GPU-Accelerated Computing with Python 3 and CUDA

Dr. Niels Cautaerts

Dr. Niels Cautaerts has 10 years of experience writing Python for scientific applications. Five years ago, he became interested in leveraging hardware acceleration in his code. Soon after, he began contributing CUDA kernels to open-source projects in his field of research. He has since applied his expertise to build GPU-accelerated code in various projects, including a low-latency framework for object detection in continuous image streams. Niels maintains a small following on YouTube and Medium, where he shares educational content about tech. Currently, Niels works as a research software developer and data scientist. He has also worked as a big-data engineer. Niels has a background in materials science and holds a Ph.D. in Applied Physics.

Hossein Ghorbanfekr

Hossein Ghorbanfekr is a computational physicist with over a decade of expertise in scientific programming for material modeling, specializing in C/C++ and Python. During his Ph.D., he wrote various codes, utilizing parallel computing and GPU acceleration. Since 2020, he has been working as a data scientist, focusing on machine learning and high-performance computing in research projects. Hossein has contributed to the development of an object detection framework for waste stream analysis and created GEOBERTje, a domain-specific large language model in geology. His recent work includes Pantea, an open-source, GPU-accelerated machine learning framework for molecular simulations.