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Shared resource aware scheduling on power-constrained tiled many-core processors

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Abstract
Power management through dynamic core, cache and frequency adaptation is becoming a necessity in today's power-constrained many-core environments. Unfortunately, as core count grows, the complexity of both the adaptation hardware and the power management algorithms increases exponentially. This calls for hierarchical solutions, such as on-chip voltage regulators per-tile rather than per-core, along with multi-level power management. As power-driven adaptation of shared resources affects multiple threads at once, the efficiency in a tile-organized many-core processor architecture hinges on the ability to co-schedule compatible threads to tiles in tandem with hardware adaptations per tile and per core. In this paper, we propose a two-tier hierarchical power management methodology to exploit per tile voltage regulators and clustered last-level caches. In addition, we include a novel thread migration layer that (i) analyzes threads running on the tiled many-core processor for shared resource sensitivity in tandem with core, cache and frequency adaptation, and (ii) co-schedules threads per tile with compatible behavior. On a 256-core setup with 4 cores per tile, we show that adding sensitivity-based thread migration to a two-tier power manager improves system performance by 10% on average (and up to 20%) while using 4x less on-chip voltage regulators. It also achieves a performance advantage of 4.2% on average (and up to 12%) over existing solutions that do not take DVFS sensitivity into account. (C) 2016 Elsevier Inc. All rights reserved.
Keywords
CHIP MULTIPROCESSORS, PERFORMANCE, MANAGEMENT, SYSTEMS, CACHE, Many-core tiled architecture, Thread migration, Power budget, Adaptive, microarchitecture

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MLA
Jha, Sudhanshu Shekhar, et al. “Shared Resource Aware Scheduling on Power-Constrained Tiled Many-Core Processors.” JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, vol. 100, 2017, pp. 30–41, doi:10.1016/j.jpdc.2016.10.001.
APA
Jha, S. S., Heirman, W., Falcon, A., Tubella, J., Gonzalez, A., & Eeckhout, L. (2017). Shared resource aware scheduling on power-constrained tiled many-core processors. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 100, 30–41. https://doi.org/10.1016/j.jpdc.2016.10.001
Chicago author-date
Jha, Sudhanshu Shekhar, Wim Heirman, Ayose Falcon, Jordi Tubella, Antonio Gonzalez, and Lieven Eeckhout. 2017. “Shared Resource Aware Scheduling on Power-Constrained Tiled Many-Core Processors.” JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 100: 30–41. https://doi.org/10.1016/j.jpdc.2016.10.001.
Chicago author-date (all authors)
Jha, Sudhanshu Shekhar, Wim Heirman, Ayose Falcon, Jordi Tubella, Antonio Gonzalez, and Lieven Eeckhout. 2017. “Shared Resource Aware Scheduling on Power-Constrained Tiled Many-Core Processors.” JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 100: 30–41. doi:10.1016/j.jpdc.2016.10.001.
Vancouver
1.
Jha SS, Heirman W, Falcon A, Tubella J, Gonzalez A, Eeckhout L. Shared resource aware scheduling on power-constrained tiled many-core processors. JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING. 2017;100:30–41.
IEEE
[1]
S. S. Jha, W. Heirman, A. Falcon, J. Tubella, A. Gonzalez, and L. Eeckhout, “Shared resource aware scheduling on power-constrained tiled many-core processors,” JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, vol. 100, pp. 30–41, 2017.
@article{8542496,
  abstract     = {{Power management through dynamic core, cache and frequency adaptation is becoming a necessity in today's power-constrained many-core environments. Unfortunately, as core count grows, the complexity of both the adaptation hardware and the power management algorithms increases exponentially. This calls for hierarchical solutions, such as on-chip voltage regulators per-tile rather than per-core, along with multi-level power management. As power-driven adaptation of shared resources affects multiple threads at once, the efficiency in a tile-organized many-core processor architecture hinges on the ability to co-schedule compatible threads to tiles in tandem with hardware adaptations per tile and per core. In this paper, we propose a two-tier hierarchical power management methodology to exploit per tile voltage regulators and clustered last-level caches. In addition, we include a novel thread migration layer that (i) analyzes threads running on the tiled many-core processor for shared resource sensitivity in tandem with core, cache and frequency adaptation, and (ii) co-schedules threads per tile with compatible behavior. On a 256-core setup with 4 cores per tile, we show that adding sensitivity-based thread migration to a two-tier power manager improves system performance by 10% on average (and up to 20%) while using 4x less on-chip voltage regulators. It also achieves a performance advantage of 4.2% on average (and up to 12%) over existing solutions that do not take DVFS sensitivity into account. (C) 2016 Elsevier Inc. All rights reserved.}},
  author       = {{Jha, Sudhanshu Shekhar and Heirman, Wim and Falcon, Ayose and Tubella, Jordi and Gonzalez, Antonio and Eeckhout, Lieven}},
  issn         = {{0743-7315}},
  journal      = {{JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING}},
  keywords     = {{CHIP MULTIPROCESSORS,PERFORMANCE,MANAGEMENT,SYSTEMS,CACHE,Many-core tiled architecture,Thread migration,Power budget,Adaptive,microarchitecture}},
  language     = {{eng}},
  pages        = {{30--41}},
  title        = {{Shared resource aware scheduling on power-constrained tiled many-core processors}},
  url          = {{http://doi.org/10.1016/j.jpdc.2016.10.001}},
  volume       = {{100}},
  year         = {{2017}},
}

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