INEOS TEAM UK Accelerates Boat Design for America’s Cup Using AWS

Using AWS, INEOS TEAM UK can process thousands of design simulations for its America’s Cup boat in one week versus in more than a month using an on-premises environment. INEOS TEAM UK will compete in the 36th edition of the America’s Cup in 2021. The team is using an HPC environment running on Amazon EC2 Spot Instances to help design its boat for the competition.

Formed in 2018, INEOS TEAM UK aims to bring the America’s Cup—the oldest international sporting trophy in the world—to Great Britain. Based in Portsmouth, INEOS TEAM UK is led and backed by Sir Jim Ratcliffe, the founder and chairman of INEOS, a global chemical producer. The team also includes Sir Ben Ainslie, a previous America’s Cup winner, as principal and skipper and four times America’s Cup winner Grant Simmer as CEO.

The 36th America’s Cup race will be decided in Auckland, New Zealand in 2021. Like all the teams, INEOS TEAM UK will compete in a boat whose design will have followed guidelines set by race organizers to ensure the crew’s sailing skills are fully tested.

The aim of the restrictions—which limit on-water design trials, too—is also to control the cost of entering the race and to attract as many entrants as possible.

Despite the restrictions, teams still have control over features such as the shape of the boat’s monohull and foils, but with limited on-water testing, engineers must turn to computer-based simulations to optimize their designs. They depend on the computational power available to process thousands of simulations, exploring possible boat shapes and positions on the water. In the case of INEOS TEAM UK, for example, it needs 2,000−3,000 computational fluid dynamics (CFD) simulations to design the dimensions of just a single boat foil.

To run these simulations using the team’s on-premises high performance computing (HPC) resources could take more than a month. Nick Holroyd, head of design at INEOS TEAM UK, says, “With so many design decisions to make before the competition, a month was too long. It reduced the time our engineers had to consider the results, limiting the freedom they needed to be innovative and make the right choices.”  

The team turned to Amazon Web Services (AWS) to migrate its CFD simulations to the AWS Cloud. The team chose AWS because of the scale of its HPC resources as well as its cost-effectiveness. INEOS TEAM UK could keep its costs low by using Amazon Elastic Compute Cloud (Amazon EC2) Spot Instances, which allow customers to access unused Amazon EC2 capacity.

To get the performance INEOS TEAM UK required and on budget, the team worked with AWS Solutions Architects and AWS Professional Services consultants, who helped design an HPC environment based on multiple Availability Zones in multiple regions and Amazon EC2 Spot Instances, which provided a 65 percent cost saving compared to on-demand capacity.

For the hull, whose design needed hundreds of compute cores for every simulation, the team used Amazon EC2 C5 instances in addition to the latest Amazon EC2 C5n Nitro-powered instances with Elastic Fabric Adapter (EFA) network interfaces.

To ensure fast disk performance for the thousands of simulations completed each week, the team also used Amazon FSx for Lustre to provide a fast, scalable, and secure high-performance file system based on Amazon Simple Storage Service (Amazon S3).

“The speed combined with the low cost of the Amazon EC2 Spot Instances means we can do many thousands more simulations within our design budget,” says Holroyd. “One question I constantly ask myself is whether we’re spending our money wisely. Using AWS, I have no doubts because it massively compresses the computational turnaround, maximizing design time.”

By running its CFD workloads on AWS, INEOS TEAM UK engineers have more time to innovate. They can wake up on a Monday morning with an idea and test it, knowing that by the end of the day, they’ll have a set of results to look at and build on.

Holroyd says, “Heading towards a design deadline is always a frantic time. You have to make decisions fast. Using AWS, we have more time to think about what makes a design successful or not. We can then use this knowledge in our next design iteration. AWS allows us to take bigger design steps, simply because we have more time to understand our results.”