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Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Peter Labus

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Tags: Algorithms, HEP, Heterogeneous systems, Intel Xeon Phi, OpenMP, Physics, QCD, Thesis

April 26, 2017 by hgpu

Machines and Algorithms

Peter A Boyle

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Tags: Algorithms, Computational Physics, CUDA, HEP, High Energy Physics - Lattice, Intel Xeon Phi, nVidia, Physics, QCD, Review

February 7, 2017 by hgpu

Design and optimization of a portable LQCD Monte Carlo code using OpenACC

Claudio Bonati, Enrico Calore, Simone Coscetti, Massimo D'Elia, Michele Mesiti, Francesco Negro, Sebastiano Fabio Schifano, Giorgio Silvi, Raffaele Tripiccione

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Tags: AMD FirePro W9100, ATI, Computational Physics, Heterogeneous systems, High Energy Physics - Lattice, nVidia, OpenACC, performance portability, Physics, QCD, Tesla K80, Tesla P100

January 4, 2017 by hgpu

Accelerating Lattice QCD Multigrid on GPUs Using Fine-Grained Parallelization

M. A. Clark, Balint Joo, Alexei Strelchenko, Michael Cheng, Arjun Gambhir, Richard Brower

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Tags: Algorithms, Computational Physics, CUDA, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla K20

December 26, 2016 by hgpu

An EoS-meter of QCD transition from deep learning

Long-Gang Pang, Kai Zhou, Nan Su, Hannah Petersen, Horst Stocker, Xin-Nian Wang

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Tags: CUDA, Deep learning, High Energy Physics - Phenomenology, Keras, Machine learning, Neural networks, Nuclear Theory, nVidia, Physics, QCD, TensorFlow, Tesla K20

December 20, 2016 by hgpu

Lattice QCD simulations using the OpenACC platform

Pushan Majumdar

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Tags: CUDA, HEP, High Energy Physics - Lattice, nVidia, OpenACC, Physics, QCD, Tesla X2090

November 19, 2016 by hgpu

A Lightweight Approach to Performance Portability with targetDP

Alan Gray, Kevin Stratford

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, performance portability, QCD, Tesla K20, Tesla K40

September 8, 2016 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

An Optimized Multiple Right-Hand Side Dslash Kernel for Intel Xeon Phi

Aaron Walden

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Tags: High Energy Physics - Lattice, Intel Xeon Phi, Physics, QCD, Thesis

July 28, 2016 by hgpu

First Application of Lattice QCD to Pezy-SC Processor

Tatsumi Aoyama, Ken-Ichi Ishikawa, Yasuyuki Kimura, Hideo Matsufuru, Atsushi Sato, Tomohiro Suzuki, Sunao Torii

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Tags: High Energy Physics - Lattice, Matrix multiplication, OpenCL, Physics, QCD

June 14, 2016 by hgpu

Accelerating Twisted Mass LQCD with QPhiX

Mario Schrock, Silvano Simula, Alexei Strelchenko

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Tags: High Energy Physics - Lattice, Intel Xeon Phi, Package, Physics, QCD

November 4, 2015 by hgpu

Efficient Numerical Evaluation of Feynman Integral

Zhao Li, Jian Wang, Qi-Shu Yan, Xiaoran Zhao

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Tags: CUDA, High Energy Physics - Phenomenology, nVidia, Physics, QCD, Tesla K20

August 12, 2015 by hgpu

Page 1 of 612 3 4 5...»Last »

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

CELES: CUDA-accelerated simulation of electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

Implementing Efficient, Portable Computations for Machine Learning

ESPRESO: Highly Parallel Solvers for Engineering Applications

Intel Xeon Phi acceleration of Hybrid Total FETI solver

Parallel and in-process compilation of individuals for genetic programming on GPU

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

MEDINA: MECCA Development in Accelerators – KPP Fortran to CUDA source-to-source Preprocessor

Internally-maintained tool for examining GPU scheduling behavior

Inferring the Scheduling Policies of an Embedded CUDA GPU

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high performance computing on graphics processing units: hgpu.org

Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Machines and Algorithms

Design and optimization of a portable LQCD Monte Carlo code using OpenACC

Accelerating Lattice QCD Multigrid on GPUs Using Fine-Grained Parallelization

An EoS-meter of QCD transition from deep learning

Lattice QCD simulations using the OpenACC platform

A Lightweight Approach to Performance Portability with targetDP

Flux tubes at Finite Temperature

An Optimized Multiple Right-Hand Side Dslash Kernel for Intel Xeon Phi

First Application of Lattice QCD to Pezy-SC Processor

Accelerating Twisted Mass LQCD with QPhiX

Efficient Numerical Evaluation of Feynman Integral

Recent source codes

Rgtsvm: Support Vector Machines on a GPU in R

Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

gloo: Collective communications library with various primitives for multi-machine training

MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU

CELES: CUDA-accelerated electromagnetic scattering by large ensembles of spheres

Boda: A C++ Framework for Efficient Experiments in Computer Vision [WIP]

ESPRESO: Highly Parallel Solvers for Engineering Applications

Parallel and in-process compilation of individuals for genetic programming on GPU

MECCA development in accelerators - KPP Fortran to CUDA source-to-source pre-processor

Internally-maintained tool for examining GPU scheduling behavior

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Featured events

4th International Conference on Biomedical and Bioinformatics Engineering (ICBBE), 2017

9th International Conference on Signal Processing Systems (ICSPS), 2017

The 5th International conference on Control, Mechatronics and Automation (ICCMA), 2017

8th International Conference on Biology, Environment and Chemistry (ICBEC), 2017

2nd International Conference on Communication and Information Systems (ICCIS), 2017