GPU-accelerated differentiable graph layout engine built on PyTorch
Project description
dagua
GPU-accelerated differentiable graph layout engine built on PyTorch.
DAG + agua. Directed acyclic graphs + water. Named after the Dagua River in Colombia — a river flows downhill (like a DAG), never cycles back (acyclic), and finds its own path through the landscape (like gradient descent finding optimal node positions).
Why?
Graphviz has dominated graph visualization for 30 years but has hard scaling limits. No existing Python package provides pip-installable, hierarchical (Sugiyama-style) graph layout. Dagua fills this gap: pip install dagua, pure Python + PyTorch, GPU-accelerated, hierarchical layout with composable constraints.
Status
Pre-alpha. Under active development.
License
MIT
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