high performance computing on graphics processing units: hgpu.org

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Parallel Matching and Clustering Algorithms on GPUs

Md. Naim

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla K40, Thesis

October 21, 2017 by hgpu

Progressive Clustering of Big Data with GPU Acceleration and Visualization

Jun Wang, Eric Papenhausen, Bing Wang, Sungsoo Ha, Alla Zelenyuk, Klaus Mueller

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Tags: Algorithms, big data, Clustering, Computer science, CUDA, nVidia, Tesla K20, Visualization

September 9, 2017 by hgpu

An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees

Ramin Javadi, Saleh Ashkboos

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 850 M

February 18, 2017 by hgpu

Clustering Throughput Optimization on the GPU

Michael Gowanlock, Cody M. Rude, David M. Blair, Justin D. Li, Victor Pankratius

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Tags: Algorithms, Clustering, Computer science, CUDA, Databases, nVidia, OpenMP, Tesla K20

February 5, 2017 by hgpu

Vispark: GPU-Accelerated Distributed Visual Computing Using Spark

Woohyuk Choi, Sumin Hong, Won-Ki Jeong

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Tags: Clustering, Computer science, CUDA, Distributed computing, DSL, GPU cluster, Image processing, MapReduce, nVidia, nVidia GeForce GTX Titan, Python, Rendering, Spark

November 8, 2016 by hgpu

Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs

Daniel Junger, Christian Hundt, Jorge Gonzalez-Dominguez, Bertil Schmidt

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Tags: Algorithms, Bioinformatics, Clustering, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX Titan X

September 3, 2016 by hgpu

OpenMP Parallelization and Optimization of Graph-based Machine Learning Algorithms

Zhaoyi Meng, Alice Koniges, Yun (Helen) He, Samuel Williams, Thorsten Kurth, Brandon Cook, Jack Deslippe, Andrea L. Bertozzi

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Tags: Clustering, Computer science, Intel Xeon Phi, Machine learning, OpenMP

June 9, 2016 by hgpu

Parallel data mining algorithms for multi-dimensional points on GPUs

Takazumi Matsumoto

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Tags: Algorithms, Clustering, Computer science, Data mining, Heterogeneous systems, Nearest neighbour, nVidia, nVidia GeForce GTX 780, OpenCL, Thesis

April 16, 2016 by hgpu

Extracting Flow Features Using Bag-of-Features and Supervised Learning Techniques

Yifei Li

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Source codes

Tags: Algorithms, Clustering, Computer science, Computer vision, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, OpenMP, Package, Thesis, Visualization

February 2, 2016 by hgpu

A Case for Work-stealing on FPGAs with OpenCL Atomics

Nadesh Ramanathan, John Wickerson, Felix Winterstein, George A. Constantinides

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Tags: Algorithms, Clustering, Computer science, FPGA, OpenCL

January 14, 2016 by hgpu

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Mishal Almazrooie, Mogana Vadiveloo, Rosni Abdullah

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

January 7, 2016 by hgpu

Optimization of a Machine Learning Algorithm on the Heterogeneous system using OpenCL

Min Gyung Song, Dongweon Yoon

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Tags: Algorithms, AMD Radeon R9 290, ATI, Clustering, Computer science, Heterogeneous systems, Machine learning, OpenCL

November 25, 2015 by hgpu

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qcgpu-rust: A High Performance, Hardware accelerated, Quantum computer simulator in Rust

Simulating Quantum Computers Using OpenCL

hStreams-benchmark: The benchmark of Intel hStreams

Auto-tuning Streamed Applications on Intel Xeon Phi

Parabix

Multidimensional Parallelization for Streaming Text Processing Applications Based on Parabix Framework

HLS4ML

Fast inference of deep neural networks in FPGAs for particle physics

cytonRL: reinforcement learning, deep Q-network, double DQN, dueling DQN, prioritized experience replay

CytonRL: an Efficient Reinforcement Learning Open-source Toolkit Implemented in C++

DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

DLL: A Blazing Fast Deep Neural Network Library

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high performance computing on graphics processing units: hgpu.org

Parallel Matching and Clustering Algorithms on GPUs

Progressive Clustering of Big Data with GPU Acceleration and Visualization

An Efficient Parallel Data Clustering Algorithm Using Isoperimetric Number of Trees

Clustering Throughput Optimization on the GPU

Vispark: GPU-Accelerated Distributed Visual Computing Using Spark

Ultra-Fast Detection of Higher-Order Epistatic Interactions on GPUs

OpenMP Parallelization and Optimization of Graph-based Machine Learning Algorithms

Parallel data mining algorithms for multi-dimensional points on GPUs

Extracting Flow Features Using Bag-of-Features and Supervised Learning Techniques

A Case for Work-stealing on FPGAs with OpenCL Atomics

GPU-Based Fuzzy C-Means Clustering Algorithm for Image Segmentation

Optimization of a Machine Learning Algorithm on the Heterogeneous system using OpenCL

Recent source codes

glow: Compiler for Neural Network hardware accelerators

GENESYS: GPU system calls from on ROCm

SR-NMT: Implementation in pytorch of SR-NMT

dlbench: Benchmarking State-of-the-Art Deep Learning Software Tools

qcgpu-rust: A High Performance, Hardware accelerated, Quantum computer simulator in Rust

hStreams-benchmark: The benchmark of Intel hStreams

Parabix

HLS4ML

cytonRL: reinforcement learning, deep Q-network, double DQN, dueling DQN, prioritized experience replay

DLL: Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

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Featured events

International Conference on Biomedicine & Pharmacotherapy, 2018

8th International Workshop on Computer Science and Engineering (WCSE’18), 2018

International Conference on Robotics, Artificial Intelligence, Automation and Mechatronics, 2018

The 3rd IEEE International Conference on Image, Vision and Computing (ICIVC), 2018

The 2th International Conference on Robotics and Automation Sciences (ICRAS), 2018