79 citations · 208 across the 29 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.AR2023★ 3 cited
A Heterogeneous Chiplet Architecture for Accelerating End-to-End Transformer Models
Harsh Sharma, Pratyush Dhingra, Janardhan Rao Doppa +2
Transformers have revolutionized deep learning and generative modeling, enabling advancements in natural language processing tasks. However, the size of transformer models is incre…
cs.AR2023
Block-Wise Mixed-Precision Quantization: Enabling High Efficiency for Practical ReRAM-based DNN Accelerators
Xueying Wu, Edward Hanson, Nansu Wang +9
Resistive random access memory (ReRAM)-based processing-in-memory (PIM) architectures have demonstrated great potential to accelerate Deep Neural Network (DNN) training/inference.…