FPG-AI RNN: A Technology-Agnostic Framework for the Automatic Acceleration of LSTM/GRU-Based Models on FPGAs
Recurrent Neural Networks (RNNs) are pivotal in artificial intelligence, excelling in tasks involving sequential data across fields such as natural language processing and time-series forecasting. FPGAs have emerged as an efficient technology for accelerating these algorithms, especially in resource...
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| Main Authors: | Tommaso Pacini, Pietro Nannipieri, Silvia Moranti, Luca Fanucci |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11027895/ |
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