high performance computing on graphics processing units: hgpu.org

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Grace: a Cross-platform Micromagnetic Simulator On Graphics Processing Units

Ru Zhu

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Tags: ATI, ATI Radeon HD 7970, C++ AMP, Computational Physics, Computer science, Physics

November 12, 2014 by hgpu

High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems

M. P. Wachowiak, B. B. Sarlo, A. E. Lambe Foster

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Tags: Computational Physics, CUDA, Heterogeneous systems, nVidia, Particle swarm optimization, Physics, Tesla S1070

October 20, 2014 by hgpu

Cholla : A New Massively-Parallel Hydrodynamics Code For Astrophysical Simulation

Evan E. Schneider, Brant E. Robertson

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Tags: Astrophysics, Computational Physics, CUDA, Fluid dynamics, Instrumentation and Methods for Astrophysics, nVidia, Physics, Tesla K20

October 18, 2014 by hgpu

Explicit Integration with GPU Acceleration for Large Kinetic Networks

Benjamin Brock, Andrew Belt, Jay Jay Billings, Mike Guidry

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Tags: Algorithms, Computational Physics, CUDA, nVidia, Physics, Solar and Stellar Astrophysics, Tesla K20

September 23, 2014 by hgpu

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

J. Spiechowicz, M. Kostur, L. Machura

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Tags: Computational Physics, CUDA, Differential equations, Monte Carlo integration, Monte Carlo simulation, nVidia, nVidia GeForce GTX 680, Physics, Stochastic simulation

September 19, 2014 by hgpu

A Framework for Lattice QCD Calculations on GPUs

F. T. Winter, M. A. Clark, R. G. Edwards, B. Joo

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Tags: Algorithms, Code generation, Computational Physics, CUDA, High Energy Physics - Lattice, Mathematical Software, nVidia, Physics, PTX, QCD, Tesla K20

August 27, 2014 by hgpu

Algorithms for Solving Non-Stationary Heat Conduction Problem for Design of a Technical Device

Alexander Ayriyan, Jan Busa Jr., Eugeny E. Donets, Hovik Grigorian, Jan Pribis

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Tags: Algorithms, Computational Physics, Differential equations, Finite difference, nVidia, nVidia GeForce GTX 470, OpenCL, Partial differential equations, PDEs, Physics

August 27, 2014 by hgpu

An Efficient Cell List Implementation for Monte Carlo Simulation on GPUs

Loren Schwiebert, Eyad Hailat, Kamel Rushaidat, Jason Mick, Jeffrey Potoff

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Tags: Algorithms, Computational Physics, CUDA, Molecular dynamics, Molecular simulation, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 550 Ti, Physics, Tesla K40

August 19, 2014 by hgpu

Accelerated Matrix Element Method with Parallel Computing

Doug Schouten, Adam DeAbreu, Bernd Stelzer

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Tags: AMD Radeon R9 290, ATI, Computational Complexity, Computational Physics, Monte Carlo integration, Neural networks, OpenCL, Physics, Probability

August 2, 2014 by hgpu

The design and verification of Mumax3

Arne Vansteenkiste, Jonathan Leliaert, Mykola Dvornik, Felipe Garcia-Sanchez, Bartel Van Waeyenberge

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Tags: Computational Physics, CUDA, Image generation, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX Titan, Package, Physics

July 1, 2014 by hgpu

Coupled Vlasov and two-fluid codes on GPUs

M. Rieke, T. Trost, R. Grauer

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Tags: Computational Physics, CUDA, Maxwell's equations, nVidia, Physics, Plasma physics

June 23, 2014 by hgpu

Efficient Energyminimization in Finite-Difference Micromagnetics: Speeding up Hysteresis Computations

Claas Abert, Gregor Wautischer, Florian Bruckner, Armin Satz, Dieter Suess

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Tags: Computational Physics, CUDA, Electrodynamics, Finite difference, nVidia, Package, Physics, Python

May 14, 2014 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

Grace: a Cross-platform Micromagnetic Simulator On Graphics Processing Units

High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems

Cholla : A New Massively-Parallel Hydrodynamics Code For Astrophysical Simulation

Explicit Integration with GPU Acceleration for Large Kinetic Networks

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

A Framework for Lattice QCD Calculations on GPUs

Algorithms for Solving Non-Stationary Heat Conduction Problem for Design of a Technical Device

An Efficient Cell List Implementation for Monte Carlo Simulation on GPUs

Accelerated Matrix Element Method with Parallel Computing

The design and verification of Mumax3

Coupled Vlasov and two-fluid codes on GPUs

Efficient Energyminimization in Finite-Difference Micromagnetics: Speeding up Hysteresis Computations

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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