Performance analysis of a distributed question/answering system

Mihai Surdeanu, Dan I. Moldovan, Sanda M. Harabagiu

Research output: Contribution to journalArticle

29 Scopus citations

Abstract

The problem of question/answering (Q/A) is to find answers to open-domain questions by searching large collections of documents. Unlike information retrieval systems very common today in the form of Internet search engines, Q/A systems do not retrieve documents, but instead provide short, relevant answers located in small fragments of text. This enhanced functionality comes with a price: Q/A systems are significantly slower and require more hardware resources than information retrieval systems. This paper proposes a distributed Q/A architecture that enhances the system throughput through the exploitation of interquestion parallelism and dynamic load balancing and reduces the individual question response time through the exploitation of intraquestion parallelism. Inter and intraquestion parallelism are both exploited using several scheduling points: one before the Q/A task is started and two embedded in the Q/A task. An analytical performance model is introduced. The model analyzes both the interquestion parallelism overhead generated by the migration of questions and the intraquestion parallelism overhead generated by the partitioning of the Q/A task. The analytical model indicates that both question migration and partitioning are required for a high-performance system: Intraquestion parallelism leads to significant speedup of individual questions, but it is practical up to about 90 processors, depending on the system parameters. The exploitation of intertask parallelism provides a scalable way to improve the system throughput. The distributed Q/A system has been implemented on a network of 16 Pentium III computers. The experimental results indicate that, at high system load, the dynamic load balancing strategy proposed in this paper outperforms two other traditional approaches. At low system load, the distributed Q/A system reduces question response times through task partitioning, with factors close to the ones indicated by the analytical model.

Original languageEnglish (US)
Pages (from-to)579-596
Number of pages18
JournalIEEE Transactions on Parallel and Distributed Systems
Volume13
Issue number6
DOIs
StatePublished - Jun 1 2002
Externally publishedYes

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Keywords

  • Distributed question answering
  • Load balancing
  • Migration
  • Partitioning

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

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