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arXiv · 1804.05038

Pieces of Eight: 8-bit Neural Machine Translation

Jerry Quinn·Miguel Ballesteros
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Abstract

Neural machine translation has achieved levels of fluency and adequacy that would have been surprising a short time ago. Output quality is extremely relevant for industry purposes, however it is equally important to produce results in the shortest time possible, mainly for latency-sensitive applications and to control cloud hosting costs. In this paper we show the effectiveness of translating with 8-bit quantization for models that have been trained using 32-bit floating point values. Results show that 8-bit translation makes a non-negligible impact in terms of speed with no degradation in accuracy and adequacy.

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Jerry Quinn, Miguel Ballesteros. 2018-04-13. Pieces of Eight: 8-bit Neural Machine Translation. https://arxiv.org/abs/1804.05038

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