Introduction
Welcome to TensorRigs documentation. Complete guides for setting up deep learning workstations, optimizing GPU performance, troubleshooting CUDA, and working with HPC clusters.
Welcome to TensorRigs Documentation
This documentation provides comprehensive guides and troubleshooting resources for deep learning practitioners, covering HPC (High Performance Computing) environments, GPU optimization, and common software challenges you may encounter when building and running deep learning workloads.
What You’ll Find Here
Whether you’re setting up your first deep learning rig, debugging GPU errors, or optimizing your training pipeline, these docs will help you navigate common issues and best practices for:
- Deep Learning Environments - Conda, virtual environments, and dependency management
- GPU Troubleshooting - Common CUDA errors, memory issues, and performance optimization
- HPC Resources - Working with cluster environments and batch systems
- Training Optimization - Batch size selection, data loading, and performance tuning
- Useful Scripts - Ready-to-use scripts for common tasks
Who This is For
This documentation is designed for anyone working with deep learning systems, whether you’re a researcher, student, or professional building ML/AI applications. The guides focus on practical solutions to real-world problems encountered during deep learning workflows.
Ready to get started? Check out the guides in the sidebar or use the search function to find specific topics.