Algorithmic design, analysis, optimization, and visualization depend on the use of computers and, frequently, have considerable computational demands. Nowadays, it is not unusual to have algorithmic processes running for weeks in high-performance computer workstations. Obviously, the duration of these processes often deters architects and engineers from their use.
These processes mostly use the same algorithmic approaches that were developed when computers operated with a single processing unit. Nowadays, we are reaching the physical limits of the computational power of a single processing unit. Therefore, to increase performance, computers now include multiple processing units. To take advantage of this parallelized form of computational power, we need to adapt the algorithmic processes of the past or invent new ones.
With that goal in mind, we proposed a short two-month project to experiment with the parallelization of algorithmic design, analysis, optimization, and visualization using a super-computer with a very large number of processing units. This allowed us to measure the scalability of those algorithmic processes relative to the number of processing units used, and more effectively develop the necessary adaptations to take advantage of the parallelism available in current computers.
Project Name: MOOB - Multi-Objective Optimization of Buildings
Time Period: 31-12-2020 to 01-03-2021
Funding: 615 Eur worth in CPU/vCPU cores time
Architecture, Engineering, and Construction (AEC) face three important challenges: the need to reduce the environmental and economic impact of buildings, the adoption of Building Information Modeling (BIM), and the introduction of computational techniques in the architectural practice.
In order to solve these challenges, it is necessary to combine algorithmic design, analysis, and optimization in a design tool for architects that want to engage in the use of computation-based architectural design while taking advantage of the portability, expressive power, and scalability of modern pedagogic programming languages. The tool, named Khepri, will support (1) the development of portable programs that create equivalent building models in BIM and non- BIM tools, (2) the automation of their analysis in relevant analysis tools, and (3) the optimization of the modeled buildings within the bounds established by the architect.
Khepri will help reduce the environmental and economic impact of buildings, will mitigate the complexity of BIM, and will be a research vehicle for advancing the state of the art in computational techniques applied to architecture.
Project Name: Khepri - Algorithmic Design, Analysis and Optimization
Time Period: 01-10-2018 to 30-09-2021
Funding: 240K Eur
In order to prepare students for the Generative Design paradigm, it becomes necessary to teach computer science in the realm of architecture problems and using programming languages appropriate for the generation of architectural models for the CAD systems currently available.
The end result of this projects was a pedagogic interactive development environment that accompanies the architect from the learning phases to the advanced uses and that is usable both for practical applications as well as for research.
Project Name: Rosetta - The Generative Design tool
Time Period: 02-05-2013 to 01-11-2015
Funding: 120K Eur
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