### Abstract

Original language | Undefined |
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Title of host publication | 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014 |

Place of Publication | USA |

Publisher | IEEE Computer Society |

Pages | 512-519 |

Number of pages | 8 |

ISBN (Print) | 978-1-4799-2728-9 |

DOIs | |

State | Published - 2014 |

Event | 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014 - Turin, Italy |

### Publication series

Name | |
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Publisher | IEEE Computer Society |

ISSN (Print) | 1066-6192 |

### Conference

Conference | 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014 |
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Abbreviated title | PDP |

Country | Italy |

City | Turin |

Period | 12/02/14 → 14/02/14 |

### Fingerprint

### Keywords

- EWI-24562
- CAES-EEA: Efficient Embedded Architectures
- EC Grant Agreement nr.: FP7/2007-2013
- EC Grant Agreement nr.: FP7/318490
- METIS-304019
- Dynamic voltage and frequency scaling
- Parallel processing
- IR-90567
- Mathematical Programming
- Energy minimization

### Cite this

*22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014*(pp. 512-519). USA: IEEE Computer Society. DOI: 10.1109/PDP.2014.103

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*22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014.*IEEE Computer Society, USA, pp. 512-519, 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014, Turin, Italy, 12-14 February. DOI: 10.1109/PDP.2014.103

**Analytic clock frequency selection for global DVFS.** / Gerards, Marco Egbertus Theodorus; Hurink, Johann L.; Holzenspies, P.K.F.; Kuper, Jan; Smit, Gerardus Johannes Maria.

Research output: Scientific - peer-review › Conference contribution

TY - CHAP

T1 - Analytic clock frequency selection for global DVFS

AU - Gerards,Marco Egbertus Theodorus

AU - Hurink,Johann L.

AU - Holzenspies,P.K.F.

AU - Kuper,Jan

AU - Smit,Gerardus Johannes Maria

N1 - eemcs-eprint-24562

PY - 2014

Y1 - 2014

N2 - Computers can reduce their power consumption by decreasing their speed using Dynamic Voltage and Frequency Scaling (DVFS). A form of DVFS for multicore processors is global DVFS, where the voltage and clock frequency is shared among all processor cores. Because global DVFS is efficient and cheap to implement, it is used in modern multicore processors like the IBM Power 7, ARM Cortex A9 and NVIDIA Tegra 2. This theory oriented paper discusses energy optimal DVFS algorithms for such processors. There are no known provably optimal algorithms that minimize the energy consumption of nontrivial real-time applications on a global DVFS system. Such algorithms only exist for single core systems, or for simpler application models. While many DVFS algorithms focus on tasks, this theoretical study is conceptually different and focuses on the amount of parallelism. We provide a transformation from a multicore problem to a single core problem, by using the amount of parallelism of an application. Then existing single core algorithms can be used to find the optimal solution. Furthermore, we extend an existing single core algorithm such that it takes static power into account.

AB - Computers can reduce their power consumption by decreasing their speed using Dynamic Voltage and Frequency Scaling (DVFS). A form of DVFS for multicore processors is global DVFS, where the voltage and clock frequency is shared among all processor cores. Because global DVFS is efficient and cheap to implement, it is used in modern multicore processors like the IBM Power 7, ARM Cortex A9 and NVIDIA Tegra 2. This theory oriented paper discusses energy optimal DVFS algorithms for such processors. There are no known provably optimal algorithms that minimize the energy consumption of nontrivial real-time applications on a global DVFS system. Such algorithms only exist for single core systems, or for simpler application models. While many DVFS algorithms focus on tasks, this theoretical study is conceptually different and focuses on the amount of parallelism. We provide a transformation from a multicore problem to a single core problem, by using the amount of parallelism of an application. Then existing single core algorithms can be used to find the optimal solution. Furthermore, we extend an existing single core algorithm such that it takes static power into account.

KW - EWI-24562

KW - CAES-EEA: Efficient Embedded Architectures

KW - EC Grant Agreement nr.: FP7/2007-2013

KW - EC Grant Agreement nr.: FP7/318490

KW - METIS-304019

KW - Dynamic voltage and frequency scaling

KW - Parallel processing

KW - IR-90567

KW - Mathematical Programming

KW - Energy minimization

U2 - 10.1109/PDP.2014.103

DO - 10.1109/PDP.2014.103

M3 - Conference contribution

SN - 978-1-4799-2728-9

SP - 512

EP - 519

BT - 22nd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, PDP 2014

PB - IEEE Computer Society

ER -