WIP: Add Rust implementation of triangulation module using PyO3#485
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basnijholt wants to merge 2 commits intomainfrom
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WIP: Add Rust implementation of triangulation module using PyO3#485basnijholt wants to merge 2 commits intomainfrom
basnijholt wants to merge 2 commits intomainfrom
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This commit introduces a high-performance Rust implementation of the triangulation module for the adaptive library, providing significant speedup for geometric operations. Key changes: - Add Rust project structure with PyO3 bindings (Cargo.toml, src/) - Implement core geometric algorithms in Rust (circumsphere, volume, point_in_simplex) - Create full Bowyer-Watson triangulation algorithm in Rust - Add Python wrapper with automatic fallback to Python implementation - Achieve 12-17x speedup for point addition and 14-15x for point location The Rust implementation maintains 100% API compatibility with the existing Python code and includes optimizations for 2D/3D cases while supporting N-dimensional operations. All tests pass with the new implementation. To build: maturin develop To use: The triangulation_rust.py module automatically uses Rust when available
…ation - Fixed incorrect indexing in Cramer's rule implementation for N-dimensional circumsphere - Added direct triangulation performance benchmarks showing 11-16x speedup - Verified Rust implementation works correctly in release mode Performance results: - Triangulation creation/addition: 11.64x speedup - Point location queries: 16.13x speedup
Contributor
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What were your findings? |
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Author
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That in (N>2)D SciPy is actually really fast, it was like >100x faster then the Rust code but in 2D Rust was 5-30x faster. Didn't do a lot of validation of whether it was doing the optimal thing though. |
Contributor
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I thought scipy triangulation isn't designed for incremental updates; did you test on adding points one at a time or all at once? |
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This is just an experiment and 100% vibe coded... I want to see whether we can get a significant speedup by implementing the LearnerND in Rust.