Case Study
“We designed every nanometer of this metasurface using Ansys Lumerical FDTD, Amazon Web Services (AWS), and Python API while making it compatible with CMOS fabrication tolerances. Lumerical’s AWS solution allowed Lumotive to scale its design cycle by two to three orders of magnitude without additional cost or accuracy compromises.”
— Prasad Iyer, Senior Lidar Engineer / Lumotive
Challenges
Lumotive’s lidar products are based on their advanced beam steering technology using liquid crystal metasurfaces (LCMs). Their LCM technology was designed and optimized with Ansys Lumerical FDTD on AWS. To succeed in developing their lidar systems, Lumotive needed to quickly and accurately model and validate the beam-steering performance of their LCM design. The most critical requirement was an efficient method for predicting anisotropic permittivity and the response of the liquid crystal at the nanometer scale.
Engineering Solution
Lumotive considered several HPC solutions to accelerate large-scale simulations, but ultimately, they decided to go with a cloud solution on Amazon Web Services (AWS) powered by Ansys Lumerical FDTD. This decision was driven by the accuracy and run-time performance of Lumerical FDTD coupled with its amenability to HPC and the cost-effective flexibility of Amazon’s cloud solution.
Results
With the help of Lumerical’s HPC solution, Lumotive rapidly scaled their simulations to AWS. This rapid scaling allowed Lumotive to reduce its design time by two orders of magnitude without compromising accuracy. Previous simulations running on their workstations that would take hours now finish in minutes.
In addition to improving the performance of their simulations, workflow improvements made possible by Lumerical’s Python API were critical for Lumotive to optimize designs dependent on many independent process parameters and constraints.
Lumotive was able to confirm the correct functionality of its LCM, allowing them to deliver their product on time. Without Lumerical’s solution, this level of validation would not have been possible, as the runtime on conventional hardware would be unreasonably long. Further, the cost of procuring dedicated hardware would not be justifiable for a task needed only intermittently for a small portion of the design cycle.
Lumotive’s Iyer says, “Lumerical’s AWS solution allowed Lumotive to scale its design cycle by two to three orders of magnitude without additional cost or accuracy compromises.”