Phase transition | hgpu.org

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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

Monte Carlo methods for massively parallel computers

Martin Weigel

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Tags: CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX Titan X, Phase transition, Physics, Spin Systems, Tesla C1060, Tesla K20

September 16, 2017 by hgpu

Deep neural networks for direct, featureless learning through observation: the case of 2d spin models

K. Mills, I. Tamblyn

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Tags: Condensed matter, CUDA, Deep learning, Ising model, Materials Science, Neural networks, nVidia, Phase transition, Physics, Tesla K40

July 2, 2017 by hgpu

Flux tubes at Finite Temperature

Pedro Bicudo, Nuno Cardoso, Marco Cardoso

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Tags: CUDA, High Energy Physics - Lattice, nVidia, Phase transition, Physics, QCD

August 31, 2016 by hgpu

CUDA programs for GPU computing of Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models

Yukihiro Komura, Yutaka Okabe

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Tags: Algorithms, Computational Physics, CUDA, Ising model, nVidia, nVidia GeForce GTX 580, Phase transition, Physics, Statistical Mechanics

April 4, 2014 by hgpu

Anomalous metastability in a temperature-driven transition

Miguel Ibanez Berganza, Pietro Coletti, Alberto Petri

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Tags: Algorithms, Condensed matter, CUDA, Ising model, nVidia, Phase transition, Physics, Statistical Mechanics, Tesla K20

April 4, 2014 by hgpu

QCDGPU: open-source package for Monte Carlo lattice simulations on OpenCL-compatible multi-GPU systems

Vadim Demchik, Natalia Kolomoyets

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, ATI Radeon HD 7970, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560 M, nVidia GeForce GTX 560 Ti, OpenCL, Package, Phase transition, Physics, Pseudo-random number generators, QCD

October 21, 2013 by hgpu

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

You-Liang Zhu, Hong Liu, Zhan-Wei Li, Hu-Jun Qian, Giuseppe Milano, Zhong-Yuan Lu

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Tags: Chemical Physics, Computational Physics, CUDA, Molecular simulation, nVidia, nVidia GeForce GTX 580, Phase transition, Physics, Soft Condensed Matter, Tesla K20

October 10, 2013 by hgpu

Phase Transition in 3d Heisenberg Spin Glasses with Strong Random Anisotropies, through a Multi-GPU Parallelization

M. Baity-Jesi, L.A. Fernandez, V. Martin-Mayor, J.M. Sanz

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Tags: Condensed matter, CUDA, Disordered Systems and Neural Networks, GPU cluster, MPI, nVidia, Phase transition, Tesla M2050

September 9, 2013 by hgpu

Parallel Algorithms for Hybrid Multi-core CPU-GPU Implementations of Component Labelling in Critical Phase Models

K.A. Hawick, D.P. Playne

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Tags: Algorithms, CUDA, Hybrid computing, Numerical simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Phase transition, Physics, Tesla M2075, Tesla M2090

June 19, 2013 by hgpu

Kinetics of liquid-solid phase transition in large nickel clusters

Alexander V. Yakubovich, Gennady Sushko, Stefan Schramm, Andrey V. Solov'yov

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Tags: ATI, ATI Radeon HD 5870, Computational Physics, Mesoscale and Nanoscale Physics, Molecular dynamics, OpenCL, Phase transition, Physics, Solidification

October 15, 2012 by hgpu

Halo Gathering Scalability for Large Scale Multi-dimensional Sznajd Opinion Models Using Data Parallelism with GPUs

K.A. Hawick, D.P. Playne

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Tags: Computer science, CUDA, Data parallelism, Numerical simulation, nVidia, nVidia GeForce GTX 580, Phase transition

July 2, 2012 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Classify QCD phase transition with deep learning

Monte Carlo methods for massively parallel computers

Deep neural networks for direct, featureless learning through observation: the case of 2d spin models

Flux tubes at Finite Temperature

CUDA programs for GPU computing of Swendsen-Wang multi-cluster spin flip algorithm: 2D and 3D Ising, Potts, and XY models

Anomalous metastability in a temperature-driven transition

QCDGPU: open-source package for Monte Carlo lattice simulations on OpenCL-compatible multi-GPU systems

GALAMOST: GPU-accelerated large-scale molecular simulation toolkit

Phase Transition in 3d Heisenberg Spin Glasses with Strong Random Anisotropies, through a Multi-GPU Parallelization

Parallel Algorithms for Hybrid Multi-core CPU-GPU Implementations of Component Labelling in Critical Phase Models

Kinetics of liquid-solid phase transition in large nickel clusters

Halo Gathering Scalability for Large Scale Multi-dimensional Sznajd Opinion Models Using Data Parallelism with GPUs

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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