Machine learning

Mathematical analysis

Linear algebra

Leverage (statistics)

Geometry

Physics

Acceleration

Pure mathematics

Mathematics

Algebra over a field

Computer science

Algorithm

Numerical analysis

Classical mechanics

Numerical linear algebra

The International Journal of High Performance Computing Applications

The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of low-precision special-function units designed for machine learning applications, the traditional numerical algorithms community urgently needs to reconsider the floating point formats used in the distinct operations to efficiently leverage the available compute power. In this work, we provide a comprehensive survey of mixed-precision numerical linear algebra routines, including the underlying concepts, theoretical background, and experimental results for both dense and sparse linear algebra problems.

A survey of numerical linear algebra methods utilizing mixed-precision arithmetic