Link between AWS and Formula One
“ For our needs, AWS outperforms all other cloud providers, in speed, scalability, reliability, global reach, partner community, and breadth and depth of cloud services available.”
Pete Samara
Director of Innovation and Digital Technology, Formula 1
Introduction
Formula One (or F1) has been one of the premier forms of auto racing around the world since it’s inaugural season in 1950. Formula One cars are the fastest regulated road-course racing cars in the world, owing to very high cornering speeds achieved through the generation of large amounts of aerodynamic downforce.
Formula One is not just a battle between the world’s best drivers, but also a battle between some of the world’s most innovative engineers. No other sport has been as dynamic in its evolution and embrace of new technology. While some of the tech goes to helping drivers, who are hitting speeds as high as 230 MPH, taking pit stops in under 2 seconds, and flying around corners with a force of 5G, much of it goes to enhance the experiences of its growing base of over a half a billion fans.
Data in Formula One
An F1 race car, with an average of 150–300 sensors on board, generates more than 1.1M data points per second, transmitted from the cars to the pit. Formula 1 is a truly data-driven sport where much of the thrill comes from extracting exciting details on performance statistics. F1 relies on the breadth and depth of AWS services to stream, process, and analyze that flood of data in real-time, and then present it in a meaningful way for F1 global TV viewers.
For such high performance battles of speed and control, a vast amount of computation, information gathering, analytics, and learning is required, before, during and after the races. So in 2018, Formula One decided to move the vast majority of its infrastructure from on-premises data centers to AWS, and standardizing on AWS’s machine learning and data analytics services to accelerate its cloud transformation.
Amazon Web Services (AWS) is the official cloud service and machine learning provider for Formula One.
Services Provided
To enhance race strategies, data tracking systems, and digital broadcasts, F1 is working with AWS with a variety of services such as Amazon SageMaker (Platform to deploy machine-learning models), AWS Lambda (event-driven server-less computing platform), and AWS analytics services — to uncover a broader perspective of the metrics involved in racing. AWS also plays a major role in Computational Fluid Dynamics (CFD).
Computational Fluid Dynamics
Formula One has been using Amazon EC2 for Computational Fluid Dynamics (CFD) to simulate race car aerodynamics, achieving the performance of a super computer at a much lower cost and reducing simulation time by an average of 70 percent — from 60 hours down to 18 hours. with the CFD project, Formula One used over 500 million data points to study downforce loss when two vehicles race in close proximity (downforce increases tire grip and cornering speeds and reduces lap time). Based on its CFD simulations, Formula 1 has designed a car for the 2021 racing season that reduces downforce loss in wheel-to-wheel racing from 50 percent to 15 percent.
Computational Fluid Dynamics Project utilizes over 12,000 hours of compute time to design the car for the 2021 racing season.
CFD simulates the impact of a liquid or gas on an object and requires extensive compute capacity to perform this kind of simulation, requiring high performance computing (HPC) clusters to do the job.
To complete the CFD work, Formula 1 used AWS ParallelCluster on Amazon EC2 to run the OpenFOAM CFD framework, and Amazon Simple Storage Service (Amazon S3) for data storage. Leveraging the scalability of the cloud, Formula 1 was able to run CFD simulations on core counts much larger than they were previously able to execute. The increased speed with which the aerodynamics team could run detailed, two car turbulence simulations on AWS meant they could increase the number of car designs they could investigate from one to five per week. Moving forward, there are plans to expand the application further, up to 2,300 cores, and to introduce AWS Machine Learning (ML) tools, such as Amazon SageMaker, to allow ML technologies to help with the design and further optimize the performance of the car.
“This project with AWS was one of the most revolutionary in the history of Formula 1 aerodynamics, … We have been able to use AWS technologies to understand the incredible aerodynamic complexities associated with multi-car simulations, and are pleased that the results indicate we have made excellent progress towards our aims of closer racing.”
Pat Symonds
Chief Technical Officer of Formula 1
Other Services
- Using Amazon SageMaker, Formula 1’s data scientists are training deep learning models with more than 65 years of historical race data, stored in both Amazon DynamoDB and Amazon Glacier. With this information, Formula 1 can extract critical race performance statistics to make race predictions and give fans insight into the split-second decisions and strategies adopted by teams and drivers.
- Formula One also selected AWS Elemental Media Services to power its video asset workflows, enhancing the viewing experience for its 500 million plus fans and viewers worldwide.
- By streaming real-time race data to AWS using Amazon Kinesis- a service for real-time data collection, processing and analysis, Formula 1 can capture and process key performance data for each car during every twist and turn of the Formula 1 circuits with unmatched accuracy and speed.
- To create new insights, Formula One uses 70 years of historical race data stored in Amazon Simple Storage Service (Amazon S3), combined with live data that is streamed from sensors on F1 race cars and the trackside to the cloud through Amazon Kinesis.
The Car Performance Scores (uses a range of AWS services) insight displays an on-screen graphic that provides fans with a complete breakdown of a car’s total performance using four core metrics: Low-Speed Cornering, High-Speed Cornering, Straight Line, and Car Handling. The new graphic illustrates how those metrics compare from one car to another, enabling race fans to gauge a given car’s relative performance in those different areas and see where each team and driver is leading the pack or losing crucial time to their rivals.
Tyre Performance graphic (powered by AWS) provides real-time information on the current condition for all four tyres on a chosen car, presented as a percentage value. The scale runs between ‘new tyre with no wear’ (100%) and a ‘used tyre’ at the end of its effective performance lifespan (0%).
F1 is able to analyze race performance metrics in real-time by deploying those ML models on AWS Lambda, which runs code without the need to provision or manage servers. All of the insights will be integrated into the international broadcast feed of F1 races around the globe, including its digital platform F1.tv, helping fans to understand the split-second decisions and race strategies made by drivers or team strategists that can dramatically affect a race outcome.
Conclusion
Formula One has collaborated with AWS for some of the best and accurate statistical data in the motorsport world. To combine high speed physics, data analytics, performance, and many other factors, into a packaged service has allowed Formula One to present a more detailed and exciting viewpoint of the sport to its viewers.
“Formula 1’s years of valuable historical race data analyzed against the real-time information that is collected in every race using AWS’s machine learning, streaming, and analytics services will uncover new racing metrics and insights that were unimaginable in the past …
Formula 1 racing mixes physics and human performance, yielding powerful, but complex data that AWS is helping them to harness.”Mike Clayville
Vice President, Worldwide Commercial Sales at AWS
