Boosting performance of a Statistical Machine Translation system using dynamic parallelism
• New Statistical Machine Translation (SMT) system based on Moses toolkit. • Translation jobs are processed in parallel using a different number of cores. • The level of parallelism changes dynamically according to the load of the server. • An autotuning module allows the system to adapt to any hard...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Fernández, M. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Umfang: |
12 |
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| Übergeordnetes Werk: |
Enthalten in: Effective mineralization of organic dye under visible-light irradiation over electronic-structure-modulated Sn(Nb1−x Ta x )2O6 solid solutions - Ren, Jian ELSEVIER, 2015, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:13 ; year:2016 ; pages:37-48 ; extent:12 |
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| DOI / URN: |
10.1016/j.jocs.2016.01.003 |
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| 520 | |a • New Statistical Machine Translation (SMT) system based on Moses toolkit. • Translation jobs are processed in parallel using a different number of cores. • The level of parallelism changes dynamically according to the load of the server. • An autotuning module allows the system to adapt to any hardware platform. • Important reductions in the translation times were observed for different scenarios. | ||
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10.1016/j.jocs.2016.01.003 doi GBVA2016011000012.pica (DE-627)ELV035313072 (ELSEVIER)S1877-7503(16)30002-3 DE-627 ger DE-627 rakwb eng 004 004 DE-600 540 VZ 570 VZ BIODIV DE-30 fid PHARM DE-84 fid 44.00 bkl Fernández, M. verfasserin aut Boosting performance of a Statistical Machine Translation system using dynamic parallelism 2016 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • New Statistical Machine Translation (SMT) system based on Moses toolkit. • Translation jobs are processed in parallel using a different number of cores. • The level of parallelism changes dynamically according to the load of the server. • An autotuning module allows the system to adapt to any hardware platform. • Important reductions in the translation times were observed for different scenarios. Load balance Elsevier Parallelism Elsevier Autotuning Elsevier Machine translation Elsevier Performance Elsevier Pichel, Juan C. oth Cabaleiro, José C. oth Pena, Tomás F. oth Enthalten in Elsevier Ren, Jian ELSEVIER Effective mineralization of organic dye under visible-light irradiation over electronic-structure-modulated Sn(Nb1−x Ta x )2O6 solid solutions 2015 Amsterdam [u.a.] (DE-627)ELV018619908 volume:13 year:2016 pages:37-48 extent:12 https://doi.org/10.1016/j.jocs.2016.01.003 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV FID-PHARM SSG-OLC-PHA SSG-OPC-PHA GBV_ILN_11 GBV_ILN_21 GBV_ILN_26 GBV_ILN_40 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2011 44.00 Medizin: Allgemeines VZ AR 13 2016 37-48 12 045F 004 |
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Fernández, M. |
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10.1016/j.jocs.2016.01.003 |
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boosting performance of a statistical machine translation system using dynamic parallelism |
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Boosting performance of a Statistical Machine Translation system using dynamic parallelism |
| abstract |
• New Statistical Machine Translation (SMT) system based on Moses toolkit. • Translation jobs are processed in parallel using a different number of cores. • The level of parallelism changes dynamically according to the load of the server. • An autotuning module allows the system to adapt to any hardware platform. • Important reductions in the translation times were observed for different scenarios. |
| abstractGer |
• New Statistical Machine Translation (SMT) system based on Moses toolkit. • Translation jobs are processed in parallel using a different number of cores. • The level of parallelism changes dynamically according to the load of the server. • An autotuning module allows the system to adapt to any hardware platform. • Important reductions in the translation times were observed for different scenarios. |
| abstract_unstemmed |
• New Statistical Machine Translation (SMT) system based on Moses toolkit. • Translation jobs are processed in parallel using a different number of cores. • The level of parallelism changes dynamically according to the load of the server. • An autotuning module allows the system to adapt to any hardware platform. • Important reductions in the translation times were observed for different scenarios. |
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| title_short |
Boosting performance of a Statistical Machine Translation system using dynamic parallelism |
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https://doi.org/10.1016/j.jocs.2016.01.003 |
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Pichel, Juan C. Cabaleiro, José C. Pena, Tomás F. |
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