RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model

Built on

J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova, “Bert: Pre-training of deep bidirectional transformers for language understanding,” arXiv preprint arXiv:1810.04805 , 2018
Original
2018
Earlier work this paper cites.
G. Huang, J. Hu, Y. He, J. Liu, M. Ma, Z. Shen, J. Wu, Y. Xu, H. Zhang, K. Zhong et al. , “Machine learning for electronic design automation: A survey,” ACM TODAES , 2021
2021
Earlier work this paper cites.
M. Rapp, H. Amrouch, Y. Lin, B. Yu, D. Z. Pan, M. Wolf, and J. Henkel, “MLCAD: A survey of research in machine learning for CAD keynote paper,” TCAD , 2021
2021
Earlier work this paper cites.
E. Nijkamp, B. Pang, H. Hayashi, L. Tu, H. Wang, Y. Zhou, S. Savarese, and C. Xiong, “A conversational paradigm for program synthesis,” arXiv preprint arXiv:2203.13474 , vol. 30, 2022
Original
2022
Earlier work this paper cites.

Synopsys, “Design Compiler® RTL Synthesis,” 2022
2022
Cited alongside, same era.
E. Nijkamp, B. Pang, H. Hayashi, L. Tu, H. Wang, Y. Zhou, S. Savarese, and C. Xiong, “Codegen: An open large language model for code with multi-turn program synthesis,” arXiv preprint arXiv:2203.13474 , 2022
Original
2022
Cited alongside, same era.
OpenAI, “GPT-4 Technical Report,” arXiv preprint arXiv:2303.08774 , 2023
Original
2023
Cited alongside, same era.
S. Thakur, B. Ahmad, Z. Fan, H. Pearce, B. Tan, R. Karri, B. Dolan-Gavitt, and S. Garg, “Benchmarking large language models for automated verilog rtl code generation,” in DATE , 2023
2023
Cited alongside, same era.