闭式默认值的艺术：张量算子的免搜索代码生成
The Art of Closed-Formula Defaults: Search-Free Code Generation for Tensor Operators
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中文总结 AI 辅助
提出应用优先的分层代码生成方法，通过清晰的计算模型使张量算子优化问题可处理，实现免搜索的GPU代码生成。
中文摘要 AI 辅助
智能体搜索和GPU内核的自动优化是大型语言模型推理的强大工具。然而，其有效性并不取决于搜索本身的复杂性，而取决于所解决的优化问题的清晰度。我们提出了一种应用优先的方法，驱动一个从算子规格说明到GPU指令的分层代码生成工具，并表明清晰定义的计算模型使优化问题变得可处理。
英文摘要
Agentic search and automated optimization of GPU kernels are powerful tools for large language model inference. Their effectiveness, however, depends not on the sophistication of the search itself, but on the clarity of the optimization problem being solved. We provide an application-first approach that drives a hierarchical code generation tool from operator specifi cation down to GPU instructions, and show that a clearly defined computational model makes the optimization problem tractable.
发表机构
- Advanced Micro Devices, Inc.（超威半导体）
机构由 AI 辅助整理，请以论文原文为准。
