high performance computing on graphics processing units: hgpu.org

hgpu.org » Torch

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

Raul Puri, Robert Kirby, Nikolai Yakovenko, Bryan Catanzaro

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, LSTM, Mixed precision, Neural networks, nVidia, Package, Tesla V100, Torch

August 11, 2018 by hgpu

NCRF++: An Open-source Neural Sequence Labeling Toolkit

Jie Yang, Yue Zhang

View

Download (PDF)

Source codes

Tags: CNN, Computer science, CUDA, Deep learning, LSTM, NLP, nVidia, nVidia GeForce GTX 1080, Package, Python, Torch

June 17, 2018 by hgpu

Deep Neural Machine Translation with Weakly-Recurrent Units

Mattia Antonino Di Gangi, Marcello Federico

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, NLP, nVidia, nVidia GeForce GTX 1080, Package, RNN, Tesla K80, Torch

May 20, 2018 by hgpu

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Shaohuai Shi, Xiaowen Chu

View

Download (PDF)

Source codes

Tags: Algorithms, Benchmarking, Caffe, Computer science, CUDA, Deep learning, MPI, Neural networks, nVidia, Package, Performance, TensorFlow, Tesla P40, Torch

November 26, 2017 by hgpu

Empower Sequence Labeling with Task-Aware Neural Language Model

Liyuan Liu, Jingbo Shang, Frank Xu, Xiang Ren, Huan Gui, Jian Peng, Jiawei Han

View

Download (PDF)

Source codes

Tags: Computer science, Machine learning, Neural networks, NLP, nVidia, nVidia GeForce GTX 1080, Package, Python, Torch

September 16, 2017 by hgpu

Memory-Efficient Implementation of DenseNets

Geoff Pleiss, Danlu Chen, Gao Huang, Tongcheng Li, Laurens van der Maaten, Kilian Q. Weinberger

View

Download (PDF)

Source codes

Tags: Computer science, Computer vision, CUDA, Deep learning, nVidia, nVidia GeForce GTX Titan X, Package, Tesla M40, Torch

July 25, 2017 by hgpu

Parle: parallelizing stochastic gradient descent

Pratik Chaudhari, Carlo Baldassi, Riccardo Zecchina, Stefano Soatto, Ameet Talwalkar

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Performance, Torch

July 5, 2017 by hgpu

Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow

Francesco Giannini, Vincenzo Laveglia, Alessandro Rossi, Dario Zanca, Andrea Zugarini

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Machine learning, Matlab, Neural networks, nVidia, nVidia GeForce GTX 960, Package, TensorFlow, Torch

March 20, 2017 by hgpu

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

Robert T. Kelly

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 970, Theano, Thesis, Torch

February 5, 2017 by hgpu

OpenNMT: Open-Source Toolkit for Neural Machine Translation

Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, Alexander M. Rush

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Machine learning, NLP, nVidia, nVidia GeForce GTX 1080, Package, Python, Torch

January 19, 2017 by hgpu

Language Modeling with Gated Convolutional Networks

Yann N. Dauphin, Angela Fan, Michael Auli, David Grangier

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, NLP, nVidia, Performance, Tesla M40, Torch

December 26, 2016 by hgpu

Batched Shift Reduce Parsing with Lists of Vectors on CUDA

Andrew Drozdov

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, NLP, nVidia, nVidia GeForce GTX Titan Black, Package, Torch

December 26, 2016 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

* * *

high performance computing on graphics processing units: hgpu.org

Large Scale Language Modeling: Converging on 40GB of Text in Four Hours

NCRF++: An Open-source Neural Sequence Labeling Toolkit

Deep Neural Machine Translation with Weakly-Recurrent Units

Performance Modeling and Evaluation of Distributed Deep Learning Frameworks on GPUs

Empower Sequence Labeling with Task-Aware Neural Language Model

Memory-Efficient Implementation of DenseNets

Parle: parallelizing stochastic gradient descent

Neural Networks for Beginners. A fast implementation in Matlab, Torch, TensorFlow

Critical Comparison of the Classification Ability of Deep Convolutional Neural Network Frameworks with Support Vector Machine Techniques in the Image Classification Process

OpenNMT: Open-Source Toolkit for Neural Machine Translation

Language Modeling with Gated Convolutional Networks

Batched Shift Reduce Parsing with Lists of Vectors on CUDA

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

Most viewed papers (last 30 days)