Nissan relies on a digital product design process to make quick and critical design decisions to improve the fuel efficiency, reliability and safety of its cars.
By moving its performance and latency sensitive-engineering simulation workloads - including computational fluid dynamics, structural mechanics simulation and 3D visualisation - to Oracle Cloud, Nissan will be able to speed the design and testing of new cars.
Nissan makes use of software-based Computational Fluid Dynamics (CFD) and structural simulation techniques to design and test cars for external aerodynamics and structural failures. These workloads require enormous computing power and Nissan has adopted a cloud-first strategy for its HPC platform to ensure engineers always have the compute capacity needed to run their complex situations.
The solution gives Nissan higher performance and lowers costs at the same time.
“Nissan is a leader in adopting cloud-based high-performance computing for large scale workloads such as safety and CFD simulations,” said Bing Xu, General Manager, Engineering Systems Department, Nissan Motor Co, Ltd. “We selected Oracle Cloud Infrastructure’s HPC solutions to meet the challenges of increased simulation demand under constant cost savings pressure. I believe Oracle will bring significant ROI to Nissan.”
Nissan is one of the first automotive OEMs to leverage GPU technology in Oracle Cloud Infrastructure for structural simulation and remote visualisation. By using Oracle’s bare-metal GPU-accelerated hardware, Nissan reduces the cost and overhead of large data transfer, while ensuring that all the data generated by simulation jobs can easily be viewed in 3D OpenGL format in the cloud.
“Oracle is excited to work alongside Nissan to change digital product design and development, and help them build the next generation of award-winning vehicles,” said Clay Magouyrk, executive vice president, Oracle Cloud Infrastructure. “Our mission has always been to build the best cloud infrastructure for enterprises, including computationally intensive and extremely latency-sensitive workloads that organisations like Nissan need to build the next generation of vehicles.”