high performance computing on graphics processing units: hgpu.org

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Solving Path Problems on the GPU

Aydin Buluc, John R. Gilbert, Ceren Budak

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 8800 Ultra, Package, Path problems

November 5, 2010 by hgpu

A Performance Comparison of CUDA and OpenCL

Kamran Karimi, Neil G. Dickson, Firas Hamze

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Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenCL, Package, Performance

November 5, 2010 by hgpu

Treecode and fast multipole method for N-body simulation with CUDA

Rio Yokota, Lorena Barba

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Tags: Computational Physics, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 295, Package, Physics

November 4, 2010 by hgpu

CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

Yongchao Liu, Douglas Maskell, Bertil Schmidt

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Smith-Waterman algorithm

November 4, 2010 by hgpu

Feature tracking and matching in video using programmable graphics hardware

Sudipta Sinha, Jan-Michael Frahm, Marc Pollefeys, Yakup Genc

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Tags: Computer science, Computer vision, nVidia, nVidia GeForce 7800 GTX, nVidia GeForce 7900 GTX, OpenGL, Package, SIFT, Video tracking

November 4, 2010 by hgpu

GPUCV: A Framework for Image Processing Acceleration with Graphics Processors

Jean-philippe Farrugia, Patrick Horain, Erwan Guehenneux, Yannick Alusse

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Tags: Computer science, Computer vision, GLSL, Image processing, nVidia, nVidia GeForce 7800 GTX, OpenGL, Package

November 4, 2010 by hgpu

Implementing sparse matrix-vector multiplication on throughput-oriented processors

Nathan Bell, Michael Garland

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Package, Sparse matrix

November 4, 2010 by hgpu

CuPP – A framework for easy CUDA integration

Jens Breitbart

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Tags: Computer science, CUDA, High-level Languages, nVidia, Package

November 4, 2010 by hgpu

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

R. Capuzzo-Dolcetta, A. Mastrobuono-Battisti, D. Maschietti

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenMP, Package, Stellar dynamics, Tesla C1060

November 4, 2010 by hgpu

Studying Thermal Management for Graphics-Processor Architectures

J. W. Sheaffer, K. Skadron, D. P. Luebke

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Tags: Computer science, nVidia, nVidia GeForce 6800 Ultra, OpenGL, Package

November 3, 2010 by hgpu

PAPER – Accelerating parallel evaluations of ROCS

Imran S. Haque, Vijay S. Pande

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Tags: Chemistry, Computational chemistry, CUDA, Molecular overlay, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Package, ROCS, Shape comparison

November 3, 2010 by hgpu

Discrete Wavelet Transform on Consumer-Level Graphics Hardware

Tien-Tsin Wong, Chi-Sing Leung, Pheng-Ann Heng, Jianqing Wang

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Tags: Discrete Wavelet Transform, Image processing, JPEG2000, nVidia, nVidia GeForce 7800 GTX, OpenGL, Package, Shaders

November 2, 2010 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

Solving Path Problems on the GPU

A Performance Comparison of CUDA and OpenCL

Treecode and fast multipole method for N-body simulation with CUDA

CUDASW++: optimizing Smith-Waterman sequence database searches for CUDA-enabled graphics processing units

Feature tracking and matching in video using programmable graphics hardware

GPUCV: A Framework for Image Processing Acceleration with Graphics Processors

Implementing sparse matrix-vector multiplication on throughput-oriented processors

CuPP – A framework for easy CUDA integration

NBSymple, a double parallel, symplectic N-body code running on Graphic Processing Units

Studying Thermal Management for Graphics-Processor Architectures

PAPER – Accelerating parallel evaluations of ROCS

Discrete Wavelet Transform on Consumer-Level Graphics Hardware

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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