high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

Brice Boyer, Jean-Guillaume Dumas, Pascal Giorgi

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Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GTX 280, OpenMP, Package, Sparse matrix, Symbolic Computation

November 11, 2010 by hgpu

A Flexible Patch-Based Lattice Boltzmann Parallelization Approach for Heterogeneous GPU-CPU Clusters

Christian Feichtinger, Johannes Habich, Harald Koestler, Georg Hager, Ulrich Ruede, Gerhard Wellein

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Tags: Computer science, CUDA, Lattice Boltzmann model, MPI, nVidia, Tesla C1060, Tesla S1070

November 11, 2010 by hgpu

Fully automatic extraction of salient objects from videos in near real-time

Akamine Kazuma, Ken Fukuchi, Akisato Kimura, Shigeru Takagi

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 9800 GT, Pattern recognition

November 10, 2010 by hgpu

A GPU-based hyperbolic SVD algorithm

Vedran Novakovic, Sanja Singer

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Tags: Computer science, CUDA, Hyperbolic system, Mathematics, MPI, Numerical Analysis, nVidia, nVidia GeForce GTX 275, nVidia GeForce GTX 280, Tesla C1060

November 10, 2010 by hgpu

Faster Radix Sort via Virtual Memory and Write-Combining

Jan Wassenberg, Peter Sanders

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Tags: Algorithms, Computer science, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 480, Sorting

November 10, 2010 by hgpu

How to obtain efficient GPU kernels: an illustration using FMM & FGT algorithms

Felipe A. Cruz, Simon K. Layton, Lorena A. Barba

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Tags: Computer science, CUDA, Fast summation methods, Mathematical Software, nVidia, Tesla C1060

November 9, 2010 by hgpu

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

Antonio Wendell De Oliveira Rodrigues, Frederic Guyomarch, Yvonnick Le Menach, Jean-Luc Dekeyser

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla C870

November 9, 2010 by hgpu

Fast Histograms using Adaptive CUDA Streams

Sisir Koppaka, Dheevatsa Mudigere, Srihari Narasimhan, Babu Narayanan

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Tags: Computer science, CUDA, nVidia, Performance

November 9, 2010 by hgpu

Rank k Cholesky Up/Down-dating on the GPU: gpucholmodV0.2

Christian Walder

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Tags: Algorithms, Computer science, CUDA, nVidia, Package, Tesla C2050

November 9, 2010 by hgpu

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Imran S. Haque, Vijay S. Pande

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9500 GT, Package, Tesla C870

November 9, 2010 by hgpu

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

HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

Danny van Dyk, Markus Geveler, Sven Mallach, Dirk Ribbrock, Dominik Goeddeke, Carsten Gutwenger

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Tags: Cell processor, Computer science, CUDA, Mathematical Software, Mixed precision, nVidia, nVidia GeForce 8800 GTX, Package

November 9, 2010 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

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high performance computing on graphics processing units: hgpu.org

Applications

Exact Sparse Matrix-Vector Multiplication on GPU’s and Multicore Architectures

A Flexible Patch-Based Lattice Boltzmann Parallelization Approach for Heterogeneous GPU-CPU Clusters

Fully automatic extraction of salient objects from videos in near real-time

A GPU-based hyperbolic SVD algorithm

Faster Radix Sort via Virtual Memory and Write-Combining

How to obtain efficient GPU kernels: an illustration using FMM & FGT algorithms

Parallel Sparse Matrix Solver on the GPU Applied to Simulation of Electrical Machines

Fast Histograms using Adaptive CUDA Streams

Rank k Cholesky Up/Down-dating on the GPU: gpucholmodV0.2

Hard Data on Soft Errors: A Large-Scale Assessment of Real-World Error Rates in GPGPU

Parallel Graph Component Labelling with GPUs and CUDA

HONEI: A collection of libraries for numerical computations targeting multiple processor architectures

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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