89 citations · 214 across the 26 of their papers we have counts for
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cs.ET2019
A Framework to Explore Workload-Specific Performance and Lifetime Trade-offs in Neuromorphic Computing
Adarsha Balaji, Shihao Song, Anup Das +4
Neuromorphic hardware with non-volatile memory (NVM) can implement machine learning workload in an energy-efficient manner. Unfortunately, certain NVMs such as phase change memory…
cs.ET2019★ 3 cited
Mapping Spiking Neural Networks to Neuromorphic Hardware
Adarsha Balaji, Anup Das, Yuefeng Wu +7
Neuromorphic hardware platforms implement biological neurons and synapses to execute spiking neural networks (SNNs) in an energy-efficient manner. We present SpiNeMap, a design met…