While there are several examples of approaches to generate architectures based on functional requirements, we believe that there are very few techniques that consider NFRs such as adaptability during the process of architecture generation.
With our approach, it is possible to generate architectures with different features (time and energy), which allows the designer to fastly obtain the architecture that best suits his application.
In order to generate architectures for the sliding clamp oligomers, we used two different approaches.
In terms of arithmetic accuracy, the generated architecture can generally only be configured through the input and output word lengths.
The generated architecture uses components (operator, register, etc).
A linear elastic material model, with a damage function and element deletion, was used and the XMT generated architecture was loaded in compression.
The assessment model detailed in this paper combines known design heuristics with quantitative, qualitative, and visual representations that assess the probability that the generated architecture will meet performance and capability requirements.
This provides a systematic approach to generating architectures.
It is a so-called conditional Monte Carlo (MC) method generating architectures of molecules of specified dimensions.
We compare the performance of our algorithm against that of a traditional Force-Directed Scheduling approach by generating architectures from algorithms selected from embedded computing and scientific computing.
