A design flow for scheduling spiking deep convolutional neural networks on heterogeneous neuromorphic system-on-chip
A Das - ACM Transactions on Embedded Computing Systems, 2023 - dl.acm.org
Neuromorphic systems-on-chip (NSoCs) integrate CPU cores and neuromorphic hardware
accelerators on the same chip. These platforms can execute spiking deep convolutional …
accelerators on the same chip. These platforms can execute spiking deep convolutional …
Hardware-software co-design for on-chip learning in AI systems
Spike-based convolutional neural networks (CNNs) are empowered with on-chip learning in
their convolution layers, enabling the layer to learn to detect features by combining those …
their convolution layers, enabling the layer to learn to detect features by combining those …
Latest Innovations in Intelligent Network-on-Chip Architectures: A Systematic Review
E Kakoulli - 2024 17th IEEE/ACM International Workshop on …, 2024 - ieeexplore.ieee.org
This review investigates the latest advancements in intelligent Network-on-Chip (NoC)
architectures, focusing on innovations from 2022 to 2024. The integration of Artificial …
architectures, focusing on innovations from 2022 to 2024. The integration of Artificial …
Preserving Privacy of Neuromorphic Hardware From PCIe Congestion Side-Channel Attack
A Das - 2023 IEEE 47th Annual Computers, Software, and …, 2023 - ieeexplore.ieee.org
Neuromorphic systems are equipped with software-managed scratchpad to cache
intermediate results and synaptic weights of a machine learning model. PCIe (Peripheral …
intermediate results and synaptic weights of a machine learning model. PCIe (Peripheral …
A scalable dynamic segmented bus interconnect for neuromorphic architectures
Large-scale neuromorphic architectures consist of computing tiles that communicate spikes
using a shared interconnect. We propose ADIONA, a dynamic segmented bus interconnect …
using a shared interconnect. We propose ADIONA, a dynamic segmented bus interconnect …
An integrated toolbox for creating neuromorphic edge applications
Abstract Spiking Neural Networks (SNNs) and neuromorphic models are believed to be
more efficient in general and have more biological realism than the activation functions …
more efficient in general and have more biological realism than the activation functions …
HeterGenMap: An Evolutionary Map** Framework for Heterogeneous NoC-based Neuromorphic Systems
While task map** for multi-core systems is known as an NP-hard problem, map** for
neuromorphic systems even scale it up due to a high number of neurons per core and a high …
neuromorphic systems even scale it up due to a high number of neurons per core and a high …
LSM-Based Hotspot Prediction and Hotspot-Aware Routing in NoC-Based Neuromorphic Processor
The traffic patterns of spiking neural networks (SNNs) exhibit high variability and stochastic,
leading to the emergence of elevated traffic hotspots on the network-on-chip (NoC)-based …
leading to the emergence of elevated traffic hotspots on the network-on-chip (NoC)-based …
In-Memory Computing: The Emerging Computing Topic in the Post-von Neumann Era
In-Memory Computing: The Emerging Computing Topic in the Post-von Neumann Era Page
1 SPOTLIGHT ON TRANSACTIONS 4 COMPUTER PUBLISHED BY THE IEEE COMPUTER …
1 SPOTLIGHT ON TRANSACTIONS 4 COMPUTER PUBLISHED BY THE IEEE COMPUTER …
SONA: A Bio-Inspired, Self-Organizing Connective Fabric for Neuromorphic Circuits and FPGAs
D Battel, AC Parker - 2023 International Joint Conference on …, 2023 - ieeexplore.ieee.org
Mature biological neurons continually grow new connections in real-time, as learning
occurs. To support similar life-long learning in silicon, it is important to build neuromorphic …
occurs. To support similar life-long learning in silicon, it is important to build neuromorphic …