211 citations · 530 across the 27 of their papers we have counts for
7 papers · 1 filter
Neuromorphic Intermediate Representation: A Unified Instruction Set for Interoperable Brain-Inspired Computing
Jens E. Pedersen, Steven Abreu, Matthias Jobst +12
Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine…
SynA-ResNet: Spike-driven ResNet Achieved through OR Residual Connection
Yimeng Shan, Xuerui Qiu, Rui-jie Zhu +3
Spiking Neural Networks (SNNs) have garnered substantial attention in brain-like computing for their biological fidelity and the capacity to execute energy-efficient spike-driven o…
Memristive Reservoirs Learn to Learn
Ruomin Zhu, Jason K. Eshraghian, Zdenka Kuncic
Memristive reservoirs draw inspiration from a novel class of neuromorphic hardware known as nanowire networks. These systems display emergent brain-like dynamics, with optimal perf…
To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Acceleration
Fabrizio Ottati, Chang Gao, Qinyu Chen +4
As deep learning models scale, they become increasingly competitive from domains spanning from computer vision to natural language processing; however, this happens at the expense…
PowerGAN: A Machine Learning Approach for Power Side-Channel Attack on Compute-in-Memory Accelerators
Ziyu Wang, Yuting Wu, Yongmo Park +4
Analog compute-in-memory (CIM) systems are promising for deep neural network (DNN) inference acceleration due to their energy efficiency and high throughput. However, as the use of…
OpenSpike: An OpenRAM SNN Accelerator
Farhad Modaresi, Matthew Guthaus, Jason K. Eshraghian
This paper presents a spiking neural network (SNN) accelerator made using fully open-source EDA tools, process design kit (PDK), and memory macros synthesized using OpenRAM. The ch…
SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks
Rui-Jie Zhu, Qihang Zhao, Guoqi Li +1
As the size of large language models continue to scale, so does the computational resources required to run it. Spiking Neural Networks (SNNs) have emerged as an energy-efficient a…