high performance computing on graphics processing units: hgpu.org

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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

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

Przemyslaw Stpiczynski

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Tags: Algorithms, Computer science, Intel Xeon Phi, Monte Carlo integration, nVidia, OpenACC, OpenMP, Pseudo-random number generators, Tesla K40

November 12, 2017 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

Multi-Threaded Automatic Integration Using OpenMP and CUDA

Rida Assaf

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Tags: Computational finance, Computer science, CUDA, Finance, Monte Carlo integration, nVidia, OpenMP, Physics, Tesla K20, Thesis

August 3, 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

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

Real-time Kd-tree Based Importance Sampling of Environment Maps

Serkan Ergun, Murat Kurt, Aydin Ozturk

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, KD-tree, Monte Carlo integration, nVidia, nVidia GeForce GTX 480

September 15, 2012 by hgpu

Monte Carlo integration on GPU

J. Kanzaki

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Tags: Computational Physics, CUDA, High Energy Physics - Experiment, High Energy Physics - Phenomenology, Monte Carlo integration, nVidia, nVidia GeForce GTX 285, Package, Physics

October 27, 2010 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

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

Vectorized algorithm for multidimensional Monte Carlo integration on modern GPU, CPU and MIC architectures

GPU accelerated Monte Carlo simulation of Brownian motors dynamics with CUDA

Multi-Threaded Automatic Integration Using OpenMP and CUDA

Accelerated Matrix Element Method with Parallel Computing

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

Real-time Kd-tree Based Importance Sampling of Environment Maps

Monte Carlo integration on GPU

Recent source codes

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MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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