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Open-source Framework for HPCA2024 paper: Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet Accelerators

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SET-Scheduling-Project/GEMINI-HPCA2024

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Please follow the AE Appendix in corresponding HPCA 2024 paper "Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet Accelerators" to initiate the framework. We supplement the scripts of DSE for 72TOPs, 128TOPs, and 512TOPs.

Many essential foundational components of Gemini are shared with the SET framework from the same project. We are currently updating the architecture and documentation of the SET framework. For urgent inquiries about Gemini, one can refer to the comments in SET (updated at 2025.2.1). Additionally, we plan to migrate and update these annotations from SET to Gemini and include comments related to code unique to Gemini.

Citations

@inproceedings{10.1145/3579371.3589048,
author = {Cai, Jingwei and Wei, Yuchen and Wu, Zuotong and Peng, Sen and Ma, Kaisheng},
title = {Inter-layer Scheduling Space Definition and Exploration for Tiled Accelerators},
year = {2023},
isbn = {9798400700958},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3579371.3589048},
doi = {10.1145/3579371.3589048},
booktitle = {Proceedings of the 50th Annual International Symposium on Computer Architecture},
articleno = {13},
numpages = {17},
keywords = {tiled accelerators, neural networks, inter-layer scheduling, scheduling},
location = {Orlando, FL, USA},
series = {ISCA '23}
}

@inproceedings{cai2024gemini,
  title={Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet Accelerators},
  author={Cai, Jingwei and Wu, Zuotong and Peng, Sen and Wei, Yuchen and Tan, Zhanhong and Shi, Guiming and Gao, Mingyu and Ma, Kaisheng},
  booktitle={2024 IEEE International Symposium on High-Performance Computer Architecture (HPCA)},
  pages={156--171},
  year={2024},
  organization={IEEE}
}

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Open-source Framework for HPCA2024 paper: Gemini: Mapping and Architecture Co-exploration for Large-scale DNN Chiplet Accelerators

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