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[PDF] Top 20 Acceleration of Deep Learning on FPGA

Has 10000 "Acceleration of Deep Learning on FPGA" found on our website. Below are the top 20 most common "Acceleration of Deep Learning on FPGA".

Acceleration of Deep Learning on FPGA

Acceleration of Deep Learning on FPGA

... Recently, the utilization of many-core architecture is popular in the HPC area to meet ever-increasing computation demand. Compared to other systems, general purpose GPU is widely chosen, due to the programming ... See full document

85

Hardware Acceleration of SVM classifier using Zynq SoC FPGA

Hardware Acceleration of SVM classifier using Zynq SoC FPGA

... hardware acceleration of vector operations of SVM was analysed and better performance was ...for acceleration of SVM was not generic and was strictly application ... See full document

9

High Performance Scalable Deep Learning Accelerator Unit on FPGA

High Performance Scalable Deep Learning Accelerator Unit on FPGA

... Largescale deep learning neural network ...accelerating deep learning algorithms are Field-Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), and Graphic ... See full document

5

Hardware Acceleration of Computer Vision and Deep Learning Algorithms on the Edge using OpenCL

Hardware Acceleration of Computer Vision and Deep Learning Algorithms on the Edge using OpenCL

... Machine vision using CNN is a key application in Industrial automation environment, enabling real time as well as offline analytics. A lot of processing is required in real time, and in high speed environment variable ... See full document

6

DLAU: A Scalable Deep Learning Accelerator Unit on FPGA

DLAU: A Scalable Deep Learning Accelerator Unit on FPGA

... performance deep learning networks with low power cost, especially for large-scale deep learning neural network ...accelerating deep learning algorithms are field-programmable ... See full document

8

FPGA-Based Acceleration of Expectation Maximization Algorithm using High Level Synthesis

FPGA-Based Acceleration of Expectation Maximization Algorithm using High Level Synthesis

... Computation demand in HPC has increased rapidly in recent years and this trend will continue for the foreseeable future. Traditionally multi-core CPUs were for HPC. Because of ease of programming, data and instruction ... See full document

95

Hardware Acceleration of Hamming Code: Design of Runtime Reconfigurable FPGA Prototype

Hardware Acceleration of Hamming Code: Design of Runtime Reconfigurable FPGA Prototype

... ACTEL-ProASIC3 FPGA (250Kgates), and programmed in ...ProASIC3 FPGA. The code rate achieved here is 57.1%.FPGA is preferred over microcontroller development boards because variable frequency and ... See full document

8

Acceleration of k-Nearest Neighbor and SRAD Algorithms Using Intel FPGA SDK for OpenCL

Acceleration of k-Nearest Neighbor and SRAD Algorithms Using Intel FPGA SDK for OpenCL

... for FPGA had better performance compared to Xeon E5- 2620 CPU in terms of execution time and power ...on FPGA compared to multi-core ...on FPGA compared to CPU because of it’s sequential nature. But ... See full document

68

FPGA Based Acceleration of Matrix Decomposition and Clustering Algorithm Using High Level Synthesis

FPGA Based Acceleration of Matrix Decomposition and Clustering Algorithm Using High Level Synthesis

... from FPGA implementations synthesized using Altera SDK for OpenCL running on Stratix V A7 FPGA is compared with results from ANN library and kNN CUDA mentioned in related ...The FPGA used in ... See full document

136

Accelerating the image processing by the optimization strategy for deep learning algorithm DBN

Accelerating the image processing by the optimization strategy for deep learning algorithm DBN

... analysis, such as data skew, lack of fine-grained data re- placement, and high automatic cache re-usability. These problems lead to the defects of high complexity and low execution time of DBN. The parallel ... See full document

8

On the Influence of Momentum Acceleration on Online Learning

On the Influence of Momentum Acceleration on Online Learning

... useful acceleration properties in the deterministic context, momen- tum terms have been subsequently introduced into stochastic optimization algorithms as well (Polyak, 1987; Proakis, 1974; Sharma et ...or ... See full document

66

Deep Imitation Learning for 3D Navigation Tasks

Deep Imitation Learning for 3D Navigation Tasks

... a deep reinforcement learning algorithm is used to teach an agent in a racing simulator from raw visual ...that learning from demonstration can be used to handle high degree of freedom low level ... See full document

28

Impact of Machine Learning on Manufacturing Industries

Impact of Machine Learning on Manufacturing Industries

... Machine learning can also help realize a company which branch or branches of it is not performing up to the mark. They can accordingly close down or shift their branch based on the prediction. The sales data of ... See full document

7

Development and Evaluation of an Educational Intervention to Enhance Deep Learning and Study Skills among Pharmacy Students in Zambia

Development and Evaluation of an Educational Intervention to Enhance Deep Learning and Study Skills among Pharmacy Students in Zambia

... meaningful learning, critical thinking, and problem-solving skills among pharmacy students ...their deep approach scores may not necessarily imply they were neither self-aware nor capable of adopting ... See full document

8

Detection of Mobile Keyloggers Using Deep Learning

Detection of Mobile Keyloggers Using Deep Learning

... Zarni Aung, Win Zaw have worked on a framework is provided for classifying Android applications using machine learning techniques (K-means) whether they are malware or normal applications[2]. Android-based ... See full document

5

Deep Learning in Neuroradiology

Deep Learning in Neuroradiology

... context, deep learning is a supervised machine learning method that uses a specific architecture, namely some form of neural ...researchers. Deep learning allows such a classifier to be ... See full document

9

Deep Learning an Overview

Deep Learning an Overview

... A deep neural network can be defined as an artificial neuron network with multiple layers separating between the input and ...machine learning and bring about great ...the deep neural networks. The ... See full document

5

Deep verification learning

Deep verification learning

... Ideally you want to calculate the loss combined for the whole training set together, in order to take the best step in parameter updates. However, this requires lots of computational power using the large datasets ... See full document

41

Deep Belief Networks Using Convolution Neural Networks Algorithm

Deep Belief Networks Using Convolution Neural Networks Algorithm

... deep learning. Natural Language Processing (NLP) is a typical example; deep learning cannot understand a story, as well as a general request to an expert ...But deep learning ... See full document

8

Deep Learning: A Review

Deep Learning: A Review

... using deep learning method, is facial ...unique deep learning face recognition models ...a deep convolutional neural network algorithm capable to recognize not only age and gender, but ... See full document

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