Elemental is a C++ framework for distributed-memory dense linear algebra that strives to be fast, portable, and programmable. It can be thought of as a generalization of PLAPACK to element-by-element distributions that also makes use of recent algorithmic advances from the FLAME project. Elemental usually outperforms both PLAPACK and ScaLAPACK, however, it heavily relies on MPI collectives so a good MPI implementation is crucial. Both pure MPI and hybrid OpenMP-MPI configurations are supported.

OpenMPF is a library for solving large, dense, multi-RHS linear systems. It is based on MPI/openMP parallelism, and relies on BLAS/LAPACK/MUMPS for the single node computations. It implements direct and iterative solvers, out-of-core matrices and vectors, and is easily accessible through a Python interface.

Topologic is a simple renderer for certain higher-dimensional geometric primitives and some regular 3D shapes. The idea is to make it easy for students of certain higher-dimensional maths and physics topics to visualize the typical primitives in those fields and get a grasp for the topic.

jMathLab is a platform for mathematical and numerical computations. It uses the Matlab/Octave programming language. It runs on any platform where Java is installed, and can also run on the Web browser. The following packages are included: symbolic calculations (simplification, differentials, integration), numeric calculations, evaluations of mathematical functions, special functions, linear algebra with vectors and matrices, plotting data and functions, saving data (vectors and matrices) in files, random numbers, statistics, and solving linear and non-linear equations

librsb is a library for sparse matrix computations featuring the Recursive Sparse Blocks (RSB) matrix format. This format allows cache-efficient and multithreaded (that is, shared memory parallel) operations on large sparse matrices. The most common operations necessary to iterative solvers are available (matrix-vector multiplication, triangular solution, rows/columns scaling, diagonal extraction/setting, blocks extraction, norm computation, formats conversion). The RSB format is especially well-suited for symmetric and transposed multiplication variants. On these variants, librsb has been found to be faster than Intel MKL's implementation for CSR. Most numerical kernels code is auto-generated, and the supported numerical types can be chosen by the user at buildtime. librsb implements the Sparse BLAS standard, as specified in the BLAS Forum documents.