The Argument for Meta-Modeling-Based Approaches to Hardware Generation Languages
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909163366383616 |
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| author | Schreiner, Johannes Gerl, Daniel Kunzelmann, Robert Sinha, Paritosh Kumar Ecker, Wolfgang |
| author_facet | Schreiner, Johannes Gerl, Daniel Kunzelmann, Robert Sinha, Paritosh Kumar Ecker, Wolfgang |
| contents | The rapid evolution of Integrated Circuit (IC) development necessitates innovative methodologies such as code generation to manage complexity and increase productivity. Using the right methodology for generator development to maximize the capability and, most notably, the feasibility of generators is a crucial part of this work. Meta-Modeling-based approaches drawing on the principles of Model Driven Architecture (MDA) are a promising methodology for generator development. The goal of this paper is to show why such an MDA-based approach can provide extremely powerful generators with minimal implementation effort and to demonstrate that this approach is a superior alternative to the most advanced hardware generation languages such as SpinalHDL and Chisel. For this purpose, this paper provides an in-depth comparison of the Meta-Modeling approach against these hardware generation languages, highlighting the unique advantages of a Meta-Modeling-based approach and summarizes the benefits. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2404_05599 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | The Argument for Meta-Modeling-Based Approaches to Hardware Generation Languages Schreiner, Johannes Gerl, Daniel Kunzelmann, Robert Sinha, Paritosh Kumar Ecker, Wolfgang Software Engineering Hardware Architecture Programming Languages The rapid evolution of Integrated Circuit (IC) development necessitates innovative methodologies such as code generation to manage complexity and increase productivity. Using the right methodology for generator development to maximize the capability and, most notably, the feasibility of generators is a crucial part of this work. Meta-Modeling-based approaches drawing on the principles of Model Driven Architecture (MDA) are a promising methodology for generator development. The goal of this paper is to show why such an MDA-based approach can provide extremely powerful generators with minimal implementation effort and to demonstrate that this approach is a superior alternative to the most advanced hardware generation languages such as SpinalHDL and Chisel. For this purpose, this paper provides an in-depth comparison of the Meta-Modeling approach against these hardware generation languages, highlighting the unique advantages of a Meta-Modeling-based approach and summarizes the benefits. |
| title | The Argument for Meta-Modeling-Based Approaches to Hardware Generation Languages |
| topic | Software Engineering Hardware Architecture Programming Languages |
| url | https://arxiv.org/abs/2404.05599 |