Hierarchical and Lightweight Imitation Learning for Power Management of Embedded Socs

This technology involves an imitation learning based power management system for use in embedded systems-on-chips (SoCs).

Background:
As technology advances, systems-on-chips (SoCs) need to be able to operate more efficiently to keep up with multiple rapidly adapting technologies. Many SoCs struggle with dynamic power management and need to be able to adapt to runtime decisions for multiple objectives. However, current systems do not have these capabilities.

This technology improves upon current state-of-the-art solutions in terms of energy efficiency and runtime aware decisions.

Applications:

• Systems-on-Chips

Advantages:

• Improved energy efficiency
• Runtime aware decisions
• Better than current state-of-the-art systems