arXiv · 2209.04626
A mixed precision Jacobi SVD algorithm
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.
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Weiguo Gao, Yuxin Ma, Meiyue Shao. 2024-11-11. A mixed precision Jacobi SVD algorithm. https://doi.org/10.1145/3721124
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