high performance computing on graphics processing units: hgpu.org

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The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability

Markus Hohnerbach, Ahmed E. Ismail, Paolo Bientinesi

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Tags: Chemistry, Computational chemistry, Computer science, CUDA, Intel Xeon Phi, Materials Science, Molecular dynamics, MPI, nVidia, Package, performance portability, Tesla K20, Tesla K40

July 13, 2016 by hgpu

Using Deep Convolutional Neural Networks in Monte Carlo Tree Search

Tobias Graf, Marco Platzner

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Tags: Algorithms, CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, Search, Tesla K20

July 11, 2016 by hgpu

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

Wolfram Schenck, Michael Horst, Tim Tiedemann, Sergius Gaulik, Ralf Moller

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Tags: ATI, ATI Radeon HD 7970, Computer science, Computer vision, FPGA, nVidia, nVidia GeForce GTX 570, nVidia Quadro NVS 4200 M, OpenCL, Review, Robotics

July 11, 2016 by hgpu

Fast Predictive Image Registration

Xiao Yang, Roland Kwitt, Marc Niethammer

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Tags: Bayesian, Computer science, Computer vision, CUDA, Deep learning, Image registration, nVidia, nVidia GeForce GTX Titan X, Package, Python

July 11, 2016 by hgpu

Large Scale GPU Accelerated PPMLR-MHD Simulations for Space Weather Forecast

Xiangyu Guo, Binbin Tang, Jian Tao, Zhaohui Huang, Zhihui Du

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Tags: CUDA, Earth and Space Sciences, Magnetohydrodynamics, MPI, nVidia, Tesla K20, Weather prediction

July 11, 2016 by hgpu

Deep Learning for Mortgage Risk

Justin Sirignano, Apaar Sadhwani, Kay Giesecke

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Tags: CUDA, Deep learning, Finance, Machine learning, Neural networks, nVidia, Statistical Finance

July 11, 2016 by hgpu

Torchnet: An Open-Source Platform for (Deep) Learning Research

Ronan Collobert, Laurens van der Maaten, Armand Joulin

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Tags: Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Torch

July 8, 2016 by hgpu

GPU Based Detection of Topological Changes in Voronoi Diagrams

Massimo Bernaschi, Matteo Lulli, Mauro Sbragaglia

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Tags: Computational Physics, Condensed matter, CUDA, Lattice Boltzmann model, nVidia, Physics, Soft Condensed Matter, Voronoi diagram

July 8, 2016 by hgpu

Using the pyMIC Offload Module in PyFR

Michael Klemm, Freddie Witherden, Peter Vincent

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Tags: Computer science, CUDA, Fluid dynamics, Intel Xeon Phi, Navier-Stokes equations, NSEs, OpenCL, OpenMP, Package, Python

July 8, 2016 by hgpu

TTC: A Tensor Transposition Compiler for Multiple Architectures

Paul Springer, Aravind Sankaran, Paolo Bientinesi

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Tags: BLAS, Compilers, Computer science, CUDA, Intel Xeon Phi, Linear Algebra, Mathematical Software, nVidia, nVidia GeForce 840 M, Package, Performance, Tesla K40

July 8, 2016 by hgpu

Matrix Multiplication Beyond Auto-Tuning: Rewrite-based GPU Code Generation

Michel Steuwer, Toomas Remmelg, Christophe Dubach

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Tags: ARM, ATI, ATI Radeon HD 7970, BLAS, Code generation, Computer science, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX Titan Black, OpenCL, performance portability

July 8, 2016 by hgpu

Accelerated cryo-EM structure determination with parallelisation using GPUs in relion-2

Dari Kimanius, Bjorn O Forsberg, Sjors HW Scheres, Erik Lindahl

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Tags: Biology, Cryo-EM, CUDA, Image processing, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980 Ti

July 5, 2016 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

Applications

The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability

Using Deep Convolutional Neural Networks in Monte Carlo Tree Search

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

Fast Predictive Image Registration

Large Scale GPU Accelerated PPMLR-MHD Simulations for Space Weather Forecast

Deep Learning for Mortgage Risk

Torchnet: An Open-Source Platform for (Deep) Learning Research

GPU Based Detection of Topological Changes in Voronoi Diagrams

Using the pyMIC Offload Module in PyFR

TTC: A Tensor Transposition Compiler for Multiple Architectures

Matrix Multiplication Beyond Auto-Tuning: Rewrite-based GPU Code Generation

Accelerated cryo-EM structure determination with parallelisation using GPUs in relion-2

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

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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