high performance computing on graphics processing units: hgpu.org

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Parallel Graph Component Labelling with GPUs and CUDA

K. A. Hawick, A. Leist, D. P. Playne

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 260

November 9, 2010 by hgpu

Spherical harmonic transform with GPUs

Ioan O. Hupca, Joel Falcou, Laura Grigori, Radek Stompor

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Tags: Astrophysics, Computer science, Cosmology and Extragalactic Astrophysics, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480

November 9, 2010 by hgpu

Multifold Acceleration of Neural Network Computations Using GPU

Alexander Guzhva, Sergey Dolenko, Igor Persiantsev

Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 260

November 8, 2010 by hgpu

Real-time multi-agent path planning on arbitrary surfaces

Rafael P. Torchelsen, Luiz F. Scheidegger, Guilherme N. Oliveira, Rui Bastos, Joao L. D. Comba

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Tags: Computer science, CUDA, Games, Geodesic Distances, nVidia, nVidia GeForce GTX 260, Path problems

November 7, 2010 by hgpu

Real-time 3D registration using GPU

Soon-Yong Park, Sung-In Choi, Jun Kim, Jeong Chae

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260

November 7, 2010 by hgpu

Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA

Ogier Maitre, Laurent A. Baumes, Nicolas Lachiche, Avelino Corma, Pierre Collet

Tags: Computer science, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, Optimization

November 5, 2010 by hgpu

ECM on Graphics Cards

Daniel Bernstein, Tien-Ren Chen, Chen-Mou Cheng, Tanja Lange, Bo-Yin Yang

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Tags: Computer science, CUDA, Edwards curves, Elliptic curves, Elliptic-curve method of factorization, Factorization, Modular arithmetic, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Security

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

Real-time optical manipulation of micron sized structures using GPU generated holograms

S. Bianchi, R. Di Leonardo

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Tags: Computer holography, CUDA, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX 260, Optical trapping, Physics, Soft Condensed Matter

November 2, 2010 by hgpu

Parallel external sorting for CUDA-enabled GPUs with load balancing and low transfer overhead

Hagen Peters, Ole Schulz-Hildebrandt, Norbert Luttenberger

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, Sorting

November 2, 2010 by hgpu

A performance study of general-purpose applications on graphics processors using CUDA

S. Che, M. Boyer, J. Meng, D. Tarjan, J. Sheaffer, K. Skadron

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenMP, Package, Performance

October 30, 2010 by hgpu

Solving the Boltzmann Equation on GPU

Aldo Frezzotti, Gian P. Ghiroldi, Livio Gibelli

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 260

October 27, 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

Parallel Graph Component Labelling with GPUs and CUDA

Spherical harmonic transform with GPUs

Multifold Acceleration of Neural Network Computations Using GPU

Real-time multi-agent path planning on arbitrary surfaces

Real-time 3D registration using GPU

Coarse grain parallelization of evolutionary algorithms on GPGPU cards with EASEA

ECM on Graphics Cards

A Performance Comparison of CUDA and OpenCL

Real-time optical manipulation of micron sized structures using GPU generated holograms

Parallel external sorting for CUDA-enabled GPUs with load balancing and low transfer overhead

A performance study of general-purpose applications on graphics processors using CUDA

Solving the Boltzmann Equation on GPU

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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