Natalie Beams

Background

About Natalie Beams

My main focus at ICL has been on GPU computing: primarily porting CUDA code for other GPU architectures, and using profiling and other tools to evaluate and improve code performance. I also have a strong interest in numerical methods for scientific computing and scientific software development. I started my journey in engineering, earning a BSME and becoming a licensed Engineer Intern. I then focused on numerical methods for PDEs during my graduate studies, with a dissertation on high-order hybrid numerical methods with Green's functions and finite elements. During my postdoc, I designed and implemented a shared-memory parallel code targeting CPUs, using OpenMP and the Intel MKL library, to accelerate a fast direct solver for the Helmholtz equation. In my current position, I have learned and applied techniques for GPU programming, and collaborated with researchers from different disciplines and institutions. I am always open to future challenges and opportunities for learning new things and solving problems with computational tools.