Deep Neural Network Hardware

FPGA Implementations Of Neural Networks
FPGA Implementations of Neural Networks Edited by AMOS R. OMONDI 1.2. Review of neural-network basics 3 1.3. ASIC vs. FPGA neurocomputers 9 1.4. various aspects of the hardware implementation of neural networks (in both ... Read Here

A P M DEEP NEURAL NETWORKS - OpenReview
We show that PALEO is robust to the choice of network architecture, hardware, software, communication deploying deep neural networks.2 PALEO applies broadly to a wide variety of neural are two major parallelization strategies when it comes to training deep neural network models at ... Retrieve Document

High Performance Hardware For Distributed Deep Learning - YouTube
In this video from Switzerland HPC Conference, Gaurav Kaul from Intel presents: High Performance Hardware for Distributed Deep Learning – System Benchmarking ... View Video

Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network ... - UBC
Cnvlutin: Ineffectual-Neuron-Free Deep Neural Network Computing a value-based approach to hardware acceleration that eliminates most of these ineffectual operations, improving performance and Deep Neural Networks (DNNs) ... View This Document

How To Profit From The A.I. Revolution (BOTZ)
Our burning desire to create an advanced civilization through technology has led us to this point. For good or for bad, the artificial intelligence (AI) revolution is upon us. If science fiction ... Read News

For Machine Learning, It's All About GPUs
Isn’t it curious that two of the top conferences on artificial intelligence are organized by NVIDIA and Intel? The answer is that nowadays, for machine learning (ML), and particularly deep learning ... Read News

Efficient Memory Compression In Deep Neural Networks Using ...
In Section 4, the architecture of the custom deep neural network hardware with memory compression is described. Section 5 presents the experimental results in 65nm LP and 40nm LP CMOS, and the paper is concluded in Section 6. 2. DNN neural network layers, ... Read Here

ICLR 2016 Best Paper Award: Deep Compression By Song Han
Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. ... View Video

RECENT ADVANCES IN DEEP LEARNING FOR MEDIA & ENTERTAINMENT
RECENT ADVANCES IN DEEP LEARNING FOR MEDIA & ENTERTAINMENT . 2 AGENDA What is Deep Learning? Recent advances in DL for Media & Entertainment Applications Hardware and Software Q&A . 3 DEEP NEURAL NETWORK “MODEL ... Doc Retrieval

Spiking Deep Convolutional Neural Networks For Energy ...
Spiking Deep Convolutional Neural Networks for Energy-Efficient morphic hardware, such as the ones being developed under (CNN) is a supervised deep-learning neural network with multiple layers of similarly structured convolutional feature extraction operations fol- ... Access Document

Efficient Implementation Of Neural Network Systems ... - Altera
Efficient Implementation of Neural Network Systems Built on FPGAs, and Programmed with OpenCLTM OpenCL Efficient Neural Networks Deep learning neural network systems currently provide the best solution to many in specific systems. Differences in hardware, software, ... Read Here

The Implementation Of A Deep Recurrent Neural Network ...
The implementation of a Deep Recurrent Neural Network Language Model on a Xilinx FPGA 1 Abstract—Recently, FPGA has been increasingly applied to ... Retrieve Here

Restructuring Of Deep Neural Network Acoustic Models With ...
Restructuring of Deep Neural Network Acoustic Models with Singular Value Decomposition Jian Xue, capability of deep neural network (DNN) all types of hardware, ... Get Document

From Model To FPGA: Software-Hardware Co-Design For Efficient ...
Co-Design for Efficient Neural Network Acceleration Kaiyuan Guo1,2, Lingzhi Sui1, Jiantao Qiu2, • New Platform Expected for Deep Learning • Trend in Neural Network Design Algorithm designer need to know nothing about hardware Generates instructions instead of RTL code ... Read Document

Traditional Computer Vision Vs. Deep Neural Networks
Comparing Deep Neural Networks and Traditional Vision Algorithms in Mobile Robotics various deep-neural network architectures for computer vi- (navigation, ROS, hardware) COMPUTER VISION BACKGROUND Computer vision can be succinctly described as finding ... Read Here

The Mathematics Of Deep Learning - Johns Hopkins University
The Mathematics of Deep Learning •It guarantees that even a single hidden-layer network can represent any when training deep neural networks. Non-Convex Optimization •[Choromaska et al, AISTATS’15] (also [Dauphin et al, ... Access Full Source

A Self-Driving Robot Using Deep Convolutional Neural Networks ...
A Self-Driving Robot Using Deep Convolutional Neural Networks on Neuromorphic Hardware Tiffany Hwu ⇤†, Jacob Isbell‡, Nicolas Oros§, and Jeffrey Krichmar¶ ... Fetch Full Source

EIE: Efficient Inference Engine On Compressed Deep Neural Network
EIE: Efficient Inference Engine on Compressed Deep Neural Network ploy on embedded systems with limited hardware resources and power budgets. While custom hardware helps the computation, fetching weights from DRAM is two orders of magnitude more ... Fetch Doc

AlphaGo - Wikipedia
According to AlphaGo's David Silver, the AlphaGo research project was formed around 2014 to test how well a neural network using deep learning can compete at Go. An early version of AlphaGo was tested on hardware with various numbers of CPUs and GPUs, ... Read Article

Rev Lebaredian On NVIDIA GameWorks And How It Will Help Democratize Game Development
It’s been a while since we first interviewed Rev Lebaredian, NVIDIA’s Vice President of GameWorks and Lightspeed Studios. Earlier this year we started talking with the fine folks at NVIDIA to ... Read News

Local Distributed Mobile Computing System For Deep Neural ...
Mobile Deep Neural Network. (ReRAM) to perform neural computations in memory and gave dedicated hardware-level architec-ture for executing deep neural networks in both the forward and backward procedures. [12] accel- ... Fetch Full Source

Efficient Processing Of Deep Neural Networks: A Tutorial And ...
That enable efficient processing of deep neural network to improve energy-efficiency and throughput without sacrificing performance accuracy or increasing hardware cost are critical to enabling the wide deployment of DNNs in AI systems. ... Fetch This Document