Use Cases for Research Development
Google Colab provides a limited amount of CPU and GPU resources and should be considered a quick and easily accessible solution. Larger research efforts and computational needs should still result in contacting the Research Computing team for available dedicated solutions.
Researchers should consider using the included Google Colab resources if they are running Python 3 or R code, not working with other licensed software, and their computations can:
Run on a single physical core, 2 logal logical cores, or TPU v2-8
Run using less than ~12.5 GB RAM
Run using no more than 15 GB of GPU memory
Complete within the 24 hour free instance limit
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Need more resources? Syracuse University does not provide additional CPUs, GPUs, or storage capacity beyond what is included with the standard g.syr.edu accounts. However, additional CPU and GPU units are available at a cost to the user. |
Getting Started
To log into Google Colab, simply visit https://colab.research.google.com/. Instead of your regular ‘syr.edu' email address, users will log in using their 'g.syr.edu’ account (i.e. <your-netid>@g.syr.edu). Note this account utilizes your currently NetID password. To manage this password, follow the normal https://su-jsm.atlassian.net/wiki/spaces/ITHELP/pages/159940907/NetID#Password-Management .
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Logged into Google with another account? Some users may be logged in with another account. To resolve this, first simply log out and attempt to log in with your ‘g.syr.edu’ account. If your browser does not cooperate, https://su-jsm.atlassian.net/wiki/x/mIWICQ or simply trying another browser may be required. |
Configuring Your Notebook (
forIncluding GPU access)
To open a new or existing notebook, use the ‘File’ dropdown. Here you can open a new notebook in your g.syr.edu Google Drive, open a new notebook, or upload an existing notebook. There is also the ability to save or open notebook from Github.
Once a new or existing notebook is open, you’ll want to configure the settings by going to Edit > Notebook Settings. Here you’ll be able to choose the work environment that best fits your needs using the runtime type for Python 3 or R and ‘Hardware accelerator’ option for CPU, GPU, or TPU. Be sure to hit Save.
Once selected, you’ll need to use the Connect button in the top right if it does not do so automatically.
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Installing Packages? For installing of packages, the Colab environment utilizes pip for Python and install.pacakges() for R. |
Users seeking additional how-to documentation should reference the Welcome to Colab page at https://colab.research.google.com/ .
Getting Help?
Users needing assistance with access, account functionality, browser-related issues, or general inquiries about Google Workspace should first contact the ITS Help Desk.
Users with questions about their research computational activities, including errors, package compatibility, or available resources, should contact researchcomputing@syr.edu.