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Kempner Institute HPC Handbook
1. Getting Started
1.1. Introduction and Cluster Basics
1.2. Overview of Kempner Institute HPC Cluster
1.3. Kempner Policies for Responsible Use of the Cluster
1.4. Accessing and Navigating the Cluster
2. Resource Management
2.1. Understanding SLURM
2.2. Job Submission Basics
2.3. Open OnDemand
2.4. Array Jobs
2.5. Job Dependencies
2.6. Advanced SLURM Features
3. Dev and Runtime Environments
3.1. Software Module and Environment Management
3.2. Containerization
3.3. Using VSCode for Remote Development
3.4. Using Conda Environment
3.5. Handling Dependencies with Spack
3.6. Customizing Shell Configuration File
4. Scalability
4.1. Parallel Computing
4.2. Distributed Computing
4.3. Parallel I/O
4.4. GPU Computing
4.5. Using Multiple GPUs
5. Storage and Data Transfer
5.1. Understanding Storage Options
5.2. Data Transfer
5.3. Shared Data Repository
6. Performance Monitoring
6.1. Introduction to Performance Monitoring
6.2. Monitoring Tools
6.3. Performance Analysis Techniques
6.4. Benchmarking Your Application
6.5. Optimizing I/O Performance
6.6. Parallel Performance Tuning
6.7. Advanced Monitoring and Tuning Tools
7. Advanced Topics
7.1. GPU Architecture and Interconnect
7.2. GPU Libraries and Frameworks
8. Efficient Use of Resources
8.1. Best Practices for HPC Efficiency
8.2. Fair Use and Prioritization Policies
9. HPC Application Scenarios
10. Workshops and Trainings
10.1. Intro to HPC
11. Support and Troubleshooting
11.1. FAQ
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Best Practices for HPC Efficiency
8.1.
Best Practices for HPC Efficiency
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[Tips and techniques for efficient use of HPC resources.]
