2 papers
cs.AR2026
An FPGA-Based SoC Architecture with a RISC-V Controller for Energy-Efficient Temporal-Coding Spiking Neural Networks
Mohammad Javad Sekonji, Ali Mahani, Maryam Mirsadeghi +1
Spiking Neural Networks (SNNs) offer high energy efficiency and event-driven computation, ideal for low-power edge AI. Their hardware implementation on FPGAs, however, faces challe…
cs.LG2026
SPARQ: Spiking Early-Exit Neural Networks for Energy-Efficient Edge AI
Parth Patne, Mahdi Taheri, Ali Mahani +3
Spiking neural networks (SNNs) offer inherent energy efficiency due to their event-driven computation model, making them promising for edge AI deployment. However, their practical…