I Built a Deep Learning Framework from Scratch in C++ and CUDA (And Beat PyTorch's Speed Multiple Run)

If you work in AI today, you are almost certainly using PyTorch or TensorFlow. They are incredible tools, but they are also massive black boxes.

As an AI developer, I realized that relying solely on these frameworks meant I didn't truly understand the underlying hardware realities, memory mechanics, or how the math actually maps to GPU acceleration.

So, I decided to strip away the abstractions. Over the last few months, I built Aakaar—a deep learning framework developed completely from scratch using native C++ and CUDA, wrapped in Python for ease of use.

Here is how I built it, the engineering challenges I faced, and how it surprisingly edged out PyTorch in a direct benchmark.

The Architecture: Hand-Coding the Math