Zach Smocha from Rescale presented this deck at the HPC User Forum in Tucson. Watch the video presentation: http://wp.me/p3RLHQ-fdC Learn more: http://www.rescale.com/ and http://hpcuserforum.com

1. Performing simulation based, real time
decision making with cloud HPC
Zack Smocha, April 2016
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Agenda
• Rescale overview
• Evolution of simulation
• Simulation in service
• F1 simulations
• Manor Racing case study

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HQ San Francisco, USA , Japan office
rapid growth
Global simulation cloud HPC platform
30+ data centers, 120 simulation software
Over 100 leading enterprises -
automotive, aerospace, energy and life
sciences
Headquarters
Technology
Customers
Investors
Rescale - Company Overview
Peter ThielJeff Bezos Richard Branson
... and several other
industry leaders,
technology experts, and
experienced executives

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Rescale Cloud HPC Enterprise Simulation Platform
So#ware
120+ software
packages
Mul,-clouds
30 varied location
and HW availability
Workflow
Administra,on
Security
Compliant, data
and user
Manage usage
access and cost
Experienced team
seamless workflow

5. 5
Simulations in Industry
Aerospace
Automotive
LifeSciences
Oil&Gas
Industrials
Semiconductor
• Complex turbine
• Wing designs
• Modelling
propulsion
• Crash simula-on
• Engine
computa-onal
fluid dynamics
• Reservoir
simula-on
workflows
• Hydrocarbon
traps
• Gene-c
engineering
• Isola-on of
gene-c traits
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Evolution of Automotive SimulationComplexity
1960 1970 1980 1990 2000 2010 Today
Vehicle
Dynamics
Crash Analysis
FEA
Multiphysics
High-fidelity
Ensemble analysis
CFD & HPC

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Simulation in the Product Life Cycle
Predict behavior
without actually
testing it in real life
Validate and optimize
the design of parts
and manufacturing
Using real data to
help make real time
decision
Engineering Design Manufacturing In Service/Production

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Simulation In Service - Time Spectrum
Real -me “next
move” gaming
analysis
Threads CPU GPU ELO
24 764 112 3,079
40 1,202 176 3,140
64 1,920 280 3,168
Maintenance
and abnormal
behavior
Using real -me
track side data
for race strategy
Make sure you
don’t crash the
bus
Days/hours Minutes Micro seconds Seconds

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F1 the Art of Race Strategy

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F1 Results Australia - Many Strategies
Superso# So# Medium Hard Wet Intermedium Used = Pit Stop

11. • Based in Banbury UK
• Partners with Mercedes-Benz engine technology
• Williams Advanced Engineering for transmissions
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Manor Racing

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Manor use case - Goals
• Best -me to take a pit stop
• What -res to fit for the next stage of the race.
• Second guess the compe--on to try and gain race
posi-on through be^er pit stop -me
For Manor Racing it is about meticulous attention to detail, eking out every
single opportunity to find every single gap. Car and driver, factory and team

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Manor use case - Users
Dave Ryan - Racing Director
James Knapton - Head of
Vehicle Science
Strategy engineers who advise the race engineers
on the op-mum strategy as the race is developing

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HPC Simulation in Service - Requirements
• Collect the data in real time?
• Insert the data into the system?
• Upload the data to the cloud HPC?
• Best HW for fast simulation?
• Download and access the data?

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Manor Cloud HPC Architecture
Cloud HPC Cluster
Head Node
HPC Scheduler
Compute Nodes
Nodes are joined to the
HPC Scheduler
Virtual Network LAN
IPSec
VPN
Manor application GUI
• For optimization jobs directly interact with the HPC cluster
• Clients running jobs join the head node domain and mount the shared file system

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Input Parameters and Live Data
• Parameters: lap time, tire
degradation rate for each tire
compound, expected car
performance as fuel level
reduces
Make a live decision
based on the
simulation results and
enter actual track
side results
Collect live track side
data and run the
simulation
Make a live decision
based on the
simulation results and
enter actual track
side results
Collect live track side
data and run the
simulation
• Example of live Input data:
Actual lap time, tire degradation

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Input Parameters
• How do I collect the data input in real time
– Data is available from the track side
• Insert the data to the system
– User enters the data into the Manor
application interface, application generates
input size files ~500kB
• Upload the data
– Data is uploaded to the head cluster node
from the user laptop

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Simulation Benchmark - Best HW for Fast Simulation
• Simulations based on Monte-Carlo methods
• Response < 45-50 sec
• Run thousands of race simulations per minute, repeat
this process over and over throughout the race
#cars #cores Strategies Permuta-ons Itera-ons Running -me on the cluster
1 Car 500 30 100 100 32.27
1 Car 500 30 300 20 69.58
1 Car 500 30 150 20 31.69
1 Car 500 90 20 20 31.82
1 Car 500 90 20 100 35.61
1 Car 750 30 100 100 31.80
1 Car 1500 30 100 100 30.75
2 Cars 750 (each) 30 100 100 35.03

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Running the Simulation
• Clusters are running
the whole race
• 3000 tasks
• Hardware:
• 1500 cores
• 16 CPU per node
• 98 nodes
• Haswell CPU

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The Results
• Output: Optimum race time
• Results size is 5MB
• Results are download to the user PC
• User views results in the Manor GUI App
• Using the results in practice: Decide when would be the
best time for a pit stop

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The Results
• Each curve is a different tire choices
• Each # represent a pit stop and the lap to stop
• POA: Prime/Option/Alternate : Hardest to the softest
Op,mum race ,me – Sensi,vity to ,re strategy

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Simulation defines our future,
join us in helping build a better world.

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Simulations in F1
• Wind tunnel, aerodynamic
• CFD and FEA
• 2014 FIA regula-ons

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F1 the Art of Tire Change
• 15-19 people
• Stop below 3 sec
• Do other adjustments

25. Appendix
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