| ## Summary |
| RuC is a grammar-driven, rule-selectable benchmark generator that automatically produces RTL code-completion tasks from a set of input hardware description sources. It uses the target HDL grammar to mask syntactically defined code regions and prompts a model to regenerate them using the surrounding unmasked code as context. |
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| **Paper**: https://arxiv.org/abs/2604.27780 |
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| RuC-datasets is a collection of design datasets processed with the RuC framework and used for the experimentations in the paper. |
| Although RuC-cve2_b72358c7-32k and RuC-tt07-32k share the same schema and preprocessing steps, they originate from different base datasets and should be treated as separate datasets. |
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| ## Datasets structure |
| Each project inside both datasets contains: |
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| - <top_module>.sv for cve2 or <top_module>.v for tt07 |
| Verilog or SystemVerilog hardware designs named after the top-level module. |
| - mask_idx.json |
| Indices of selected rule occurrences used for RuC. |
| - all_mask_idx.json |
| Full set of candidate rule occurrences eligible for masking. |
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| ## Dataset creation |
| Both datasets computed mask_idx.json and all_mask_idx.json using RuC as explained in the paper. |
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| ### RuC-tt07-32k |
| NotSoTiny shuttle tt07 (https://huggingface.co/datasets/HPAI-BSC/NotSoTiny-25-12) filtered to keep designs that contain less than 32000 tokens. |
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| ### RuC-cve2_b72358c7-32k |
| CVE2 is an industry-grade RISC-V core maintained by OpenHWGroup. The CVE2 codebase preprocessed using vppreproc and filtered to keep designs that contain less than 32000 tokens. |
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| ## Datasets usage |
| These datasets are intended to be used together with the RuC framework (https://github.com/HPAI-BSC/RuC) to directly perform inference and evaluation with different LLMs. |
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| license: apache-2.0 |
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