Cluster Computing for $0.27/hr using Amazon EC2 and IPython Notebook
- 3. 1. Launch Spot Instance from Spot Instance Menu
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- 4. 1b. Launch Spot Instance – Ubuntu Server 12.04LTS for
HVM Instances
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- 5. 1c. Launch Spot Instance – Choose cc2.8xl instance
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- 6. 1d. Launch Spot Instance – Set bid price
For max bid, set price that you’re comfortable paying to keep instance running. Cost has
been pretty stable at $0.27/hr for a while
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- 7. 1e. Launch Spot Instance – Set security
I generally open all ports and only allow my IP address as a simplistic security
protocol, since this is a spot instance that I use for a few hours
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- 9. 1g. Launch Spot Instance – Pick .pem keys
If you don’t specify a key pair, you can’t login to the instance!
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- 10. 1g. Launch Spot Instance – Wait for fulfillment
If your spot request is fulfilled, it will take about 5-10 minutes to launch
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- 11. 2. Installing & Configuring Python/IPython Using
Anaconda
FULL INSTRUCTIONS:
HTTP://IPYTHON.ORG/IPYTHON-DOC/DEV/INTERACTIVE/PUBLIC_SERVER.HTML#NOTEBOOK-PUBLIC-SERVER
- 12. 2a. Installing IPython – SSH into EC2 Instance
SSH into EC2 instance, create /temp directory, then download Anaconda (64-bit, Linux).
http://continuum.io/downloads
Run script after downloading to install Anaconda: bash Anaconda-1.8.0-Linux-x86_64.sh
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- 13. 2b. Installing IPython – Generate Password
In IPython REPL, use the IPython.lib passwd() feature to create a password. Copy
password to a text editor for later use.
(No, this is not a real password to use on my EC2 instance!)
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- 14. 2c. Installing IPython – Create nbserver profile
Create an IPython profile called ‘nbserver’, which we will use as our profile to create
the public Notebook server
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- 15. 2d. Installing IPython – Generate SSL certificate
Create a self-signed SSL certificate so that we can use HTTPS on the IPython Notebook
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- 16. 2e. Installing IPython – Modify nbserver profile
Navigate to the profile_nbserver directory, then modify the ipython_notebook_config.py
file with your certificate location and password.
Place these commands at the top of the file; you don’t need to uncomment any of the
lines generated when nbserver profile was created.
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- 17. 2f. Installing IPython – Launch IPython Notebook
Launch IPython Notebook with the nbserver profile. At this point, we can now access
IPython Notebook from our local browser!
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- 19. 3a. Accessing IPython Notebook – SSL Warning
Use any modern browser to access the public DNS of your EC2 image. It is expected to see
a warning, as we’re using a self-signed SSL certificate
Ex: https://ec2-54-205-25-4.compute-1.amazonaws.com:8888
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- 20. 3b. Accessing IPython Notebook – Enter Password
Sign in using password that you set during the prior step (the actual password, not the
SHA1 version)
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- 21. 3c. Accessing IPython Notebook – Success!
At this point, you’ve got a fully functional Python clusterenvironment running on EC2,
which you are accessing from your local browser
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- 22. 3c. Accessing IPython Notebook – Use 32 cores for ML
Running a toy example from Scikit-Learn, we can specify use of 32 cores for the
ExtraTreesClassifier
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