An efficient sparse LSTM accelerator on embedded FPGAs with bandwidth-oriented pruning

• Main Authors: Li, Shiqing, Zhu, Shien, Luo, Xiangzhong, Luo, Tao, Liu, Weichen
• 其他作者: School of Computer Science and Engineering
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2023
• 主題: Engineering::Computer science and engineering; Engineering::Computer science and engineering::Hardware; Sparse LSTM; Pruning; Bandwidth
• 在線閱讀: https://hdl.handle.net/10356/172603
• 機構: Nanyang Technological University

Long short-term memory (LSTM) networks have been widely used in natural language processing applications. Although over 80% weights can be pruned to reduce the memory requirement with little accuracy loss, the pruned model still cannot be buffered on-chip for small embedded FPGAs. Considering that w...