Randomized flexible GMRES with deflated restarting

Y Jang, L Grigori, E Martin, C Content - Numerical Algorithms, 2024 - Springer
For a high dimensional problem, a randomized Gram-Schmidt (RGS) algorithm is beneficial
in computational costs as well as numerical stability. We apply this dimension reduction …
被引用次数：5 相关文章
[PDF] researchgate.net

[PDF][PDF] Randomized Flexible GMRES with Deflated Restarting

Y Jang, L Grigori, E Martin, C Content - researchgate.net
For high dimensional spaces, a randomized Gram-Schmidt (RGS) algorithm is beneficial in
computational costs as well as numerical stability. We apply this dimension reduction …

Randomized Flexible GMRES with Deflated Restarting

Y Jang, L Grigori, E Martin, C Content - 2023 - cnrs.hal.science
For high dimensional spaces, a randomized Gram-Schmidt (RGS) algorithm is beneficial in
computational costs as well as numerical stability. We apply this dimension reduction …

Randomized Flexible GMRES with Deflated Restarting

Y Jang, L Grigori, E Martin, C Content - 2023 - inria.hal.science
For high dimensional spaces, a randomized Gram-Schmidt (RGS) algorithm is beneficial in
computational costs as well as numerical stability. We apply this dimension reduction …

Randomized flexible GMRES with deflated restarting

Y Jang, L Grigori, E Martin, C Content - Numerical Algorithms, 2024 - infoscience.epfl.ch
For a high dimensional problem, a randomized Gram-Schmidt (RGS) algorithm is beneficial
in computational costs as well as numerical stability. We apply this dimension reduction …

Randomized Flexible GMRES with Deflated Restarting

Y Jang, L Grigori, E Martin, C Content - 2023 - hal.science
For high dimensional spaces, a randomized Gram-Schmidt (RGS) algorithm is beneficial in
computational costs as well as numerical stability. We apply this dimension reduction …
[PDF] hal.science

[PDF][PDF] Randomized Flexible GMRES with Deflated Restarting

Y Jang, L Grigori, E Martin, C Content - hal.science
For high dimensional spaces, a randomized Gram-Schmidt (RGS) algorithm is beneficial in
computational costs as well as numerical stability. We apply this dimension reduction …