here it is my friends concrete proof that satire truly is dead the GPU beside
me contains 36 NVIDIA Grace Blackwell
Super Chips and is estimated to cost over $3
million now obviously the big heat sink
on the side is illustrative you won't be installing one of these in your gaming
rig unless uh you happen to have a 100,000 watts of power on tap and a
building scale liquid cooling system but
many of the Technologies NVIDIA is introducing here will benefit Gamers the
the biggest one isn't really obvious until you go under the hood in my hands
is one gb200 super chip now some of this we've
seen before like this 72 core NVIDIA
Grace CPU but these puppies right here
these are all new and very very exciting
do you guys see this tiny tiny line here thinner than the width of a human hair
that is the gap between the two black
well dyes that make up a b200
GPU wait a second GPU is that not two
gpus yes but also no while SLI might be
dead for consumers NVIDIA has been hard at work creating interconnects that run
at absolutely dizzying speeds allowing
multiple G GPU dies to now act as a
single GPU that allow multiple gpus to
act as a single super chip and that
allow multiple Super Chips to act as a
single oh no to act as a single cohesive
processing unit and it is going to unlock gaming experiences and more that
are going to blow your mind you speak English right yes I speak English
how can I help
you can you also speak segue to our
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we'll get to the Demos in a bit but first let's take a closer look at the
product that is turning Global Tech media into Jensen hang's swifties NVIDIA
chose not to disclose the number of cacor tenores or even the size of the
ony caches of their new b200 Blackwell
GPU but they did give us some numbers to work with Apples to Apples they expected
to hit around 10 petaflops at fp8 sparse
which puts it roughly 2 and half times faster than last gen Hopper also each of
these is expected to draw about 1,000 Watts hence the
uh liquid cooling each of our gpus gets
192 GB of hbm 3E high-speed memory
running at a casual 8 terabytes a second
and is equipped with 1.8 terabyte per second Envy link and these numbers get
even more ridiculous when we look at the super chip as a whole each super chip
has two b200 gpus and a gray CPU for a
total of 72 ARM CPU cores 864 GB of RAM
and draws a total of 2700 Watts oh and
by the way each of the 18 of these
Blackwell compute nodes that make up an nvl 72 rack contains two Super Chips
good Lord in California the rack that I
was standing to in the intro would cost a whopping $30 an hour to run or about
A4 million doar a year assuming you're paying residential energy rates speaking
of running they literally need to take these demos to another room so I'm going
to have to tell you about the spline on our way out of here we got our hands
however temporarily on what NVIDIA is calling the spline of their nvl 72 rack
this here contains 5,000 wires totaling
over 2 miles mil and is cleverly laid out to optimize the latency and power
efficiency see the networking all goes in the middle right here and the
Blackwell compute nodes like the one they just took from us go at the top and
the Bottom now they could have used fiber optics except that uh that would
have cost them a casual 20,000 watts of additional power
consumption so uh clever layout for the
win put it all together and you've got a w
72 Blackwell gpus 2600 gray CPU cores
132 terab of hbm 3E memory with over
half a pyte per second of aggregate bandwidth that's good for 720 pedop
flops of fp8 training delivering results upwards of 30 times faster than a
previous generation hgx h100 and if you
didn't notice with perfect linear scaling something that is only possible
when integrating your system this tightly even the placement of the
individual blades matter on our super micro rack that we're looking at here
you can see that they've got 10 up top and eight at the bottom with the nine
nvlink switch units sandwiched in between that's because timing the
electrical signals matters a lot and is easier on a more symmetrical setup now
unfortunately NVIDIA didn't have a switch for us to show you they'll have
to be represented by this piece of plastic but each of the nine units can
handle 14.4 terabytes per second of NV
link it is so integrated that NVIDIA
says they think of this entire rack as
one massive power hungry single GPU and
it's kind of hard to argue otherwise other than that most of the time it's
not doing graphics and I thought that's what the G was for and the craziest part
is we haven't even looked at the craziest systems yet that was all mgx a
standard set of reference designs that's intended to be compatible with multiple
Generations hence the mg hgx is a whole
different beast in this or on it it is
eight Blackwell b200 gpus with a
combined 1.44 terabytes of GPU memory absolutely
ridiculous but the difference between this and what I just showed you is
completely gone is any trace of Grace CPUs this is purely a GPU board because
this insanity is meant to be integrated into a partner system like say from
Super Micro now NVIDIA does sell their
own dgx unit with this board and the
rest of the components that make up a complete system but that's mostly
intended to be a reference system these
8 gpus get combined with Envy link just
like the the rack setup for a whopping
72 peda flops of FPA training while
drawing nearly really 10,000 Watts now
naturally this much power is a little
hard to cool which is why it's so massive but the good thing about it is
it doesn't require messing around with water or racks with 120,000 watts of
power if you're installing these into an existing data center since
those practically don't exist so you've got to spread them out a little bit
according to your power budget which means you need networking and that is
where NVIDIA's new hardware networking products come in this Ethernet switch
will do something in the neighborhood if I think it's like 50 terabits per second
of switching which is all really cool but what are we doing with this exactly
I don't know how about Healthcare the tools I'm looking at right here use
machine learning to approximate viral protein folding generate potential drug
molecules to disable them and then test rapidly accelerating drug development oh
and this is cool finding exactly what it is you're supposed to be taking a
picture of with the ultrasound wand can take a bit of time why not let the
machine identify it for you that's a left ventricle right cool know what else
is cool simulations like the one we're
living in behind me is Earth 2 a climate
and weather simulation program that can run at such a high resolution that you
can determine what's going to happen on a 1 km x 1 km basis is which is pretty
cool but what if you need to simulate the movement of hot and cold air on a
molecular level well you can do that too
that is nuts which is all cool but what
if I can't afford a dgx or an mgx to
train those data sets well you can still
use or experience NVIDIA's new Nims or
NVIDIA inference microservices Nims are
pre-trained and pre-optimized containerized AI models that you can
download and deploy for any number of use cases and if that all sounded like
gobleg um let's go back to that bilingual demo for a second facial
animations can be an extremely timec consuming component of game development
and are one of the big reasons that localization can be such a challenge the
Nim in use here allows automatic mapping
of speech to mouth animations and facial expressions meanwhile this guy takes
things to two steps further using Nims for automatic speech recognition and
facial animations but also a third one that I think is perhaps the most
interesting to me there's a major concern right now in the games industry
that AI is going to take jobs away from writers but this guy uses a n for data
retrieval that is part of inworld ai's
platform and this is really cool instead of him just crapping out whatever
response chat GPT might throw at you he's actually got an extensive backstory
that does need to be written by a human writer in order to give you a
personality and context specific
information that will help you advance the story have you ever tried any of the
fine merchandise from LTT
store.com now that is really cool and
we're just scratching the surface right now over time NVIDIA is going to be
looking to The Gaming Community both developers and Gamers for inspiration
for what to do with these and oh I've got one more really cool demo G assist
here might just be a tech demo at the moment but it's a pretty darn compelling
one how do I craft a stone
axe okay that is cool but what dinosaur
am I looking at right
now okay that's kind of sick and what's
cool is the image recognition and I believe the voice to text are both
running locally on this RTX series GPU I
don't know about you guys but I think this is so cool that I don't know what to say way to our sponsor back Blaze
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if you guys enjoyed this video uh why not check out our video from last
computex showing off the grace CPUs and their last gen Super Chips we got a
little bit more into the weeds and it was very very cool