Letras M (2024)
Publication Language: English
Publication Type: Thesis
Publication year: 2024
URI: https://open.fau.de/handle/openfau/31834
The power of modern multi-core and many-core platforms is an excellent fit for meeting the performance needs of embedded software applications. However, there are many ways to map these applications to a specific multi-core or many-core architecture, leading to a large design space that requires extensive analysis. This analysis is needed to weigh the trade-offs of a set of design goals that need to be optimized. Therefore, there is a need for efficient design methods that can identify the Pareto-optimal application mappings while considering well-defined design constraints.
This thesis proposes approaches to address these challenges and integrate them into SystemCoDesigner’s Electronic System Level (ESL) design flow. The contributions presented in this thesis aim to facilitate the definition of dataflow applications by combining the model-based design of dataflow applications with block diagrams in MATLAB/Simulink to define the input application for the subsequent steps of the SystemCoDesigner methodology. Additionally, Design Space Exploration (DSE) methods were proposed to accelerate the exploration of mappings of dataflow-based applications to multi-core and many-core architectures. Compared to other DSE approaches, the methods proposed in this dissertation improve the quality of the found Pareto fronts.
APA:
Letras, M. (2024). Techniques for Efficient Performance Analysis and Memory Optimization in Mapping Dataflow Models of Computation onto Embedded Systems (Dissertation).
MLA:
Letras, Martin. Techniques for Efficient Performance Analysis and Memory Optimization in Mapping Dataflow Models of Computation onto Embedded Systems. Dissertation, 2024.
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