Abstract: Nonlinear finite element analysis (FEA) is a cornerstone of computational mechanics, but its computational demands remain a central challenge. This presentation will first provide a brief overview of standard nonlinear FEA procedures, establishing the computational flow from local element evaluations to global system solution. We will then examine implementation details that significantly affect performance in large-scale simulations. The dominant cost lies in solving the global system of equations, where choices in degree-of-freedom (DOF) numbering, solver type, and parallelization strategy (shared vs. distributed memory) directly influence efficiency and scalability. Beyond the global solver, we will consider often-overlooked aspects of element-level computations, including allocation and manipulation of local arrays. Issues such as memory alignment, heap versus stack allocation, and return semantics can meaningfully impact runtime. By highlighting these practical considerations, the talk aims to provide insight into both high-level algorithmic choices and low-level implementation details that determine performance in modern finite element frameworks.
About the speaker: Claudio M. Perez is a PhD student specializing in scientific computing. His research focuses on computational mechanics and structural health monitoring, with a particular interest in differentiable computing. As a core member of the STAIRLab, Claudio has designed the computational backend and curated the software ecosystem employed by the research lab to execute large-scale regional models of civil infrastructure. Claudio is the active maintainer of the xara Python package for nonlinear finite element analysis.