Numerical Behavior of Mixed Precision Iterative Refinement Using the BiCGSTAB Method
Author:
Affiliation:
1. Graduate School of Information Science and Technology, Hokkaido University
2. Information Initiative Center, Hokkaido University
Publisher
Information Processing Society of Japan
Subject
General Computer Science
Link
https://www.jstage.jst.go.jp/article/ipsjjip/31/0/31_860/_pdf
Reference46 articles.
1. [1] Abdelfattah, A., Anzt, H., Boman, E.G., Carson, E., Cojean, T., Dongarra, J., Fox, A., Gates, M., Higham, N.J., Li, X.S., Loe, J., Luszczek, P., Pranesh, S., Rajamanickam, S., Ribizel, T., Smith, B.F., Swirydowicz, K., Thomas, S., Tomov, S., Tsai, Y.M. and Yang, U.M.: A survey of numerical linear algebra methods utilizing mixed-precision arithmetic, The International Journal of High Performance Computing Applications, Vol.35, No.4, pp.344-369 (2021).
2. [2] Aihara, K.: GPBi-CGstab(L): A Lanczos-type product method unifying Bi-CGstab(L) and GPBi-CG, Numerical Linear Algebra with Applications, Vol.27, No.3, e2298 (2020).
3. [3] Angerer, C.M., Polig, R., Zegarac, D., Giefers, H., Hagleitner, C., Bekas, C. and Curioni, A.: A fast, hybrid, power-efficient high-precision solver for large linear systems based on low-precision hardware, Sustainable Computing: Informatics and Systems, Vol.12, pp.72-82 (2016).
4. [4] Anzt, H., Heuveline, V. and Rocker, B.: An Error Correction Solver for Linear Systems: Evaluation of Mixed Precision Implementations, High Performance Computing for Computational Science - VECPAR 2010, pp.58-70 (2011).
5. [5] Anzt, H., Heuveline, V. and Rocker, B.: Mixed Precision Iterative Refinement Methods for Linear Systems: Convergence Analysis Based on Krylov Subspace Methods, Applied Parallel and Scientific Computing, pp.237-247 (2012).
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