Watch This Virtual Dinosaur Fall Into A Cactus! 🦖🌵
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Watch This Virtual Dinosaur Fall Into A Cactus! 🦖🌵

Two Minute Papers 30.10.2021 60 273 просмотров 3 314 лайков

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❤️ Check out the Gradient Dissent podcast by Weights & Biases: http://wandb.me/gd  📝 The paper "Medial IPC: accelerated incremental potential contact with medial elastics" is available here: https://yangzzzy.github.io/PDF/medial_IPC_SIG21.pdf https://dl.acm.org/doi/10.1145/3450626.3459753 🙏 We would like to thank our generous Patreon supporters who make Two Minute Papers possible: Aleksandr Mashrabov, Alex Haro, Andrew Melnychuk, Angelos Evripiotis, Benji Rabhan, Bryan Learn, Christian Ahlin, Eric Haddad, Eric Martel, Gordon Child, Ivo Galic, Jace O'Brien, Javier Bustamante, John Le, Jonas, Kenneth Davis, Klaus Busse, Lorin Atzberger, Lukas Biewald, Matthew Allen Fisher, Mark Oates, Michael Albrecht, Michael Tedder, Nikhil Velpanur, Owen Campbell-Moore, Owen Skarpness, Rajarshi Nigam, Ramsey Elbasheer, Steef, Taras Bobrovytsky, Thomas Krcmar, Timothy Sum Hon Mun, Torsten Reil, Tybie Fitzhugh, Ueli Gallizzi. If you wish to appear here or pick up other perks, click here: https://www.patreon.com/TwoMinutePapers Thumbnail background design: Felícia Zsolnai-Fehér - http://felicia.hu Meet and discuss your ideas with other Fellow Scholars on the Two Minute Papers Discord: https://discordapp.com/invite/hbcTJu2 Károly Zsolnai-Fehér's links: Instagram: https://www.instagram.com/twominutepapers/ Twitter: https://twitter.com/twominutepapers Web: https://cg.tuwien.ac.at/~zsolnai/

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Intro

Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér. Today we are going to do this and this on a budget.

Simulation

Today, through the power of computer graphics research works, we can simulate all these amazing elastic interactions. If we are very patient that is, because they take forever to compute. But, if we wish to run these simulations quicker, what we can is increasing something that we call the time step size. Usually, this means that the simulation takes less time, but is also less accurate. Let’s see this phenomenon through a previous method from just a year ago. Here, we set the time step size relatively small, and drop an elastic barbarian ship onto these rods. And this is a challenging scene because the ship is made out of half a million tiny elements, and we have to simulate their interactions with the scene. How does this perform? Uh-oh. This isn’t good. Did you see the issues? Issue number one is that the simulation is unstable. Look. Things remain in motion when they shouldn’t. And two, this is also troubling.

Solution

Penetrations. Now, let’s increase the time step size. What do we expect to happen? Well, now, we advance the simulation in bigger chunks, so we should expect to miss even more interactions in between these bigger steps. And…whoa! Sure enough. Even more instability, even more penetration. So, what is the solution? Well, let’s have a look at this new method and see if it can deal with this difficult scene. Now, hold on to your papers, and…wow, I am loving this. Issue number one, things coming to rest is solved, and, issue number two, no penetrations. That is amazing. Now, what is so interesting here? Well, what you see here should not be possible at all, because this new technique computes a reduced simulation instead. This is a simulation on a budget. And not only that, but let’s increase the time step size a little. This means that we can advance the time when in bigger chunks when computing the simulation, at the cost of potentially missing important interactions between these steps. Expect a bad simulation now, like with the previous one, and…wow, this is amazing. It still looks fine. But we don’t know that for sure, because we haven’t seen the reference simulation yet. So, you know what’s coming. Oh yes! Let’s compare it to the reference simulation that takes forever to compute. This looks great. And, let’s see… this looks great too. They don’t look the same, but if I were asked which one reference is, and which is the cheaper, reduced simulation, I am not sure if I would be able to tell. Are you able to tell? Well, be careful with your answer, because I have swapped the two. In reality, this is the reference, and this is the reduced simulation. Were you able to tell? Let me know in the comments below. And that is exactly the point! All this means that we got away with only computing the simulation in bigger steps. So, why is that good? Well, of course, we get through it quicker! Okay, but how much quicker? 110 times quicker. What? The two are close to equivalent, but this is more than a 100 times quicker? Sign me up, right away! Note that this is still not real time, but we are firmly in the seconds per frame domain, so we don’t need an all nighter for such a simulation, just a coffee break. Now note that this particular scene is really suited for the new technique, other scenes aren’t typically a hundred times faster, but, worst case scenario is when we throw around a bunch of furballs, but even that is at least ten to fifteen times faster. What does that mean? Well, an all-nighter simulation can be done maybe not during a coffee break, but during a quick little nap. Yes, we can rest like this tiny dinosaur for a while, and by the time we wake up, the simulation is done, and we can count on it being close to the real deal. So good! Just make sure to keep the friction high while resting here, or otherwise…this happens. So, from now on, we get better simulations, up to a hundred times faster. What a time to be alive! Thanks for watching and for your generous support, and I'll see you next time!

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