Supercomputing Co-Design for Solving Ill-Posed Linear Inverse Problems Using Iterative Algorithms - Antonov, Alexander S.; Voevodin, Vladimir V.; Lukyanenko, Dmitry V. (Supercomputing Frontiers and Innovations, 2026)
The paper considers an approach to applying the ideas of supercomputing co-design for the effective use of arbitrary multiprocessor computing systems with distributed memory when using iterative regularization algorithms to solve ill-posed linear inverse problems, which are reduced to solving large overdetermined systems of linear algebraic equations with a dense matrix. The proposed methodology allows for a large number of algorithms to select the best virtual topology of processes (in terms of parallelization efficiency) for solving problems of the class under consideration within the allocated resources of the supercomputer system being used.