NumKong: Mixed Precision for All by ashvardanian

Portable mixed-precision math, linear-algebra, & retrieval library with 2'000+ SIMD kernels for x86, Arm, RISC-V, LoongArch, Power, & WebAssembly, leveraging rare algebraic transforms with both 1D & 2D registers like AMX & SME, covering 15+ numeric types from 4-bit integers & 6-bit floats to 128-bit complex numbers, validated against 118-bit extended-precision baselines with saturation, casting, & rounding edge-case coverage, in a 5-100x smaller binary than other BLAS-like alternatives, co-designed with Tensor abstractions in C++, Python, Rust, JavaScript, GoLang, & Swift. Latency, Throughput, & Numerical Stability

Most libraries return dot products in the same type as the input, Float16 × Float16 → Float16, Int8 × Int8 → Int8. This leads to quiet overflow: a 2048-dimensional dot product can reach ±10 million, but maxes out at 127. NumKong promotes to wider accumulators, Float16 → Float32, BFloat16 → Float32, Int8 → Int32, Float32 → Float64, so results stay in range.