COOL-NPU: Complementary Online Learning Neural Processing Unit with CNN-SNN Heterogeneous Core and Event-driven Backpropagation

Abstract

This paper presents a low power NPU, COmplementary Online Learning Neural Processing Unit (COOL-NPU) with three key features: 1) low-power forward gradient generation logic with global counter and local gradient unit, 2) skip index generator and sparsity-aware CNN core for neuron-level backpropagation, 3) SNN core with distributed L1 cache to eliminate redundant SRAM access. By using complementary characteristic of CNN and SNN, we achieve 47.7% energy reduction than previous state-of-the-art online learning processor.