Performance analysis of a distributed question/answering system

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