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Xiang-Tao Guan, Shu-Yao Cheng, Mo Zou, Rui Zhang, Yun-Ji Chen. Data-Driven Automated Processor DesignJ. Journal of Computer Science and Technology. DOI: 10.1007/s11390-026-6043-x
Citation: Xiang-Tao Guan, Shu-Yao Cheng, Mo Zou, Rui Zhang, Yun-Ji Chen. Data-Driven Automated Processor DesignJ. Journal of Computer Science and Technology. DOI: 10.1007/s11390-026-6043-x

Data-Driven Automated Processor Design

  • Fully automated processor design has recently exploded in popularity due to its fast convergence speed and reduced human costs. However, automated design remains challenging in processor correctness and performance guarantee. In this article, we introduce a series of chip auto-design methods based on Binary Speculative Diagram (BSD), emphasizing how they guarantee design correctness and improve the auto-designed chip performance. Auto-designed by BSD, QiMeng-CPU-v1, an industrial-scale RISC-V CPU, achieves up to 99.9999999999999\% accuracy. Auto-designed by State-BSD, QiMeng-CPU-v2 is comparable to ARM Cortex A53 (2010s CPU), a human-designed superscalar processor. Finally, we introduce future explorations on the QiMeng series.
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