high performance computing on graphics processing units: hgpu.org

hgpu.org » Clustering

A GPU-based interactive bio-inspired visual clustering

Ugo Erra, Bernardino Frola, Vittorio Scarano

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Tags: Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 470, OpenGL

July 23, 2011 by hgpu

Living Flows: Enhanced Exploration of Edge-Bundled Graphs Based on GPU-Intensive Edge Rendering

Antoine Lambert, David Auber, Guy Melancon

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Tags: Clustering, Computer science, GLSL, nVidia, nVidia Quadro FX 1700 M, OpenGL, Rendering, Visualization

July 22, 2011 by hgpu

Accelerating Partitional Algorithms for Flow Cytometry on GPUs

Jeremy Espenshade, Andrew Pangborn, Gregor von Laszewski, Douglas Roberts, James S. Cavenaugh

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Tags: Algorithms, Biology, Clustering, CUDA, nVidia, Tesla C870

July 18, 2011 by hgpu

Speedup of Fuzzy Clustering Through Stream Processing on Graphics Processing Units

Derek T. Anderson, Robert H. Luke, James M. Keller

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Tags: Cg, Clustering, Image processing, nVidia, nVidia GeForce 7800 GS, nVidia GeForce 8800 GTX, nVidia GeForce FX 5900 Ultra, nVidia Quadro FX 2500 M

July 17, 2011 by hgpu

Accelerating data clustering on GPU-based clusters under shared memory abstraction

K.I. Karantasis, E.D. Polychronopoulos, G.N. Dimitrakopoulos

Tags: Clustering, Computer science, GPU cluster, OpenMP

July 9, 2011 by hgpu

CAMPAIGN: An open-source Library of GPU-accelerated Data Clustering Algorithms

Kai J. Kohlhoff, Marc H. Sosnick, William T. Hsu, Vijay S. Pande, Russ B. Altman

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Tags: Bioinformatics, Biology, Clustering, CUDA, nVidia, Package

July 1, 2011 by hgpu

Tracking and Clustering Salient Features in Image Sequences

Werner Bailer, Hannes Fassold, Felix Lee, Jakub Rosner

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Rendering, Video tracking

April 25, 2011 by hgpu

Scalable Clustering Using Graphics Processors

Feng Cao, Anthony Tung, Aoying Zhou

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Tags: Algorithms, Cg, Clustering, Computer science, nVidia, nVidia GeForce 6800 GT, OpenGL

April 22, 2011 by hgpu

Clustering billions of data points using GPUs

Ren Wu, Bin Zhang, Meichun Hsu

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 280

November 5, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

A GPU-based interactive bio-inspired visual clustering

Living Flows: Enhanced Exploration of Edge-Bundled Graphs Based on GPU-Intensive Edge Rendering

Accelerating Partitional Algorithms for Flow Cytometry on GPUs

Speedup of Fuzzy Clustering Through Stream Processing on Graphics Processing Units

Accelerating data clustering on GPU-based clusters under shared memory abstraction

CAMPAIGN: An open-source Library of GPU-accelerated Data Clustering Algorithms

Tracking and Clustering Salient Features in Image Sequences

Scalable Clustering Using Graphics Processors

Clustering billions of data points using 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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