(Interactive – for a tutorial on running Octave in batch mode click here)
Getting started with Octave in Galileo
Let’s have a look at our files
The downloaded file consists of a .ipynb file and a .csv file. The octave_example notebook conducts a simple linear regression using the supplied mtcars.csv dataset and makes a simple plot. It also demonstrates how to use a dataset loaded from an online source.
Next, the notebook conducts a Monte Carlo experiment that simulates 50,000 throws of two six-sided dice to calculate the probability that the sum of one throw of two dice is greater than or equal to seven. It then repeats the same experiment 10 million times. Finally it compares the means of the two samples and the amount of time it took to calculate them.
Understanding the user interface
When you log into Galileo, the first thing you’ll see is your Dashboard:
To run the Octave notebook, start by navigating to the Missions tab using the side menu. On the Missions tab, click the Create a custom mission button.
Configure the mission by selecting the mission type. Choose Octave and then select the version. This tutorial will use Interactive (Jupyter).
Next, give the mission a name and assign it to a default station to use. This tutorial will use the Linux station. Click Next.
Set the default amount of computational resources for the mission. Choose the CPU resources, GPU resources, and memory resources. Click Next.
Create the mission environment by choosing a password to access the Jupyter session. You can install any dependencies either by selecting them from the drop-down menu of popular repositories or by entering the packages’ names manually. Click Next.
Finally, select the Cargo Bay you will use for this Mission. You can choose from the default Hypernet storage or an external storage provider. Galileo works seamlessly with cloud storage platforms such as Dropbox and Storj. Find out more about using these platforms here. Click Submit.
The Mission has now been created!
Running a job and collecting results
You will now see the new Mission reflected in the Mission tab. Click Update Mission to add and edit the Mission’s files.
Upload the .ipynb and .csv example files by clicking the Upload File button. You will see the files in the Mission interface.
It is possible to edit text files directly in the Mission tab by using the Mission text editor. Find out more about the editor by clicking here to visit the Galileo forum.
Now we are ready to run a job using the Mission. Click the Run button in the upper right corner of the Mission tab. You will see a “Mission run successfully!” message. At the bottom of the Mission tab, you can track the progress of the job.
Once the job’s status is “Job In Progress”, you are ready to open Jupyter. Click Job In Progress and then click the tunnel URL.
Enter the Mission password you set previously. Click Log in.
You are now using Jupyter in Galileo and you have immediate access to the files you uploaded as part of the Mission.
Once you have finished working in Jupyter, navigate back to the Mission tab and open the three-dot menu in the Jobs progress panel. Stop the job by clicking Stop Job.
The job will shut down and collect the results. Once the job progress reads “Completed”, you can download any files generated by the Juypter job by opening the three-dot menu again and clicking Download.