Lena Oden recently became a Junior Professor for Computer Architecture at the FernUniversität Hagen. Before that, she worked as a postdoctoral researcher at the Forschungszentrum Jülich and at Argonne National Laboratory in the USA. She received her PhD in Computer Science from the Ruprecht-Karls-Universität Heidelberg and a Diploma in Electrical Engineering from RWTH Aachen. During her PhD, she worked at the Fraunhofer Institute for Industrial Mathematics. Her main research areas are Computer Architectures and Runtime Systems for HPC.
Her interest in Python started when she worked with people from other scientific areas. She likes the simplicity of Python, and started to use it as her main programming language for teaching parallel programming.
She is interested in improving the performance of Python, to make it more usable in HPC.
Lessons learned from comparing Numba-CUDA and C-CUDA
We compared the performance of GPU-Applications written in C-CUDA and Numba-CUDA. By analyzing the GPU assembly code, we learned about the reasons for the differences. This helped us to optimize our codes written in NUMBA-CUDA and NUMBA itself.