XpulpNN: Enabling Energy Efficient and Flexible Inference of Quantized Neural Networks on RISC-V based IoT End Nodes.
Angelo GarofaloGiuseppe TagliaviniFrancesco ContiLuca BeniniDavide RossiPublished in: ARITH (2021)
Keyphrases
- energy efficient
- neural network
- sensor nodes
- wireless sensor networks
- sensor networks
- energy consumption
- battery powered
- data dissemination
- energy efficiency
- sink node
- data aggregation
- location information
- base station
- multi core architecture
- data transmission
- multi hop
- management system
- transmission power
- routing algorithm
- real time
- data gathering
- instruction set
- application specific
- routing protocol
- data collection
- wireless communication
- mobile computing
- data center
- data analysis