@article{oai:ipsj.ixsq.nii.ac.jp:00231141,
 author = {Yingqi, Zhao and Takeshi, Fukaya and Takeshi, Iwashita and Yingqi, Zhao and Takeshi, Fukaya and Takeshi, Iwashita},
 issue = {2},
 journal = {情報処理学会論文誌コンピューティングシステム（ACS）},
 month = {Nov},
 note = {Mixed precision numerical methods using low precision computing have attracted much attention under recent computational hardware trends. In this research, we focus on solving large, sparse, and non-symmetric linear systems, and consider developing a numerical method based on a mixed precision variant of the iterative refinement scheme (MP-IR), in which we can exploit low precision computing and provide a computed solution with the same accuracy as that obtained by conventional methods without low precision computing. We employ the BiCGSTAB solver with FP32 as an inner solver of MP-IR and investigate its numerical behavior through numerical experiments. From the analyses on the obtained results including a comparison with MP-IR using GMRES(m), which is also known as MP-GMRES(m) and has been widely studied, the potential of MP-IR using BiCGSTAB has been confirmed. Together with other obtained results, this paper provides insights that are helpful in developing an efficient mixed precision linear solver for practical applications.
------------------------------
This is a preprint of an article intended for publication Journal of
Information Processing(JIP). This preprint should not be cited. This
article should be cited as: Journal of Information Processing Vol.31(2023) (online)
------------------------------, Mixed precision numerical methods using low precision computing have attracted much attention under recent computational hardware trends. In this research, we focus on solving large, sparse, and non-symmetric linear systems, and consider developing a numerical method based on a mixed precision variant of the iterative refinement scheme (MP-IR), in which we can exploit low precision computing and provide a computed solution with the same accuracy as that obtained by conventional methods without low precision computing. We employ the BiCGSTAB solver with FP32 as an inner solver of MP-IR and investigate its numerical behavior through numerical experiments. From the analyses on the obtained results including a comparison with MP-IR using GMRES(m), which is also known as MP-GMRES(m) and has been widely studied, the potential of MP-IR using BiCGSTAB has been confirmed. Together with other obtained results, this paper provides insights that are helpful in developing an efficient mixed precision linear solver for practical applications.
------------------------------
This is a preprint of an article intended for publication Journal of
Information Processing(JIP). This preprint should not be cited. This
article should be cited as: Journal of Information Processing Vol.31(2023) (online)
------------------------------},
 title = {Numerical Behavior of Mixed Precision Iterative Refinement Using the BiCGSTAB Method},
 volume = {16},
 year = {2023}
}