high performance computing on graphics processing units: hgpu.org

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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

GPU Enhancement of the Trigger to Extend Physics Reach at the LHC

V. Halyo, A. Hunt, P. Jindal, P. LeGresley, P. Lujan

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Tags: Algorithms, CUDA, Hadronic Colliders, High Energy Physics - Experiment, nVidia, Physics, Tesla K20

May 23, 2013 by hgpu

GPU Programming for Physics Applications

Matthew Grossman

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Tags: CUDA, Differential equations, nVidia, nVidia GeForce GT 640 M, ODEs, Ordinary differential equations, Physics, Thesis

May 19, 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

Gauge fixing in lattice QCD with multi-GPUs

Mario Schrock, Hannes Vogt

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Tags: Algorithms, CUDA, High Energy Physics - Lattice, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia Quadro FX 4000, Package, Physics, QCD, Tesla C2070

May 16, 2013 by hgpu

The Lattice Boltzmann Equation Method for Complex Flows

Laura Schaefer, Michael Ikeda, Jie Bao

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Tags: Boltzmann equation, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280, Physics

May 15, 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

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

GPU Acceleration of the Variational Monte Carlo Method for Many Body Physics

Rajagopalan Kaushik Ragavan

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Tags: CUDA, Data parallelism, Heterogeneous systems, Monte Carlo simulation, MPI, nVidia, Physics, Tesla M2070, Thesis

May 1, 2013 by hgpu

Analysis of Multicore CPU and GPU Toward Parallelization of Total Focusing Method Ultrasound Reconstruction

Jason Lambert, Antoine Pedron, Guillaume Gens, Franck Bimbard, Lionel Lacassagne, Ekaterina Iakovleva, Stephane Le Berre

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Physics, Ultrasound

April 29, 2013 by hgpu

Accelerating Image Reconstruction in Three-Dimensional Optoacoustic Tomography on Graphics Processing Units

Kun Wang, Chao Huang, Yu-Jiun Kao, Cheng-Ying Chou, Alexander A. Oraevsky, Mark A. Anastasio

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Tags: CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C1060, Tesla C2050, Tomography

April 9, 2013 by hgpu

Exploring complex quantum systems with a hybrid CPU-GPU computing platform

A. Yu. Polyakov, S. Denisov, P. Hanggi

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Tags: CUDA, Differential equations, nVidia, Physics, Quantum Physics, Tesla M2050

April 7, 2013 by hgpu

FBLAS: BLAS implementation for Intel FPGA

FBLAS: Streaming Linear Algebra Kernels on FPGA

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

FANN-on-MCU: An Open-Source Toolkit for Energy-Efficient Neural Network Inference at the Edge of the Internet of Things

Titan: A CUDA-based physics simulation sandbox for high-performance robotics, physics, and reinforcement learning applications

Titan: A Parallel Asynchronous Library for Multi-Agent and Soft-Body Robotics using NVIDIA CUDA

onYourMarks: A deep learning benchmark implementation for Nvidia's Jetson TX2

Benchmarking Deep Learning Models on Jetson TX2

Hacking Neural Networks: A small course on exploiting and defending neural networks

Hacking Neural Networks: A Short Introduction

A Computing Kernel for Network Binarization on PyTorch

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

SHA512AOCLStudy

Study of OpenCL Processing Models for FPGA Devices

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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