One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency

Understand

Spiking Neural Networks (SNNs) are energy efficient alternatives to commonly used deep neural networks (DNNs).

• Through event-driven information processing, SNNs can reduce the expensive compute requirements of DNNs considerably, while achieving comparable performance.
• However, high inference latency is a significant hindrance to the edge deployment of deep SNNs.
• Computation over multiple timesteps not only increases latency as well as overall energy budget due to higher number of operations, but also incurs memory access overhead of fetching membrane potentials, both of which lessen the energy benefits of SNNs.