Abstract: An approach for generating synthetic treebanks to be used in training a parser in a production system is provided. A processor receives a request to generate one or more synthetic treebanks from a production system, wherein the request indicates a language for the one or more synthetic treebanks. A processor retrieves at least one corpus of text in which the requested language is present. A processor provides the at least one corpus to a transformer enhanced parser neural network model. A processor generates at least one synthetic treebank associated with a string of text from the at least one corpus of text in which the requested language is present. A processor sends the at least one synthetic treebank to the production system, wherein the production system trains a parser utilized by the production system with the at least one synthetic treebank.

Abstract: One or more computer processors responsive to neural network run-time, reduce one or more sets of maximum activations along a hidden dimension respectively associated with one or more activation tensors and one or more layers of a neural network. The one or more computer processors compute an interquartile range (IQR) clip threshold for each reduced set for each sequence dimension in the neural network. The one or more computer processors clip one or more activations based on respective computed IQR clip thresholds. The one or more computer processors quantize the clipped activations.

Abstract: An approach for generating synthetic treebanks to be used in training a parser in a production system is provided. A processor receives a request to generate one or more synthetic treebanks from a production system, wherein the request indicates a language for the one or more synthetic treebanks. A processor retrieves at least one corpus of text in which the requested language is present. A processor provides the at least one corpus to a transformer enhanced parser neural network model. A processor generates at least one synthetic treebank associated with a string of text from the at least one corpus of text in which the requested language is present. A processor sends the at least one synthetic treebank to the production system, wherein the production system trains a parser utilized by the production system with the at least one synthetic treebank.

Abstract: Herein provided are methods and systems for generating finite element modelling results. Finite element method (FEM) data relating to establish a FEM problem to be solved for a portion of a physical system being analyzed is received. A FEM mesh comprising at least FEM mesh node locations relating to the portion of the physical system is generated. FEM mesh values for each FEM mesh node location are automatically generated with a microprocessor. A factor graph model comprising a plurality of random variable nodes and a plurality of factor nodes is automatically generated with a microprocessor based upon the FEM mesh node locations. A set of belief propagation update rules are automatically executed upon the factor graph model using Gaussian function parametrization and the FEM mesh values. The belief propagation update rules are iteratively executed until a predetermined condition has been met.

Abstract: The computational efficiency of Finite Element Methods (FEM) on parallel architectures is typically severely limited by sparse iterative solvers. Standard iterative solvers are based on sequential steps of global algebraic operations, which limit their parallel efficiency, and prior art techniques exploit sophisticated programming techniques tailored to specific CPU architectures to improve performance. The inventors present a FEM Multigrid Gaussian Belief Propagation (FMGaBP) technique that eliminates global algebraic operations and sparse data-structures based upon reformulating the variational FEM into a probabilistic inference problem based upon graphical models. Further, the inventors present new formulations for FMGaBP, which further enhance its computation and communication complexities where the parallel features of FMGaBP are leveraged to multicore architectures.