Description
Provides benchmark-driven backend libraries for general matrix-matrix multiplication, commonly used in GPU and high-performance numerical computing workflows. It helps software choose optimized kernels for linear algebra workloads.
Developers and researchers use it as a performance library, usually through higher-level compute stacks. Results depend on hardware, drivers, generated kernels, and benchmark configuration, so validate performance and numerical behavior on target systems.