Computational & Technology Resources
an online resource for computational,
engineering & technology publications
Computational Science, Engineering & Technology Series
ISSN 1759-3158
Edited by: P. Iványi, B.H.V. Topping and G. Várady
Chapter 3

Massively Parallel Evolutionary Structural Optimization for High Resolution Architecture Design

J. Martínez-Frutos and D. Herrero-Pérez

Computational Mechanics & Scientific Computing Group, Department of Structures and Construction, Technical University of Cartagena, Murcia, Spain

Full Bibliographic Reference for this chapter
J. Martínez-Frutos, D. Herrero-Pérez , "Massively Parallel Evolutionary Structural Optimization for High Resolution Architecture Design", in P. Iványi, B.H.V. Topping and G. Várady, (Editors), "Advances in Parallel, Distributed, Grid and Cloud Computing for Engineering", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 3, pp 29-49, 2017. doi:10.4203/csets.40.3
Keywords: GPU computing, evolutionary structural optimization, sustainable architecture, multilevel preconditioner, large-scale..

This paper shows how the proper use of massively parallel architectures can increase significantly the tractable resolution of topology optimization problems in the field of architecture and urban design. Evolutionary topology optimization techniques are redefining architectural practice providing structurally sound and aesthetically pleasing architectural designs, which commonly mimic nature’s own evolutionary optimization process. Though these techniques provide architects with a powerful tool to integrate function and form in a synergistic way, the resolution of the models to obtain proper designs may be challenging both in computation and memory consumption terms. This work aims to alleviate these constraints proposing a well-suited strategy for Graphics Processing Unit (GPU) computing. Such a proposal makes use of fine grained assembly-free methods along with multilevel parallelizable preconditioner, which notably increase the tractable resolution of the models. The stages of the evolutionary topology optimization pipeline using GPU are compared to the classically used CPU implementation achieving significant speedups. The proposal is evaluated in high resolution real-world architecture and urban designs.

purchase the full-text of this chapter (price £25)

go to the previous chapter
go to the next chapter
return to the table of contents
return to the book description
purchase this book (price £85 +P&P)