一句话：提出组合式操作模型，刻画不同一致性模型设备融合后的复合内存模型，并以 x86TSO/PTX 为例验证。
针对异构处理器中 CPU、GPU 等设备共享内存但各自拥有不同指令集与内存一致性模型的问题，本文研究融合后整体机器应遵循何种内存模型。作者形式化提出“复合”内存模型，给出一种组合式操作语义，用于描述具有不同一致性模型的设备组合后的行为。文中以 x86TSO CPU 与 PTX GPU 构成的复合 x86TSO/PTX 模型为实例。关键结果是该复合模型保留了来自语言级（scoped）C 内存模型的编译器映射：映射到 x86TSO 设备的线程可继续使用已有的 C 到 x86TSO 编译器映射，PTX 同样如此。
Today's mobile, desktop, and server processors are heterogeneous, consisting not only of CPUs but also GPUs and other accelerators. Such heterogeneous processors are starting to expose a shared memory interface across these devices.Given that each of these individual devices typically supports a distinct instruction set architecture and a distinct memory consistency model, it is not clear what the memory consistency model of the heterogeneous machine should be. In this paper, we answer this question by formalizing "compound" memory models: we present a compositional operational model describing the resulting model when devices with distinct consistency models are fused together. We instantiate our model with the compound x86TSO/PTX model -- a CPU enforcing x86TSO and a GPU enforcing the PTX model. A key result is that the x86TSO/PTX compound model retains compiler mappings from the language-based (scoped) C memory model. This means that threads mapped to the x86TSO device can continue to use the already proven C-to-x86TSO compiler mapping, and the same for PTX.
@article{paperbot1942,
title = {Compound Memory Models},
author = {Andrés Goens and Soham Chakraborty and Susmit Sarkar and Sukarn Agarwal and Nicolai Oswald and Vijay Nagarajan},
journal = {Proceedings of the ACM on Programming Languages},
volume = {7},
number = {PLDI},
year = {2023},
doi = {10.1145/3591267}
}