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Variability-aware Management in Multicore Processors
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Proactive Thermal Management

Conventional thermal management techniques are reactive in nature; that is, they take action after temperatures reach a predetermined threshold value. Such approaches do not always minimize and balance the temperature on the chip, and furthermore, they control temperature at a noticeable performance cost.

We investigate how to use an autoregressive moving average (ARMA) predictor for forecasting future temperatures, and we propose a proactive thread allocation technique for multiprocessor systems. When implemented in the Solaris kernel on an UltraSPARC T1 chip, our proactive technique achieved 60% reduction in hot spot occurrences, 80% reduction in spatial gradients and 75% reduction in thermal cycles on average in comparison to reactive management.

We also introduce a new thermal predictor that utilizes the band-limited property of the temperature frequency spectrum. The big advantage of this predictor is that it does not require training phase. We leverage this novel predictor and workload characterization to develop a new proactive thermal management technique. The experimental results show that applying this approach reduces the processor average temperature, hottest core temperature, product MTTF and performance by 6 C, 8 C, 41% and 72% respectively.


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.

More Information:

  • Raid Ayoub, Tajana Simunic Rosing. Predict and act:dynamic thermal management for multi-core processors. In Proceedings of International Symposium on Low Power Electronics and Design (ISLPED), 2009. [Acceptance Rate (Regular Papers) = 24.7%]. pdf
  • Ayse K. Coskun, Tajana Simunic Rosing and Kenny Gross. Proactive Temperature Balancing for Low Cost Thermal Management in MPSoCs. In Proceedings of International Conference on Computer-Aided Design (ICCAD), pp. 250-257, 2008. pdf
  • Ayse K. Coskun, Tajana Simunic Rosing and Kenny Gross. Proactive Temperature Management in MPSoCs. In Proceedings of International Symposium on Low Power Electronics and Design (ISLPED), pp. 165-170, 2008. pdf
  • 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. pdf
  • 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. pdf
  • 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. pdf
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