Neuromorphic hardware platforms can significantly lower the energy overh...
Non-Volatile Memory (NVM) cells are used in neuromorphic hardware to sto...
We present a design-technology tradeoff analysis in implementing
machine...
The design of many-core neuromorphic hardware is getting more and more
c...
Spiking Neural Networks (SNN) are an emerging computation model, which u...
Non-Volatile Memories (NVMs) such as Resistive RAM (RRAM) are used in
ne...
Neuromorphic computing systems uses non-volatile memory (NVM) to impleme...
Recently, both industry and academia have proposed many different
neurom...
Neuromorphic computing systems such as DYNAPs and Loihi have recently be...
Artificial intelligence (AI) and Machine Learning (ML) are becoming perv...
Neuromorphic computing systems are embracing memristors to implement hig...
Modern computing systems are embracing non-volatile memory (NVM) to impl...
Phase-change memory (PCM) is a scalable and low latency non-volatile mem...
With growing model complexity, mapping Spiking Neural Network (SNN)-base...
Neuromorphic computing with non-volatile memory (NVM) can significantly
...
As process technology continues to scale aggressively, circuit aging in ...
A prominent characteristic of write operation in Phase-Change Memory (PC...
Modern computing systems are embracing hybrid memory comprising of DRAM ...
Machine learning applications that are implemented with spike-based
comp...
Neuromorphic hardware with non-volatile memory (NVM) can implement machi...
Phase-change memory (PCM) devices have multiple banks to serve memory
re...