Modernize your motor sport race strategy on Oracle Cloud Infrastructure

February 9, 2022 | 3 minute read
Arnaud Froidmont
HPC Solution Architect
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2021 might go down as one of the most epic Formula 1 seasons that was ever raced. It had speed, drama, controversy, everything you could ask for in a Hollywood blockbuster. In the end, it came down to race strategy and who had the freshest tires for an incredible last lap.

Alleviate uncertainty with Monte Carlo simulations

Formula 1 is not an outlier in the field. Almost any motor sport race is using a race strategy, whether it’s for tire management, pit strategy, or coping with crashes, safety cars, or weather changes.

The biggest challenge that engineers face is uncertainty. What are the odds of light rain? How about heavy rain? Will one of the cars crash? Will it need repairs? What lap did the crash happen? To cope with those probabilities, engineers are using MonteCarlo methods to simulate the race millions, even billions of times. No one right answer exits, but some strategies give you better odds of winning than others. As the race develops, uncertain events become reality and teams gather enormous amounts of data. The quicker the data gets processed, the quicker you can react with real numbers instead of intuition.

Using cloud native technologies like functions, Oracle Container Engine for Kubernetes (OKE), and flexible Compute shapes, it’s natural to use resources only during the race and shut down when the checkered flag is waived.

Many areas use Monte Carlo strategies, including life science and financial services. The architecture used is similar for all use cases.

MonteCarlo Cloud Native Architecture on OCI
Figure 1: Monte Carlo simulation reference architecture on Oracle Cloud Infrastructure (OCI)

Run Monte Carlo simulations on OCI

Data has many forms and use cases. Depending on parameters like time needed to retrieve, access frequency, size, and destination, you can choose the right data storage, whether it’s on a file system as an object, in an autonomous database, or in a data warehouse. You can stream live race data directly from the track to the closest Oracle data center. When the data is stored, it can be automatically processed by functions to run Monte Carlo jobs on it.

Using cloud native architecture and open source technology like RabbitMQ on OKE, you can submit jobs to any numbers of workers. From dozens to thousands, autoscaling handles the right number of workers for the job. By running the right amount of resources on the cloud, you can design specific architecture for each workload.

In Figure 1, the workers are ready for messages from the queue. Monte Carlo analysis with high throughput benefits from running each experiment without any container startup time. Even though it only takes a few milliseconds, it quickly adds up when running millions or billions of experiments.

You can use any OCI Compute shape, but with our latest generation Ampere A1 shapes, you don’t compromise performance for the lowest cost. Flexible virtual machines (VMs) let you adjust the CPU-memory ratio to make it as cost-effective as possible. Running your application in a container might be an extra step. It gives you the confidence of running on any platform. Whether you’re on-premises or in the cloud, on ARM or x86 platform, you can run your workload with minimal performance loss and great flexibility.

When the results are pushed back to your storage option of choice for postprocessing in the cloud or streamed, they’re immediately sent to the strategists on the track for a winning move!

Modernize your race strategy today

Start your 30-day free trial and get access to a wide range of Oracle Cloud Infrastructure services for 30 days, including flexible Ampere A1 Compute and Oracle Container Engine for Kubernetes.

Arnaud Froidmont

HPC Solution Architect

I am an HPC Solution Architect for Oracle Cloud. I have a master in Engineering in Applied Mathematics from UCL in Belgium and a master in Applied Physics from Northern Arizona University. I previously worked for Noesis Solutions as an Application Engineer. I live in Boulder and am loving all the outdoor activities it provides.

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