Thread by @ProjectPhysX

I did @officialBinotto's @ScuderiaFerrari SF71H in @FluidX3D #CFD on a supercomputer.
- 1s in real life @ 100km/h
- 20s 4K60 video (3x)
- 14h compute on 8x @AMDInstinct #MI200 64GB #GPU
- 144TB data visualized
What I found is absolutely wild. A #SimulationFriday #F1 thread: 🧵1/5

The @FluidX3D simulation was done at 10 billion voxel grid resolution (2152×4304×1076), over 217k time steps (1 second), at Re=3.75M (100km/h).
The fins on the front spoiler create a turbulent boundary layer and kick up it up onto the front wheels to reduce drag. 🧵2/5

The streamlined chassis guides airflow under the spoiler to create down force. The halo - one of the best additions to the sport in terms of safety - is rather aerodynamic.
Each frame of the video is 120GB, 144TB for 1201 frames. @FluidX3D renders the data directly in VRAM. 🧵3/5

With commercial #CFD software, where a licence can cost $120k, such a detailed simulation would take months. I did it in 14 hours, including rendering, on 8 #GPU​s. I have put the C++/#OpenCL source code of @FluidX3D on @github, for free: github.com/ProjectPhysX/F…
🧵4/5

The 3D model is from Rafael Rodrigues: thingiverse.com/thing:2990512/…
The video is available on YouTube in 4K60, along with more details on the simulation setup and methods:
🧵5/5