Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Open Machine Learning Compiler Framework
NumPy & SciPy for GPU
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types — from 6-bit floats to 64-bit complex — across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go 📐
Read and write Neuroglancer datasets programmatically.