1
Towards Automated Kernel Generation in the Era of LLMs
用LLM自动生成GPU内核，突破AI系统性能瓶颈的前沿研究
arXiv:2601.15727v3 Announce Type: replace Abstract: The performance of modern AI systems is fundamentally constrained by the quality of their underlyi…
2
Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode
揭示LLM推理瓶颈新视角：batch-1解码受内存限制而非带宽限制，挑战传统认知。
arXiv:2605.30571v1 Announce Type: cross Abstract: Physical AI systems, including robots, autonomous vehicles, embodied agents and edge copilots, often…
3
GenAI-Driven Approach to RISC-V Supply Chain Exploration
用多模态AI大模型突破RISC-V供应链异构数据分析，打通视觉与文本的芯片溯源新范式
arXiv:2605.15223v1 Announce Type: cross Abstract: This paper presents an LLM-empowered workflow for RISC-V supply chain analysis, integrating Vision-L…