Massively Parallel Computation
Foundations and Trends in Optimization(2023)
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.
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