Vau da muntanialas: Energy-efficient multi-die scalable acceleration of RNN inference
Recurrent neural networks such as Long Short-Term Memories (LSTMs) learn temporal
dependencies by keeping an internal state, making them ideal for time-series problems such …
dependencies by keeping an internal state, making them ideal for time-series problems such …
A Fully Integrated 5-mW, 0.8-Gbps Energy-Efficient Chip-to-Chip Data Link for Ultralow-Power IoT End-Nodes in 65-nm CMOS
The increasing complexity of Internet-of-Things (IoT) applications and near-sensor
processing algorithms is pushing the computational power of low-power, battery-operated …
processing algorithms is pushing the computational power of low-power, battery-operated …
[PDF][PDF] System-on-chip Architectures for Event-Driven Computing
A Di Mauro - 2022 - research-collection.ethz.ch
The number of electronic devices deployed around us has followed a steadily increasing
trend over the last decade. As the transistor miniaturization and integration processes …
trend over the last decade. As the transistor miniaturization and integration processes …