research
∙
10/24/2022
SpikeSim: An end-to-end Compute-in-Memory Hardware Evaluation Tool for Benchmarking Spiking Neural Networks
SNNs are an active research domain towards energy efficient machine inte...
share
research
∙
05/15/2022
COIN: Communication-Aware In-Memory Acceleration for Graph Convolutional Networks
Graph convolutional networks (GCNs) have shown remarkable learning capab...
research
∙
08/14/2021
SIAM: Chiplet-based Scalable In-Memory Acceleration with Mesh for Deep Neural Networks
In-memory computing (IMC) on a monolithic chip for deep learning faces d...
research
∙
07/06/2021
Impact of On-Chip Interconnect on In-Memory Acceleration of Deep Neural Networks
With the widespread use of Deep Neural Networks (DNNs), machine learning...
research
∙
11/11/2019
Structural Pruning in Deep Neural Networks: A Small-World Approach
Deep Neural Networks (DNNs) are usually over-parameterized, causing exce...
research
∙
05/28/2019