[P] I got tired of PyTorch Geometric OOMing my laptop, so I wrote a C++ zero-copy graph engine to bypass RAM entirely.

If you train Graph Neural Networks on large datasets (like Papers100M), you already know the pain: trying to load the edge list and feature matrix usually results in an instant 24GB+ OOM allocation crash before the GPU even gets to do any work. I just open-sourced GraphZero v0.2, a custom C++ data engine I built to fix this by bypassing system RAM entirely. How it works: Standard libraries try to load everything into memory. GraphZero instead compiles your raw CSVs into two highly optimized binary formats (.gl for topology,.gd for features.