My contributions: design and implement a state-of-the-art high-performance SVD software, PRIMME_SVDS on top of PRIMME for solving large-scale SVD problems. It can be used in a single node or a large cluster, supporting computation of both largest and smallest singular triplets in full accuracy. It provides C, Fortran, Matlab, Octave, Python, and R interfaces to serve a broad class of users.
Free download at: https://github.com/primme/primme. PRIMME library has been widely used in various National Labs in U.S., including Thomas Jefferson National Accelerator Facility, Lawrence Berkeley National Lab, Oak Ridge National Lab, Sandia National Lab and more!
Please cite the following papers if you use or build upon this software:
Lingfei Wu, Eloy Romero, and Andreas Stathopoulos, “PRIMME_SVDS: A High-Performance Preconditioned SVD Solver for Accurate Large-scale Computations”, SIAM J. Sci. Comput. (2017), 39(5), pp. S248–S271. [SIAM SISC, Flagship Journal in Scientific Computing]
Lingfei Wu and Andreas Stathopoulos, “A Preconditioned Hybrid SVD Method for Computing Accurately Singular Triplets of Large Matrices”, SIAM J. Sci. Comput. (2017), 37(5), pp. S365-S388. [SIAM SISC, Flagship Journal in Scientific Computing]