TY - GEN
T1 - Fast, Scalable Phrase-Based SMT Decoding
AU - Hoang, Hieu
AU - Bogoychev, Nikolay
AU - Schwartz, Lane
AU - Junczys-Dowmunt, Marcin
N1 - This work is sponsored by the Air Force Research Laboratory, prime contract FA8650-11-C-6160. The views and conclusions contained in this document are those of the authors and should not be interpreted as representative of the official policies, either expressed or implied, of the Air Force Research Laboratory or the U.S. Government. Thanks to Kenneth Heafield for advice and code.
PY - 2016
Y1 - 2016
N2 - The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community. As commercial use has increased, there is need for software that is optimized for commercial requirements, in particular, fast phrase-based decoding and more efficient utilization of modern multicore servers. In this paper we re-examine the major components of phrase-based decoding and decoder implementation with particular emphasis on speed and scalability on multicore machines. The result is a drop-in replacement for the Moses decoder which is up to fifteen times faster and scales monotonically with the number of cores.
AB - The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community. As commercial use has increased, there is need for software that is optimized for commercial requirements, in particular, fast phrase-based decoding and more efficient utilization of modern multicore servers. In this paper we re-examine the major components of phrase-based decoding and decoder implementation with particular emphasis on speed and scalability on multicore machines. The result is a drop-in replacement for the Moses decoder which is up to fifteen times faster and scales monotonically with the number of cores.
UR - https://www.scopus.com/pages/publications/85072939955
UR - https://www.scopus.com/pages/publications/85072939955#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:85072939955
T3 - Proceedings - AMTA 2016: 12th Conference of the Association for Machine Translation in the Americas
SP - 40
EP - 52
BT - MT Researchers' Track
A2 - Green, Spence
A2 - Schwartz, Lane
PB - Association for Machine Translation in the Americas
T2 - 12th Conference of the Association for Machine Translation in the Americas, AMTA 2016
Y2 - 28 October 2016 through 1 November 2016
ER -