PolyTop++: an efficient alternative for serial and parallel topology optimization on CPUs & GPUs. This paper presents the PolyTop++, an efficient and modular framework for parallel structural topology optimization using polygonal meshes. It consists of a C++ and CUDA (a parallel computing model for GPUs) alternative implementations of the PolyTop code by Talischi et al. (Struct Multidiscip Optim 45(3):329–357 2012b). PolyTop++ was designed to support both CPU and GPU parallel solutions. The software takes advantage of the C++ programming language and the CUDA model to design algorithms with efficient memory management, capable of solving large-scale problems, and uses its object-oriented flexibility in order to provide a modular scheme. We describe our implementation of different solvers for the finite element analysis, including both direct and iterative solvers, and an iterative ‘matrix-free’ solver; these were all implemented in serial and parallel modes, including a GPU version. Finally, we present numerical results for problems with about 40 million degrees of freedom both in 2D and 3D.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Nguyen, Nam V.; Nguyen-Xuan, H.; Lee, Jaehong: Polygonal composite elements for stress-constrained topology optimization of nearly incompressible materials (2022)
- Wang, Zhijun; Suiker, Akke S. J.; Hofmeyer, Hèrm; Kalkman, Ivo; Blocken, Bert: Sequentially coupled gradient-based topology and domain shape optimization (2022)
- Neuenhofen, Martin P.; Greif, Chen: Mstab: stabilized induced dimension reduction for Krylov subspace recycling (2018)
- Duczek, Sascha; Gabbert, Ulrich: The finite cell method for polygonal meshes: poly-FCM (2016)