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Parallel technologies for solving system of the linear equations by the conjugate gradient method

Eduard Bondarenko

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Tags: Computer science, Conjugate gradient solver, CUBLAS, nVidia, OpenACC, OpenMP, Tesla M2070

June 14, 2014 by hgpu

StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators

Cedric Augonnet, Olivier Aumage, Nathalie Furmento, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, OpenCL, Tesla M2070

May 18, 2014 by hgpu

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

Alexander Agathos, Jun Li, Dana Petcu, Antonio Plaza

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Tags: Algorithms, Computer science, CUDA, GPU cluster, nVidia, Sensing, Tesla M2070

April 29, 2014 by hgpu

Task-based FMM for heterogeneous architectures

Emmanuel Agullo, Berenger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, Toru Takahashi

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Tags: Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla M2070, Tesla M2090

April 9, 2014 by hgpu

Shape Transformation of Multidimensional Density Functions using Distribution Interpolation of the Radon Transforms

Marton Jozsef Toth, Balazs Csebfalvi

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Tags: Algorithms, Computer science, CUDA, nVidia, Radon transform, Tesla M2070

March 17, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Ani Anciaux-Sedrakian, Peter Gottschling, Jean-Marc Gratien, Thomas Guignon

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Review, Tesla M2070, Tesla M2090

February 1, 2014 by hgpu

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

Xavier Lacoste, Mathieu Faverge, Pierre Ramet, Samuel Thibault, George Bosilca

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Sparse direct solvers, Tesla M2070

January 30, 2014 by hgpu

A QUDA-branch to compute disconnected diagrams in GPUs

Constantia Alexandrou, Kyriacos Hadjiyiannakou, Giannis Koutsou, Alexei Strelchenko, Alejandro Vaquero

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, MPI, nVidia, Physics, QCD, Tesla M2070

January 30, 2014 by hgpu

Runtime Support toward Transparent Memory Access in GPU-accelerated Heterogeneous Systems

Feng Ji

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Tags: Computer science, Hadoop, Heterogeneous systems, MapReduce, MPI, nVidia, nVidia GeForce GTX 280, Tesla M2070, Thesis

December 11, 2013 by hgpu

A Highly Extensible Framework for Molecule Dynamic Simulation on GPUs

Xiao Zhang, Wan Guo, Xiao Qin, Xiaonan Zhao

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Source codes

Tags: Chemistry, CUDA, Molecular dynamics, nVidia, Package, Tesla C2070, Tesla M2070, Tesla S1070

December 8, 2013 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

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Parallel technologies for solving system of the linear equations by the conjugate gradient method

StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

Task-based FMM for heterogeneous architectures

Shape Transformation of Multidimensional Density Functions using Distribution Interpolation of the Radon Transforms

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

A QUDA-branch to compute disconnected diagrams in GPUs

Runtime Support toward Transparent Memory Access in GPU-accelerated Heterogeneous Systems

A Highly Extensible Framework for Molecule Dynamic Simulation on GPUs

Recent source codes

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

LLaMA-Inference-Bench

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

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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