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Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization
In decentralized optimization, nodes cooperate to minimize an overall objective function that is the sum (or average) of per-node private objective functions.
Optimization and Control Distributed, Parallel, and Cluster Computing Multiagent Systems
A Massively Parallel Associative Memory Based on Sparse Neural Networks
In this paper we implement a variation of the Gripon-Berrou associative memory on a general purpose graphical processing unit (GPU).
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization
We study the scalability of consensus-based distributed optimization algorithms by considering two questions: How many processors should we use for a given problem, and how often should they communicate when communication is not free?
