ML is Sandia's main multigrid preconditioning package. ML is designed to solve large sparse linear systems of equations arising primarily from elliptic PDE discretizations. ML is used to define and build multigrid solvers and preconditioners, and it contains black-box classes to construct highly-scalable smoothed aggregation preconditioners. ML preconditioners have been used on thousands of processors for a variety of problems, including the incompressible Navier-Stokes equations with heat and mass transfer, linear and nonlinear elasticity equations, the Maxwell equations, semiconductor equations, and more.

The Compute Unified Device Architecture (CUDA) enables NVIDIA graphics processing units (GPUs) to be used for massively parallel general purpose computation.

The CUDA Profiler Tools Interface (CUPTI) enables the creation of profiling and tracing tools that target CUDA applications. CUPTI provides a set of APIs targeted at ISVs creating profilers and other performance optimization tools. The CUPTI APIs are not intended to be used by developers in their CUDA applications.

This package supplies capabilities for nonconforming mesh tying and contact formulations in 2 and 3 dimensions using Mortar methods. Mortar methods are a type of Lagrange Multiplier constraint that can be used in contact formulations and in non-conforming or conforming mesh tying as well as in domain decomposition techniques. Originally introduced as a domain decomposition method for spectral elements, Mortar methods are used in a large class of nonconforming situations such as the surface coupling of different physical models, discretization schemes or non-matching triangulations along interior interfaces of a domain.

LLVM is a collection of libraries and tools that make it easy to build compilers, optimizers, just-in-time code generators, and many other compiler-related programs.

MueLu is designed to solve large sparse linear systems of equations arising from PDE discretizations. MueLu provides easy-to-use multigrid solvers and preconditioners based on smoothed aggregation algorithms. As a multigrid framework, MueLu supports the design of highly application specific multigrid preconditioners.