redsvd: RandomizED Singular Value Decomposition

From a discussion on the Matrix Factorization Group on LinkedIn, Shankar let us know of redsvd, a RandomizED Singular Value Decomposition solver:

redsvd is a C++ library for solving several matrix decompositions including singular value decomposition (SVD), principal component analysis (PCA), and eigen value decomposition. redsvd can handle very large matrix efficiently, and optimized for a truncated SVD of sparse matrices. For example, redsvd can compute a truncated SVD with top 20 singular values for a 100K x 100K matrix with 1M nonzero entries in less than one second.

The algorithm is based on the randomized algorithm for computing large-scale SVD. Although it uses randomized matrices, the results is very accurate with very high probability.

It is evidently featured in the Matrix Factorization Jungle page.

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