Static and Dynamic Temperature-Aware Job Scheduling
This work explores the benefits of temperature-aware task scheduling for multiprocessor system-on-a-chip (MPSoC).
We first solve the task scheduling problem statically using integer linear programming (ILP). This solution can be
utilized for embedded systems with an a priori known workload, and also for setting a baseline comparison to dynamic
methods. The ILP solution is guaranteed to be optimal for the given assumptions of tasks. ILPs for minimizing energy,
balancing energy, and reducing hot spots are formulated and compared against the thermally-aware optimization method.
Our static solution can reduce the frequency of hot spots by 35%, spatial gradients by 85%, and thermal cycles by 61% in
comparison to the ILP for minimizing energy.
For dynamic thermal management, we introduce scheduling policies at the OS-level with negligible performance overhead.
We design a novel adaptive policy, which adjusts the probability value of receiving workloads for each core. Our policy
reduces the frequency of
high-magnitude thermal cycles and spatial gradients by around 50% and 90%, respectively, in comparison to state-of-the-art
schedulers. Reactive thermal management strategies, such as thread migration, can be combined with this scheduling
policy to further reduce hot spots, temperature variations, and the associated performance cost.
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Ayse K. Coskun, Tajana Simunic Rosing, Keith Whisnant and Kenny Gross. Static and Dynamic
Temperature-Aware Scheduling for Multiprocessor SoCs. In IEEE Transactions on VLSI, vol.16 no.9, pp. 1127-1140,Sept. 2008.
Ayse K. Coskun, Tajana Simunic Rosing, Keith Whisnant and Kenny Gross. Temperature-Aware MPSoC Scheduling
for Reducing Hot Spots and Gradients. In Proceedings of Asia and
South Pacific Design Automation Conference (ASPDAC), pp. 49-54, 2008.
Ayse K. Coskun, Tajana Simunic Rosing and Keith Whisnant.
Temperature Aware Task Scheduling in MPSoCs. In Proceedings of
Design Automation and Test in Europe (DATE), pp. 1659-1664, 2007.