Abstract
In this paper we propose an evaluation method for parallel algorithms that can be used independently of the used parallel programming library and architecture. We propose to predict the execution costs using a simple but efficient framework that consists in modeling the strategies via a BSP architecture, and estimating the real costs using as input real query traces over real or stochastically generated data. In particular we apply this method on a 2D inverted file index used to resolve web search queries. We present results for OR queries, for which we compare different ranking and caching strategies, and show how our framework works. In addition, we present and evaluate intelligent ranking and caching algorithms for AND queries.
Partially supported by Universidad de Buenos Aires’ UBACYT project X436.
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Feuerstein, E., Gil-Costa, V., Mizrahi, M., Marin, M. (2011). Performance Evaluation of Improved Web Search Algorithms. In: Palma, J.M.L.M., Daydé, M., Marques, O., Lopes, J.C. (eds) High Performance Computing for Computational Science – VECPAR 2010. VECPAR 2010. Lecture Notes in Computer Science, vol 6449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19328-6_23
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DOI: https://doi.org/10.1007/978-3-642-19328-6_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19327-9
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