 Dear Fellow Scholars, this is two minute papers with Dr. Karo Zsolnai-Fahir. Today, we are going to conquer some absolutely insane fluid and smoke simulations. A common property of these simulation programs is that they subdivide the simulation domain into a grid and they compute important quantities like velocity and pressure in these grid points. Normally, regular grid looks something like this, but this crazy new technique throws away the idea of using this as a grid and uses this instead. This is called an adaptive staggered tilted grid, an AST grid in short. So, what does that really mean? The tilted part means that cells can be rotated by 45 degrees like this and interestingly, they typically appear only where needed, I'll show you in a moment. The adaptive part means that the size of the grid cells is not fixed and can be all over the place. And even better, this concept can be easily generalized to 3D grids as well. Now, when I first read this paper, two things came to my mind, one that is an insane idea, I kinda like it, and two, it cannot possibly work. It turns out only one of these is true. And I was also wondering why? Why do all this? And the answer is because this way we get better fluid and smoke simulations. Oh yeah, let's demonstrate it through 4 beautiful experiments. Experiment number 1, Carmen Vortex Streets. We noted that the tilted grid points only appear where they are needed and these are places where there is a great deal of vorticity. Let's test that. This phenomenon showcases repeated vortex patterns and the algorithm is hard at work here. How do we know? Well, of course, we don't know that yet. So, let's look under the hood together and see what is going on. Oh wow, look at that. The algorithm knows where the vorticity is and as a result, these tilted cells are flowing through the simulation beautifully. Experiment number 2, Smoke Plumes and Porousnets. This technique refines the grids with these tilted grid cells in areas where there is a great deal of turbulence. And wait a second, what is this? The net is also covered with tilted cells. Why is that? The reason for this is that the tilted cells not only cover turbulent regions, but other regions of interest as well. In this case, it enables us to capture this narrow flow around the obstacle. Without this no AST grid, some of these smoke plumes wouldn't make it through the net. Experiment number 3, the boat ride. Note that the surface of the pool is completely covered with the new tilted cells, making sure that the wake of the boat is as detailed as it can possibly be. But, in the meantime, the algorithm is not wasteful. Look, the volume itself is free of them. And now, hold onto your papers for experiment number 4, thin water sheets. You can see the final simulation here, and if we look under the hood, my goodness, just look at how much work this algorithm is doing. And what is even better, it only does so, where it is really needed, it doesn't do any extra work in these regions. I am so far very impressed with this technique. We saw that it does a ton of work for us, and increases the detail in our simulations, and helps things flow through, where they should really flow through. Now, with that said, there is only one question left. What does this cost us? How much more expensive is this ASD grid simulation than a regular grid? Plus 100% computation time? Plus 50%? How much is it worth to you? Please stop the video and leave a comment with your guess. I'll wait. Thank you. The answer is none of those. It costs almost nothing and adds typically an additional 1% of computation time. And in return for that almost nothing, we get all of these beautiful fluid and smoke simulations. What a time to be alive. This episode has been supported by Lambda GPU Cloud. If you're looking for inexpensive Cloud GPUs for AI, check out Lambda GPU Cloud. They've recently launched Quadro RTX 6000, RTX 8000, and V100 instances. And hold onto your papers because Lambda GPU Cloud can cost less than half of AWS and Asia. Plus, they are the only Cloud service with 48GB RTX 8000. Join researchers at organizations like Apple, MIT, and Caltech in using Lambda Cloud instances, workstations, or servers. Make sure to go to lambdalabs.com slash papers to sign up for one of their amazing GPU instances today. Our thanks to Lambda for their long-standing support and for helping us make better videos for you. Thanks for watching and for your generous support, and I'll see you next time.