How does a large automotive manufacturer leverage the elasticity of the cloud, and what do they look for in a provider?
To find out, we asked a CAE manager at American Axle & Manufacturing, a Tier 1 automotive supplier of driveline and drivetrain systems that operates in 13 countries globally with annual revenues of $3.9 billion. Read below for his take on how Rescale has added value to his organization.
Rescale: Alexy, can you start off by introducing yourself and American Axle & Manufacturing?
Alexy: My name is Alexy Kolesnikov. I manage computational fluid dynamics and thermal projects for American Axle & Manufacturing. American Axle & Manufacturing is a leading global Tier 1 automotive supplier. Our clients are all the major automotive companies. We supply driveline and drivetrain systems, for example front axles, rear axles, PTUs, and eDrive units.
Rescale: Tell us more about your role.
Alexy: I work in a CAE department, and we simulate all these components. In our products, we simulate oil flows, heating and cooling, those kinds of things. Simulation is like a design tool; instead of testing any given product 20 times and ordering parts, you pick an advanced optimizer to run simulations.
Rescale: Can you describe your simulation needs and the computing environment that you were operating with before you started using Rescale?
Alexy: We use computational fluid dynamics to simulate the lubrication process. We want to optimize the way oil goes onto bearings or gears inside our products. These simulations are fairly complex. It’s fairly hard to simulate how oil is going to move. Because it is a multi-phased problem, high-fidelity, accurate simulation requires significant computing resources. Usually our jobs, our runs, our models require anywhere between 32 to 150 cores to run, which dictates the size of the server you need. Before Rescale, we had a single server with 64 cores.
Rescale: What were the pain points that led you to consider Rescale or another cloud HPC solution?
Alexy: Well, it was the scalability of hardware requirement. For us to optimize a specific axle, be it a front axle or an eDrive unit, we need to conduct several runs. (By runs, I mean different angles of inclination of a moving car, for example, or an SUV driving at different speeds.) You need to look at a number of these conditions, which dictate how the oil moves. Depending on how soon you need an answer, you might want to run a number of these jobs simultaneously, instead of waiting to run them one by one. What Rescale provides is essentially the on-demand capability to scale up your hardware resources almost infinitely. You can do large numbers of runs in parallel in a very limited number of days. That’s what Rescale gives us.
Rescale: Did you consider other cloud HPC solutions, and if so why did you choose Rescale?
Alexy: We did. One of the important factors in our decision was the availability of a code from CD-adapco called STAR-CCM+. We use it in-house to model lubrication and a number of other things. Rescale has an established relationship with CD-adapco, which allows us to use the software licenses provided by CD-adapco efficiently in conjunction with the hardware provided by Rescale. It’s called the Power-on-Demand license. We only utilize it when we have to run a large number of projects, and we are not billed when we are not running. That was a very efficient way for us to use our software and hardware resources.
Another thing we like about Rescale is the willingness of your company to install new software. For example, when we wanted to try different software packages that you guys didn’t have, you installed them for us. That kind of willingness to work with a client is pretty impressive.
Rescale: Could you give us an overview of how you use Rescale? Has Rescale changed the way you approach simulation?
Alexy: It has allowed us to efficiently deliver answers to internal or external clients. All clients and all problems and all projects are different. Sometimes you have weeks or months to deliver results, but sometimes all of a sudden an issue comes up and you have to have the answers tomorrow. Rescale gives us the flexibility to satisfy both needs. It fits into the structure of how we run our analysis. For example, we use Rescale anytime we need to run five jobs at the same time to deliver results in two days. We can run them in parallel on Rescale, which would require us otherwise to have five servers in-house. This on-demand scalability enables us to deliver results that are urgently needed.
Rescale: How has using Rescale impacted the business overall?
Alexy: It clearly made CAE simulation way more efficient. It’s hard to estimate the advantage of having the ability to deliver results on-demand. We’ve been using Rescale for a year and a half, and at this point the main advantage is the ability to scale up and scale down. Going forward, we will probably use additional types of software for different types of analyses. But for right now, the main impact is this ability to quickly deliver results when an urgent problem comes up.
Rescale: How do you think you’ll use Rescale in the future?
Alexy: We are considering using Rescale not just for bursting, but also to substitute the in-house server a little bit. As we look forward to determine how many servers we need in-house to run 24/7 jobs, we might consider using Rescale for those jobs, in addition to on-demand, scale-up jobs. We have to look at how much it costs to maintain our server in-house compared to how much it costs to run on the cloud.
Click here for more information on using STAR-CCM+ on Rescale.
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This article was written by Mika Pegors.