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FASRC AI Facilitation
FASRC Policy and Safety Guidelines for AI Workflows
FASRC allows the use of AI tools on the Cannon and FASSE FASRC clusters. Our users are free to install AI tools they need to execute their AI-based workflow under their cluster profile and provide it with data. However, we urge our users to be aware of the guidelines that the University has put forward for the use of such tools at Harvard. We do ask that for all HUIT-supported LLMs, our users register apps and access API keys that are under Harvard agreement prior to accessing those LLMs on the cluster.
Additionally, if you are using AI agents for your work, you need to know how to use them responsibly on the cluster without compromising your data security or your user profile on the cluster. The AI Agents on the FASRC Clusters policy page walks you through the main points you need to be aware of in order to use AI agents responsibly on the cluster while maintaining the data integrity and data privacy of your work.
Note: Sometimes Chrome does not work for HUIT websites, especially if you are *not* on the University VPN. In that case, you can access those websites using Firefox.
Best Practices for AI workflows on FASRC Clusters
In order to execute an AI/ML workflow successfully on the cluster, it is important to understand:
- How to safely install and launch a tool/software on the cluster that’s needed for your workflow
- How to request resources for it properly
- What are some of the pitfalls to be mindful of
This section provides a landing area for all the relevant documentation that will help you implement your AI/ML workflow on the cluster correctly. Before executing your AI workflow on the FASRC clusters, make sure to follow the safety guidelines mentioned above, and FASRC guidelines for launching an AI tool such as OpenAI’s ChatGPT.
How to install and utilize AI/ML tools or platforms?
To successfully execute your AI/ML workflow on the cluster, you may need a variety of tools or platforms. The list below captures various tools and platforms that are currently available on FASRC clusters. Based on your needs, you can go through the relevant documentation to get guidance on how to install and execute these tools on the cluster, or utilize these platforms for your work.
* HeavyAI
* Knime
* OpenAI
* PyTorch
* VSCode
* Cursor
How to request resources for AI workflows?
This will typically require you to request GPUs and utilize them efficiently. GPU Computing on FASRC Clusters walks you through:
- The resource allocation process for GPUs for a batch and an interactive job,
- How to load and work with CUDA modules,
- Example codes for GPU computing on the cluster
- How to monitor your job’s performance on a GPU node.
In addition to that, one must be mindful of their job’s efficiency. A detailed description of what it means to run a job efficiently on the cluster is provided on Job Efficiency and Optimization Best Practices.
Lookout For:
In addition to following the best practices mentioned above, one must be aware of some of the pitfalls associated with executing AI workflows on the cluster. For example:
- Are you using an AI tool or an extension via a code editor, such as VSCode or Cursor, on the login node?
- Have you inadvertently given permission to the AI tool to delete files or folders?
- Are you aware of prompt injection attacks while using an LLM-based application?
- What steps have you taken to secure your data against data leakage?
- Are you aware of your data security level?
Training
We regularly hold training sessions to support AI-based workflows on the cluster. Please refer to our Training Calendar for upcoming sessions, and Training Material to access AI/ML computing documentation and presentation slide decks &/or video recordings of our previous training sessions.