BLAS-like Library Instantiation Software Framework
High-efficiency floating-point neural network inference operators for mobile, server, and Web
SIMD-accelerated distances, dot products, matrix ops, geospatial & geometric kernels for 16 numeric types β from 6-bit floats to 64-bit complex β across x86, Arm, RISC-V, and WASM, with bindings for Python, Rust, C, C++, Swift, JS, and Go π
Tuned OpenCL BLAS
Library for specialized dense and sparse matrix operations, and deep learning primitives.
Pure Java LP, QP and MIP solvers plus fast linear algebra. Zero dependencies, MIT licensed. Mathematical optimization and linear algebra for the JVM.
Lean formalization work extending the matrix multiplication 9/4 argument to arbitrary fields