一句话：提出面向 GPU 的作用域缓冲持久性模型，为持久内存感知 GPU 程序的正确性推理提供基础。
持久内存（PM）对 CPU 软硬件的影响已被广泛研究，但对 GPU 而言仍不充分。已有工作 GPM 展示了 GPU 程序如何受益于 PM 的细粒度持久性，然而由于缺乏持久性模型，无法对 PM 感知的 GPU 程序进行正确性推理。持久性模型规定对 PM 的写操作以何种顺序持久化。本文探索面向 GPU 的持久性模型，并提出一种作用域缓冲持久性模型，旨在填补 GPU 持久内存编程语义的空白。摘要未报告具体实验评估，工作重点在于模型层面的探索与定义。
While the implications of persistent memory (PM) on CPU hardware and software are well-explored, the same is not true for GPUs (Graphics Processing Units). A recent work, GPM, demonstrated how GPU programs can benefit from the fine-grain persistence of PM. However, in the absence of a persistency model, one cannot reason about the correctness of PM-aware GPU programs. Persistency models define the order in which writes to PM are persisted. We explore persistency models for GPUs.