high performance computing on graphics processing units: hgpu.org

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Auto-tuning of fast fourier transform on graphics processors

Yuri Dotsenko, Sara S. Baghsorkhi, Brandon Lloyd, Naga K. Govindaraju

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Tags: Computer science, CUDA, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, nVidia GeForce GTX 280, Performance, Software Engineering

September 14, 2011 by hgpu

Shadowfax: scaling in heterogeneous cluster systems via GPGPU assemblies

Alexander M. Merritt, Vishakha Gupta, Abhishek Verma, Ada Gavrilovska, Karsten Schwan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GTS, Performance, Virtualization

September 14, 2011 by hgpu

Nikola: embedding compiled GPU functions in Haskell

Geoffrey Mainland, Greg Morrisett

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Programming Languages, Tesla T10

September 14, 2011 by hgpu

A practical approach of curved ray prestack Kirchhoff Time Migration on GPGPU

Xiaohua Shi, Chuang Li, Xu Wang, Kang Li

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Tags: Algorithms, CUDA, Earth and Space Sciences, Floating point error, Geoscience, nVidia, nVidia GeForce 8800 GT, Optimization, Tesla C870

September 14, 2011 by hgpu

Subpixel reconstruction antialiasing for deferred shading

Matthaus G. Chajdas, Morgan McGuire, David Luebke

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 480

September 14, 2011 by hgpu

Computational stereo camera system with programmable control loop

Simon Heinzle, Pierre Greisen, David Gallup, Christine Chen, Daniel Saner, Aljoscha Smolic, Andreas Burg, Wojciech Matusik, Markus Gross

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480, Stereo vision, Visualization

September 13, 2011 by hgpu

Data-intensive document clustering on graphics processing unit (GPU) clusters

Yongpeng Zhang, Frank Mueller, Xiaohui Cui, Thomas Potok

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, GPU cluster, nVidia, nVidia GeForce GTX 280, Tesla C1060

September 13, 2011 by hgpu

Parallel volume rendering implementation on graphics cards using CUDA

Jens Fangerau, Susanne Kromker

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, OpenGL, Rendering, Visualization

September 13, 2011 by hgpu

Gate-Level Simulation with GPU Computing

Debapriya Chatterjee, Andrew Deorio, Valeria Bertacco

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Tags: Algorithms, CAD, Computer science, CUDA, nVidia, nVidia GeForce 8800 GT, Performance

September 13, 2011 by hgpu

Collision-streams: fast GPU-based collision detection for deformable models

Min Tang, Dinesh Manocha, Jiang Lin, Ruofeng Tong

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL

September 11, 2011 by hgpu

Parallel programming with NVIDIA CUDA

Alejandro Segovia

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8600 GT, Package, Tutorial

September 11, 2011 by hgpu

High-performance SIMT code generation in an active visual effects library

Jay L.T. Cornwall, Lee Howes, Paul H.J. Kelly, Phil Parsonage, Bruno Nicoletti

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Tags: Algorithms, Code generation, CUDA, Image processing, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, Performance, Software Engineering, Visualization

September 11, 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

Auto-tuning of fast fourier transform on graphics processors

Shadowfax: scaling in heterogeneous cluster systems via GPGPU assemblies

Nikola: embedding compiled GPU functions in Haskell

A practical approach of curved ray prestack Kirchhoff Time Migration on GPGPU

Subpixel reconstruction antialiasing for deferred shading

Computational stereo camera system with programmable control loop

Data-intensive document clustering on graphics processing unit (GPU) clusters

Parallel volume rendering implementation on graphics cards using CUDA

Gate-Level Simulation with GPU Computing

Collision-streams: fast GPU-based collision detection for deformable models

Parallel programming with NVIDIA CUDA

High-performance SIMT code generation in an active visual effects library

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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