2013 | OriginalPaper | Chapter
When Distributed Computation Is Communication Expensive
Authors : David P. Woodruff, Qin Zhang
Published in: Distributed Computing
Publisher: Springer Berlin Heidelberg
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We consider a number of fundamental statistical and graph problems in the message-passing model, where we have
k
machines (sites), each holding a piece of data, and the machines want to jointly solve a problem defined on the union of the
k
data sets. The communication is point-to-point, and the goal is to minimize the total communication among the
k
machines. This model captures all point-to-point distributed computational models with respect to minimizing communication costs. Our analysis shows that exact computation of many statistical and graph problems in this distributed setting requires a prohibitively large amount of communication, and often one cannot improve upon the communication of the simple protocol in which all machines send their data to a centralized server. Thus, in order to obtain protocols that are communication-efficient, one has to allow approximation, or investigate the distribution or layout of the data sets.