ character of the command. If everything is ok, you will see something like this:
We begin the second part with starting an instance. Firstly, let download an image from the internet with the command:
Then upload it to glance:
$glance add name=”Ubuntu 12.04 cloudimg amd64″ is_public=true container_format=ovf disk_format=qcow2 < precise-server-cloudimg-amd64-disk1.img
We also can find it on the dashboard web interface: Read more…
This entry looks through the installation guide posted on the official website of Openstack for the current version Essex, which you can find out here. The following configurations are almost the same with the guided ones, so you can refer to them for more details. What needs to be highlighted here is slight changes are also made to throw errors away deal to inadequate considerations of the Openstack guide. Here we go!
Step 1: install ubuntu 12.04 with the user name as localadmin and Openssh-server selected during the installation progress. Then run the followings: Read more…
Trang web http://devstack.org/ đã viết sẵn một script để cài openstack, tiết kiệm bao nhiêu công sức cho các bạn mới làm quen. Chỉ cần 2 lệnh sau là bạn đã có thể cài tất cả các thành phần của openstack, trừ Swift, lên trên cùng một server, bao gồm luôn cả Dashboard (Horizon). Script này được giới thiệu là chạy tốt trên Ubuntu Oneiric (11.10), Precise (12.04) or Fedora 16. Và thực tế nhóm tôi đã thử cài thành công trên Ubuntu Precise.
git clone https://github.com/openstack-dev/devstack.git cd devstack && ./stack.sh
With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for CUDA, including image and video processing, computational biology and chemistry, fluid dynamics simulation, CT image reconstruction, seismic analysis, ray tracing, and much more. 
To run CUDA program, you need to make sure that an Nvidia GPU has been attached to your computer. It’s GeForce 9800 GTX+ in my case. The CUDA Toolkit, which can be found here, should also be installed (all CUDA Toolkit, developer driver and GPU Computing SDK). Read more…