Bart Oldeman
Scientific Computing Analyst at McGill HPC Centre, Calcul Québec, Compute Canada
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolBart Oldeman is a Scientific Computing Analyst with 26 years of experience bridging high-performance computing support and computational research, currently assisting users on McGill’s Guillimin HPC cluster. He holds a Ph.D. in Engineering Mathematics and is a world expert and long-term maintainer of the AUTO numerical continuation package, having driven algorithmic, usability and parallelization improvements since 2002. His background spans nonlinear dynamics, bifurcation theory and numerical methods applied to cell and laser dynamics, celestial mechanics and molecular motors, and he has taught and coordinated mathematics courses across five countries. As an experienced backend and performance engineer, he contributes to prominent open-source projects such as OpenBLAS and EasyBuild, improving microkernels, compiler toolchain support and build automation for scientific software stacks. Colleagues know him as a patient, effective instructor who combines deep mathematical insight with practical system administration and parallel programming expertise.
26 years of coding experience
8 years of employment as a software developer
M.Sc. (doctoraal), Mathematics, M.Sc. (doctoraal), Mathematics at Rijksuniversiteit GroningenPh.D., Engineering Mathematics, Ph.D., Engineering Mathematics at University of Bristol
Github Skills (26)
assembly10
scite10
python10
ebuild10
linux10
hpc10
blas10
vectorization10
x8610
openblas10
automation10
installer10
automation-testing10
performance-optimization10
x86-6410
Programming languages (15)
Github contributions (5)
easybuilders/easybuild-easyblocks
Aug 2015 - Jan 2023
Collection of easyblocks that implement support for building and installing software with EasyBuild.
Role in this project:
Backend Developer
Backend DeveloperContributions:109 reviews, 170 commits, 149 PRs in 7 years 6 months
Contributions summary:Bart primarily contributed to the development and maintenance of easyblocks, which are used for building and installing scientific software with EasyBuild. Their work included creating and improving easyblocks for PGI compilers, involving code modifications and adjustments to installation procedures. They also addressed capitalization issues and added features such as parameters for controlling the installation of specific components like AMD, Java, and NVIDIA software within the PGI easyblock.
pythoninstallinglinuxscientific-softwarehpc
easybuilders/easybuild-framework
Aug 2015 - Dec 2022
EasyBuild is a software installation framework in Python that allows you to install software in a structured and robust way.
Role in this project:Back-end Developer, Automation Engineer
Back-end Developer, Automation EngineerContributions:80 reviews, 311 commits, 146 PRs in 7 years 6 months
Contributions summary:Bart primarily focused on enhancing the EasyBuild framework with support for the PGI compiler toolchain, including adding compiler toolchain definitions, setting compiler flags, and incorporating build environment variables. They also implemented support for new toolchains, such as pompi and pomkl. The user also made updates to the testing framework for various functionalities. These commits demonstrate a focus on build system automation and integration.
pythonstructuredlinuxscientific-softwareinstallation
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