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Classify QCD phase transition with deep learning

Long-Gang Pang, Kai Zhou, Nan Su, Hannah Petersen, Horst Stoecker, Xin-Nian Wang

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Tags: Deep learning, HEP, Machine learning, Neural networks, OpenCL, Package, Pattern recognition, Phase transition, Physics, QCD

June 2, 2019 by hgpu

GPU-Accelerated SVM Training Algorithm Based on PC and Mobile Device

Yi-Yan Nan, Quan-Zhe Li, Jin-Chun Piao, Shin-Dug Kim

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Tags: Algorithms, AMD Radeon R9 M200X, Android, ATI, Computer science, Image processing, Matrix multiplication, OpenCL, Pattern recognition

February 10, 2017 by hgpu

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Sriram Kankatala

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Tags: Computer science, CUDA, Data mining, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 550 Ti, Pattern recognition, Pthreads, Thesis

March 5, 2016 by hgpu

Deep Learning for Computer Vision: A comparison between Convolutional Neural Networks and Hierarchical Temporal Memories on object recognition tasks

Vincenzo Lomonaco

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Pattern recognition, Tesla C2075, Thesis

November 8, 2015 by hgpu

A Survey of CUDA-based Multidimensional Scaling on GPU Architecture

Hasmik Osipyan, Martin Krulis, Stephane Marchand-Maillet

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Tags: Algorithms, Computer science, CUDA, Machine learning, Multidimensional scaling, nVidia, nVidia GeForce GT 740 M, Pattern recognition

September 26, 2015 by hgpu

Convolutional Neural Network-Based Image Representation for Visual Loop Closure Detection

Yi Hou, Hong Zhang, Shilin Zhou

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia Quadro K4200, Pattern recognition, Robotics

April 23, 2015 by hgpu

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

David Markvica

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Tags: Algorithms, Biology, Computational biology, Computer science, Heterogeneous systems, Metaheuristics, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Optimization, Pattern recognition, Thesis

October 27, 2014 by hgpu

Caffe: Convolutional Architecture for Fast Feature Embedding

Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell

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Tags: Cloud, Computer science, CUDA, Neural networks, nVidia, Package, Pattern recognition, Python

August 23, 2014 by hgpu

Parallel Bio-Inspired Methods for Model Optimization and Pattern Recognition

Youssef S. G. Nashed

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GT 630 M, nVidia GeForce GTS 450, Pattern recognition, Thesis

August 23, 2014 by hgpu

Efficient On-the-fly Category Retrieval using ConvNets and GPUs

Ken Chatfield, Karen Simonyan, Andrew Zisserman

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan, Pattern recognition

July 18, 2014 by hgpu

A Parallel Algorithm of PCA-SIFT Based on CUDA

Ping Zhang, Yongqi Sun, Hao Shen, Rui Zhang

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 240, OpenCV, Pattern recognition, SIFT

June 15, 2014 by hgpu

Utilizing Graphics Processing Units for Rapid Facial Recognition Using Video Input

Charles J. Gala

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Pattern recognition, Tesla C2050, Thesis

June 3, 2014 by hgpu

Ginkgo: a high-performance linear algebra library for manycore systems

Preparing Ginkgo for AMD GPUs – A Testimonial on Porting CUDA Code to HIP

GROMACS with CUDA-aware MPI direct GPU communication support

Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

Rodinia_SYCL: The Rodinia Benchmark Suite in SYCL

The Rodinia Benchmark Suite in SYCL

Neural Architecture Search Without Training

Neural Architecture Search without Training

OpenABLext: An extension to OpenABL, a framework to generate high- performance code for agent-based simulations

OpenABLext: An automatic code generation framework for agent-based simulations on CPU-GPU-FPGA heterogeneous platforms

SOFF: SNU OpenCL Framework for FPGAs

SOFF: An OpenCL High-Level Synthesis Framework for FPGAs

GCOOSpDM: Sparse-dense matrix-matrix multiplication on GPUs

Efficient Sparse-Dense Matrix-Matrix Multiplication on GPUs Using the Customized Sparse Storage Format

Programming Your GPU with OpenMP: A Hands-On Introduction

Evaluating the performance of HPC-style SYCL applications

sycl-bench: SYCL Benchmark Suite

SYCL-Bench: A Versatile Single-Source Benchmark Suite for Heterogeneous Computing

BlaBla: A Python package for clinical linguistic feature extraction in multiple languages

BlaBla: Linguistic Feature Extraction for Clinical Analysis in Multiple Languages

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2020

November

24-27

Naha, Okinawa, Japan

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2021

January

13-15

Shenzhen, China

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

2020

December

14-16

Bangkok, Thailand

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020

2020

December

14-16

Bangkok, Thailand

International Conference on Wireless Networks and Embedded Systems (ICWNES’20), 2020

2020

December

14-16

Bangkok, Thailand

International Joint Conference on Signals, Systems and Computers (CSSC’20), 2020

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