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GPU Accelerated Discrete Element Method (DEM) Molecular Dynamics for Conservative, Faceted Particle Simulations

Matthew Spellings, Ryan L. Marson, Joshua A. Anderson, Sharon C. Glotzer

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia Quadro M 6000, Package, Particle simulation, Physics

July 13, 2016 by hgpu

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

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

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

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

GPRM: a high performance programming framework for manycore processors

Ashkan Tousimojarad

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Tags: Computer science, Intel Xeon Phi, OpenMP, Package, Thesis

June 30, 2016 by hgpu

Persistent RNNs: Stashing Recurrent Weights On-Chip

Gregory Diamos, Shubho Sengupta, Bryan Catanzaro, Mike Chrzanowski, Adam Coates, Erich Elsen, Jesse Engel, Awni Hannun, Sanjeev Satheesh

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Tags: Computer science, CUDA, Deep learning, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX Titan X, Package, RNN, Speech recognition

June 30, 2016 by hgpu

A Synchronization-Free Algorithm for Parallel Sparse Triangular Solves

Weifeng Liu, Ang Li, Jonathan Hogg, Iain S. Duff, Brian Vinter

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Tags: Algorithms, AMD Radeon R9 Fury X, ATI, Computer science, CUDA, Linear Algebra, nVidia GeForce GTX Titan X, OpenCL, Package, Sparse direct solvers, Tesla K40

June 28, 2016 by hgpu

Efficient and High-quality Sparse Graph Coloring on the GPU

Xuhao Chen, Pingfan Li, Canqun Yang

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, Tesla K40

June 22, 2016 by hgpu

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

Hugh Perkins

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Tags: Algorithms, CNN, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520, OpenCL, Package

June 21, 2016 by hgpu

Splotch: porting and optimizing for the Xeon Phi

Timothy Dykes, Claudio Gheller, Marzia Rivi, Mel Krokos

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Tags: Computer science, CUDA, Intel Xeon Phi, Numerical simulation, nVidia, OpenCL, Package, Tesla K20, Visualization

June 16, 2016 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

GPU Accelerated Discrete Element Method (DEM) Molecular Dynamics for Conservative, Faceted Particle Simulations

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

Fast Predictive Image Registration

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

Using the pyMIC Offload Module in PyFR

TTC: A Tensor Transposition Compiler for Multiple Architectures

GPRM: a high performance programming framework for manycore processors

Persistent RNNs: Stashing Recurrent Weights On-Chip

A Synchronization-Free Algorithm for Parallel Sparse Triangular Solves

Efficient and High-quality Sparse Graph Coloring on the GPU

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

Splotch: porting and optimizing for the Xeon Phi

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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