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Vectorized QuickScorer

Vectorized QuickScorer was designed by Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., Tonellotto, N., and Venturini, R. with the support of Tiscali S.p.A.

Vectorized QuickScorer is an extension of QuickScorer to exploit SIMD capabilities of modern CPUs. The algorithm is presented in Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., Tonellotto, N., and Venturini, R. Exploiting CPU SIMD Extensions to Speed-up Document Scoring with Tree Ensembles. In SIGIR '16: Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (2016).

The QuickScorer algorithm is discussed in Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., Tonellotto, N., and Venturini, R. Quickscorer: a fast algorithm to rank documents with additive ensembles of regression trees. In SIGIR '15: Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (2015).

Dato, D., Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., Tonellotto, N., and Venturini, R. Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees. In ACM Trans. Inf. Syst., 2016 (to appear) presents an extensive and detailed test assessment on two standard Learning-to-Rank datasets and on a novel very-large dataset we made publicly available for conducting significant efficiency tests (istella dataset).

QuickScorer is undergoing a patent process. Title of invention: A method to rank documents by a computer, using additive ensembles of regression trees and cache optimization, and search engine using such a method, applicant Tiscali S.p.A., inventors: Dato, D., Lucchese, C., Nardini, F. M., Orlando, S., Perego, R., Tonellotto, N., and Venturini, R.. International patent pending no. PCT29914.

The source code of Vectorized QuickScorer is made available under NDA with Tiscali S.p.A. For any information please contact us at quickscorer@isti.cnr.it.