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Implementing Efficient, Portable Computations for Machine Learning

Matthew Walter Moskewicz

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Tags: Algorithms, AMD R9 Nano, ATI, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

May 24, 2017 by hgpu

Real-Time Adaptive Image Compression

Oren Rippel, Lubomir Bourdev

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Tags: Algorithms, Compression, Computer science, Computer vision, Machine learning, nVidia, nVidia GeForce GTX 980 Ti

May 18, 2017 by hgpu

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

Xinyu Zhang, Srinjoy Das, Ojash Neopane, Ken Kreutz-Delgado

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Tags: Algorithms, Computer science, Computer vision, Deep learning, DSP, FPGA, Neural networks

May 11, 2017 by hgpu

Deep Learning in the Automotive Industry: Applications and Tools

Andre Luckow, Matthew Cook, Nathan Ashcraft, Edwin Weill, Emil Djerekarov, Bennie Vorster

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Tags: Cloud, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia GRID K520, Performance

May 2, 2017 by hgpu

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X

April 30, 2017 by hgpu

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

Pascal Libuschewski

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Tags: Biology, Computer vision, Design space exploration, Microscopy, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 560 Ti, nVidia Quadro NVS 3100 M, OpenCL, Thesis, Visualization

April 20, 2017 by hgpu

CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data

Lukas Cavigelli, Philippe Degen, Luca Benini

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Tags: Artificial intelligence, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Tegra TX1

April 17, 2017 by hgpu

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

Siyang Qin, Roberto Manduchi

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Tags: Algorithms, Caffe, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan X

April 7, 2017 by hgpu

Large-scale image analysis using docker sandboxing

B. Sengupta, E. Vazquez, M. Sasdelli, Y. Qian, M. Peniak, L. Netherton, G. Delfino

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Tags: Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia Quadro M 6000

March 14, 2017 by hgpu

Optimizing Deep CNN-Based Queries over Video Streams at Scale

Daniel Kang, John Emmons, Firas Abuzaid, Peter Bailis, Matei Zaharia

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Tags: Computer science, Computer vision, Databases, Deep learning, Machine learning, Neural networks, nVidia, nVidia DGX-1, Package, TensorFlow, Tesla P100

March 9, 2017 by hgpu

Speckle Reduction with Trained Nonlinear Diffusion Filtering

Wensen Feng, Yunjin Chen

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Tags: CNN, Computer vision, Filtering, Image processing, Matlab, nVidia, nVidia GeForce GXT 780 Ti, Package, SAR

February 28, 2017 by hgpu

Improving the Performance of OpenCL-based FPGA Accelerator for Convolutional Neural Network

Jialiang Zhang, Jing Li

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Tags: Computer science, Computer vision, Deep learning, FPGA, Neural networks, OpenCL

February 26, 2017 by hgpu

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

On the Compilation Performance of Current SYCL Implementations

M1 GPUs for (scientific) computations in C++

Seamless GPU acceleration for C++ based physics with the Metal Shading Language on Apple’s M series unified chips

CUB: Cooperative primitives for CUDA C++

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Simulator and workload generator for Edge-to-Cloud environments

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Implementing Efficient, Portable Computations for Machine Learning

Real-Time Adaptive Image Compression

A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

Exploration of cyber-physical systems for GPGPU computer vision-based detection of biological viruses

CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

Large-scale image analysis using docker sandboxing

Optimizing Deep CNN-Based Queries over Video Streams at Scale

Speckle Reduction with Trained Nonlinear Diffusion Filtering

Improving the Performance of OpenCL-based FPGA Accelerator for Convolutional Neural Network

Recent source codes

Rodinia Benchmarks for DPC++

DCA++: a state of the art implementation of the dynamical cluster approximation

tntorch - Tensor Network Learning with PyTorch

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

M1 GPUs for (scientific) computations in C++

CUB: Cooperative primitives for CUDA C++

Simulator and workload generator for Edge-to-Cloud environments

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