@inproceedings{a8012d2e765343c5ae773af06008cdf7,
title = "FPGA-based acceleration of word2vec using OpenCL",
abstract = "Word2vec is a word embedding method that converts words into vectors in such a way that the semantically and syntactically relevant words are close to each other in the vector space. The processing time of Word2vec is very large due to the huge data size. We propose a power efficient FPGA-based accelerator designed using OpenCL. We achieved 13.4 times speed-up compared to single-core CPU implementation with only 53W of power consumption. The proposed FPGA-based accelerator has the highest power-efficiency compared to existing top-end GPU-based accelerators.",
keywords = "FPGA, Machine learning, Natural language processing, Word embedding",
author = "Taisuke Ono and Tomoki Shoji and Waidyasooriya, {Hasitha Muthumala} and Masanori Hariyama and Yuichiro Aoki and Yuki Kondoh and Yaoko Nakagawa",
note = "Funding Information: A part of the experimental results in this research were obtained using supercomputing resources at Cyberscience Center, Tohoku University. Publisher Copyright: {\textcopyright} 2019 IEEE; 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 ; Conference date: 26-05-2019 Through 29-05-2019",
year = "2019",
doi = "10.1109/ISCAS.2019.8702700",
language = "English",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings",
address = "United States",
}