Squeezing a Matrix into Half Precision, with an Application to Solving Linear Systems

Motivated by the demand in machine learning, modern computer hardware is increasingly supporting reduced precision floating-point arithmetic, which provides advantages in speed, energy, and memory usage over single and double precision. Given the availability of such hardware, mixed precision algorithms that work in single or double precision but carry out part of a computation in half precision are now of great interest for general scientific...