Dear Fellow Scholars, this is Two Minute Papers with Dr. Károly Zsolnai-Fehér.
If we study the laws of fluid motion and implement them in a computer program, we can create
and enjoy these beautiful fluid simulations.
And not only that, but today, with the amazing progress in computer graphics research, we
can even enrich our physics simulations with anisotropic damage and elasticity.
So what does that mean exactly?
This means that we can simulate more extreme topological changes in these virtual objects.
This leads to better material separation when the damage happens.
So it appears that today we can do a great deal, but these techniques are pretty complex,
and take quite a while to compute, and they typically run on your processor.
That’s a pity, because many powerful consumer computers also have a graphics card, and if
we could restate some of these algorithms to be able to run them on those, they would
run significantly faster.
So, do we have any hope for that?
Well, today’s paper promises a new particle data structure that is better suited for number
crunching on the graphics card, and is, hence, much faster than its predecessors.
As a result, this runs the Material Point Method, the algorithm that is capable of simulating
these wondrous things you are seeing here, not only on your graphics card, but the work
on one problem can be also be distributed between many-many graphics cards.
This means that we get crushing concrete, falling soil, candy bowls, sand armadillos,
oh my!
You name it.
And all this, much faster than before.
Now, since these are some devilishly detailed simulations, please do not expect several
frames per second kind of performance, we are still in the seconds per frame region,
but we are not that far away.
For instance, hold on to your papers because this candy bowl example contains nearly 23
million particles, and despite that, it runs in about 4 seconds per frame on a system equipped
with four graphics cards.
Four seconds per frame!
My goodness!
If somebody told this to me today without showing me this paper, I would have not believed
a word of it.
But there is more.
You know what, let’s double the number of particles and pull up this dam break scene.
What you see here is 48 million particles that runs in 15 seconds per frame.
Let’s do even more.
These sand armadillos contain a total of 55 million particles, and take about 30 seconds
per frame.
And in return, look at that beautiful mixture of the two sand materials.
And with half a minute per frame, that’s a great deal, I’ll take this any day of
the week.
And if we wish to simulate crushing this piece of concrete with a hydraulic press, that will
take nearly a hundred million particles.
Just look at that footage.
This is an obscene amount of detail.
And the price to be paid for this is nearly four minutes of simulation time for every
frame that you see on the screen here.
Four minutes you say?
Hmm, that’s a little more than expected.
Why is that?
We had several seconds per frame for the others, not minutes per frame.
Well, it is because the particle count matters a great deal, but that’s not the only consideration
for such a simulation.
For instance, here, you see with delta t something that we call time step size.
The smaller this number is, the tinier the time steps with which we can advance the simulation
when computing every interaction, and hence, the more steps there are to compute.
In simpler words, generally, time step size is also an important factor in the computation
time, and the smaller this is, the slower the simulation will be.
As you see, we have to simulate 5 times more time steps to make sure that we don’t miss
any particle interactions, and hence, this takes much longer.
Now, this one appears to be perhaps the simplest simulation of the bunch, isn’t it?
No, no, no.
Quite the opposite!
If you have been holding on to your papers so far, now squeeze that paper, because, and
watch carefully.
They wiggle.
They… wiggle!
Why do they wiggle?
These are just around 6 thousand bombs, which is not a lot, however, wait a minute…each
bomb is a collection of particles, giving us a total of not a measly 6 thousand, but,
a whopping 134 million particle simulation, and hence, we may think that it’s nearly
impossible to perform in a reasonable amount of time.
The time steps are not that far apart for this one, so we can do it in less than one
minute per frame.
This was nearly impossible when I started my PhD, and today, less than a minute for
one frame.
It truly feels like we are living in a science fiction world.
What a time to be alive!
I also couldn’t resist creating a slow-motion version of some of these videos, so if this
is something that you wish to see, make sure to visit our Instagram page in the video description
for more.
Thanks for watching and for your generous support, and I'll see you next
time!