# A 1,000,000,000 Particle Simulation! 🌊 ## Метаданные - **Канал:** Two Minute Papers - **YouTube:** https://www.youtube.com/watch?v=jRMy6lxlqjM - **Дата:** 04.09.2022 - **Длительность:** 6:35 - **Просмотры:** 695,679 - **Источник:** https://ekstraktznaniy.ru/video/13461 ## Описание ❤️ Check out Weights & Biases and sign up for a free demo here: https://wandb.com/papers 📝 The paper "A Fast Unsmoothed Aggregation Algebraic Multigrid Framework for the Large-Scale Simulation of Incompressible Flow" is available here: http://computationalsciences.org/publications/shao-2022-multigrid.html ❤️ Watch these videos in early access on our Patreon page or join us here on YouTube: - https://www.patreon.com/TwoMinutePapers - https://www.youtube.com/channel/UCbfYPyITQ-7l4upoX8nvctg/join 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Balfanz, Alex Haro, Andrew Melnychuk, Benji Rabhan, Bryan Learn, B Shang, Christian Ahlin, Eric Martel, Geronimo Moralez, Gordon Child, Ivo Galic, Jace O'Brien, Jack Lukic, John Le, Jonas, Jonathan, Kenneth Davis, Klaus Busse, Kyle Davis, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Michael Albrecht, Michael Tedder, Nevin Spoljaric, Nikhil Velpanur, Owen Campbell-M ## Транскрипт ### Introduction [] Dear Fellow Scholars, this is Two Minute  Papers with Dr. Károly Zsolnai-Fehér. Today we are going to find out  whether it is possible to write   a fluid simulation on a computer that  showcases no less than 1 billion particles!    So, is it this one? Maybe! Of  course, I will tell you in a moment. But note that there are plenty of fluid and  physics simulation research papers out there. This   is a mature research field, and we can do so  much today. Here are 4 of my favorite works ### Reality [0:33] in this area, and then, we will talk  about what is the problem with them. One, in reality, we can experiment with whatever  objects we have at our disposal, but in a   simulation, we can do anything. Including changing  the physical parameters of these objects, and   thus, this previous work can simulate three jello  blocks of different stiffness values. So cool! ### Strong Two Way Coupling [1:01] Two, this technique simulates strong two-way  coupling. What does that mean? Well, you see a   simulation here that doesn’t have it. So is this  correct? Well, not quite. The honey should be   supporting the dipper, and it not only falls, but  it falls in a very unnatural way. Instead, this   technique can simulate strong two-way coupling,  and finally it gets this right. And not only that,   but what I really love about this is that it also  gets small nuances right. I will try to speed up   the footage a little, so you can see that the  honey doesn’t only support the dipper, but the   dipper still has some subtle movements both  in reality and in the simulation. A+. Love it. ### Baking [1:50] Three, we can even simulate the physics of baking  on a computer. Let’s see…yes, expansion and baking   is happening here. Are we done? Well, let’s have  a look inside. Yup, this is a good one. Yum! And perhaps my favorite work in this area is  this. Four, now, you may be wondering, Károly, ### Real Video [2:15] why are you showing a real video to me? Well,  this is not a real video. This is a simulation.    And so is this one. And hold on to your papers,  because this is not a screenshot taken from the   simulation, nuh-uh. No sir. This is a real photo.   How cool is that? Whenever you feel a little sad,   just think about the fact that through the  power of computer graphics research, we can   simulate reality on our computers. At least,  a small slice of reality. Absolutely amazing. ### The Problem [2:54] However, there is a problem. And the  problem is that all of these simulations   have a price. And that price is time.   Oh yes, some of these works require   long all-nighters to compute. And, unfortunately, as a research   field matures, it gets more and more difficult to  say something new, and improve upon previous work.    So, can we expect no more meaningful speedups  at this point? Are we at a saturation point? Well, just two years ago, we talked about  a technique that was able to simulate   100 million particles. My goodness, this was  absolutely amazing. And now, just a couple   more papers down the line, we go 10x. Yes, that’s  right! Here is an even better one that is finally   able to simulate 10 times as many particles. Yes,  1 billion particles. Now, hold on to your papers,   and let’s marvel together  at this glorious footage. Yes, this is a scene with 1 billion. Can that  really be? Well, I can hardly believe it,   but here it is. Look, that is a beautiful  simulation. I love it. Now, this technique is ### Speed [4:17] not only able to simulate this many particles, but  it also does it faster than previous techniques.    The speedup factor is typically 3x, but  not on honey buckling scenes. Why is that? Well, the more viscous the fluids  are, at the risk of simplification,   let’s say that the more honeylike they are,  the higher the speedup. How much higher?    What? Yes, that’s right. On this honey buckling  scene, it is 15 times faster! What took   nearly 2 all nighters now only takes an hour?   That is insanity. What a time to be alive! Now, note that these simulations still  take a while, about half a minute per   frame for 150 million particles, and about  ten minutes per frame for a billion particles.    But for a simulation of this quality? That  is not a lot at all! Sign me up, right now! ### Conclusion [5:19] So, as you see even for such a mature research  field as fluid simulations in computer graphics,   the pace of progress nothing short of amazing.   You see a lot of videos on what AI techniques   are capable of today, and what you see here  is through the power of sheer human ingenuity. So, what do you think? Does this get your  mind going? Let me know in the comments below! ### Sponsor [5:47] Thanks for watching and for your generous  support, and I'll see you next time!