Implementing a Neural Net in CUDA From Scratch, Part 1: Introduction

In this series, we are going to write a neural net completely from scratch (down to rudimentary tensor operations) with Nvidia's CUDA, the GPU parallel computing platform behind modern deep learning libraries. You can find the GitHub repository here. Audience: Familiarity with core concepts of C, such as pointers and object-oriented programming, is needed, and you must be thoroughly comfortable with neural networks and their various aspects like backpropagation. However, you need not know any CUDA or parallel programming, and everything will be covered in the upcoming articles. Without further ado, let's get coding!