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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

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

May 4, 2020 by hgpu

GEVO: GPU Code Optimization using Evolutionary Computation

Jhe-Yu Liou, Xiaodong Wang, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, Package, PTX, Tesla P100

April 26, 2020 by hgpu

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

Nicolas Weber, Florian Schmidt, Mathias Niepert, Felipe Huici

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Tags: AI, Artificial intelligence, cache, CNN, Computer science, cpu, CUDA, Deep learning, GPU, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti

April 25, 2018 by hgpu

A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems

Nikolaos Antoniadis, Angelo Sifaleras

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Tags: Computer science, Metaheuristics, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 960, nVidia GeForce GTX 980, OpenACC, OpenMP, Optimization

April 20, 2017 by hgpu

BrainFrame: A heterogeneous accelerator platform for neuron simulations

Georgios Smaragdos, Georgios Chatzikonstantis, Rahul Kukreja, Harrys Sidiropoulos, Dimitrios Rodopoulos, Ioannis Sourdis, Zaid Al-Ars, Christoforos Kachris, Dimitrios Soudris, Chris I. De Zeeuw, Christos Strydis

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Tags: Biophysics, Computer science, Heterogeneous systems, Intel Xeon Phi, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX Titan X, OpenMP

December 10, 2016 by hgpu

Learning Structured Sparsity in Deep Neural Networks

Wei Wen, Chunpeng Wu, Yandan Wang, Yiran Chen, Hai Li

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan Black, nVidia Quadro K600, Tesla K40

August 16, 2016 by hgpu

RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks

Patrick Doetsch, Albert Zeyer, Paul Voigtlaender, Ilya Kulikov, Ralf Schluter, Hermann Ney

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Package, RNN, Speech recognition

August 4, 2016 by hgpu

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

Yani Ioannou, Duncan Robertson, Roberto Cipolla, Antonio Criminisi

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Tags: Computer science, CUDA, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan Z

May 23, 2016 by hgpu

dMath: A Scalable Linear Algebra and Math Library for Heterogeneous GP-GPU Architectures

Steven Eliuk, Cameron Upright, Anthony Skjellum

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Linear Algebra, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, OpenMPI, Tesla K80

April 9, 2016 by hgpu

Neural GPUs Learn Algorithms

Lukasz Kaiser, Ilya Sutskever

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Tesla K40

December 1, 2015 by hgpu

Supervised Hashing with Deep Neural Networks

Ziming Zhang, Yuting Chen, Venkatesh Saligrama

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Tags: Computer science, CUDA, Deep learning, Hashing, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan

November 20, 2015 by hgpu

Large Scale Artificial Neural Network Training Using Multi-GPUs

Linnan Wang, Wei Wu, Jianxiong Xiao, Yang Yi

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX Titan X, Tesla K40

November 20, 2015 by hgpu

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Hummingbird: a library for compiling trained traditional ML models into tensor computations

A Tensor Compiler for Unified Machine Learning Prediction Serving

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Deep Learning for Digital Asset Limit Order Books

Dream to Control

Mastering Atari with Discrete World Models

visrec-api: specification of standard Visual Recognition API for Java (JSR381)

Transparent Acceleration of Java-based Deep Learning Engines

LoopBench: An Evaluation of Loop Acceleration in Heterogeneous Systems

GemmKernels: Flexible and performant GEMM kernels in Julia

Flexible Performant GEMM Kernels on GPUs

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Extending High-Level Synthesis for Task-Parallel Programs

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2020

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10-14

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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

2020

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14-16

Bangkok, Thailand

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

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high performance computing on graphics processing units: hgpu.org

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

GEVO: GPU Code Optimization using Evolutionary Computation

BrainSlug: Transparent Acceleration of Deep Learning Through Depth-First Parallelism

A hybrid CPU-GPU parallelization scheme of variable neighborhood search for inventory optimization problems

BrainFrame: A heterogeneous accelerator platform for neuron simulations

Learning Structured Sparsity in Deep Neural Networks

RETURNN: The RWTH Extensible Training framework for Universal Recurrent Neural Networks

Deep Roots: Improving CNN Efficiency with Hierarchical Filter Groups

dMath: A Scalable Linear Algebra and Math Library for Heterogeneous GP-GPU Architectures

Neural GPUs Learn Algorithms

Supervised Hashing with Deep Neural Networks

Large Scale Artificial Neural Network Training Using Multi-GPUs

Recent source codes

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Hummingbird: a library for compiling trained traditional ML models into tensor computations

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Deep Learning for Digital Asset Limit Order Books

Dream to Control

visrec-api: specification of standard Visual Recognition API for Java (JSR381)

LoopBench: An Evaluation of Loop Acceleration in Heterogeneous Systems

GemmKernels: Flexible and performant GEMM kernels in Julia

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Extending High-Level Synthesis for Task-Parallel Programs

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Featured events

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

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

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

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

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