A mixed precision Jacobi SVD algorithm
组织者
杜洁
, Computational & Applied Mathematics Group
, 蔚辉
演讲者
Meiyue Shao
时间
2022年01月14日 09:30 至 10:30
地点
中会议室一
摘要
We propose a mixed precision Jacobi algorithm for computing the singular value decomposition (SVD) of a dense matrix. After appropriate preconditioning, the proposed algorithm computes the SVD in a lower precision as an initial guess, and then performs one-sided Jacobi rotations in the working precision as iterative refinement. By carefully transforming a lower precision solution to a higher precision one, our algorithm achieves about 2x speedup on the x86 architecture compared to the usual one-sided Jacobi SVD algorithm in LAPACK, without sacrificing the accuracy.