high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Cg: a system for programming graphics hardware in a C-like language

William R. Mark, R. Steven Glanville, Kurt Akeley, Mark J. Kilgard

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Tags: 3D Graphics and Realism, Cg, Code generation, Compilers, Computer science, High-level Languages, nVidia, Package, Review

February 10, 2011 by hgpu

3D tumor localization through real-time volumetric x-ray imaging for lung cancer radiotherapy

Ruijiang Li, John H. Lewis, Xun Jia, Xuejun Gu, Michael Folkerts, Chunhua Men, William Y. Song, Steve B. Jiang

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

February 9, 2011 by hgpu

High-precision molecular dynamics simulation of UO2-PuO2: superionic transition in uranium dioxide

S.I. Potashnikov, A.S. Boyarchenkov, K.A. Nekrasov, A.Ya. Kupryazhkin

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Tags: Condensed matter, CUDA, Materials Science, Molecular dynamics, nVidia, Physics

February 9, 2011 by hgpu

High-precision molecular dynamics simulation of UO2-PuO2: pair potentials comparison

S.I. Potashnikov, A.S. Boyarchenkov, K.A. Nekrasov, A.Ya. Kupryazhkin

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Tags: Condensed matter, CUDA, Materials Science, Molecular dynamics, nVidia, Physics

February 9, 2011 by hgpu

Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units – Radial Distribution Function Histogramming

Benjamin G. Levine, John E. Stone, Axel Kohlmeyer

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Tags: Chemistry, CUDA, GPU cluster, Molecular dynamics, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Tesla C1060, Tesla C2050, Tesla S1070

February 9, 2011 by hgpu

Accelerating urban fast response Lagrangian dispersion simulations using inexpensive graphics processor parallelism

B. Singh, E. R. Pardyjak, A. Norgren, P. Willemsen

Tags: Computer science, nVidia, Visualization

February 9, 2011 by hgpu

Next-generation acceleration and code optimization for light transport in turbid media using GPUs

Erik Alerstam, William C. Yip Lo, Tianyi D. Han, Jonathan Rose, Stefan Andersson-Engels, Lothar Lilge

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Source codes

Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Optics, Package

February 9, 2011 by hgpu

Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition

Dan Claudiu Ciresan, Ueli Meier, Luca Maria Gambardella, Juergen Schmidhuber

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Tags: Artificial intelligence, CUDA, Image processing, Image recognition, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX 280

February 9, 2011 by hgpu

Deep, Big, Simple Neural Nets for Handwritten Digit Recognition

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

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Tags: Artificial intelligence, CUDA, Image processing, Image recognition, Neural and Evolutionary Computing, Neural networks, nVidia

February 9, 2011 by hgpu

Real-time GPU color-based segmentation of football players

Miguel Angel Montanes Laborda, Enrique F. Torres Moreno, Jesus Martinez del Rincon and Jose Elias Herrero Jaraba

Tags: CUDA, Image processing, Image recognition, nVidia

February 9, 2011 by hgpu

Scalable SMT-based verification of GPU kernel functions

Guodong Li, Ganesh Gopalakrishnan

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Tags: Computer science, CUDA, nVidia, Package, Software Engineering

February 9, 2011 by hgpu

Mobile 3D Graphics

Alessio Malizia

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Tags: 3D Graphics and Realism, Book, Computer science, Programming Languages, Tutorial

February 8, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Cg: a system for programming graphics hardware in a C-like language

3D tumor localization through real-time volumetric x-ray imaging for lung cancer radiotherapy

High-precision molecular dynamics simulation of UO2-PuO2: superionic transition in uranium dioxide

High-precision molecular dynamics simulation of UO2-PuO2: pair potentials comparison

Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units – Radial Distribution Function Histogramming

Accelerating urban fast response Lagrangian dispersion simulations using inexpensive graphics processor parallelism

Next-generation acceleration and code optimization for light transport in turbid media using GPUs

Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition

Deep, Big, Simple Neural Nets for Handwritten Digit Recognition

Real-time GPU color-based segmentation of football players

Scalable SMT-based verification of GPU kernel functions

Mobile 3D Graphics

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

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

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