PETScML: Second-order solvers for training regression problems in Scientific Machine Learning

no code implementations • 18 Mar 2024 • Stefano Zampini, Umberto Zerbinati, George Turkiyyah, David Keyes

In recent years, we have witnessed the emergence of scientific machine learning as a data-driven tool for the analysis, by means of deep-learning techniques, of data produced by computational science and engineering applications.

regression

The PetscSF Scalable Communication Layer

no code implementations • 25 Feb 2021 • Junchao Zhang, Jed Brown, Satish Balay, Jacob Faibussowitsch, Matthew Knepley, Oana Marin, Richard Tran Mills, Todd Munson, Barry F. Smith, Stefano Zampini

PetscSF, the communication component of the Portable, Extensible Toolkit for Scientific Computation (PETSc), is designed to provide PETSc's communication infrastructure suitable for exascale computers that utilize GPUs and other accelerators.

Distributed, Parallel, and Cluster Computing 65F10, 65F50, 68N99, 68W10 G.4; C.2