An Optimized, Easy-to-use, Open-source GPU Solver for Large-scale Inverse Homogenization Problems

Abstract

We propose a high-performance GPU solver for inverse homogenization problems to design high-resolution 3D microstructures. Central to our solver is a favorable combination of data structures and algorithms, making full use of the parallel computation power of today's GPUs through a software-level design space exploration. This solver is demonstrated to optimize homogenized stiffness tensors, such as bulk modulus, shear modulus, and Poisson's ratio, under the constraint of bounded material volume. Practical high-resolution examples with 512 3 ≈ 134.2 million finite elements run in less than 32 seconds per iteration with a peak memory of 21 GB. Besides, our GPU implementation is equipped with an easy-to-use framework with less than 20 lines of code to support various objective functions defined by the homogenized stiffness tensors. Our open-source high-performance implementation is publicly accessible at https://github.com/lavenklau/homo3d.

Programmable 3D metamaterials with tailored Poisson's ratios over large deformation

“…This approach can be used to design self-bridging metamaterials 31 , and auxetic materials over large deformation 29,30,32 . Open source codes for large-scale metamaterial design 33,34 also provide extensive prospects for the inverse design of metamaterials. To achieve more flexible and precise control over the Poisson's ratio of metamaterials, it is necessary to construct an accurate constitutive model under the premise of large deformation.…”