一句话：指出现有内存层次与 processing-in-memory 方法导致数据移动昂贵，并提出 Livia 以应对该扩展性挑战。
论文关注未来系统扩展所面临的数据移动瓶颈。作者指出，当前设计中数据移动代价高昂有两个原因：传统内存层次结构迫使计算远离数据，而 processing-in-memory 方法未能利用局部性。为此，论文以 Livia 为题提出一种应对方案，目标应是减少数据移动并更好利用数据局部性。不过，给出的摘要非常简短，未说明 Livia 的具体架构、编程抽象、实现方式或实验评估，因此无法从现有信息判断其关键结果与适用范围。
In order to scale, future systems will need to dramatically reduce data movement. Data movement is expensive in current designs because (i) traditional memory hierarchies force computation to happen unnecessarily far away from data and (ii) processing-in-memory approaches fail to exploit locality.
@inproceedings{paperbot5411,
title = {Livia},
author = {Elliot Lockerman and Axel Feldmann and Mohammad Bakhshalipour and Alexandru Stanescu and Shashwat Gupta and Daniel Sanchez and Nathan Beckmann},
booktitle = {ASPLOS},
year = {2020},
doi = {10.1145/3373376.3378497}
}