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PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

Axel Hübl

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Tags: CUDA, HPC, nVidia, Package, Particle-in-cell methods, Physics, Tesla P100, Thesis

July 4, 2019 by hgpu

Classify QCD phase transition with deep learning

Long-Gang Pang, Kai Zhou, Nan Su, Hannah Petersen, Horst Stoecker, Xin-Nian Wang

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Tags: Deep learning, HEP, Machine learning, Neural networks, OpenCL, Package, Pattern recognition, Phase transition, Physics, QCD

June 2, 2019 by hgpu

FPGA-based acceleration of a particle simulation High Performance Computing application

Aldo Conte

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Tags: FPGA, Molecular dynamics, OpenCL, Particle simulation, Physics, Thesis

May 8, 2019 by hgpu

TensorNetwork: A Library for Physics and Machine Learning

Chase Roberts, Ashley Milsted, Martin Ganahl, Adam Zalcman, Bruce Fontaine, Yijian Zou, Jack Hidary, Guifre Vidal, Stefan Leichenauer

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Tags: Machine learning, Package, Physics, TensorFlow

May 8, 2019 by hgpu

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

Harri Renney, Benedict R. Gaster, Tom Mitchell

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Tags: AMD Radeon 530, ATI, FDTD, Finite-difference time-domain, OpenCL, OpenGL, Package, Physics

April 14, 2019 by hgpu

High Performance Monte Carlo Simulation of Ising Model on TPU Clusters

Kun Yang, Yi-Fan Chen, Georgios Roumpos, Chris Colby, John Anderson

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Tags: Cloud, CUDA, Ising model, Machine learning, Monte Carlo simulation, Neural networks, nVidia, Package, Physics, Tesla V100, TPU

April 7, 2019 by hgpu

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

Ada Sedova, Andreas Tillack, Arnold Tharrington

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Tags: Chemistry, Molecular dynamics, Molecular simulation, nVidia, OpenACC, performance portability, Physics, Tesla K20

March 3, 2019 by hgpu

A Package for Multi-Dimensional Monte Carlo Integration on Multi-GPUs

Hong-zhong Wu, Junjie Zhang, Long-gang Pang, Qun Wang

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Tags: Computational Physics, Monte Carlo integration, nVidia, Package, Physics, Python, TensorFlow, Tesla K40

February 24, 2019 by hgpu

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

Reuben D. Budiardja, Christian Y. Cardall

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Tags: cfd, CUDA, Fluid dynamics, Fortran, MPI, nVidia, OpenMP, Package, Physics, Tesla V100

December 23, 2018 by hgpu

Towards Lattice Quantum Chromodynamics on FPGA devices

Grzegorz Korcyl, Piotr Korcyl

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Tags: FPGA, High Energy Physics - Lattice, HLS, Physics, QCD

October 13, 2018 by hgpu

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung

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Tags: Chemical Physics, Code generation, Computational Physics, Factorization, nVidia, OpenCL, Package, Physics, Tesla C2075, Tesla K40

September 9, 2018 by hgpu

Cracks in the Sky: Abelian-Higgs Cosmic String Evolution with CUDA

J. R. C. C. C. Correia, C. J. A. P. Martins

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Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, nVidia, nVidia Quadro P 5000, Physics

September 9, 2018 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

Classify QCD phase transition with deep learning

FPGA-based acceleration of a particle simulation High Performance Computing application

TensorNetwork: A Library for Physics and Machine Learning

OpenCL vs: Accelerated Finite-Difference Digital Synthesis

Using Compiler Directives for Performance Portability in Scientific Computing: Kernels from Molecular Simulation

A Package for Multi-Dimensional Monte Carlo Integration on Multi-GPUs

Targeting GPUs with OpenMP Directives on Summit: A Simple and Effective Fortran Experience

Towards Lattice Quantum Chromodynamics on FPGA devices

Using SIMD and SIMT vectorization to evaluate sparse chemical kinetic Jacobian matrices and thermochemical source terms

Cracks in the Sky: Abelian-Higgs Cosmic String Evolution with CUDA

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

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