This technology involves task scheduling to optimize the processing elements at runtime using imitation learning.
Background:
Harvesting the full potential of many-core systems-on-chips is difficult. The goals are to minimize execution time, power dissipation, and energy consumption. This technology intends to solve this problem by assigning tasks to specific processing elements using imitation learning instead of reinforcement learning.
Applications:
- Optimized processing elements
- System-on-Chips
Advantages:
- Minimized execution time
- Less power dissipation
- Lower energy consumption
- The optimized potential of system-on-chips
Website
Contact Information
TTO Home Page: https://arizona.technologypublisher.com
Name: Brett Mortenson
Title: Licensing Manager, College of Engineering
Email: BrettM@tla.arizona.edu