SparTen

SparTen provides capabilities for computing reduced-dimension representations of sparse multidimensional count value data. The software consists of the data decompositions methods described in published journal papers. These decomposition methods consist of several numerical optimization methods (one based on a multiplicative update iterative approach, one based on quasi-Newton optimization, and one based on damped Newton optimization) for fitting the input data to a reduced-dimension model of the data with the lowest amount of error. The software also consists of generalized computation that leverages Kokkos to compute the reduced-data representations on multiple computer architectures, including multicore and GPU systems. 

Software Website

Contact
Dunlavy, Daniel (Danny), dmdunla@sandia.gov