5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.AR2022
QUIDAM: A Framework for Quantization-Aware DNN Accelerator and Model Co-Exploration
Ahmet Inci, Siri Garudanagiri Virupaksha, Aman Jain +4
As the machine learning and systems communities strive to achieve higher energy-efficiency through custom deep neural network (DNN) accelerators, varied precision or quantization l…
cs.AR2022★ 5 cited
Efficient Deep Learning Using Non-Volatile Memory Technology
Ahmet Inci, Mehmet Meric Isgenc, Diana Marculescu
Embedded machine learning (ML) systems have now become the dominant platform for deploying ML serving tasks and are projected to become of equal importance for training ML models.…