SPARX: Secure and Privacy-Aware Approximate CNN Acceleration with Edge RISC-V SoC
Researchers have developed SPARX, a framework for accelerating Convolutional Neural Networks (CNNs) on edge devices. This system integrates approximate computing with security and privacy features within a RISC-V System-on-Chip. SPARX utilizes a custom RISC-V instruction extension and an approximate logarithmic CNN accelerator, enhanced by a differential-noise privacy engine and authentication mechanisms. Evaluations show significant reductions in area and power, alongside improved throughput, with a minimal impact on accuracy for specific CNN models. AI
IMPACT Enables more efficient and secure AI inference on resource-constrained edge devices.