Energy Conscious Dynamic Window Scheduling of Chip Multiprocessors

TL;DR

This paper introduces a novel energy-aware scheduling method for chip multiprocessors that balances load and temperature using dynamic time windows and a modified Gale-Shapely algorithm, improving thermal management.

Contribution

It presents the non-preemptive dynamic window (NPDW) scheduling approach, a new method for thermal and load balancing in multicore systems using dynamic windows and stable matching.

Findings

NPDW effectively balances thermal and computational load.

The scheduler outperforms baseline schedulers in load distribution.

Dynamic window heuristic adapts to current system conditions.

Abstract

The need to develop systems that exploit multi and many-core architectures to reduce wasteful heat generation is of utmost importance in compute-intensive applications. We propose an energy-conscious approach to multicore scheduling known as non-preemptive dynamic window (NPDW) scheduling that achieves effective load and temperature balancing over chip multiprocessors. NPDW utilizes the concept of dynamic time windows to accumulate tasks and find an optimal stable matching between accumulated tasks and available processor cores using a modified Gale-Shapely algorithm. The metrics of window and matching performance are defined to create a dynamic window heuristic to determine the next time window size based on the current and previous window sizes. Based on derived formulation and experimental results, we show that our NPDW scheduler is able to distribute the computational and thermal load throughout the processors in a multicore environment better than baseline schedulers. We believe that within multicore compute applications requiring temperature and energy-conscious system design, our scheduler may be employed to effectively disperse system load and prevent excess core heating.