Cursor+NVIDIA：多智能体系统加速GPU内核优化

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Cursor 与 NVIDIA 合作开发的一种多智能体系统，该系统能够自主优化用于 Blackwell GPU 的 CUDA 内核。在为期三周的实验中，该系统处理了 235 个真实的内核优化问题，并在这些任务上实现了平均 38% 的速度提升。通过独立学习硬件底层指令和复杂的编程接口，智能体展现出了超越传统手动优化且极具适应性的开发能力。这种自动化的方法显著降低了人工智能模型训练与推理的成本，同时提高了硬件效率。作者认为，这项研究证明了多智能体架构在处理复杂、开放式软件工程任务方面具有巨大潜力。

Episode metadata supplied by the publisher feed · Published Apr 18, 2026

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Cursor+NVIDIA：多智能体系统加速GPU内核优化

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