Merge pull request #28271 from permcody/CA2024-1659

Improving documentation for acquired software related to CA2024-1659

framework/doc/content/sqa/framework_sll.md

@@ -10,6 +10,11 @@
 > of the library is to provide support for adaptive mesh refinement (AMR) computations in parallel
 > while allowing a research scientist to focus on the physics they are modeling.
 
++Testing:+ libMesh is a core library providing significant functionality for MOOSE and MOOSE-based
+applications. Every Functional test in the [framework RTM](framework_rtm.md) that manipulates a mesh
+or solves a problem is using an integrated piece of the libMesh library. For all practical purposes
+there are almost no differences between the set of tests for the framework and the set of tests for libMesh.
+
 Current Version of libMesh: [!git!submodule-hash url=https://github.com/libmesh/libmesh/commit](libmesh)
 
 ## [!ac](PETSc)
@@ -21,5 +26,80 @@ Current Version of libMesh: [!git!submodule-hash url=https://github.com/libmesh/
 > scalable (parallel) solution of scientific applications modeled by partial differential equations. It
 > supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism. PETSc
 > (sometimes called PETSc/Tao) also contains the Tao optimization software library.
+>
+
++Testing:+ PETSc is a core library providing significant functionality for MOOSE and MOOSE-based
+applications. Every Functional test in the [framework RTM](framework_rtm.md) that
+solves a problem is using an integrated piece of the PETSc library. For all practical purposes
+there are almost no differences between the set of tests for the framework and the set of tests for PETSc.
+
 
 Current Version of [!ac](PETSc): [!git!submodule-hash url=https://github.com/petsc/petsc/commit](petsc)
+
+## HYPRE (optional)
+
+[!ac](MOOSE) can optionally use preconditioners from the HYPRE library to assist with the solvers
+in [!ac](PETSc). The BoomerAMG preconditioner is frequeuntly used in MOOSE for elliptic PDEs.
+This project is summarized as follows on the project website:
+[https://computing.llnl.gov/projects/hypre-scalable-linear-solvers-multigrid-methods](https://computing.llnl.gov/projects/hypre-scalable-linear-solvers-multigrid-methods).
+
+> Livermore’s hypre library of linear solvers makes possible larger, more detailed simulations by solving
+> problems faster than traditional methods at large scales. It offers a comprehensive suite of scalable
+> solvers for large-scale scientific simulation, featuring parallel multigrid methods for both structured
+> and unstructured grid problems. The hypre library is highly portable and supports a number of languages.
+
++Testing:+ [!ac](PETSc) is able to utilize several externally-developed preconditioners in its solution
+scheme. Explicit testing of the Hypre BoomerAMG preconditioner is not done by the MOOSE suite since it
+is an optional dependency and isn't strictly required to solve MOOSE's linear and nonlinear systems.
+However, this preconditioner option does appear in a number of the Functional tests in the
+[framework RTM](framework_rtm.md), such that breaking changes would likely result in differences in many
+of MOOSE's tests.
+
+## SuperLU (optional)
+
+[!ac](MOOSE) can optionally use the SuperLU "solver" package for accelerating the factorization of
+certain types of linear systems. This package is summarized as follows on the project website:
+
+> SuperLU is a general-purpose library for the direct solution of large, sparse, nonsymmetric systems of
+> linear equations. The library is written in C and is callable from either C or Fortran program. It uses
+> MPI, OpenMP and CUDA to support various forms of parallelism. It supports both real and complex datatypes,
+> both single and double precision, and 64-bit integer indexing. The library routines perform an LU
+> decomposition with partial pivoting and triangular system solves through forward and back substitution.
+> The LU factorization routines can handle non-square matrices but the triangular solves are performed only
+> for square matrices.
+
++Testing:+ [!ac](PETSc) is able to utilize the SuperLU package to solve linear system matrices in parallel.
+This acceleration is suitable for certain small-to-moderately-sized linear systems that are not easily
+solved with other schemes. Explicit testing of the SuperLU factorization package is not done by the MOOSE
+suite since it is an optional dependency. However, this solver option does appear in a number of
+Functional tests in the [framework RTM](framework_rtm.md) and module RTMs. Breaking changes
+would likely result in differences in many of these tests.
+
+## MUMPS (optional)
+
+[!ac](MOOSE) can optionally use the MUMPS "solver" package for accelerating the factorization of
+certain types of linear systems. This package is summarized as follows on the project website:
+
+> MUMPS Main Features:
+>
+> - Solution of large linear systems with symmetric positive definite matrices general symmetric matrices general unsymmetric matrices.
+> - Real or complex arithmetic (single or double precision)
+> - Parallel factorization and solve phases (uniprocessor version also available)
+> - Out of core numerical phases
+> - Iterative refinement and backward error analysis
+> - Various matrix input formats assembled, distributed, elemental format
+> - Partial factorization and Schur complement matrix (centralized or 2D block-cyclic) with reduced/condensed right-hand side
+> - Interfaces to MUMPS: Fortran, C, Matlab and Scilab
+> - Several reorderings interfaced: AMD, QAMD, AMF, PORD, METIS, PARMETIS, SCOTCH, PT-SCOTCH
+> - Symmetric indefinite matrices: preprocesssing and 2-by-2 pivots
+> - Parallel analysis and matrix scaling
+> - Computation of the determinant (with an option to discard factors)
+> - Forward elimination during factorization 
+>
+
++Testing:+ [!ac](PETSc) is able to utilize the MUMPS package to solve linear system matrices in parallel.
+This acceleration is suitable for certain small-to-moderately-sized linear systems that are not easily
+solved with other schemes. Explicit testing of the MUMPS factorization package is not done by the MOOSE
+suite since it is an optional dependency. However, this solver option does appear in a number of
+Functional tests in the [framework RTM](framework_rtm.md) and module RTMs. Breaking changes
+would likely result in differences in many of these tests.