2 citations · 6 across the 13 of their papers we have counts for
3 papers · 1 filter
Effective Interplay between Sparsity and Quantization: From Theory to Practice
Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok +8
The increasing size of deep neural networks (DNNs) necessitates effective model compression to reduce their computational and memory footprints. Sparsity and quantization are two p…
Tao: Re-Thinking DL-based Microarchitecture Simulation
Santosh Pandey, Amir Yazdanbakhsh, Hang Liu
Microarchitecture simulators are indispensable tools for microarchitecture designers to validate, estimate, and optimize new hardware that meets specific design requirements. While…
Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers
Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian +4
N:M Structured sparsity has garnered significant interest as a result of relatively modest overhead and improved efficiency. Additionally, this form of sparsity holds considerable…