Work

A Mixed Precision Jacobi SVD Algorithm

Year: 2025

Type: article

Abstract: 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 \(2\times\) speedup on the x86-64 architecture compared to the usual one-sided Jacobi SVD algorithm in LAPACK, without sacrificing the accuracy.

Source: ACM Transactions on Mathematical Software

DOI: 10.1145/3721124

Authors: Weiguo Gao, Yuxin Ma, Meiyue Shao

Institutions: Fudan University, Charles University

Language: English

Topic: Matrix Theory and Algorithms

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Key Research and Development Program of China

Awards: G514708732, G8836136279