From Deadlocks to DDP: My Journey Building a 3-Node PyTorch Cluster
When you are training deep learning models, you inevitably hit a wall where a single GPU just isn’t cutting it anymore. The industry standard for scaling compute across multiple machines is PyTorch’s Distributed Data Parallel (DDP). But reading the documentation is one thing; actually building a distributed network from scratch is a completely different beast. I didn’t want to just rent a cloud cluster. I wanted to understand the absolute lowest-level plumbing of how computers talk to each other to solve math. So, I decided to build a local simulation lab. No fancy Kubernetes, no Slurm workload managers—just pure Debian Virtual Machines, a local network bridge, and a lot of debugging. ...