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Difference between revisions of "How To Connect"
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= Connecting to the Math Systems =
== Math Portal ==
NOTE! Most of what is below has been replaced by the [[Math Portal]]. Use the math portal to connect to the Math department resources without the need for any special software.
== Connecting from outside of the Cornell Network ==
To connect to the Math department network from outside of Cornell, you will need to use the Cornell VPN. In particular, you will need to connect to the Math Department network through the Cornell VPN.
=== Graphical Desktop ===
The [[Math Portal]] is the easiest way to connect to a remote desktop on the Math systems. Some users may prefer to use a dedicated client program if connecting through a browser is not suitable. To connect without a browser you'll need to use the [[Cornell VPN]].
To use a remote desktop on the Math Linux systems, the primary way to do this is to use X2GO. You can download the [https://wiki.x2go.org/doku.php/download:start X2GO client software] here. This software works on Windows, Mac, or Linux. If you are installing the Mac version, you will first want to install the latest version of [https://xquartz.org Xquartz]. For the other platforms, no additional downloads are necessary.▼
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====== <big>Remote Desktop Connection</big> ======
The latest version of the Math software supports Remote Desktop Connection from Windows. There is also and RDC client available for Mac. To use an RDC client directly, you will need to connect through the Cornell VPN.
====== SSH Access ======
You can connect to the Math machines using SSH. This is a text-only method, which some people are very comfortable with. For Linux or Mac, you can ssh into a math system with the built-in SSH client that comes with your machine. Open up a terminal window, and type
where 'mortimer' is replaced with your Math username, and 'fibonacci.math.cornell.edu' can be any one of the Math linux machines.
== Transferring Files ==
You can use the [https://portal.math.cornell.edu/ Math Portal] to transfer files from inside your browser, using JupyterHub, or the WebDisk. You can also use sftp or rsync.
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