![]() Now paste the URL from before into your local browser, but change the IP address (130.74.110.5) to localhost: Windows users will need to setup SSH forwarding via PuTTY. Ssh -N -L 8888:catalpa:8888 and Linux users have SSH installed by default. This is the port number that Jupyter Notebook is listening on.įrom your local system, run the below, changing both instances of the port number if needed, and substituting your username: Generally, it will be 8888, but it could vary. But it’s not, so you need to do a couple of extra steps. If Catalpa were directly on the Internet, you would be able to copy and paste this URL into your browser and start computing. This will produce several lines of output, including one that looks like this: If you need to load a specific Anaconda environment, do it after loading the Python module, but before starting jupyter-notebook. Next, load the python module and start jupyter-notebook: However, realize that if you walk off and leave Jupyter Notebook running, it is keeping other users from using the system. If you need it to run longer than 8 hours, modify this parameter. This is to ensure that you don’t accidentally leave your Jupyter Notebook session running when it’s not in use. The walltime parameter means that your PBS session will be automatically killed after 8 hours. Modify the command above if you need more resources, but don’t request more than 1 CPU unless you know what you’re doing. Then, start an interactive PBS session similar to below: To start Jupyter Notebook, login to Catalpa via hpcwoods. First Timeįirst, send an email to requesting permission to use Jupyter Notebooks. However, we realize some of you will want to use Jupyter Notebooks despite our warnings, so below are instructions on how to do so.Ĭatalpa is the only system that we support running Jupyter Notebook on. We suggest you use Jupyter Notebook on your own system during the development stage, then, once you’re ready to run it on large datasets, convert it to straight Python and run it on the supercomputers in the traditional manner. In short, it wastes resources that could be used by other users. Supercomputers are setup to process jobs in a batch fashion, while Jupyter Notebook is designed to be interactive. I’m using them to provide temporary access to my workshop server but I’m not using it in the production environment or for important tasks.We discourage the use of Jupyter Notebook on the supercomputers. Security notice: the changes to the configuration file allows everyone to access your Jupyter Notebook server. Once the changes are made, you can save the file and run your Jupyter Notebook server. The same situation here – I changed the value but also removed the comment. The second is related to the IP address the notebook server will listen on: # an old line: Please note that I not only placed ‘*’ at the end of the line but also removed the comment (#) at the beginning. These lines are is related to the origin of the request: # an old line: Once the config is generated, you have to adjust two lines in the config file. First, you have to create the configuration file: $ jupyter notebook -generate-config If you want to allow various users to access your Jupyter Notebook, you can change the configuration. By creating a tunnel between your computer and remote host, you will be able to access Jupyter Notebook as it was locally. ![]() ![]() By default, Jupyter Notebook starts on port 8888 and accepts only requests from the localhost. I wrote about this in more detail in the article about AutoSSH tunneling. If you want to access your remote Jupyter Notebook alone, the easiest way is to create the SSH tunnel between your computer and the remote machine. On the other hand, sometimes it is handy to be able to connect remotely. ![]() This is a good policy – in general, we don’t want someone from the Internet to access our machine and steal our notebooks or our CPU power. This is due to the default policy: allow only local connections. ![]() This is common when I want to leverage the possibilities of cloud computing – purchase a powerful machine and use it only for an hour or two.Īs you probably noticed, when trying to connect to the Jupyter Notebook located on the remote computer, you are getting Connection Refused. The second use case is when I install Jupyter Notebook on the remote machine and I want to use it on my own. I know that there are solutions such as Jupyter Hub, but this is too big for my needs. I simply want to run Jupyter Notebook on my machine and give them access to it. I don’t want attendants to install Anaconda and use Jupyter Notebooks on their computers. I’m just about to host the small Machine Learning workshop. ![]()
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