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A flexible algorithm for calculating pair interactions on SIMD architectures

Szilard Pall, Berk Hess

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Tags: Algorithms, Computational Physics, CUDA, Molecular dynamics, nVidia, Physics

June 10, 2013 by hgpu

Using GPU Simulation to Accurately Fit to the Power-Law Distribution

Efstratios Rappos, Stephan Robert

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Tags: Computational Physics, CUDA, Mathematics, nVidia, nVidia GeForce GTX 590, Statistics

May 30, 2013 by hgpu

Making the case of GPUs in courses on computational physics

Knut Skogstrand Gjerden

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Tags: Computational Physics, CUBLAS, CUDA, Education, FFT, Mathematical Software, nVidia, nVidia GeForce GTX 320 M, Physics, Tesla C2050

May 17, 2013 by hgpu

Fast computation of MadGraph amplitudes on graphics processing unit (GPU)

K. Hagiwara, J. Kanzaki, Q. Li, N. Okamura, T. Stelzer

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Tags: Computational Physics, CUDA, Fortran, Monte Carlo integration, nVidia, Physics, Pseudo-random number generators, QCD, Tesla C2075

May 6, 2013 by hgpu

Feasibility Analysis of Low Cost Graphical Processing Units for Electromagnetic Field Simulations by Finite Difference Time Domain Method

A. V. Choudhari, N. A. Pande, M. R. Gupta

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Tags: Computational Physics, Computer science, CUDA, Electrodynamics, FDTD, Finite difference, Finite-difference time-domain, Maxwell's equations, nVidia, nVidia GeForce GT 520

May 3, 2013 by hgpu

GPU accelerated Trotter-Suzuki solver for quantum spin dynamics

Axel D. Dente, Carlos S. Bederian, Pablo R. Zangara, Horacio M. Pastawski

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Tags: Algorithms, Computational Physics, CUDA, nVidia, Physics, Quantum Physics, Spin Systems, Statistical Mechanics, Tesla C2070

May 2, 2013 by hgpu

Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods

Christopher Cooper, Lorena A. Barba

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Tags: Bioinformatics, Biophysics, Boltzmann equation, Computational Physics, Computer science, CUDA, Electrostatics, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

January 31, 2013 by hgpu

Reaction-diffusion model Monte Carlo simulations on the GPU

Raoul D. Schram

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Tags: Computational Physics, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, OpenCL, Physics, Statistical Mechanics

January 28, 2013 by hgpu

Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries

Denis Demidov, Karsten Ahnert, Karl Rupp, Peter Gottschling

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Tags: ATI, ATI Radeon HD 7970, Computational Physics, Computer science, CUDA, Differential equations, Mathematical Software, nVidia, ODEs, OpenCL, Ordinary differential equations, Package, Tesla C2070

January 2, 2013 by hgpu

Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance

Qing Hou, Min Li, Yulu Zhou, Jiechao Cui, Zhenguo Cui, Jun Wang

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Tags: Computational Physics, CUDA, GPU cluster, Materials Science, Molecular dynamics, nVidia, Physics, Tesla C2050

January 2, 2013 by hgpu

Toward GPU-accelerated Traffic Simulation and Its Real-Time Challenge

Manato Hirabayashi, Shinpei Kato, Masato Edahiro, Yuki Sugiyama

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti

December 23, 2012 by hgpu

IceCubes GPGPU’s cluster for extensive MC production

Martin Merck, Dmitry Chirkin, Juan Carlos Diaz Velez, Heath Skarlupka

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Tags: Computational Physics, CUDA, GPU cluster, Monte Carlo simulation, Nuclear physics, nVidia, Particle physics and field theory, Physics, Raytracing, Tesla M2070

December 20, 2012 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

A flexible algorithm for calculating pair interactions on SIMD architectures

Using GPU Simulation to Accurately Fit to the Power-Law Distribution

Making the case of GPUs in courses on computational physics

Fast computation of MadGraph amplitudes on graphics processing unit (GPU)

Feasibility Analysis of Low Cost Graphical Processing Units for Electromagnetic Field Simulations by Finite Difference Time Domain Method

GPU accelerated Trotter-Suzuki solver for quantum spin dynamics

Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods

Reaction-diffusion model Monte Carlo simulations on the GPU

Programming CUDA and OpenCL: A Case Study Using Modern C++ Libraries

Molecular dynamics simulations with many-body potentials on multiple GPUs – the implementation, package and performance

Toward GPU-accelerated Traffic Simulation and Its Real-Time Challenge

IceCubes GPGPU’s cluster for extensive MC production

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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