Build Your Own Deep Learning Inference Engine
Build Your Own Deep Learning Inference Engine
A Hands-On Guide to Implementing Operators, Graphs, and Optimization from Scratch
About the Book
KuiperInfer: Build Your Own Deep Learning Inference Framework from Scratch
KuiperInfer is an open source project that teaches you how to build a high performance deep learning inference framework in C++. Written by expert developer zjhellofss, this book guides you through implementing key components like computational graphs, common operators, and optimizations.
Follow along with the video tutorials on Bilibili to gain first-hand engineering experience. Understand techniques like im2col and kernel fusion to accelerate neural network inference. The well-structured C++ codebase features extensive unit testing.
This hands-on guide covers:
- Essential deep learning framework architecture
- Designing and implementing computational graphs
- Supporting operators like convolution, pooling, and fully connected layers
- Optimizing performance critical parts
- Deploying models like ResNet and YOLOv5
Whether you want to level up your skills or ace technical interviews, building your own inference framework from the ground up will give you a huge boost. Get started with KuiperInfer!
About the Author
Table of Contents
- The Basics
- Previewing and publishing
- Basic formatting
- Markdown and Markua
- Generate a preview version of your book
- Either read a tutorial, or just go for it!
- Thanks for being a Leanpub author!
- The Basics
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