Victor Paludetto Magri

Victor A. P. Magri is a computational mathematician in the Center for Applied Scientific Computing (CASC) at Lawrence Livermore National Laboratory (LLNL). He contributes to the following software projects:

• hypre: A library of high-performance solvers and preconditioners for large, sparse linear systems. His work spans hypre’s three conceptual interfaces (structured, semi-structured, and IJ), with a primary focus on the SSAMG, FSAI, MGR, and BoomerAMG algorithms.
• hypredrive: A flexible framework for solving large, sparse linear systems with hypre. It provides a standalone command-line driver and interfaces for C, C++, Fortran, Julia, Python, and MATLAB/Octave, with YAML-based configuration for solver and preconditioner options.    
• GEOS: A performance-portable multiphysics simulation framework for subsurface processes, including geological carbon storage. He develops hypre-based linear solver support, focusing on multigrid reduction (MGR) and BoomerAMG to improve solver efficiency, robustness, and scalability for coupled subsurface simulations.
• Vertex-CFD: A multiphysics computational fluid dynamics code for modeling complex flow problems. He develops efficient, scalable linear solvers for magnetohydrodynamics (MHD) applications involving liquid-metal blankets, supporting simulations of interactions between electrically conducting fluids and magnetic fields.

Victor also serves as principal investigator of a Laboratory Directed Research and Development (LDRD) project on frictional contact mechanics simulations across multiple engineering and physics codes at LLNL. His technical contributions focus on linear solver aspects.

He earned his Ph.D. in Civil Engineering, with an emphasis on numerical analysis, from the University of Padua, Italy, in 2019. He holds M.S. and B.S. degrees in Mechanical Engineering from the Federal University of Santa Catarina, Brazil, earned in 2015 and 2013, respectively. His research interests include multigrid methods, preconditioning techniques, subsurface flow, multiphysics applications, scientific data compression, and high-performance computing.

External links

• Researchgate
• Google Scholar
• ORCID