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From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

John-Alexander M. Assael

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Tags: CNN, Computer science, CUDA, Deep learning, Lua, Machine learning, nVidia, Package, Tesla K40, Thesis

September 26, 2015 by hgpu

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Fabian Tschopp

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Tags: AMD FirePro W9100, Artificial intelligence, ATI, Caffe, CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Thesis

September 15, 2015 by hgpu

Convolutional Neural Network for Sentence Classification

Yahui Chen

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

September 5, 2015 by hgpu

Semantic Pose using Deep Networks Trained on Synthetic RGB-D

Jeremie Papon, Markus Schoeler

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Tags: CNN, Computer science, Computer vision, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, Rendering

August 5, 2015 by hgpu

Efficient Convolutional Patch Networks for Scene Understanding

Clemens-Alexander Brust, Sven Sickert, Marcel Simon, Erik Rodner, Joachim Denzler

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Tags: CNN, Computer science, Deep learning, Machine learning, OpenCL, Package

July 24, 2015 by hgpu

DeepFont: Identify Your Font from An Image

Zhangyang Wang, Jianchao Yang, Hailin Jin, Eli Shechtman, Aseem Agarwala, Jonathan Brandt, Thomas S. Huang

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Tags: CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia

July 17, 2015 by hgpu

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Andre Viebke, Sabri Pllana

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Tags: CNN, Computer science, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Performance

July 1, 2015 by hgpu

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Package, Tesla K40

June 7, 2015 by hgpu

U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger, Philipp Fischer, Thomas Brox

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Tags: CNN, Computer science, CUDA, Deep learning, Image processing, Medicine, Microscopy, Neural networks, nVidia, nVidia GeForce GTX Titan, Package

May 20, 2015 by hgpu

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions

Michael Figurnov, Dmitry Vetrov, Pushmeet Kohli

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Tags: CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 980

May 5, 2015 by hgpu

A Convolutional Neural Network Cascade for Face Detection

Haoxiang Li, Zhe Lin, Xiaohui Shen, Jonathan Brandt, Gang Hua

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Tags: CNN, Computer science, CUDA, Deep learning, Face detection, Neural networks, nVidia, nVidia GeForce GTX Titan

April 20, 2015 by hgpu

Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification

Dashiell Bodington, Eric Greenstein, Matthew Hu

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 780

March 12, 2015 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

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high performance computing on graphics processing units: hgpu.org

From Pixels to Torques: Policy Learning using Deep Dynamical Convolutional Networks

Efficient Convolutional Neural Networks for Pixelwise Classification on Heterogeneous Hardware Systems

Convolutional Neural Network for Sentence Classification

Semantic Pose using Deep Networks Trained on Synthetic RGB-D

Efficient Convolutional Patch Networks for Scene Understanding

DeepFont: Identify Your Font from An Image

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

U-Net: Convolutional Networks for Biomedical Image Segmentation

PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions

A Convolutional Neural Network Cascade for Face Detection

Implementing Machine Learning Algorithms on GPUs for Real-Time Traffic Sign Classification

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

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