Journal ArticleDOI
Power reduction techniques for microprocessor systems
TLDR
It is concluded that power management is a multifaceted discipline that is continually expanding with new techniques being developed at every level and it remains too early to tell which techniques will ultimately solve the power problem.Abstract:
Power consumption is a major factor that limits the performance of computers. We survey the “state of the art” in techniques that reduce the total power consumed by a microprocessor system over time. These techniques are applied at various levels ranging from circuits to architectures, architectures to system software, and system software to applications. They also include holistic approaches that will become more important over the next decade. We conclude that power management is a multifaceted discipline that is continually expanding with new techniques being developed at every level. These techniques may eventually allow computers to break through the “power wall” and achieve unprecedented levels of performance, versatility, and reliability. Yet it remains too early to tell which techniques will ultimately solve the power problem.read more
Citations
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Book ChapterDOI
A Taxonomy and Survey of Energy-Efficient Data Centers and Cloud Computing Systems
Anton Beloglazov,Anton Beloglazov,Rajkumar Buyya,Rajkumar Buyya,Young Choon Lee,Young Choon Lee,Albert Y. Zomaya,Albert Y. Zomaya +7 more
TL;DR: This study discusses causes and problems of high power/energy consumption, and presents a taxonomy of energy-efficient design of computing systems covering the hardware, operating system, virtualization, and data center levels.
Journal ArticleDOI
Data Center Energy Consumption Modeling: A Survey
TL;DR: An in-depth study of the existing literature on data center power modeling, covering more than 200 models, organized in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models.
Journal ArticleDOI
Energy efficient utilization of resources in cloud computing systems
Young Choon Lee,Albert Y. Zomaya +1 more
TL;DR: Two energy-conscious task consolidation heuristics are presented, which aim to maximize resource utilization and explicitly take into account both active and idle energy consumption and demonstrate their promising energy-saving capability.
Journal ArticleDOI
A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems
Mohand Mezmaz,Nouredine Melab,Y. Kessaci,Young Choon Lee,El-Ghazali Talbi,Albert Y. Zomaya,Daniel Tuyttens +6 more
TL;DR: This work proposes a new parallel bi-objective hybrid genetic algorithm that takes into account, not only makespan, but also energy consumption, and focuses on the island parallel model and the multi-start parallel model.
References
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Proceedings ArticleDOI
Route packets, not wires: on-chip interconnection networks
William J. Dally,Brian Towles +1 more
TL;DR: This paper introduces the concept of on-chip networks, sketches a simple network, and discusses some challenges in the architecture and design of these networks.
Proceedings ArticleDOI
Scheduling for reduced CPU energy
TL;DR: A new metric for cpu energy performance, millions-of-instructions-per-joule (MIPJ), and several methods for varying the clock speed dynamically under control of the operating system, and examine the performance of these methods against workstation traces.
Proceedings ArticleDOI
Razor: a low-power pipeline based on circuit-level timing speculation
Daniel J. Ernst,Nam Sung Kim,Shidhartha Das,Sanjay Pant,Rajeev R. Rao,Toan Pham,Conrad H. Ziesler,David Blaauw,Todd Austin,Krisztian Flautner,Trevor Mudge +10 more
TL;DR: A solution by which the circuit can be operated even below the ‘critical’ voltage, so that no margins are required and thus more energy can be saved.
Journal ArticleDOI
Bus-invert coding for low-power I/O
Mircea R. Stan,Wayne Burleson +1 more
TL;DR: In this article, the bus-invert method of coding the I/O was proposed to decrease the bus activity and thus decrease the peak power dissipation by 50% and the average power disipation by up to 25%.