high performance computing on graphics processing units: hgpu.org

hgpu.org » Deep learning

Data Analysis of Minimally-Structured Heterogeneous Logs: An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes

Chang Liu

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, LSTM, NLP, nVidia, Package, RNN, Thesis

September 13, 2016 by hgpu

A New Architecture for Optimization Modeling Frameworks

Matt Wytock, Steven Diamond, Felix Heide, Stephen Boyd

View

Download (PDF)

Source codes

Tags: Algorithms, CUDA, Deep learning, Linear Algebra, Mathematics, nVidia, nVidia GeForce GTX Titan X, Package, Python

September 13, 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

Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong

View

Download (PDF)

Tags: Caffe, Computer science, CUDA, Deep learning, DSP, FPGA, Neural networks, nVidia, Tesla K40

September 8, 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

DeepPy: Pythonic deep learning

Anders Boesen Lindbo Larsen

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Python

September 3, 2016 by hgpu

Deep Learning on FPGAs

Griffin James Lacey

View

Download (PDF)

Tags: Computer science, Deep learning, FPGA, nVidia, nVidia Quadro K600, OpenCL, Thesis

August 31, 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

Learning Structured Sparsity in Deep Neural Networks

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

View

Download (PDF)

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

CaffePresso: An Optimized Library for Deep Learning on Embedded Accelerator-based platforms

Gopalakrishna Hegde, Siddhartha, Nachiappan Ramasamy, Nachiket Kapre

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, DSP, FPGA, nVidia, nVidia Tegra TX1

August 11, 2016 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Data Analysis of Minimally-Structured Heterogeneous Logs: An experimental study of log template extraction and anomaly detection based on Recurrent Neural Network and Naive Bayes

A New Architecture for Optimization Modeling Frameworks

3D Object Recognition with Convolutional Neural Networks

Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks

Optimizing Memory Efficiency for Deep Convolutional Neural Networks on GPUs

DeepPy: Pythonic deep learning

Deep Learning on FPGAs

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

Learning Structured Sparsity in Deep Neural Networks

CaffePresso: An Optimized Library for Deep Learning on Embedded Accelerator-based platforms

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)