We propose VibeCodeHPC, an automatic tuning system for HPC programs based on multi-agent LLMs for code generation. VibeCodeHPC tunes programs through multi-agent role allocation and iterative prompt refinement. We describe the system configuration with four roles: Project Manager (PM), System Engineer (SE), Programmer (PG), and Continuous Delivery (CD). We introduce dynamic agent deployment and activity monitoring functions to facilitate effective multi-agent collaboration. In our case study, we convert and optimize CPU-based matrix-matrix multiplication code written in C to GPU code using CUDA. The multi-agent configuration of VibeCodeHPC achieved higher-quality code generation per unit time compared to a solo-agent configuration. Additionally, the dynamic agent deployment and activity monitoring capabilities facilitated more effective identification of requirement violations and other issues.

翻译：我们提出了VibeCodeHPC，一种基于多智能体大语言模型进行代码生成的高性能计算程序自动调优系统。VibeCodeHPC通过多智能体角色分配与迭代提示优化来实现程序调优。我们描述了包含四个角色的系统配置：项目经理（PM）、系统工程师（SE）、程序员（PG）和持续交付（CD）。我们引入了动态智能体部署与活动监控功能，以促进有效的多智能体协作。在我们的案例研究中，我们将用C语言编写的基于CPU的矩阵乘法代码转换并优化为使用CUDA的GPU代码。与单智能体配置相比，VibeCodeHPC的多智能体配置在单位时间内实现了更高质量的代码生成。此外，动态智能体部署与活动监控能力有助于更有效地识别需求违规及其他问题。