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@QiMeng-IPRC

QiMeng-IPRC

README.md

QiMeng aims to achieve fully automated design of the chip hardware/software stack by leveraging large language models (LLMs), agents, and Boolean logic generation technologies. QiMeng has successfully automated designing RISC-V CPUs, optimizing operating system configurations, transcompiling tensor programs, and developing high-performance libraries, with performance comparable to that of human expertise. https://qimeng-ict.github.io/

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  1. QiMeng-cpu-v1 QiMeng-cpu-v1 Public

    [IJCAI 2024] QiMeng-CPU-v1: Automated CPU Design by Learning from Input-Output Examples

    Verilog 27 5

  2. AutoOS AutoOS Public

    [ICML 2024] AutoOS: Make Your OS More Powerful by Exploiting Large Language Models

    Python 14 7

  3. QiMeng-MuPa QiMeng-MuPa Public

    [NeurIPS 2025] QiMeng-MuPa: Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

    Python 10

  4. QiMeng-SALV QiMeng-SALV Public

    [NeurIPS 2025] QiMeng-SALV: Signal-Aware Learning for Verilog Code Generation

    Python 10 1

  5. BabelTower BabelTower Public

    [ICML 2022]BabelTower: Learning to Auto-parallelized Program Translation

    6 2

  6. QiMeng-GEMM QiMeng-GEMM Public

    [AAAI 2025] QiMeng-GEMM: Automatically Generating High-Performance Matrix Multiplication Code by Exploiting Large Language Models

    C 5

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