The next BriefingsDirect extreme use-case for high-performance computing (HPC) examines how the strictly governed redesign of Formula 1 race cars relies on data center innovation to coax out the best in fluid dynamics analysis and refinement.
We’ll now learn how Alfa Romeo Racing (formerly Alfa Romeo Sauber F1 Team) in Hinwil, Switzerland leverages the latest in IT to bring hard-to-find but momentous design improvements -- from simulation, to wind tunnel, to test track, and ultimately, to victory. The goal: To produce cars that are glued to the asphalt and best slice through the air.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy.
Here to describe the
challenges and solutions from the compute-intensive design of Formula 1 cars is
Francesco
Del Citto, Head of Computational Fluid Dynamics Methodology for Alfa Romeo
Racing, and Peter
Widmer, Worldwide Category Manager for Moonshot/Edgeline and Internet of
Things (IoT) at Hewlett Packard
Enterprise (HPE). The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.
Here are some excerpts:
Gardner: Why does
Alfa Romeo Racing need to prepare for another car design again?
Del Citto |
Del Citto: Effectively,
it’s a continuous design process. We never stop, especially on the aerodynamic side.
And what every Formula 1 team does is dictated by each race season and by the specific
planning and concept of your car in terms of performance.
For Formula 1 racing, the most
important and discriminating factor in terms of performance is aerodynamics. Every Formula
1 team puts a lot of effort in designing the aerodynamic shape of their cars.
That includes for brake cooling, engine cooling, and everything else. So all
the airflow around and inside of the car is meticulously simulated to extract
the maximum performance.
Gardner: This
therefore becomes as much an engineering competition as it is a
racing competition.
Engineered to race
Del Citto: Actually,
it’s both. On the track, it’s clearly a racing competition between drivers and
teams. But before you ever get to the track, it is an engineering competition in
which the engineers both design the cars as well as the methods used to design
the cars. Each Formula 1 team has its own closely guarded methodologies and
processes – and they are each unique.
Gardner: When
I first heard about fluid dynamics and aerodynamic optimization for cars, I was
thinking primarily about reduction of friction. But this is about a lot more,
such as the cooling but also making the car behave like a reverse airplane wing.
Tell us why the aerodynamic impacts
are much more complicated than people might have appreciated.
Del Citto: It is
very complicated. Most of the speed and lap-time reductions you gain are not on
the straightaways. You gain over your competitors in how the car behaves in the
corners. If you can increase the force of the air acting on the car -- to push
the car down onto the ground -- then you have more force preventing the car from
moving out of line in the corners.
Why use the force of the air? Because
it is free. It doesn’t come with any extra weight. But it is difficult to gain
such extra inertial control forces. You must generate them in an efficient way,
without being penalized too much from friction.
It’s also difficult to
generate such forces without breaking the rules, because there
are rules. There are limits for designing the shapes of the car. You cannot
do whatever you want. Still, within these rules, you have to try to extract the
maximum benefits.
The force the car generates is
called downforce,
which is the opposite of lift
force from the design of an airplane. The airplane has wings designed
to lift. The racing car is designed to be pushed down to the ground. The more
you can push to the ground, the more grip you have between the tires and the
asphalt and the faster you can go in the corners before the friction gives up
and you just slide.
Gardner: And
how fast do these cars go nowadays?
Del Citto: They
are very fast on the straight, around 360-370 km/hour (224-230 mph), especially
in Mexico City, where the air is thin due to the altitude. You have less
resistance and they have a very long straight there, so this is where you get
the maximum speeds.
But what is really impressive
is the corner speed. In the corners you can now have a side acceleration force that
is four to five times the force of gravity. It’s like being in a jet fighter plane.
It’s really, really high.
Widmer |
Widmer: They wear
their security belts not only to hold them in in case of an accident, but also
for when they brake and steer. Otherwise, they could be catapulted out of the
car because the forces are close to 5G. The efficiency of the car is really
impressive, not only from the acceleration or high speeds. The other invisible
forces also differentiate a Formula 1 car from a street car.
Gardner:
Peter, because this is an engineering competition, we know the simulations
result in impactful improvements. And that then falls back on the performance
of the data center and its level of innovation. Why is the high-performance
computing environment such an essential part of the Formula 1 team?
Widmer: Finding
tens of thousands of a second on the racetrack, where a lap time can be one minute
or less, pushes the design of the cars to the extreme edge. To find that best
design solution requires computer-aided design
(CAD) guidance -- and that’s where the data center plays an important part.
Those computational
fluid dynamics (CFD) simulations take place in the data center. That’s why we
are so happy to work together with Alfa Romeo Racing as a technology partner.
Gardner:
Francesco, do you have constraints on what you can do with the computers as
well as what you can do with the cars?
Limits to compute for cars
Del Citto: Yes, there
are limits in all aspect of the car, design, and especially in the aerodynamic
research. That’s because aerodynamics is where you can extract more performance
-- but it’s where you can spend more money as well.
The Formula 1 governing body,
the FIA, a few years ago put in place ways
of controlling the money spent for aerodynamic research. So instead of putting on
a budget cap, they decided to put a limit on the resources you can use. The
resources are both the wind tunnel and the computational fluid dynamics. It’s a
tradeoff between the two. The more wind tunnel you use, the less computational
power you can use, and vice versa. So each team has its sweet spot, depending
on their strategy.
You have restrictions in how
much computational capacity you can use to solve your simulations. You can do a
lot of post-processing and pre-processing, but you cannot extract too much from
that. The solving part, in which it tells you the performance results of the new
car design, is what is limited.
Gardner:
Peter, how does that translate into an HPE
HPC equation? How do you continuously innovate to get the most from the
data center, but without breaking the rules?
Widmer: We work with a competency center on the HPC to determine the right combination of CPU, throughput, and whatever it takes to get the end results, which are limited by the regulations.
We are very open on the
platform requirements for not only Alfa Romeo Racing, but for all of the teams,
and that’s based on the most efficient combination of CPU, memory, networking,
and other infrastructure so that we can offer the CFD use-case.
Gardner: Let’s
hear more about that recipe for success.
Memory makes the difference
Widmer: It’s an
Intel Skylake
CPU, which includes graphic cards onboard. That obviously is not used for
the CFD use-case, but the memory we do use as a level-four memory cache. That
then provides us extra performance, which is not coming from the CPU, which is
regulated. Due to the high-density packaging of the HPE Moonshot
solution -- where we can put 45 compute notes in a 4.30 rack chassis -- this is
quite compact. And it’s just topped out at about 5,000-plus cores.
Del Citto: Yes,
5,760 cores. As Peter was saying before, the key factor here is the software. There
are three main CFD software applications used by all the Formula 1 teams.
The main limitation for this
kind of software is always the memory bandwidth, not the computational power. It’s
not about the clock speed frequency. The main limitation is the memory
bandwidth. This is why the four-level cache gives the extra performance, even
compared to a higher spec Intel server CPU. The lower spec with low energy use
CPU version gives us the extra performance we need because of the extra memory cache.
Gardner: And
this isn’t some workload you can get off of a public cloud. You need to have
this on-premises?
Del Citto: That’s
right. The HPC facility is completely owned and run by us for the Formula 1
team. It’s used for research and even for track analysis data. We use it for
multiple purposes, but it’s fully dedicated to the team.
It is not in the cloud. We
have designed a building where we have a lot of electricity and cooling capacity
requirements. Consider that the wind tunnel fan -- only
the fan – uses 3 megawatts. We need to have a lot of electricity there.
Gardner: Do
you use the wind tunnel to cool the data center?
Del Citto: Sort
of. We use the same water to cool the wind tunnel and the data center. But the
wind tunnel has to be cooled because you need the air at a constant temperature
to have consistent tests.
Gardner: And
Peter, this configuration that HPE has put together isn’t just a one-off. You’re
providing the basic Moonshot design for other Formula 1 teams as well?
A winning platform
Widmer: Yes,
the solution and fit-for-regulations design was so compelling that we managed
to get 6
out of 10 teams to use the platform. We can say that at least the first
three teams are on our customer list. Maybe the other ones will come to us as
well, but who knows?
We are proud that we can
deliver a platform to a sport known for such heavy competition and that is very
technology-oriented. It’s not comparable to any other sport because you must consistently
evolve, develop, and build new stuff. The evolution never stops in Formula
1 racing.
For a vendor like HPE, it’s
really a very nice environment. If they have a new idea that can give a team a
small competitive advantage, we can help them do it. And that’s been the case for
10 years now.
Let’s figure out how much faster
we can go, and then let’s go for it. These teams are literally open-minded to
new solutions, and they are eager to learn about what’s coming down the street
in technology and how could we get some benefits out of it. So that’s really
the nice story around it.
These
teams are literally open-minded to new solutions, and they are eager to
learn about what's coming down the street in technology and how they
could get benefits out of it. That's the nice story around it.
Gardner:
Francesco, you mentioned this is a continuous journey. You are always looking for
new improvements, and always redesigning.
Now that you have a
sophisticated HPC environment for CFD and simulations, what about taking
advantage of HPC data center for data analysis? For using artificial
intelligence (AI) and machine learning
(ML)?
Is that the next stage you can
go to with these powerful applications? Do you further combine the data
analysis and CFD to push the performance needle even further?
Del Citto: We
generate tons of data -- from experiments, the wind tunnel, the CFD side, and
from the track. The cars are full of sensors. During a practice run, there are hundreds
of pressure sensors around the car. In the wind tunnel, there are 700
sensors constantly running. So, as you can imagine, we have accumulated a lot
of data.
Now, the natural step will be how we can use it. Yes, this is something everyone is considering. I don’t know where this will bring us. There is nothing else I can comment on at the moment.
Gardner: If
they can put rules around the extent to which you can use a data center for AI,
for example, it could be very powerful.
Del Citto: It could
be very powerful, yes. You are suggesting something to the rule-makers now.
Obviously, we have to work with what we have now and see what will come next. We
don’t know yet, but this is something we are keeping our eyes on, yes.
Widmer:
Thanks a lot.
Listen to the podcast. Find it on iTunes. Read a full transcript or download a copy. Sponsor: Hewlett Packard Enterprise.
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