@article {,
	title = {A survey of numerical linear algebra methods utilizing mixed-precision arithmetic},
	journal = {The International Journal of High Performance Computing Applications},
	volume = {35},
	number = {4},
	year = {2021},
	pages = {344{\textendash}369},
	abstract = {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.},
	keywords = {GPUs, High-performance computing, linear algebra, Mixed-precision arithmetic, numerical mathematics},
	doi = {10.1177/10943420211003313},
	author = {Abdelfattah, Ahmad and Anzt, Hartwig and Boman, Erik G and Carson, Erin and Cojean, Terry and Jack Dongarra and Fox, Alyson and Mark Gates and Higham, Nicholas J and Li, Xiaoye S and others}
}
