Low Power

Low-power computing focuses on designing and optimizing hardware and software systems to minimize energy consumption while maintaining acceptable performance. Current research emphasizes efficient neural network architectures, such as spiking neural networks (SNNs) and lightweight convolutional neural networks (CNNs), along with techniques like pruning, quantization, and knowledge distillation to reduce model size and computational complexity. This field is crucial for enabling the deployment of advanced AI applications on resource-constrained edge devices, impacting areas like wearable health monitoring, industrial IoT, and always-on smart devices.