We built a CUDA emulator that profiles GPU code with zero hardware

Quick context on what this actually does

This is not static analysis. It runs your CUDA kernel in a CPU-backed simulator and predicts how it behaves on real GPUs

Basicly it uses a tile model tied to L2 size and SM limits

Right now it covers 80+ NVIDIA architectures and the Mean error on exec time is around 1–2% on our test kernals that we made 'more info in the blog'

It still struggles with dynamic parallelism but I will figure it out soon