Nils Friess
Student
Schriesheim, Baden-Württemberg, Germany
Summary
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Rockstar🎓
Top SchoolNils Friess is an MSc student in scientific computing at Heidelberg University with a decade of hands-on experience in software engineering, specializing in numerical analysis and uncertainty quantification. He contributes to open-source compiler work for heterogeneous C++ programming models, improving hipSYCL backend stability and memory/operator handling to better support CPUs and GPUs from multiple vendors. Comfortable in low-level, performance-sensitive code, he focuses on bug fixes, type and variable refinements, and backend compatibility that help applications adapt to diverse hardware at runtime. Based in Schriesheim, Germany, he pairs rigorous academic training with practical system-building skills. Colleagues describe him as a detail-oriented developer who brings numerical insight to complex compiler and HPC problems.
10 years of coding experience
Ruprecht-Karls-Universität Heidelberg
Github Skills (11)
compiler-optimization10
compiler10
compiler-compiler10
c-language10
cprogramming-language10
scientific-computing9
accelerated-computing9
parallel-computing9
gpgpu9
gpu9
cluster-computing9
Programming languages (7)
Github contributions (5)
AdaptiveCpp/AdaptiveCpp
Nov 2022 - Jan 2023
Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
Role in this project:
Back-end Developer
Back-end DeveloperContributions:38 reviews, 6 commits, 76 PRs in 2 months
Contributions summary:Nils primarily focused on improving the hipSYCL compiler's core functionality. They addressed bugs by removing unnecessary code and incorrect variable declarations, such as the `my_id` comparison in the `item` class. The user made modifications to the compiler's support for memory caching and operators. This involved renaming variables and converting data types to improve compatibility and stability within the compiler's backend implementations.
cudaclanggpuhigh-performance-computingrocm
nilsfriess/OpenSYCL
Mar 2023 - Oct 2024
Multi-backend implementation of SYCL for CPUs and GPUs
Contributions:190 pushes, 60 branches in 1 year 7 months
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