A Case Study in Complexity Estimation: Towards Parallel Branch-and-Bound over Graphical ModelsDownload PDF

28 Mar 2024 (modified: 20 Apr 2013)ICML 2013 Inferning submissionReaders: Everyone
Decision: conferencePoster
Abstract: We study the problem of complexity estimation in the context of parallelizing an advanced Branch and Bound-type algorithm over graphical models. The algorithm's pruning power makes load balancing, one crucial element of every distributed system, very challenging. We propose using a statistical regression model to identify and tackle disproportionally complex parallel subproblems, the cause of load imbalance, ahead of time. The proposed model is evaluated and analyzed on various levels and shown to yield robust predictions. We then demonstrate its effectiveness for load balancing in practice.
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