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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.00642 |
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| _version_ | 1866910769202855936 |
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| author | Zakharov, Mark Kashanaki, Farzaneh Rabiei Renau, Jose |
| author_facet | Zakharov, Mark Kashanaki, Farzaneh Rabiei Renau, Jose |
| contents | Large Language Models (LLMs) based agents are transforming the programming language landscape by facilitating learning for beginners, enabling code generation, and optimizing documentation workflows. Hardware Description Languages (HDLs), with their smaller user community, stand to benefit significantly from the application of LLMs as tools for learning new HDLs. This paper investigates the challenges and solutions of enabling LLMs for HDLs, particularly for HDLs that LLMs have not been previously trained on. This work introduces HDLAgent, an AI agent optimized for LLMs with limited knowledge of various HDLs. It significantly enhances off-the-shelf LLMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_00642 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Enabling New HDLs with Agents Zakharov, Mark Kashanaki, Farzaneh Rabiei Renau, Jose Hardware Architecture Artificial Intelligence Machine Learning Programming Languages Large Language Models (LLMs) based agents are transforming the programming language landscape by facilitating learning for beginners, enabling code generation, and optimizing documentation workflows. Hardware Description Languages (HDLs), with their smaller user community, stand to benefit significantly from the application of LLMs as tools for learning new HDLs. This paper investigates the challenges and solutions of enabling LLMs for HDLs, particularly for HDLs that LLMs have not been previously trained on. This work introduces HDLAgent, an AI agent optimized for LLMs with limited knowledge of various HDLs. It significantly enhances off-the-shelf LLMs. |
| title | Enabling New HDLs with Agents |
| topic | Hardware Architecture Artificial Intelligence Machine Learning Programming Languages |
| url | https://arxiv.org/abs/2501.00642 |