Massively Parallel Computation

Foundations and Trends in Optimization(2023)

引用 0|浏览8
暂无评分
摘要
The algorithms community has been modeling the underlying key features and constraints of massively parallel frameworks and using these models to discover new algorithmic techniques tailored to them. This monograph focuses on the Massively Parallel Model of Computation (MPC) framework, also known as the MapReduce model in the literature. It describes algorithmic tools that have been developed to leverage the unique features of the MPC framework. These tools were chosen for their broad applicability, as they can serve as building blocks to design new algorithms. The monograph is not exhaustive and includes topics such as partitioning and coresets, sample and prune, dynamic programming, round compression, and lower bounds.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要