research
∙
04/09/2022
Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs
On-device ML accelerators are becoming a standard in modern mobile syste...
share
research
∙
03/01/2021
Mitigating Edge Machine Learning Inference Bottlenecks: An Empirical Study on Accelerating Google Edge Models
As the need for edge computing grows, many modern consumer devices now c...
research
∙
02/20/2021
An Evaluation of Edge TPU Accelerators for Convolutional Neural Networks
Edge TPUs are a domain of accelerators for low-power, edge devices and a...
research
∙
02/17/2021
Rethinking Co-design of Neural Architectures and Hardware Accelerators
Neural architectures and hardware accelerators have been two driving for...
research
∙
02/02/2021
Apollo: Transferable Architecture Exploration
The looming end of Moore's Law and ascending use of deep learning drives...
research
∙
08/18/2020
Discovering Multi-Hardware Mobile Models via Architecture Search
Developing efficient models for mobile phones or other on-device deploym...
research
∙
04/30/2020
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators
Inverted bottleneck layers, which are built upon depthwise convolutions,...
research
∙
03/05/2020