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Caffe2 Quick Start Guide

You're reading from Caffe2 Quick Start Guide Modular and scalable deep learning made easy

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781789137750

Length 136 pages

Edition 1st Edition

Languages

C++

Tools

Caffe

Concepts

Deep Learning

Author (1):

Ashwin Nanjappa

View More author details

Table of Contents (9) Chapters

Preface

1. Introduction and Installation

2. Composing Networks FREE CHAPTER

3. Training Networks

4. Working with Caffe

5. Working with Other Frameworks

6. Deploying Models to Accelerators for Inference

7. Caffe2 at the Edge and in the cloud

8. Other Books You May Enjoy

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NVIDIA TensorRT

TensorRT is the most popular inference engine for deploying trained models on NVIDIA GPUs for inference. Not surprisingly, this library and its set of tools are developed by NVIDIA and it is available free for download and use. A new version of TensorRT typically accompanies the release of every new NVIDIA GPU architecture, adding optimizations for the new GPU architecture and also support for new types of layers, operators, and DL frameworks.

Installing TensorRT

TensorRT installers can be downloaded from the web at https://developer.nvidia.com/tensorrt. Installation packages are available for x86-64 (Intel or AMD 64-bit CPU) computers, PowerPC computers, embedded hardware such as NVIDIA TX1/TX2, and NVIDIA...

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Authors (1)

Ashwin Nanjappa

Ashwin Nanjappa

Ashwin Nanjappa is a senior architect at NVIDIA, working in the TensorRT team on improving deep learning inference on GPU accelerators. He has a PhD from the National University of Singapore in developing GPU algorithms for the fundamental computational geometry problem of 3D Delaunay triangulation. As a post-doctoral research fellow at the BioInformatics Institute (Singapore), he developed GPU-accelerated machine learning algorithms for pose estimation using depth cameras. As an algorithms research engineer at Visenze (Singapore), he implemented computer vision algorithm pipelines in C++, developed a training framework built upon Caffe in Python, and trained deep learning models for some of the world's most popular online shopping portals.

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