Batched computation of the singular value decompositions of order two by the AVX-512 vectorization
Vedran Novaković
Abstract:In this paper a vectorized algorithm for simultaneously computing up to eight singular value decompositions (SVDs, each of the form A = U ΣV * ) of real or complex matrices of order two is proposed. The algorithm extends to a batch of matrices of an arbitrary length n, that arises, for example, in the annihilation part of the parallel Kogbetliantz algorithm for the SVD of a square matrix of order 2n. The SVD algorithm for a single matrix of order two is derived first. It scales, in most instances error-free, t… Show more
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