Szilárd Páll
PhD Student at KTH
Greater Stockholm Metropolitan Area Sweden
Summary
👤
Senior🎓
Top SchoolSzilárd Páll is a computational researcher and PhD student with 13 years’ experience specializing in high-performance molecular dynamics, parallel algorithms, and accelerator-aware optimization. As a core GROMACS developer and performance engineer, he has driven heterogeneous and multi-level parallelization work—optimizing CUDA and OpenCL kernels for one of the most widely used open-source MD engines. His expertise spans SIMD-level code tuning to large-scale hybrid GPU/CPU deployments, with practical experience on Intel MIC and modern GPU architectures. Based in Greater Stockholm, he blends deep academic research with production-grade software engineering, often extracting significant speedups by removing overhead and replacing redundant computations. An under-the-radar strength is his ability to translate low-level performance wins into scalable parallel methods that benefit the broader simulation community.
13 years of coding experience
MSc, MSc at Johannes Kepler Universität LinzPhD, PhD at KTH Royal Institute of TechnologyBSc (4 years), BSc (4 years) at Babes-Bolyai UniversityPhD, PhD at Stockholm University
Github Skills (5)
cuda10
opencl10
cprogramming-language9
c-language9
multithreading8
Programming languages (10)
Github contributions (5)
gromacs/gromacs
Nov 2012 - Jan 2023
Public/backup repository of the GROMACS molecular simulation toolkit. Please do not mine the metadata blindly; we use https://gitlab.com/gromacs/gromacs for code review and issue tracking.
Role in this project:
Backend Developer & Performance Engineer
Backend Developer & Performance EngineerContributions:502 commits, 2 comments in 10 years 3 months
Contributions summary:Szilárd primarily contributed to the performance of the GROMACS molecular simulation toolkit. Their work involved optimizing CUDA GPU kernels for non-bonded interactions. Specific improvements included removing code that introduced overhead and replacing redundant computations with optimized code using vector load/store operations, as well as various efforts to improve the performance in CUDA and OpenCL kernels. The user also fixed OpenCL compilation and performance issues.
molecular-simulation
pszi1ard/spack
Mar 2023 - Oct 2024
A flexible package manager that supports multiple versions, configurations, platforms, and compilers.
Contributions:7 pushes, 2 branches in 1 year 7 months
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