CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++

Xiaolin Wang, Masao Utiyama, Eiichiro Sumita


Abstract
This paper presents an open-source neural machine translation toolkit named CytonMT. The toolkit is built from scratch only using C++ and NVIDIA’s GPU-accelerated libraries. The toolkit features training efficiency, code simplicity and translation quality. Benchmarks show that cytonMT accelerates the training speed by 64.5% to 110.8% on neural networks of various sizes, and achieves competitive translation quality.
Anthology ID:
D18-2023
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Eduardo Blanco, Wei Lu
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
133–138
Language:
URL:
https://aclanthology.org/D18-2023
DOI:
10.18653/v1/D18-2023
Bibkey:
Cite (ACL):
Xiaolin Wang, Masao Utiyama, and Eiichiro Sumita. 2018. CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 133–138, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++ (Wang et al., EMNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/D18-2023.pdf
Code
 arthurxlw/cytonMt