研究人员开发了一种在AI编译器中跟踪数据和操作来源的新方法。该方法使用观测语义和协代数模型来保留溯源信息，即使在中间计算步骤被移除的情况下也是如此。一个名为COVAN的原型编译器已被构建，以展示这种轻量级技术的有效性，该技术旨在改进编译器转换的调试和验证。 AI
影响 增强了AI编译器转换的调试和验证能力，有望改进AI开发工作流程。
排序理由 该集群包含一篇详细介绍新研究方法及其在原型中实现的学术论文。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
arXiv:2606.10937v1 Announce Type: cross Abstract: AI compilers aggressively rewrite computation graphs through normalization, lowering, and optimization, making it difficult to track the provenance of tensors and operators across compilation. Reliable provenance is essential for …
AI compilers aggressively rewrite computation graphs through normalization, lowering, and optimization, making it difficult to track the provenance of tensors and operators across compilation. Reliable provenance is essential for attaching platform-specific postprocessing, debugg…