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Efficiently Computing Tensor Eigenvalues on a GPU
2011
2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum
The tensor eigenproblem has many important applications, and both mathematical and application-specific communities have taken recent interest in the properties of tensor eigenpairs as well as methods for computing them. In particular, Kolda and Mayo [3] present a generalization of the matrix power method for symmetric tensors. We focus in this work on efficient implementation of their algorithm, known as the shifted symmetric higher-order power method, and on how a GPU can be used to
doi:10.1109/ipdps.2011.287
dblp:conf/ipps/BallardKP11
fatcat:fx25hkyq7fbuxpbonouy4jrkt4