#simulationfriday — Public Fediverse posts

The red lightning bolt continues: #FluidX3D has passed 3000 Stargazers on #GitHub - from 82 countries! 🖖🥳⭐
Releasing this software for free really has turned out win-win: I've received so much valuable feedback, and answered with as many bug fixes and updates, with many more to come. I am enabling cutting-edge #CFD simulations for everyone, with very little hardware resources, on literally every computer that has a #GPU, regardless of vendor.
👉 https://github.com/ProjectPhysX/FluidX3D
#SimulationFriday #OpenCL

This is wild: #FluidX3D can "SLI" together 🔵 #Intel Arc A770 + 🟢 #Nvidia Titan Xp, pooling 12GB+12GB of their VRAM for one large 450M cell #CFD simulation. Top half on A770, bottom half on Titan Xp. They seamlessly communicate over PCIe. Performance is ~1.7x of what either #GPU could do on its own. 🖖😋🖥🔥
#OpenCL shows its true power here - one implementation works on literally all GPUs at full performance, even at the same time. Happy #SimulationFriday!
https://youtu.be/PscbxGVs52o

I haven't posted a #CFD simulation in a while; well things are a little different now with the new job. So here is a raytraced #FluidX3D simulation, 109 million cells, running on the #INTEL Arc A750 #GPU! Happy #SimulationFriday! 🖖😁🟦
https://youtu.be/RRWZXFk88hA
FluidX3D on #GitHub: https://github.com/ProjectPhysX/FluidX3D

The Pioneers used to ride these for miles! 🖖🧐💺
Aerodynamics of an arm chair at 50km/h. 1 second real-time, 3 billion cells, 66k timesteps, 3 hours on 4x Nvidia #A100 40GB #GPU​s. Happy #SimulationFriday!
https://youtu.be/vD7Tj7H17jA
#FluidX3D #CFD: https://github.com/ProjectPhysX/FluidX3D

Here is the most detailed #CFD #simulation of a #quadcopter ever, at 3 Billion microscopic (0.2mm)³ grid cells. Compute time was 8 hours on 4 Nvidia #A100 40GB #GPU​s, for 86k timesteps + 5400 videoframes. Happy #SimulationFriday!
https://youtu.be/QvpNUdX8LNY

#FluidX3D on #GitHub: https://github.com/ProjectPhysX/FluidX3D

Kudos to Musa Maluegha for the awesome #CAD model: https://www.thingiverse.com/thing:2540161/files

I've always wanted to do a helicopter! 🖖😎🚁
Here it is, a Bell 222 in #CFD. With massive 10 billion cells. 71 TeraByte data visualized. Just for #SimulationFriday fun, because I can! Took 6.4 hours on 8x AMD Instinct #MI200 #GPU​s.
https://youtu.be/BStzTRmLW7Q
#FluidX3D on GitHub: https://github.com/ProjectPhysX/FluidX3D

It's #SimulationFriday again! Here is a real time @FluidX3D #CFD simulation of a #Cessna 172, 20M cells, on my old Titan Xp Pascal #GPU. 33 lines of code for this setup.
For #FluidX3D v2.8 I'm improving composite geometries with moving parts, and I'm adding transparent rendering.
https://youtu.be/Gd_MEHPecw0

Testing something... Siemens Simcenter takes 12 hours on 8x A100 for a #CFD simulation of a car, at 55M cells & 16600 (?) time steps. How fast is #FluidX3D for the same thing? *Checks watch* 147 seconds. And that is with only one A100 #GPU. Happy #SimulationFriday! 🖖😋
https://youtu.be/2R2aRO1MaqA

1200 rendered frames, 4 revoxelizations per frame, 10 time steps per revoxelization. 220000000 cells, 3.2TB data. An average gaming #GPU does this #CFD #simulation in 45min. For $0. This #SimulationFriday, #FluidX3D blows the competition out of the water. 🖖😎
https://youtu.be/aqG8qZ_Gc4U #OpenCL

In my 2022 JSC proposal I wanted to do the raindrop on an entire 8x AMD Instinct MI200 node, at a mental 8 billion (!) voxels. I have now successfully extended the #FluidX3D free-surface code to multi-#GPU. Enjoy this #SimulationFriday #CFD gem!💧
https://youtu.be/oC6U1M0Fsug

#OpenCL compute (34650 LBM time steps at 2122×2122×1804 resolution) + seamless domain decomposition rendering took 5.5 hours.

I'm preparing the multi-GPU code for the update on GitHub. Stay tuned!