high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260, OpenMP, Partial differential equations, PDEs, Tesla C2050

October 5, 2011 by hgpu

GPU accelerated 2-D staggered-grid finite difference seismic modelling

Zhangang Wang, Suping Peng, Tao Liu

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Tags: Cg, Earth and Space Sciences, Finite difference, nVidia, nVidia GeForce 9800 GT, OpenGL, Seismic modeling, Seismology

October 5, 2011 by hgpu

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Mark Silberstein, Assaf Schuster, John D. Owens

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285, Optimization, Package, Performance, Probability, Task scheduling, Tesla C2050

October 5, 2011 by hgpu

Parallel Direct Simulation Monte Carlo Computation Using CUDA on GPUs

C.-C. Su, C.-W. Hsieh, M. R. Smith, M. C. Jermy, and J.-S. Wua

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Tags: Benchmarking, Computer science, CUDA, Monte Carlo simulation, nVidia, Tesla C1060

October 5, 2011 by hgpu

A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

Allison S. Gehrke, Ilkyeun Ra, Daniel A. Connors

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Tags: Code generation, Computer science, Numerical simulation, nVidia, Optimization, Performance, PTX

October 5, 2011 by hgpu

High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: CUDA, Differential equations, Mathematics, nVidia, nVidia GeForce GTX 280, Python, Tesla T10

October 5, 2011 by hgpu

Flexible, high performance convolutional neural networks for image classification

Dan C. Ciresan, Ueli Meier, Jonathan Masci, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Benchmarking, Computer science, CUDA, Image processing, Neural networks, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 580

October 5, 2011 by hgpu

A parallel error diffusion implementation on a GPU

Yao Zhang, John Ludd Recker, Robert Ulichney, Giordano B. Beretta, Ingeborg Tastl, I-Jong Lin, and John D. Owens

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 460

October 5, 2011 by hgpu

GPU performance comparison for accelerated radar data processing

Chris Fallen, Beau Bellamy, Greg Newby, Brent Watkins

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Tags: Measurement techniques, nVidia, nVidia GeForce GTX 480, OpenCL, Presentation, Signal processing, Tesla M2050

October 4, 2011 by hgpu

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Marek Blazewicz, Steven R. Brandt, Peter Diener, David M. Koppelman, Krzysztof Kurowski, Frank Loffler, Erik Schnetter, Jian Tao

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia, OpenCL, Optimization, Package, Programming techniques, Tesla S1070

October 4, 2011 by hgpu

Architecture-Aware Optimization on a 1600-core Graphics Processor

Mayank Daga, Thomas R.W. Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, Cluster computing, Computer science, CUDA, Molecular modeling, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Tesla C2050

October 4, 2011 by hgpu

Fine-grained Parallel ILU Preconditioners with Fill-ins for Multi-core CPUs and GPUs

Vincent Heuveline, Dimitar Lukarski and Jan-philipp Weiss

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Tags: Algorithms, Computer science, FEM, Finite element method, Heterogeneous systems, Numerical simulation, OpenCL, Package, Partial differential equations, PDEs

October 4, 2011 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

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high performance computing on graphics processing units: hgpu.org

Applications

Performance Analysis and Optimisation of the OP2 Framework on Many-core Architectures

GPU accelerated 2-D staggered-grid finite difference seismic modelling

Applying software-managed caching and CPU/GPU task scheduling for accelerating dynamic workloads

Parallel Direct Simulation Monte Carlo Computation Using CUDA on GPUs

A Framework for Automated Performance Tuning and Code Verification on GPU Computing Platforms

High-Order Discontinuous Galerkin Methods by GPU Metaprogramming

Flexible, high performance convolutional neural networks for image classification

A parallel error diffusion implementation on a GPU

GPU performance comparison for accelerated radar data processing

A Massive Data Parallel Computational Framework on Petascale/Exascale Hybrid Computer Systems

Architecture-Aware Optimization on a 1600-core Graphics Processor

Fine-grained Parallel ILU Preconditioners with Fill-ins for Multi-core CPUs and GPUs

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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

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