high performance computing on graphics processing units: hgpu.org

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Multi-GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional q-state Potts model

Yukihiro Komura, Yutaka Okabe

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Tags: Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, Physics, Statistical Mechanics, Tesla M2050

August 13, 2012 by hgpu

Hybrid Update Algorithms for Regular Lattice and Small-World Ising Models on Graphical Processing Units

A. Leist, K.A. Hawick, D.P. Playne

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Tags: Algorithms, CUDA, Ising model, nVidia, Physics

May 29, 2012 by hgpu

GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional classical spin systems

Yukihiro Komura, Yutaka Okabe

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, Physics, Spin Systems, Statistical Mechanics

February 6, 2012 by hgpu

Accelerating the Simulations of the Ising Model by the GPU under the CUDA Environment

Xing Lu, Jing Cai, Peidong Cui, Wei Zhang

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Tags: Algorithms, CUDA, Ising model, Monte Carlo simulation, nVidia, Physics, Tesla C1060

January 22, 2012 by hgpu

Bit-Packed Damaged Lattice Potts Model Simulations with CUDA and GPUs

Ken A. Hawick, Mitchell G.B. Johnson

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Tags: CUDA, Data parallelism, Ising model, Materials Science, Nearest neighbour, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Phase transition, Physics, Probability, Tesla C2050, Tesla C2070

October 16, 2011 by hgpu

GPU-based single-cluster algorithm for the simulation of the Ising model

Yukihiro Komura, Yutaka Okabe

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, Physics

October 6, 2011 by hgpu

Connected-component identification and cluster update on graphics processing units

Martin Weigel

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla M2070

October 6, 2011 by hgpu

Connected component identification and cluster update on GPU

Martin Weigel

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Tags: Computational Physics, CUDA, High Energy Physics - Lattice, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Statistical Mechanics, Tesla M2070

May 31, 2011 by hgpu

GPU-computing in econophysics and statistical physics

T. Preis

Tags: Computer science, CUDA, Finance, Ising model, nVidia, Physics

April 11, 2011 by hgpu

Cluster and Fast-Update Simulations of Regular and Rewired Lattice Ising Models Using CUDA and Graphical Processing Units

K.A. Hawick, A.Leist and D.P.Playne

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Tags: CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Physics

February 13, 2011 by hgpu

Visualising spins and clusters in regular and small-world Ising models with GPUs

A. Leist, D.P. Playne and K.A. Hawick

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Tags: CUDA, Ising model, nVidia, nVidia GeForce GTX 260, OpenGL, Physics, Visualization

February 13, 2011 by hgpu

Interactive visualisation of spins and clusters in regular and small-world Ising models with CUDA on GPUs

A. Leist, D.P. Playne and K.A. Hawick

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Tags: CUDA, Ising model, nVidia, nVidia GeForce GTX 260, OpenGL, Physics, Visualization

February 13, 2011 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

Multi-GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional q-state Potts model

Hybrid Update Algorithms for Regular Lattice and Small-World Ising Models on Graphical Processing Units

GPU-based Swendsen-Wang multi-cluster algorithm for the simulation of two-dimensional classical spin systems

Accelerating the Simulations of the Ising Model by the GPU under the CUDA Environment

Bit-Packed Damaged Lattice Potts Model Simulations with CUDA and GPUs

GPU-based single-cluster algorithm for the simulation of the Ising model

Connected-component identification and cluster update on graphics processing units

Connected component identification and cluster update on GPU

GPU-computing in econophysics and statistical physics

Cluster and Fast-Update Simulations of Regular and Rewired Lattice Ising Models Using CUDA and Graphical Processing Units

Visualising spins and clusters in regular and small-world Ising models with GPUs

Interactive visualisation of spins and clusters in regular and small-world Ising models with CUDA on GPUs

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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