high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

A Scalable High Performant Cholesky Factorization for Multicore with GPU Accelerators

Hatem Ltaief, Stanimire Tomov, Rajib Nath, Peng Du and Jack Dongarra

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla S1070

June 4, 2011 by hgpu

Synthesizing Subdivision Meshes Using Real Time Tessellation

Matthias Hollander, Tamy Boubekeur

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 295, OpenGL, Tessellation, Triangular meshes, Visualization

June 3, 2011 by hgpu

High Performance Stereo Vision Designed for Massively Data Parallel Platforms

Wei Yu, Tsuhan Chen, Franz Franchetti, James C. Hoe

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Real-time graphics, Stereo vision

June 3, 2011 by hgpu

Interactive Approximate Rendering of Reflections, Refractions, and Caustics

Wei Hu, Kaihuai Qin

Tags: Computer science, Raytracing, Rendering

June 3, 2011 by hgpu

Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

Peng Du, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Performance

June 3, 2011 by hgpu

CUDA-based Signed Distance Field Calculation for Adaptive Grids

Taejung Park, Sung-Ho Lee, Jong-Hyun Kim, Chang-Hun Kim

Tags: Algorithms, Computer science, CUDA, nVidia, Triangular meshes

June 2, 2011 by hgpu

Sparse matrix computations on manycore GPU’s

Michael Garland

Tags: Algorithms, Computer science, CUDA, nVidia, Path problems, Programming techniques, Sparse matrix

June 2, 2011 by hgpu

MapCG: writing parallel program portable between CPU and GPU

Chuntao Hong, Dehao Chen, Wenguang Chen, Weimin Zheng, Haibo Lin

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Tags: Computer science, CUDA, High-level Languages, MapReduce, nVidia, nVidia GeForce GTX 280, Programming techniques

June 2, 2011 by hgpu

Swarm’s flight: Accelerating the particles using C-CUDA

Lucas de P. Veronese, Renato A. Krohling

Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, Optimization

June 2, 2011 by hgpu

Spherical harmonic transform on heterogeneous architectures using hybrid programming

Mikolaj Szydlarski, Pierre Esterie, Joel Falcou, Laura Grigori, Radek Stompor

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Tags: Computer science, CUDA, GPU cluster, Hybrid computing, MPI, nVidia, OpenMP, Tesla S1070

June 2, 2011 by hgpu

GPS forward model computing study on CPU/GPU co-processing parallel system using CUDA

Fukang Yin, Fengshun Lu, Xiaoqun Cao, Junqiang Song

Tags: Computational modelling, Computer science, CUDA, Earth and Space Sciences, GPU cluster, nVidia, nVidia GeForce GTX 480, Weather prediction

June 1, 2011 by hgpu

GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units

N. Lopes, B. Ribeiro, R. Quintas

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Source codes

Tags: Computer science, CUDA, Machine learning, nVidia, Package

June 1, 2011 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

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high performance computing on graphics processing units: hgpu.org

Applications

A Scalable High Performant Cholesky Factorization for Multicore with GPU Accelerators

Synthesizing Subdivision Meshes Using Real Time Tessellation

High Performance Stereo Vision Designed for Massively Data Parallel Platforms

Interactive Approximate Rendering of Reflections, Refractions, and Caustics

Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

CUDA-based Signed Distance Field Calculation for Adaptive Grids

Sparse matrix computations on manycore GPU’s

MapCG: writing parallel program portable between CPU and GPU

Swarm’s flight: Accelerating the particles using C-CUDA

Spherical harmonic transform on heterogeneous architectures using hybrid programming

GPS forward model computing study on CPU/GPU co-processing parallel system using CUDA

GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units

Recent source codes

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Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

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MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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