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Kempner Computing Handbook

High Performance Computing

1. Kempner AI Cluster
2. Job Submission
3. Development Environment
4. Storage and Data Transfer

Software Engineering for Research

5. Collaborative Code Development
6. Software Design Principles
7. Documentation and Readability
8. Testing and Continues Integration
9. Package Development
10. Reproducible Research

AI Tools and Workflows

11. Data Discovery and Tokenization
12. Distributed Inference
13. NVIDIA NeMo Workflow
14. Scalable Vision Workflows
15. Hugging Face Models

Neuro AI Workflows

16. Spike Sorting

AI Scaling and Engineering

17. Scalability
18. Efficiency
19. Experiment Management
- 19.1. Weights & Biases (WandB)

Security and Compliance

20. Security and Compliance

Open Source Hub

21. Open Source Hub

Support

22. Support and Troubleshooting
- 22.1. FAQ

Workshops

23. About Workshops @ Kempner
- 23.2. Introduction to the Kempner AI cluster Workshop
- 23.3. Introduction to Distributed Computing Workshop

Repository
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ML Efficiency

18.1. ML Efficiency#

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18. Efficiency

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18.2. Peformance Monitoring

By Kempner Institute

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