high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer vision

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera, Maurizio Martina, Muhammad Shafique

View

Tags: Artificial intelligence, Benchmarking, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Medicine, Neural networks, nVidia, Tesla V100

December 27, 2020 by hgpu

Transparent Acceleration of Java-based Deep Learning Engines

Athanasios Stratikopoulos, Mihai-Cristian Olteanu, Ian Vaughan, Zoran Sevarac, Nikos Foutris, Juan Fumero, Christos Kotselidis

View

Tags: AMD RX Vega 64, ATI, Computer science, Computer vision, Deep learning, Java, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

October 4, 2020 by hgpu

Applications of Deep Neural Networks

Jeff Heaton

View

Tags: Book, Computer science, Computer vision, Deep learning, Neural networks, NLP, Package, Python, Security

September 20, 2020 by hgpu

A Distributed Architecture for Smart Recycling Using Machine Learning

Dimitris Ziouzios, Dimitris Tsiktsiris, Nikolaos Baras, Minas Dasygenis

View

Tags: Algorithms, Cloud, Computer science, Computer vision, CUDA, Machine learning, nVidia, Security

September 6, 2020 by hgpu

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Aditya Agarwal, Yupeng Han, Maxim Likhachev

View

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Robotics, Tesla P100, Tesla V100

August 9, 2020 by hgpu

EDSSA: An Encoder-Decoder Semantic Segmentation Networks Accelerator on OpenCL-Based FPGA Platform

Hongzhi Huang, Yakun Wu, Mengqi Yu, Xuesong Shi, Fei Qiao, Li Luo, Qi Wei, Xinjun Liu

View

Tags: Algorithm optimization, Computer science, Computer vision, FPGA, Neural networks, OpenCL

July 26, 2020 by hgpu

An Overview on the Latest Nature-Inspired and Metaheuristics-Based Image Registration Algorithms

J. Santamaría, M. L. Rivero-Cejudo, M. A. Martos-Fernández, F. Roca

View

Tags: Computer science, Computer vision, Evolutionary Computations, Image registration, Metaheuristics, Neural and Evolutionary Computing, Overview

May 4, 2020 by hgpu

Deep-Edge: An Efficient Framework for Deep Learning Model Update on Heterogeneous Edge

Anirban Bhattacharjee, Ajay Dev Chhokra, Hongyang Sun, Shashank Shekhar, Aniruddha Gokhale, Gabor Karsai, Abhishek Dubey

View

Tags: Cloud, Computer science, Computer vision, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia Jetson TX2, Performance

April 19, 2020 by hgpu

Open Source Face Recognition API

Diogo Neto Coxinho Mourisco da Conceição

View

Tags: Algorithms, Computer science, Computer vision, Databases, Face detection, Package, Python, Thesis

April 12, 2020 by hgpu

Parallelization of the Honeybee Search Algorithm for Object Tracking

Oscar E. Perez-Cham, Cesar Puente, Carlos Soubervielle-Montalvo, Gustavo Olague, Carlos A. Aguirre-Salado, Alberto S. Nuñez-Varela

View

Tags: AMD Radeon R9 270, Artificial intelligence, ATI, Computer science, Computer vision, nVidia, nVidia GeForce GTX 1050, OpenCL, Particle swarm optimization

April 5, 2020 by hgpu

PyMatting: A Python Library for Alpha Matting

Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

View

Tags: Computer vision, CUDA, Image processing, nVidia, OpenCL, Package, PyOpenCL, Python

April 5, 2020 by hgpu

Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO

Balazs Nagy, Philipp Foehn, Davide Scaramuzza

View

Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 960 M, nVidia Jetson TX2, OpenCV, Package

April 5, 2020 by hgpu

Adaptive Partial STEM

Advances in Electron Microscopy with Deep Learning

Linus: easy-to-share, interactive 3D figures

linus: Conveniently explore, share, and present large-scale biological trajectory data from a web browser

Compound Word Transformer

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

SAPFOR

Interactive Parallelization of C Programs in SAPFOR

CUDA Memtrace

Exploiting BSP Abstractions for Compiler Based Optimizations of GPU Applications on multi-GPU Systems

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

ANGHABENCH: a Suite with One Million Compilable C Benchmarks for Code-Size Reduction

waLBerla: (widely applicable Lattice Boltzmann from Erlangen), massively parallel framework for multi physics applications

Highly Efficient Lattice-Boltzmann Multiphase Simulations of Immiscible Fluids at High-Density Ratios on CPUs and GPUs through Code Generation

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

NaturalCC: A Toolkit to Naturalize the Source Code Corpus

Systolic CNN

Systolic-CNN: An OpenCL-defined Scalable Run-time-flexible FPGA Accelerator Architecture for Accelerating Convolutional Neural Network Inference in Cloud/Edge Computing

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

See all packages

* * *

* * *

2021

April

27-29

Munich, Germany

9th International Workshop on OpenCL and SYCL, 2021

2020

December

10-14

Virtually in Barcelona, Spain

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

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

+

HGPU group © 2010-2021 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: