Cargando…
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors
Although the quest for more accurate solutions is pushing deep learning research towards larger and more complex algorithms, edge devices demand efficient inference and therefore reduction in model size, latency and energy consumption. One technique to limit model size is quantization, which implies...
| Autores principales: | , , , , , , , , , |
|---|---|
| Lenguaje: | eng |
| Publicado: |
2020
|
| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1038/s42256-021-00356-5 http://cds.cern.ch/record/2724942 |