大模型正重塑编译器，让编程更智能、更高效。
The New Compiler Stack: A Survey on the Synergy of LLMs and Compilers
- 用多维度分类法梳理大模型如何参与编译流程
- 提升编译器开发门槛，发现新优化策略，扩展应用场景
- 适合编译器研究者和大模型应用开发者参考
本综述系统梳理了大模型赋能编译领域的新兴方向，回答了三大核心问题。首先，通过提出多维分类体系，将相关工作按设计哲学（选择器、翻译器、生成器）、大模型方法、代码抽象层级及任务类型进行归类。其次，总结出三大进展：降低编译器开发门槛、发现新型优化策略、拓展编译器传统功能边界。最后，指出当前主要挑战在于保证正确性和可扩展性，而混合系统的发展是最具前景的方向。该综述为研究人员与实践者提供了面向下一代智能、自适应、协同式编译工具的路线图。
原文摘要 · Abstract (English)
This survey has provided a systematic overview of the emerging field of LLM-enabled compilation by addressing several key research questions. We first answered how LLMs are being integrated by proposing a comprehensive, multi-dimensional taxonomy that categorizes works based on their Design Philosophy (Selector, Translator, Generator), LLM Methodology, their operational Level of Code Abstraction, and the specific Task Type they address. In answering what advancements these approaches offer, we identified three primary benefits: the democratization of compiler development, the discovery of novel optimization strategies, and the broadening of the compiler's traditional scope. Finally, in addressing the field's challenges and opportunities, we highlighted the critical hurdles of ensuring correctness and achieving scalability, while identifying the development of hybrid systems as the most promising path forward. By providing these answers, this survey serves as a foundational roadmap for researchers and practitioners, charting the course for a new generation of LLM-powered, intelligent, adaptive and synergistic compilation tools.
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