high performance computing on graphics processing units: hgpu.org

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Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

Weiyi Xia, Maxim Moraru, Ying Wai Li, Timothy Liao, James R. Chelikowsky, Cai-Zhuang Wang

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Tags: Anisotropy, Computational Physics, Condensed matter, CUDA, Machine learning, Materials Science, Neural networks, nVidia, nVidia A100, Package, Physics

July 6, 2025 by hgpu

Engineering Supercomputing Platforms for Biomolecular Applications

Robert Welch, Charles Laughton, Oliver Henrich, Tom Burnley, Daniel Cole, Alan Real, Sarah Harris, James Gebbie-Rayet

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct MI300X, ATI, Benchmarking, Biology, Biomolecules, Computational biology, CUDA, HPC, Molecular dynamics, nVidia, nVidia A100, nVidia GH200, nVidia H100, Package, Physics, ROCm, Tesla V100

June 22, 2025 by hgpu

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

Paul Fuchs, Weilong Chen, Stephan Thaler, Julija Zavadlav

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Tags: Chemistry, Computational Physics, Computer science, CUDA, Machine learning, Molecular dynamics, Neural networks, nVidia, nVidia A100, nVidia GH200, nVidia H100, Package, Physics

June 15, 2025 by hgpu

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

Timothée David--Cléris, Guillaume Laibe, Yona Lapeyre

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Tags: AMD, AMD Radeon Instinct MI250X, Astrophysics, CUDA, MPI, nVidia, nVidia A100, OpenMP, Package, Physics, PTX, ROCm, SYCL

March 23, 2025 by hgpu

Asynchronous-Many-Task Systems: Challenges and Opportunities – Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

Gregor Daiß, Patrick Diehl, Jiakun Yan, John K. Holmen, Rahulkumar Gayatri, Christoph Junghans, Alexander Straub, Jeff R. Hammond, Dominic Marcello, Miwako Tsuji, Dirk Pflüger, Hartmut Kaiser

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, Astrophysics, ATI, Computer science, CUDA, Heterogeneous systems, HIP, HPC, nVidia, nVidia A100, Package, performance portability, Physics

December 29, 2024 by hgpu

TorchQC – A framework for efficiently integrating machine and deep learning methods in quantum dynamics and control

Dimitris Koutromanos, Dionisis Stefanatos, Emmanuel Paspalakis

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Tags: Deep learning, Machine learning, Package, Physics, Python, PyTorch, Quantum Physics

December 29, 2024 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

Simone Balducci

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Tags: Astrophysics, ATI, Clustering, CUDA, FPGA, HIP, Machine learning, nVidia, Package, performance portability, Physics, Python, Tesla T4, Thesis

December 1, 2024 by hgpu

Scaling SU(2) to 1000 GPUs using HiRep

Sofie Martins, Erik Kjellgren, Emiliano Molinaro, Claudio Pica, Antonio Rago

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Tags: AMD Radeon Instinct MI250X, ATI, CUDA, HEP, High Energy Physics - Lattice, HIP, Monte Carlo simulation, nVidia, nVidia H100, Package, Physics

December 1, 2024 by hgpu

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

Giulio Malenza, Valentina Cesare, Marco Edoardo Santimaria, Robert Birke, Alberto Vecchiato, Ugo Becciani, Marco Aldinucci

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Tags: AMD Radeon Instinct MI250X, Astrophysics, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, nVidia H100, nVidia V100, OpenMP, Package, Performance, performance portability, SYCL, Tesla T4

November 24, 2024 by hgpu

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Dániel Koics, Endre Kovács 2, Olivér Hornyák

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Tags: nVidia, OpenCL, Package, PDEs, Performance, Physics

October 13, 2024 by hgpu

RBMD: A molecular dynamics package enabling to simulate 10 million all-atom particles in a single graphics processing unit

Weihang Gao, Teng Zhao, Yongfa Guo, Jiuyang Liang, Huan Liu, Maoying Luo, Zedong Luo, Wei Qin, Yichao Wang, Qi Zhou, Shi Jin, Zhenli Xu

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Tags: Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce RTX 4090, Package, Physics, Tesla A100, Tesla V100

July 28, 2024 by hgpu

Gaining Cross-Platform Parallelism for HAL’s Molecular Dynamics Package using SYCL

Viktor Skoblin, Felix Höfling, Steffen Christgau

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Tags: AMD Radeon Instinct MI210, ATI, Computer science, CUDA, Molecular dynamics, nVidia, nVidia A100, nVidia A40, Package, Physics, SYCL

June 9, 2024 by hgpu

high performance computing on graphics processing units: hgpu.org

Applications

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

Engineering Supercomputing Platforms for Biomolecular Applications

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

Asynchronous-Many-Task Systems: Challenges and Opportunities – Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

TorchQC – A framework for efficiently integrating machine and deep learning methods in quantum dynamics and control

CLUEstering: a high-performance density-based clustering library for scientific computing

Scaling SU(2) to 1000 GPUs using HiRep

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

RBMD: A molecular dynamics package enabling to simulate 10 million all-atom particles in a single graphics processing unit

Gaining Cross-Platform Parallelism for HAL’s Molecular Dynamics Package using SYCL

Recent source codes

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Specx: Speculative task-based runtime system

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