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Accelerating Ultrasonic Fingerprint Sensor R&D with Cloud Simulation

Aug. 6, 2019
OnScale describes the virtual prototyping and beamforming optimization of a 110 x 56 PMUT array fingerprint sensor.

In this paper, OnScale describes the virtual prototyping and beamforming optimization of a 110 x 56 PMUT array fingerprint sensor first designed and prototyped by Horsley et al at the Berkeley Sensor & Actuator Center.

OnScale demonstrates the powerful capabilities of its time-domain multiphysics simulation in the cloud by circumventing the legacy empirical approach to physical sensor design that imposes an immense cost, risk, and delayed time to market on device OEMs. The sensor was modeled in full-3D and included the PDMS die coating and a virtual finger, resulting in 130 million degrees of freedom model that was solved in 29 minutes per image on 106 parallel cloud nodes using a total of 4,240 processor cores.

All of the simulation capabilities described herein are available in OnScale’s standard simulation product.

Download the whitepaper: Accelerating Ultrasonic Fingerprint Sensor R&D with Cloud Simulation

About the Author

OnScale

OnScale Computer-Aided Engineering tools are based on proprietary multiphysics solvers that were developed and validated over 30 years by one of the largest engineering consulting firms in the world for DARPA, the U.S. Department of Defense (DOD), and large commercial customers.

The CAE solvers were architected for highly parallel mainframe computers to handle very large engineering simulation problems and are a perfect fit for modern cloud-based, high-performance computing. OnScale and its new team were spun out of Thornton Tomasetti in 2017.

OnScale gives engineers a wealth of design insights and highly accurate simulation results up to 100x faster than legacy CAE offerings. Current OnScale solutions address the simulation needs of Semiconductor and MEMS, 5G mobile, next-gen biomedical, and autonomous vehicle markets.