Open-source SNN accelerator integrated into FPGA-based neuromorphic SoC

Researchers have developed a heterogeneous System-on-Chip (SoC) that integrates an open-source Recurrent Spiking Neural Network (SNN) accelerator called ReckOn. This design aims to bring efficient, low-power neuromorphic computing to edge devices by implementing SNNs on Field-Programmable Gate Arrays (FPGAs), offering a cost-effective alternative to silicon tape-outs. The SoC manages ReckOn's operations alongside traditional processors like the RISC-V-based X-HEEP microcontroller and ARM processors, validating accuracy and evaluating online learning capabilities. AI

IMPACT Enables more efficient and cost-effective deployment of neuromorphic computing on edge devices.

RANK_REASON Academic paper detailing a novel hardware architecture for neuromorphic computing. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• FPGA
• ReckOn
• RISC-V
• Spiking Neural Networks
• SoC
• X-HEEP

• paper
• infra
• other

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