AMSNet: Netlist Dataset for AMS Circuits
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913536713687040 |
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| author | Tao, Zhuofu Shi, Yichen Huo, Yiru Ye, Rui Li, Zonghang Huang, Li Wu, Chen Bai, Na Yu, Zhiping Lin, Ting-Jung He, Lei |
| author_facet | Tao, Zhuofu Shi, Yichen Huo, Yiru Ye, Rui Li, Zonghang Huang, Li Wu, Chen Bai, Na Yu, Zhiping Lin, Ting-Jung He, Lei |
| contents | Today's analog/mixed-signal (AMS) integrated circuit (IC) designs demand substantial manual intervention. The advent of multimodal large language models (MLLMs) has unveiled significant potential across various fields, suggesting their applicability in streamlining large-scale AMS IC design as well. A bottleneck in employing MLLMs for automatic AMS circuit generation is the absence of a comprehensive dataset delineating the schematic-netlist relationship. We therefore design an automatic technique for converting schematics into netlists, and create dataset AMSNet, encompassing transistor-level schematics and corresponding SPICE format netlists. With a growing size, AMSNet can significantly facilitate exploration of MLLM applications in AMS circuit design. We have made an initial set of netlists public, and will make both our netlist generation tool and the full dataset available upon publishing of this paper. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_09045 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AMSNet: Netlist Dataset for AMS Circuits Tao, Zhuofu Shi, Yichen Huo, Yiru Ye, Rui Li, Zonghang Huang, Li Wu, Chen Bai, Na Yu, Zhiping Lin, Ting-Jung He, Lei Computer Vision and Pattern Recognition Today's analog/mixed-signal (AMS) integrated circuit (IC) designs demand substantial manual intervention. The advent of multimodal large language models (MLLMs) has unveiled significant potential across various fields, suggesting their applicability in streamlining large-scale AMS IC design as well. A bottleneck in employing MLLMs for automatic AMS circuit generation is the absence of a comprehensive dataset delineating the schematic-netlist relationship. We therefore design an automatic technique for converting schematics into netlists, and create dataset AMSNet, encompassing transistor-level schematics and corresponding SPICE format netlists. With a growing size, AMSNet can significantly facilitate exploration of MLLM applications in AMS circuit design. We have made an initial set of netlists public, and will make both our netlist generation tool and the full dataset available upon publishing of this paper. |
| title | AMSNet: Netlist Dataset for AMS Circuits |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2405.09045 |