The research group Supercomputation-Algorithms focuses his interest on a set of problems that require intensive computation and that come from different scientific and technological fields, our lines are: (1) Development of High Performance Computing techniques and; (2) its application to the fields of: (a) image processing and tomographic reconstruction; (b) global optimization and (c) multimedia. In HPC area, our goals are: design of new dynamic load balancing approaches focused on heterogeneous or non-dedicated clusters and tuning the sparse matrix-vector product to current parallel architectures. For image processing and tomographic reconstruction, our lines are: Improvement of the algorithms for noise reduction and the methodologies for 3D tomographic reconstruction; development of a new algorithm for segmentation embedded in our noise reduction method; parallelization of 3D reconstruction methods for computer clusters and supercomputers. In global optimization the problems to be tackled are: the study of the effectiveness and efficiency of meta-heuristic methods; development of techniques for the reduction of the complexity and the search space in Branch and Bound algorithms; the design of efficient high performance metaheuristic algorithms to solve engineering, and industrial problems. In multimedia our research is intended to improve the characteristic of a fully scalable video compression system into P2P multicast networks and mobile environments.