Learn about the newest developments in high-performance numerical linear algebra for heterogeneous GPU-based systems. A number of novel algorithms and the methodology used for their implementation on multiGPU platforms will be shown. The implementations are open source, available through the MAGMA library ÃÂ¢ÃÂ ÃÂ a next generation of LAPACK for heterogeneous architectures. Included are both linear system and eigenproblem solvers for both dense and sparse computations. The developments incorporate advances made through the CUDA Center of Excellence (CCOE) at University of Tennessee, the CCOE at King Abdullah University of Science and Technology, Saudi Arabia, and at INRIA, France though the StarPU and MORSE projects.