4 papers
RHNAS: Realizable Hardware and Neural Architecture Search
Yash Akhauri, Adithya Niranjan, J. Pablo Muñoz +6
The rapidly evolving field of Artificial Intelligence necessitates automated approaches to co-design neural network architecture and neural accelerators to maximize system efficien…
Exposing Hardware Building Blocks to Machine Learning Frameworks
Yash Akhauri
There are a plethora of applications that demand high throughput and low latency algorithms leveraging machine learning methods. This need for real time processing can be seen in i…
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications
Yaman Umuroglu, Yash Akhauri, Nicholas J. Fraser +1
Deployment of deep neural networks for applications that require very high throughput or extremely low latency is a severe computational challenge, further exacerbated by inefficie…
HadaNets: Flexible Quantization Strategies for Neural Networks
Yash Akhauri
On-board processing elements on UAVs are currently inadequate for training and inference of Deep Neural Networks. This is largely due to the energy consumption of memory accesses i…