报告人：邵美悦 教授（复旦大学）

时间：2022年7月11日，14:00-15:00

腾讯会议 ID： 197-427-954

题目：A mixed precision Jacobi SVD algorithm

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.

邀请人：张雷洪