high performance computing on graphics processing units: hgpu.org

hgpu.org » CNN

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang

View

Download (PDF)

Tags: ASIC, CNN, Computer science, Deep learning, FPGA, Neural networks, nVidia, Tesla C2075

November 22, 2016 by hgpu

PipeCNN: An OpenCL-Based FPGA Accelerator for Large-Scale Convolution Neuron Networks

Dong Wang, Jianjing An, Ke Xu

View

Download (PDF)

Source codes

Tags: CNN, Computer science, Deep learning, DSP, FPGA, Hardware Architecture, Neural networks, OpenCL, Package

November 10, 2016 by hgpu

3D Object Recognition with Convolutional Neural Networks

Alberto Garcia-Garcia

View

Download (PDF)

Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GT 730, nVidia GeForce GTX Titan X, Tesla K40, Thesis

September 10, 2016 by hgpu

Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs

Chao Li, Yi Yang, Min Feng, Chakradhar Srimat, Huiyang Zhou

View

Download (PDF)

Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X

September 5, 2016 by hgpu

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

Shaohuai Shi, Qiang Wang, Pengfei Xu, Xiaowen Chu

View

Download (PDF)

Source codes

Tags: Benchmarking, CNN, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, Package, RNN, Tesla K80

August 28, 2016 by hgpu

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, Lei Zhang

View

Download (PDF)

Source codes

Tags: CNN, CUDA, Deep learning, Image processing, Matlab, nVidia, nVidia GeForce GTX Titan X, Package, Signal denoising

August 18, 2016 by hgpu

Convolutional Neural Networks for Large-Scale Bird Song Classification in Noisy Environment

Balint Pal Toth, Balint Czeba

View

Download (PDF)

Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan X, Speech recognition

August 16, 2016 by hgpu

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken Perlin

View

Download (PDF)

Tags: 3D Graphics and Realism, CNN, Computational Complexity, CUDA, Deep learning, Fluid dynamics, Fluid simulation, Machine learning, nVidia, nVidia GeForce GTX Titan X

July 16, 2016 by hgpu

Using Deep Convolutional Neural Networks in Monte Carlo Tree Search

Tobias Graf, Marco Platzner

View

Download (PDF)

Tags: Algorithms, CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, Search, Tesla K20

July 11, 2016 by hgpu

Parallel and Distributed Deep Learning

Vishakh Hegde, Sheema Usmani

View

Download (PDF)

Tags: Caffe, CNN, Computer science, CUDA, Deep learning, nVidia, nVidia GRID K520

June 28, 2016 by hgpu

CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis

Maohua Zhu, Liu Liu, Chao Wang, Yuan Xie

View

Download (PDF)

Tags: CNN, Computer science, CUDA, Deep learning, FPGA, MapReduce, Neural networks, nVidia, OpenCL, Tesla K40

June 22, 2016 by hgpu

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

Hugh Perkins

View

Download (PDF)

Source codes

Tags: Algorithms, CNN, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520, OpenCL, Package

June 21, 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

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing

PipeCNN: An OpenCL-Based FPGA Accelerator for Large-Scale Convolution Neuron Networks

3D Object Recognition with Convolutional Neural Networks

Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs

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

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Convolutional Neural Networks for Large-Scale Bird Song Classification in Noisy Environment

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Using Deep Convolutional Neural Networks in Monte Carlo Tree Search

Parallel and Distributed Deep Learning

CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

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)