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De-specializing an HLS library for Deep Neural Networks: improvements upon hls4ml

Serena Curzel, Nicolò Ghielmetti, Michele Fiorito, Fabrizio Ferrandi

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Tags: Computer science, FPGA, Hardware Architecture, Image recognition, Machine learning, Neural networks, Physics

March 28, 2021 by hgpu

Performance benchmarking of deep learning framework on Intel Xeon Phi

Chao-Tung Yang, Jung-Chun Liu, Yu-Wei Chan, Endah Kristiani, Chan-Fu Kuo

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Tags: Benchmarking, Caffe, Computer science, Deep learning, Image recognition, Intel Xeon Phi, MPI, OpenMP, Performance, TensorFlow

June 28, 2020 by hgpu

Benchmarking Deep Learning Models on Jetson TX2

Lucas Pedro Bordignon, Aldo von Wangenheim

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Image recognition, nVidia, nVidia Jetson TX2, Overview, Package, Tutorial

November 24, 2019 by hgpu

FPGA Implementation of Reduced Precision Convolutional Neural Networks

Muhammad Mohid Nabil

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Tags: Computer science, CUDA, Deep learning, FPGA, HLS, Image recognition, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, Precision, Thesis

May 12, 2019 by hgpu

Optimization of Spatial Convolution in ConvNets on Intel KNL

Sangamesh Nagashattappa Ragate

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Tags: Computer science, Deep learning, Image recognition, Intel Xeon Phi, Neural networks, Thesis

September 9, 2017 by hgpu

Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded Modes

Yuriy Kochura, Sergii Stirenko, Oleg Alienin, Michail Novotarskiy, Yuri Gordienko

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Tags: Computer science, CUDA, Deep learning, Image recognition, Java, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Performance, TensorFlow, Tesla K40

September 3, 2017 by hgpu

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Chenghua Li, Qi Kang, Guojing Ge, Qiang Song, Hanqing Lu, Jian Cheng

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

June 30, 2016 by hgpu

Fast Algorithms for Convolutional Neural Networks

Andrew Lavin

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Tags: Algorithms, CNN, Computer science, Deep learning, FFT, Image recognition, Machine learning, Neural networks

October 3, 2015 by hgpu

Target Marker: A Visual Marker for Long Distances and Detection in Realtime on Mobile Devices

Oliver Christen, Edwin Naroska, Alexander Micheel, Shanq-Jang Ruan

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Tags: Computer science, Computer vision, Image recognition, OpenCL, OpenCV

August 5, 2015 by hgpu

An efficient KNN algorithm implemented on FPGA based heterogeneous computing system using OpenCL

Yuliang Pu, Jun Peng, Letian Huang, John Chen

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Tags: Algorithms, Computer science, Data mining, FPGA, Heterogeneous systems, Image recognition, Nearest neighbour, OpenCL

July 27, 2015 by hgpu

On the use of deep Boltzmann machines for road signs classification

Carlo D'Eramo

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Tags: Computer science, Computer vision, CUDA, Image recognition, Machine learning, nVidia, Python, Tesla C1060, Thesis

July 22, 2015 by hgpu

Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors

Ming Zeng, Le T. Nguyen, Bo Yu, Ole J. Mengshoel, Jiang Zhu, Pang Wu, Joy Zhang

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Tags: CNN, CUDA, Image recognition, Neural networks, nVidia, Sensing, Speech recognition, Tesla K20

January 13, 2015 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

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high performance computing on graphics processing units: hgpu.org

De-specializing an HLS library for Deep Neural Networks: improvements upon hls4ml

Performance benchmarking of deep learning framework on Intel Xeon Phi

Benchmarking Deep Learning Models on Jetson TX2

FPGA Implementation of Reduced Precision Convolutional Neural Networks

Optimization of Spatial Convolution in ConvNets on Intel KNL

Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded Modes

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Fast Algorithms for Convolutional Neural Networks

Target Marker: A Visual Marker for Long Distances and Detection in Realtime on Mobile Devices

An efficient KNN algorithm implemented on FPGA based heterogeneous computing system using OpenCL

On the use of deep Boltzmann machines for road signs classification

Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors

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

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