Description
Scientific and machine-learning software can speed up small matrix multiplications with specialized kernels.
This library is useful for developers working on simulations, numerical computing, deep learning, and high-performance code where many small dense or sparse matrix operations dominate runtime. It does not add a math application by itself; parent programs call it for optimized computation.
Performance depends on CPU features, compiler settings, matrix shapes, and workload. Benchmark on the target hardware before relying on gains.