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Found 5 papers, 0 papers with code
DRESS: Dynamic REal-time Sparse Subnets
The limited and dynamically varied resources on edge devices motivate us to deploy an optimized deep neural network that can adapt its sub-networks to fit in different resource constraints.
Memory-Oriented Design-Space Exploration of Edge-AI Hardware for XR Applications
Low-Power Edge-AI capabilities are essential for on-device extended reality (XR) applications to support the vision of Metaverse.
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems
We design deep neural networks (DNNs) and corresponding networks' splittings to distribute DNNs' workload to camera sensors and a centralized aggregator on head mounted devices to meet system performance targets in inference accuracy and latency under the given hardware resource constraints.
Distributed On-Sensor Compute System for AR/VR Devices: A Semi-Analytical Simulation Framework for Power Estimation
Augmented Reality/Virtual Reality (AR/VR) glasses are widely foreseen as the next generation computing platform.
Power-of-Two Quantization for Low Bitwidth and Hardware Compliant Neural Networks
Eventually, the experiments showed that for low bit width precision, non-uniform quantization performs better than uniform, and at the same time, PoT quantization vastly reduces the computational complexity of the neural network.
