################################### Accessing Amazon Web Services (AWS) ################################### To run the interactive activities for this JEDI Academy, each padawan will be granted the use of a dedicated virtual computer in the Amazon cloud. Specifically, we will launch an EC2 (Elastic Compute Cloud) instance through Amazon Web Services (`AWS `_) for each participant in the Academy. And, this is where you will be running JEDI. Throughout the documentation, we will refer to this as your AWS instance, or equivalently, your AWS node. This document explains how to access your AWS node throughout the duration of the Academy. Feel free to return to it each day when is time to engage in each activity. Some users may be tempted to run the activities on their own laptop or workstation or on an HPC platform if they have access to `JEDI Environment modules `_. However, we discourage this. The use of AWS instances and Singularity containers allows us to provide a uniform computing environment for all so that we can focus on learning the JEDI code without the distraction of platform-related debugging. So, please use your AWS node to do all the academy activities. The only exception is Friday afternoon, when instructors (JEDI masters) will be available to provide guidance on how you can run JEDI on the platform of your choice. So, to participate in the activities, you will need two things: 1. The ip address of your AWS node 2. A password to allow you to log into it See the table below for the first item. The password will be provided during the first activity on Monday (:doc:`Getting Started `). **Write them down**: these will not change over the course of the Academy so you will need them every day. .. note:: **Write down your password. Bookmark your Jupyter URL**. Though you can access your AWS node directly through ``ssh`` if you wish, we have set up a web interface to each of the nodes by means of `JupyterLab `_. We recommend that you use the web interface because this provides a number of attractive features, including the ability to navigate the directory tree, open new terminals, transfer files, and most importantly, to conveniently display graphics. So, to access your AWS node, open a web browser and navigate to this URL: .. code-block:: bash http://:8080 Enter your password at the prompt. You should bookmark this link because, again, it will not change - it will be yours for the entire Academy. Important: The AWS EC2 instances (and their associated JupyterLab URLs) will only be active in the afternoons during the week of the Academy. We will create the instances on Monday so the links below will not work before then. Then, each night of the Academy (Monday-Thursday), we will shut the instances down overnight as a cost-saving measure. However, all data will be saved so you can pick up the next day precisely where you left off. Then, after our last activity on Friday afternoon, we will permanently terminate all instances. .. note:: **If you ever wish to leave your node up longer (for example, one evening to complete a particular activity), just make arrangements with a JEDI Master (Mark).** Now, to log into your cloud computing instance, merely select the appropriate URL from the Table above and enter the password at the prompt. You should now see the default JupyterLab interface, which includes a directory tree displayed as an interactive (i.e. clickable) menu on the left and a large display area. At the top of the display area you should see several tabs. One is labeled ``Console 1``. This is a Jupyter python console, capable of interpreting python commands. Another tab is labeled ``ubuntu`` with a local ip address. This is an ``ssh`` terminal, running bash. From here you have access to the linux command line. This is where we will be doing most of our work. For more tips on how to work with the Jupyter interface, see :doc:`the first activity on Monday `. If you are unable to link to the web interface, you can access the node directly through ssh, as mentioned above. To follow this method, you first need to acquire the ``academy-virginia.pem`` file from a JEDI master which contains an ssh key for authentication. Then you should use the ``-Y`` option to ssh to set up X forwarding as follows (remember that your username is ``ubuntu``): .. code:: ssh -i academy-virginia.pem -Y ubuntu@ Then you can use the linux ``feh`` application to display image files over the internet (this application is available both inside and outside the Singularity container). Or, you can ``scp`` the files to your local machine (using the same ``pem`` file for authentication) and view them locally. AWS node assignments -------------------- ========== =============== ======================= First Name Last Name AWS Node ip address ========== =============== ======================= Jeff Beck 18.212.43.54 Jamie Bresch 18.213.5.3 Natalia Buzulukova 18.235.216.118 Benjamin Cash 23.22.99.195 Ligang Chen 3.210.25.216 Shu-Hua Chen 3.211.239.57 Jing Cheng 3.215.250.158 Guoqing Ge 3.226.35.84 Tseganeh Gichamo 3.234.59.8 Rick Grubin 34.195.127.111 Craig Hartsough 34.196.154.112 Matthew Hei 34.197.60.200 Ivette Hernandez Banos 34.200.34.9 Christina Holt 34.225.202.34 Feng Hsiao 34.230.212.39 Chu-Chun Huang 34.232.125.181 Eric James 34.234.26.113 Michael Kavulich 34.235.65.82 Aditya Kumar 52.20.41.214 Agnes Lim 52.201.91.85 Liaofan Lin 52.201.98.60 Isaac Moradi 52.203.223.48 Jiongming Pang 52.22.122.188 Jun Park 52.72.6.48 Zhaoxia Pu 52.87.131.140 Zilong Qin 54.161.211.30 Giovanni Ruggiero 54.162.197.7 Craig Schwartz 54.163.246.75 Robina Shaheen 54.165.60.21 Greg Thompson 54.166.190.221 Mingjing Tong 54.208.156.171 Peter Jan van Leeuwen 54.225.161.106 Chuan-Kai Wang 54.227.160.240 Chunhua Zhou 54.237.155.226 Fabio Diniz 54.242.241.227 ========== =============== ======================= ... Contact Mark Miesch (miesch@ucar.edu) if you have any problems or questions.