Overview
What this challenge is about.
Read the existing scheduler's energy model (provided). Design an improved policy using one or more of: per-task IPC-aware placement, exponential moving average load smoothing to prevent ping-pong migration, or a contention-aware avoidance term. Prototype the policy as a Linux kernel patch on the SoC's reference Android board. Run a 5-workload day-in-the-life suite (web browse, video stream, gaming benchmark, camera shutter, idle) on instrumented hardware. Measure joules consumed per workload and frames-per-second regression. Deliver the patch, energy measurements, and an 8-page policy-design document.
The Brief
What you'll do, and what you'll demonstrate.
Design and prototype an improved Big.LITTLE scheduling policy that reduces energy on representative mobile workloads without sacrificing user-perceptible performance.
Earning criteria — what you'll demonstrate
- Reason about heterogeneous scheduling across performance and efficiency cores
- Design energy-aware scheduling policies grounded in IPC and load behavior
- Prototype kernel changes and validate on real instrumented hardware
- Trade energy against user-perceptible performance honestly
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career mappings coming soon.