high performance computing on graphics processing units: hgpu.org

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Solving $k$-Nearest Vector Problem on Multiple Graphics Processors

Kimikazu Kato, Tikara Hosino

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Tags: Computer science, CUDA, Data Structures and Algorithms, Information Retrieval, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 280

November 8, 2010 by hgpu

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Anthony Lee, Christopher Yau, Michael B. Giles, Arnaud Doucet, Christopher C. Holmes

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Tags: CUDA, Mathematics, Monte Carlo simulation, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 280, Package, Statistics

November 8, 2010 by hgpu

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

K. Hagiwara, J. Kanzaki, N. Okamura, D. Rainwater, T. Stelzer

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Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, nVidia, nVidia GeForce GTX 280, Physics

November 8, 2010 by hgpu

GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model

Tobias Preis, Peter Virnau, Wolfgang Paul, Johannes J. Schneider

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Tags: CUDA, Finite size scaling, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, Package, Phase transition, Physics

November 8, 2010 by hgpu

Solving lattice QCD systems of equations using mixed precision solvers on GPUs

M. A. Clark, R. Babich, K. Barros, R. C. Brower, C. Rebbi

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Tags: CUDA, High Energy Physics - Lattice, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, Package, Physics, QCD

November 8, 2010 by hgpu

A GPU-based matting Laplacian solver for high resolution image matting

Mengcheng Huang, Fang Liu, Enhua Wu

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Tags: Conjugate gradient solver, CUDA, Image processing, nVidia, nVidia GeForce GTX 280

November 8, 2010 by hgpu

Accelerating glassy dynamics using graphics processing units

Peter H. Colberg, Felix Hofling

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Tags: Computational Physics, CUDA, nVidia, nVidia GeForce GTX 280, Package, Physics, Soft Condensed Matter

November 8, 2010 by hgpu

Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems

Stanimire Tomov, Jack Dongarra, Marc Baboulin

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Tags: Computer science, CUDA, Hybrid computing, Linear Algebra, nVidia, nVidia GeForce GTX 280

November 8, 2010 by hgpu

Parallel Banding Algorithm to compute exact distance transform with the GPU

Thanh T. Cao, Ke Tang, Anis Mohamed, Tiow S. Tan

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9600 M, nVidia GeForce 9800 GT, nVidia GeForce GTX 280, Tesla C1060, Voronoi diagram

November 8, 2010 by hgpu

Accelerating epistasis analysis in human genetics with consumer graphics hardware

Nicholas S. Armstrong, Casey Greene, Fabio Cancare, Jason Moore

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 280

November 7, 2010 by hgpu

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Yongchao Liu, Bertil Schmidt, Douglas Maskell

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

November 6, 2010 by hgpu

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

Jayram M. Nageswaran, Nikil Dutt, Jeffrey L. Krichmar, Alex Nicolau, Alex Veidenbaum

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Tags: Biology, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 280, STDP

November 6, 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 $k$-Nearest Vector Problem on Multiple Graphics Processors

On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Calculation of HELAS amplitudes for QCD processes using graphics processing unit (GPU)

GPU accelerated Monte Carlo simulation of the 2D and 3D Ising model

Solving lattice QCD systems of equations using mixed precision solvers on GPUs

A GPU-based matting Laplacian solver for high resolution image matting

Accelerating glassy dynamics using graphics processing units

Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems

Parallel Banding Algorithm to compute exact distance transform with the GPU

Accelerating epistasis analysis in human genetics with consumer graphics hardware

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Efficient simulation of large-scale spiking neural networks using CUDA graphics processors

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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