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.
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.
HOPSPACK solves derivative-free optimization problems in a C++ software framework. The framework enables parallel operation using MPI (for distributed machine architectures) and multithreading (for single machines with multiple processors or cores). Optimization problems can be very general: functions can be noisy, nonsmooth, and nonconvex, linear and nonlinear constraints are supported, and variables may be continuous or integer-valued.