Low-Complexity Distributed-Arithmetic-Based Pipelined Architecture for an LSTM Network

Long short-term memory (LSTM) networks have addressed the shortcomings of recurrent neural networks, such as vanishing gradients and the lack of ability in developing connections across discontinuous parts of sequences. However, the implementations of state-of-the-art LSTM networks face the computat...

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Vydané v:	IEEE transactions on very large scale integration (VLSI) systems Ročník 28; číslo 2; s. 329 - 338
Hlavní autori:	Yalamarthy, Krishna Praveen, Dhall, Saurabh, Khan, Mohd. Tasleem, Shaik, Rafi Ahamed
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.02.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Acceleration Arithmetic Binary codes Boolean algebra Complexity Complexity theory Computer architecture Distributed arithmetic (DA) Hardware Logic gates long short-term memory (LSTM) networks Mathematical analysis Matrix algebra Matrix methods Memory management Neural networks offset binary coding (OBC) Power consumption Recurrent neural networks Selectors Table lookup
ISSN:	1063-8210, 1557-9999
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