First of all, thank you very much for your presence and your time, your valuable time.
Not everybody may know Super Micro, so I'm just going to glance at a few slides.
Because of customer preference, the last years we have grown at a 40% rate.
We thank all of our end customers and partners to help us accomplish that.
It has meant a very important growth in our campus in California as well as in Asia and
in Europe.
We thank all of you for your support.
If you go back to history at Super Micro in 1993, we commenced by making a custom board
of a high performance.
And the end customer has been driving us to higher, higher complexity of the solution.
From a chassis, from a power supply, from an integrated solution that you can now get
delivered from any of our facilities.
Today we can deliver you our own rack, fully assembled systems at your delight.
At this show we presented a very advanced system with eight nodes in a tree U.
And this is what basically we're understanding of customers.
And these kind of systems are the ones that are giving us a challenge to go through exascale
and also the power consumption and the cooling of all of that.
So I want to take you that all of our product line, yes and let's concentrate in one point,
which is how we should take direct considerations as we build systems that are pushing the limit
of cooling power consumption and compute power.
An example that I present today is if you take one of our racks, our 42U racks and fully
populate that with blades, you will end up with 120 processors, Intel processors.
And you have a variance on these Intel processors, a key consideration to make in this election
of the processor.
Either you take the 38 watt processor or you take the 95 watt processor and that gives
you a variance from 4,500 watts to 11 kilowatts only in processor in a rack configuration
of this nature.
As well it happens on the memory modules.
If you were to select a different memory module, when you're running this for a benchmark or
you're running this with life applications, you're going to be challenged between how
many watts you're going to end up.
And it's a dramatic ratio.
And I'm going to show you a particular example how memory behaves in an application.
Surely if you were to use GPUs or MICs, multi-integrated cores, you would be challenged by having 120
units in such a configuration where the power consumption could reach between 220 to 250.
And this is what we have certified thus far in this configuration.
I'm certainly certain end customers will challenge for us to further take that 250 watts to possibly
320.
In some of our other chassis we're having end customers asking us and forcing us to
dissipate up to 320 watts per GPU or MIC.
So therefore in a rack you have the 60 blades, the infrastructure for the blade to support
the memory and the processors.
It's around 45 watts each.
And we have all the necessary interfaces at QDR, InfiniBand QDR.
And those take also electrical power.
So based on our blade server series, we're challenging how we can just concentrate in
GPUs and using very efficient power supplies, integrated switches, and our GPU blade.
We're trying to find and help our customers for power usage effectiveness.
And yes, usage effectiveness is a ratio between the total facility power and IT equipment.
The end customer likes to use this point of reference.
But also he's focusing to the IT equipment power and he wants to have maximum efficiency.
Therefore the considerations of what memory and how I drive the memory, what processor
should I select so I can get how many watts for how many teraflops or gigaflops in this case.
We have particular examples with end customers where the PUE has been measured for the last
12 months at 107 by using very effective cooling ways.
This example is being used with our 2U-Tween server.
And for the last 12 months there's proof that you can reach such efficiency with air cooling
and very effective heat exchangers and very effective industrial well-established cooling
systems, for example evaporation.
But let's not forget, as I said, the actual consumption of the servers where we can assess
in many cases the kind of processor we should use for the gigaflops we're going to get.
And I have a particular example here that's the actual testing from one of our end customers
of an application.
You see how the end customer running the same application with three memory configurations,
he could have a difference up to 270 watts.
Just by making a different selection on 16 DIMMs or 12 DIMMs of memory, he can have a
dramatic delta of watts.
And many times these are not scrutinized at the moment of installation.
After we did some further tuning to the node, this ratio changed.
And this is the kind of points we want to address as we build these configurations to
get to the point of component selection makes a dramatic difference.
So you can get the flops you want, with the watts you want, and the costs you want.
PUE efficiency is essential to a quantum leap, but surely we have to be backed up by that
the power consumption of the components as well as off-the-shelf components.
This is so important to the end customer.
This is what the clear message we get for the end customer.
And we're working hard with all the products I just showed in the early slides.
I think I have still a few minutes left, but I'm done with my presentation.
So for the sake of the audience, we can commence questions if you like.
Thank you, Rammar.
Thank you.
Thank you, Rammar.
First inquisitor is Frank Piedron, please.
Thank you, Rammar.
Thank you.
And then, essentially, in two parts.
You mentioned that you achieved the PUE of 1.07 in a very defined environment.
Is it correct to state that achieving good PUEs for such kind of a system absolutely
requires a very close interaction between the rack maker or the rack configurator and
the persons who are deciding the room where the rack will end up in in the environment
of the room?
That's the first part of the question.
And given the fact that we are talking a lot about energy efficiency, and especially in
Germany and Europe, a move from fossil fuels more to renewable energies, did you consider
to combine your systems with kind of container solutions supplying energy from renewable
sources, maybe windmills, maybe PV system, and something like this, as an overall solution
for a customer who has an absolute need for given situations of a very green low PUE
solution?
Thank you for the question.
That is a great opportunity to further expand on this object.
So I'll address the first point.
Surely, any data center and any configuration of more than 800 servers requires a special
environment, a special planning, and all the considerations.
And surely, making sense of where you get the source of energy is essential to our progress.
So answering the first question, this is our end customer, University Frankfurt, who has
basically leveraged an industrial facility, and we have helped in a minor way by providing
very efficient servers to the specially designed cooling system they have.
So you have a cross-intersection of University Frankfurt making special developments in
the cooling system, and also making a small collaboration in adding to that point.
And it was selected by University Frankfurt, an industrial site, precisely to leverage
electrical source, or energy source.
The site is where Bayer and many other industrial companies are present, therefore is the most
effective energy source there is.
And this is where you have the convergence of multiple energy sources.
They use all kinds of energies because they already have the challenge by producing paints,
by producing chemicals, pharmaceuticals.
So we're next in the middle engraving to this environment, which is very efficient.
So I hope that I have addressed both points.
Next, Peter Kranselmuller.
Okay.
So you were mentioning in your conclusions that choosing the right components is the
key to energy savings and all that.
I was wondering, I mean, that seems obvious, but I was wondering where is the biggest win?
Where do you see the biggest win?
That was not clear from your presentation.
Well, that's a good point, and thank you for allowing me to make it clear.
Surely, when you're building these kind of configurations, you have the thousands of
components.
For example, in processors, we have 120 processors in this configuration.
We have so many GPUs, also 120 GPUs.
It depends how much watts you're putting in all points.
Memory could be maybe the least changing factor.
But then again, you don't want to use a memory that is going to take two times the power
consumption like we do in this case.
Or you see the memory can be from 8 to 15 watts, actually below 8 watts.
And at the end, it's a savings of 10 kilowatts.
And 10 kilowatts in 500 kilowatts could be a fifth of the change or less within the server.
So all components are really important.
Maybe the processor would be more important to find exactly the point of the processor,
because then you can go 38 to 95 times 120.
So that delta could be more significant.