Siemens Simcenter Star-CCM+ and Nvidia GPU compute combination a ‘game-changer’

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According to Siemens Digital Industries Software it has opened the door to a new dawn of computational fluid dynamics (CFD) simulation through a tie-up with Nvidia. The Simcenter Star-CCM+ 2022.1 software now brings Nvidia CUDA-enabled GPU acceleration to enable faster turnaround times at lower hardware investment costs – to developers of all types and sizes.

“Siemens and Nvidia are opening the door to a whole new era of CFD simulation acceleration techniques in Simcenter Star-CCM+. With GPU-enabled technology, users can achieve faster turnaround time of CFD simulations at significantly lower per-simulation cost​,” said Stamatina Petropoulou, technical product management, Siemens Digital Industries Software. “This technology will enable engineers working on external aerodynamics, aerospace, building and infrastructure/civil engineering applications, etc. to massively improve their simulation throughput at equivalent hardware investments with an increased per-dollar performance of GPUs compared to CPUs​.”

Running a set of industrial-grade external vehicle aerodynamics simulations, the engineers at Siemens and Nvidia were able to demonstrate how usage of GPUs could reduce required hardware compute investments by up to 40% and the power consumption down to 10% of the CPU equivalent, while maintaining identical simulation turnaround times.

While CPU-based high-performance computing in conjunction with highly scalable CFD parallelization greatly speeds up the absolute times it can take to reach a solution, it comes at the cost of high hardware or cloud computing investments.

Niveditha Krishnamoorthy, developer relations manager, Nvidia, said, “Siemens Simcenter Star-CCM+ is giving an incredible boost to CFD simulations by using Nvidia GPU technology via the CUDA platform and accelerated libraries. Leveraging Nvidia GPU architecture, Star-CCM+ users can now run more simulations, faster, and can gain critical insights for their design and operation workflows without compromising on accuracy.”

Comparison of GPU- and CPU-based equivalent simulations: GPU run time and number of CPU cores required to reach almost identical turn-around times for the same vehicle aerodynamics CFD on GPUs and CPUs. GPUs see legend. Compute-optimized CPU instance: dual-socket Xeon Gold (40 cores per node)

Comparison of GPU- and CPU-based equivalent simulations: GPU run time and number of CPU cores required to reach almost identical turnaround times for the same vehicle aerodynamics CFD on GPUs and CPUs. GPUs see legend. Compute-optimized CPU instance: dual-socket Xeon Gold (40 cores per node)

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Rachel's career in journalism has seen her write for various titles at UKi Media & Events within automotive, tire and marine. Her favourite aspect of the job is interviewing industry experts, including researchers, scientists, engineers and technicians, and learning more about the groundbreaking technologies and innovations that are shaping the future of transportation.

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