HACScale : hardware-aware compound scaling for resource-efficient DNNs
Model scaling is an effective way to improve the accuracy of deep neural networks (DNNs) by increasing the model capacity. However, existing approaches seldom consider the underlying hardware, causing inefficient utilization of hardware resources and consequently high inference latency. In this pape...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/155808 |