Saturday, 23 September 2017

Power Publications

Publications by the RG Power Working Group and previous publications with the OSG Power Subcommittee.

Jóakim von Kistowski, Maximilian Deffner, Jeremy A. Arnold, Klaus-Dieter Lange, John Beckett, and Samuel Kounev. Autopilot: Enabling easy Benchmarking of Workload Energy Efficiency (Demonstration Paper). In Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017), L'Aquila, Italy, April 2017. ACM, New York, NY, USA. April 2017, Best Demo Award.
[ bibtex | abstract | pdf ]
Keywords: Benchmarking, Power, Variation, SPEC, Workloads, Energy Efficiency, Load level, Deployment, Development.

Benchmarking of energy efficiency is important as it helps researchers, customers, and developers to evaluate and compare the energy efficiency of software and hardware solutions. Developing and deploying energy-efficiency benchmarking workloads are challenging tasks, as work must be able to be executed in a power measurement environment using an energy-efficiency measurement methodology. The existing SPEC Chauffeur Worklet Development Kit (WDK) enables the development and use of custom workloads (called worklets) within a standardized power measurement methodology. However, it features no integration in development environments, making building and deployment of workloads challenging. We address this challenge by proposing Autopilot, a plugin for the Eclipse IDE. Autopilot enables fast and easy building and deployment of a workload under development on a system for testing. It also enables benchmark execution directly from the development environment.
@inproceedings{KiDeArLaBeKo2017-ICPE-Autopilot,
  author = {J{\'o}akim von Kistowski and Maximilian Deffner and Jeremy A. Arnold and Klaus-Dieter Lange and John Beckett and Samuel Kounev},
  title = {{Autopilot: Enabling easy Benchmarking of Workload Energy Efficiency}},
  titleaddon = {{(Demonstration Paper)}},
  year = {2017},
  booktitle = {Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017)},
  location = {L'Aquila, Italy},
  month = {April},
  publisher = {ACM},
  address = {New York, NY, USA},
  keywords = {Benchmarking, Power, Variation, SPEC, Workloads, Energy Efficiency, Load level, Deployment, Development},
  note = {Best Demo Award},
  pdf = {https://se2.informatik.uni-wuerzburg.de/pa/publications/download/paper/1171.pdf}
}
						
Jóakim von Kistowski, Hansfried Block, John Beckett, Cloyce Spradling, Klaus-Dieter Lange, and Samuel Kounev. Variations in CPU Power Consumption. In Proceedings of the 7th ACM/SPEC International Conference on Performance Engineering (ICPE 2016), Delft, the Netherlands, March 2016. ACM, New York, NY, USA. March 2016.
[ bibtex | abstract | pdf ]
Keywords: Benchmarking, CPU, Power, Variation, SPEC, SERT, Workloads, Energy Efficiency, Metrics, Load level, Utilization.

Experimental analysis of computer systems' power consumption has become an integral part of system performance evaluation, efficiency management, and model-based analysis. As with all measurements, repeatability and reproducibility of power measurements is a major challenge. Nominally identical systems can have different power consumption running the same workload under otherwise identical conditions. This behavior can also be observed for individual system components. Specifically, CPU power consumption can vary amongst different samples of nominally identical CPUs. This in turn has a significant impact on the overall system power, considering that a system's processor is the largest and most dynamic power consumer of the overall system. The concrete impact of CPU sample power variations is unknown, as comprehensive studies about differences in power consumption for nominally identical systems are currently missing. We address this lack of studies by conducting measurements on four different processor types from two different architectures. For each of these types, we compare up to 30 physical processor samples with a total sum of 90 samples over all processor types. We analyze the variations in power consumption for the different samples using six different workloads over five load levels. Additionally, we analyze how these variations change for different processor core counts and architectures. The results of this paper show that selection of a processor sample can have a statistically significant impact on power consumption. With no correlation to performance, power consumption for nominally identical processors can differ as much as 29.6% in idle and 19.5% at full load. We also show that these variations change over different architectures and processor types.
@inproceedings{KiBlBeSpLaKo2016-ICPE-PowerVariation,
author = {J\'{o}akim von Kistowski and Hansfried Block and John Beckett and Cloyce Spradling and Klaus-Dieter Lange and Samuel Kounev},
abstract = {{Experimental analysis of computer systems' power consumption has become an integral part of system performance evaluation, efficiency management, and model-based analysis. As with all measurements, repeatability and reproducibility of power measurements is a major challenge. Nominally identical systems can have different power consumption running the same workload under otherwise identical conditions. This behavior can also be observed for individual system components. Specifically, CPU power consumption can vary amongst different samples of nominally identical CPUs. This in turn has a significant impact on the overall system power, considering that a system's processor is the largest and most dynamic power consumer of the overall system. The concrete impact of CPU sample power variations is unknown, as comprehensive studies about differences in power consumption for nominally identical systems are currently missing. We address this lack of studies by conducting measurements on four different processor types from two different architectures. For each of these types, we compare up to 30 physical processor samples with a total sum of 90 samples over all processor types. We analyze the variations in power consumption for the different samples using six different workloads over five load levels. Additionally, we analyze how these variations change for different processor core counts and architectures. The results of this paper show that selection of a processor sample can have a statistically significant impact on power consumption. With no correlation to performance, power consumption for nominally identical processors can differ as much as 29.6\% in idle and 19.5\% at full load. We also show that these variations change over different architectures and processor types.}},
title = {{Variations in CPU Power Consumption}},
year = {2016},
booktitle = {Proceedings of the 7th ACM/SPEC International Conference on Performance Engineering (ICPE 2016)},
location = {Delft, the Netherlands},
month = {March},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {Benchmarking, CPU, Power, Variation, SPEC, SERT, Workloads, Energy Efficiency, Metrics, Load level, Utilization},
doi = {http://dx.doi.org/10.1145/2851553.2851567},
slides = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/slides/911},
pdf = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/paper/911.pdf}
}
						
Jóakim von Kistowski, John Beckett, Klaus-Dieter Lange, Hansfried Block, Jeremy A. Arnold, and Samuel Kounev. Energy Efficiency of Hierarchical Server Load Distribution Strategies. In Proceedings of the IEEE 23nd International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2015), Atlanta, GA, USA, October 5-7, 2015. IEEE. October 2015.
[ bibtex | abstract | pdf ]
Keywords: SPEC, SERT, Power, Benchmarking, Workload, Energy Efficiency, Metrics, Utilization, Load level.

Energy efficiency of servers has become a significant issue over the last years. Load distribution plays a crucial role in the improvement of energy efficiency as (un-)balancing strategies can be leveraged to distribute load over one or multiple systems in a way in which resources are utilized at high performance, yet low overall power consumption. This can be achieved on multiple levels, from load distribution on single CPU cores to machine level load balancing on distributed systems. With modern day server architectures providing load balancing opportunities at several layers, answering the question of optimal load distribution has become non-trivial. Work has to be distributed hierarchically in a fashion that enables maximum energy efficiency at each level. Current approaches balance load based on generalized assumptions about the energy efficiency of servers. These assumptions are based either on very machine-specific or highly generalized observations that may or may not hold true over a variety of systems and configurations. In this paper, we use a modified version of the SPEC SERT suite to measure the energy efficiency of a variety of hierarchical load distribution strategies on single and multi-node systems. We introduce a new strategy and evaluate energy efficiency for homogeneous and heterogeneous workloads over different hardware configurations. Our results show that the selection of a load distribution strategy depends heavily on workload, system utilization, as well as hardware. Used in conjunction with existing strategies, our new load distribution strategy can reduce a single system's power consumption by up to 10.7%.
@inproceedings{KiBeLaBlArKo2015-MASCOTS,
author = {J\'{o}akim von Kistowski and John Beckett and Klaus-Dieter Lange and Hansfried Block and Jeremy A. Arnold and Samuel Kounev},
abstract = {{Energy efficiency of servers has become a significant issue over the last years. Load distribution plays a crucial role in the improvement of energy efficiency as (un-)balancing strategies can be leveraged to distribute load over one or multiple systems in a way in which resources are utilized at high performance, yet low overall power consumption. This can be achieved on multiple levels, from load distribution on single CPU cores to machine level load balancing on distributed systems. With modern day server architectures providing load balancing opportunities at several layers, answering the question of optimal load distribution has become non-trivial. Work has to be distributed hierarchically in a fashion that enables maximum energy efficiency at each level. Current approaches balance load based on generalized assumptions about the energy efficiency of servers. These assumptions are based either on very machine-specific or highly generalized observations that may or may not hold true over a variety of systems and configurations. In this paper, we use a modified version of the SPEC SERT suite to measure the energy efficiency of a variety of hierarchical load distribution strategies on single and multi-node systems. We introduce a new strategy and evaluate energy efficiency for homogeneous and heterogeneous workloads over different hardware configurations. Our results show that the selection of a load distribution strategy depends heavily on workload, system utilization, as well as hardware. Used in conjunction with existing strategies, our new load distribution strategy can reduce a single system's power consumption by up to 10.7%.}},
title = {{Energy Efficiency of Hierarchical Server Load Distribution Strategies}},
year = {2015},
booktitle = {Proceedings of the IEEE 23nd International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS 2015)},
location = {Atlanta, GA, USA},
month = {October},
day = {5--7},
publisher = {IEEE},
keywords = {SPEC, SERT, Power, Benchmarking, Workload, Energy Efficiency, Metrics, Utilization, Load level},
note = {Full paper acceptance rate: 19\%},
pdf = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/paper/878.pdf},
slides = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/slides/878},
doi = {http://dx.doi.org/10.1109/MASCOTS.2015.11}
}
						
Jóakim von Kistowski, Jeremy A. Arnold, Karl Huppler, Klaus-Dieter Lange, John L. Henning, and Paul Cao. How to Build a Benchmark. In Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015), Austin, TX, USA, February 2015, ICPE '15. ACM, New York, NY, USA. February 2015.
[ bibtex | abstract | pdf ]
Keywords: SPEC, TPC, SPECpower_ssj2008, SERT, SPEC CPU.

Standardized benchmarks have become widely accepted tools for the comparison of products and evaluation of methodologies. These benchmarks are created by consortia like SPEC and TPC under confidentiality agreements which provide little opportunity for outside observers to get a look at the processes and concerns that are prevalent in benchmark development. This paper introduces the primary concerns of benchmark development from the perspectives of SPEC and TPC committees. We provide a benchmark definition, outline the types of benchmarks, and explain the characteristics of a good benchmark. We focus on the characteristics important for a standardized benchmark, as created by the SPEC and TPC consortia. To this end, we specify the primary criteria to be employed for benchmark design and workload selection. We use multiple standardized benchmarks as examples to demonstrate how these criteria are ensured.
@inproceedings{KiArHuLaHeCa2015-ICPE-Benchmark,
author = {J\'{o}akim von Kistowski and Jeremy A. Arnold and Karl Huppler and Klaus-Dieter Lange and John L. Henning and Paul Cao},
abstract = {{Standardized benchmarks have become widely accepted tools for the comparison of products and evaluation of methodologies. These benchmarks are created by consortia like SPEC and TPC under confidentiality agreements which provide little opportunity for outside observers to get a look at the processes and concerns that are prevalent in benchmark development. This paper introduces the primary concerns of benchmark development from the perspectives of SPEC and TPC committees. We provide a benchmark definition, outline the types of benchmarks, and explain the characteristics of a good benchmark. We focus on the characteristics important for a standardized benchmark, as created by the SPEC and TPC consortia. To this end, we specify the primary criteria to be employed for benchmark design and workload selection. We use multiple standardized benchmarks as examples to demonstrate how these criteria are ensured.}},
title = {{How to Build a Benchmark}},
year = {2015},
booktitle = {Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015)},
location = {Austin, TX, USA},
month = {February},
publisher = {ACM},
series = {ICPE '15},
doi = {http://dx.doi.org/10.1145/2668930.2688819},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {SPEC; TPC; SPECpower\_ssj2008; SERT; SPEC CPU},
pdf = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/paper/773.pdf}
}
						
Jóakim von Kistowski, Hansfried Block, John Beckett, Klaus-Dieter Lange, Jeremy A. Arnold, and Samuel Kounev. Analysis of the Influences on Server Power Consumption and Energy Efficiency for CPU-Intensive Workloads. In Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015), Austin, TX, USA, February 2015, ICPE '15. ACM, New York, NY, USA. February 2015.
[ bibtex | abstract | pdf ]
Keywords: SPEC, SERT, Power, Workload Characterization, Energy Efficiency, Metrics, Utilization.

Energy efficiency of servers has become a significant research topic over the last years, as server energy consumption varies depending on multiple factors, such as server utilization and workload type. Server energy analysis and estimation must take all relevant factors into account to ensure reliable estimates and conclusions. Thorough system analysis requires benchmarks capable of testing different system resources at different load levels using multiple workload types. Server energy estimation approaches, on the other hand, require knowledge about the interactions of these factors for the creation of accurate power models. Common approaches to energy-aware workload classification classify workloads depending on the resource types used by the different workloads. However, they rarely take into account differences in workloads targeting the same resources. Industrial energy-efficiency benchmarks typically do not evaluate the system's energy consumption at different resource load levels, and they only provide data for system analysis at maximum system load. In this paper, we benchmark multiple server configurations using the CPU worklets included in SPEC's Server Efficiency Rating Tool (SERT). We evaluate the impact of load levels and different CPU workloads on power consumption and energy efficiency. We analyze how functions approximating the measured power consumption differ over multiple server configurations and architectures. We show that workloads targeting the same resource can differ significantly in their power draw and energy efficiency. The power consumption of a given workload type varies depending on utilization, hardware and software configuration. The power consumption of CPU-intensive workloads does not scale uniformly with increased load, nor do hardware or software configuration changes affect it in a uniform manner.
@inproceedings{KiBlBeLaArKo2015-ICPE-SERT,
author = {J\'{o}akim von Kistowski and Hansfried Block and John Beckett and Klaus-Dieter Lange and Jeremy A. Arnold and Samuel Kounev},
abstract = {{ Energy efficiency of servers has become a significant research topic over the last years, as server energy consumption varies depending on multiple factors, such as server utilization and workload type. Server energy analysis and estimation must take all relevant factors into account to ensure reliable estimates and conclusions. Thorough system analysis requires benchmarks capable of testing different system resources at different load levels using multiple workload types. Server energy estimation approaches, on the other hand, require knowledge about the interactions of these factors for the creation of accurate power models. Common approaches to energy-aware workload classification classify workloads depending on the resource types used by the different workloads. However, they rarely take into account differences in workloads targeting the same resources. Industrial energy-efficiency benchmarks typically do not evaluate the system's energy consumption at different resource load levels, and they only provide data for system analysis at maximum system load. In this paper, we benchmark multiple server configurations using the CPU worklets included in SPEC's Server Efficiency Rating Tool (SERT). We evaluate the impact of load levels and different CPU workloads on power consumption and energy efficiency. We analyze how functions approximating the measured power consumption differ over multiple server configurations and architectures. We show that workloads targeting the same resource can differ significantly in their power draw and energy efficiency. The power consumption of a given workload type varies depending on utilization, hardware and software configuration. The power consumption of CPU-intensive workloads does not scale uniformly with increased load, nor do hardware or software configuration changes affect it in a uniform manner.}},
title = {{Analysis of the Influences on Server Power Consumption and Energy Efficiency for CPU-Intensive Workloads}},
year = {2015},
booktitle = {Proceedings of the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015)},
location = {Austin, TX, USA},
month = {February},
publisher = {ACM},
series = {ICPE '15},
doi = {http://dx.doi.org/10.1145/2668930.2688057},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {SPEC, SERT, Power, Workload Characterization, Energy Efficiency, Metrics, Utilization},
pdf = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/paper/772.pdf},
slides = {http://se2.informatik.uni-wuerzburg.de/pa/publications/download/slides/772},
note = {acceptance rate: 27\%}
}
						
Klaus-Dieter Lange, Jeremy A. Arnold, Hansfried Block, Nathan Totura, John Beckett, and Mike G. Tricker. Further Implementation Aspects of the Server Efficiency Rating Tool (SERT). In Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering, ICPE '13, New York, NY, USA, 2013. ACM.
[ bibtex | abstract ]
Keywords: Affinitization, Benchmark, Energy Efficiency, Energy Star, Environment Protection Agency (EPA), Framework, Memory, Performance Engineering, Reporting, Server, SPEC, System Discovery, System Performance.

The Server Efficiency Rating Tool (SERT) has been developed by the Standard Performance Evaluation Corporation (SPEC) at the request of the US Environmental Protection Agency (EPA). Almost 3% of all electricity consumed within the US in 2010 went to running datacenters. With this in mind, the EPA released Version 2.0 of the ENERGY STAR for Computer Servers program in early 2013 to include the mandatory use of the SERT. Other governments world-wide that are also concerned by growing power consumption of servers and datacenters are considering the adoption of the SERT.
@inproceedings{Lange:2013:IAS:2479871.2479926,
 author = {Lange, K.-D. and Arnold, Jeremy A. and Block, Hansfried and Totura, Nathan and Beckett, John and Tricker, Mike G.},
 title = {{Further Implementation Aspects of the Server Efficiency Rating Tool (SERT)}},
 booktitle = {Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering},
 series = {ICPE '13},
 year = {2013},
 isbn = {978-1-4503-1636-1},
 location = {Prague, Czech Republic},
 pages = {349--360},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/2479871.2479926},
 doi = {10.1145/2479871.2479926},
 acmid = {2479926},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {Affinitization, Benchmark, Energy Efficiency, Energy Star, Environment Protection Agency (EPA), Framework, Memory, Performance Engineering, Reporting, Server, SPEC, System Discovery, System Performance},
} 
						
Klaus-Dieter Lange, Mike G. Tricker, Jeremy A. Arnold, Hansfried Block, and Christian Koopmann. The Implementation of the Server Efficiency Rating Tool. In Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering, ICPE '12, New York, NY, USA, 2012. ACM.
[ bibtex | abstract ]
Keywords: ENERGY STAR, EPA, SERT, SPEC, Benchmark, Datacenter, Energy Efficiency, Environmental Protection Agency, Power, Rating Tool, Server, Storage.

The Server Efficiency Rating Tool (SERT) has been developed by Standard Performance Evaluation Corporation (SPEC) at the request of the US Environmental Protection Agency (EPA), prompted by concerns that US datacenters consumed almost 3% of all energy in 2010. Since the majority was consumed by servers and their associated heat dissipation systems the EPA launched the ENERGY STAR Computer Server program, focusing on providing projected power consumption information to aid potential server users and purchasers. This program has now been extended to a world-wide audience. This paper expands upon the one published in 2011, which described the initial design and early development phases of the SERT. Since that publication, the SERT has continued to evolve and has entered the first Beta phase in October 2011 with the goal of being released in 2012. This paper describes more of the details of how the SERT is structured. This includes how components interrelate, how the underlying system capabilities are discovered, and how the various hardware subsystems are measured individually using dedicated worklets.
@inproceedings{Lange:2012:ISE:2188286.2188307,
 author = {Lange, Klaus-Dieter and Tricker, Mike G. and Arnold, Jeremy A. and Block, Hansfried and Koopmann, Christian},
 title = {{The Implementation of the Server Efficiency Rating Tool}},
 booktitle = {Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering},
 series = {ICPE '12},
 year = {2012},
 isbn = {978-1-4503-1202-8},
 location = {Boston, Massachusetts, USA},
 pages = {133--144},
 numpages = {12},
 url = {http://doi.acm.org/10.1145/2188286.2188307},
 doi = {10.1145/2188286.2188307},
 acmid = {2188307},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {ENERGY STAR, EPA, SERT, SPEC, Benchmark, Datacenter, Energy Efficiency, Environmental Protection Agency, Power, Rating Tool, Server, Storage},
} 
						
Klaus-Dieter Lange and Mike G. Tricker. The Design and Development of the Server Efficiency Rating Tool (SERT). In Proceedings of the 2nd ACM/SPEC International Conference on Performance Engineering, ICPE '11, New York, NY, USA, 2011. ACM.
[ bibtex | abstract ]
Keywords: SPEC, Benchmark, Energy Efficiency, Power Analysis, Server, Datacenter, Energy Star, Environmental Protection Agency (EPA).

According to the United States Environmental Protection Agency (US EPA) almost 3% of all electricity consumed within the US in 2010 goes to running datacenters, with the majority of that powering servers and the associated air conditioning systems dedicated to eliminating the heat they produce. The EPA launched the ENERGY STAR® Computer Server program in May 2009, intended to deliver information to better enable server purchasing decisions based on projected power consumption. The Server Efficiency Rating Tool (SERT) has been developed by the Standard Performance Evaluation Corporation (SPEC) SPECpower committee to address the EPA requirements for Version 2 of the ENERGY STAR server program. Unlike many tools sourced from the SPEC organization the SERT is not intended to be a benchmark, and for Version 2 does not offer a single score model. Instead it produces detailed information regarding the influence of CPU, memory, network and storage I/O configurations on overall server power consumption. This paper describes the design and development of the SERT, including discussion of the collaborative nature of working with the EPA and the various industry stakeholders involved in the design, review and development process. Many of the core ideas behind SERT were derived from theSPECpower_ssj2008 and other SPEC-developed benchmarks, and this paper illustrates where ideas and code were shared, as well as where new thinking resulted in entirely new solutions. It also includes thoughts for the future, as the ENERGY STAR server program continues to evolve and the SERT will evolve with it.
@inproceedings{Lange:2011:DDS:1958746.1958769,
 author = {Lange, K.-D. and Tricker, Michael G.},
 title = {{The Design and Development of the Server Efficiency Rating Tool (SERT)}},
 booktitle = {Proceedings of the 2Nd ACM/SPEC International Conference on Performance Engineering},
 series = {ICPE '11},
 year = {2011},
 isbn = {978-1-4503-0519-8},
 location = {Karlsruhe, Germany},
 pages = {145--150},
 numpages = {6},
 url = {http://doi.acm.org/10.1145/1958746.1958769},
 doi = {10.1145/1958746.1958769},
 acmid = {1958769},
 publisher = {ACM},
 address = {New York, NY, USA},
}
						
Klaus-Dieter Lange. Identifying Shades of Green: The SPECpower Benchmarks. Computer, 42(3):95-97, March 2009.
[ bibtex | abstract ]
Keywords: Benchmark ,Performance Evaluation, Energy Efficiency, Industry-Standard SPECpower Benchmark, Measurement Standards, Power measurement, SPECpower_ssj2008, Green IT.

To drive energy efficiency initiatives, SPEC established SPECpower_ssj2008, the first industry-standard benchmark for measuring power and performance characteristics of computer systems.
@ARTICLE{4803904, 
author={Lange, K.-D.}, 
journal={Computer}, 
title={{Identifying Shades of Green: The SPECpower Benchmarks}}, 
year={2009}, 
month={March}, 
volume={42}, 
number={3}, 
pages={95-97}, 
keywords={benchmark testing;performance evaluation;computer system performance measurement;computer system power measurement;energy-efficiency initiative;industry-standard SPECpower benchmark;Benchmark testing;Computer industry;Energy efficiency;Energy management;Energy measurement;Measurement standards;Personal communication networks;Power engineering computing;Power measurement;Proposals;SPECpower_ssj2008;benchmarks;green IT}, 
doi={10.1109/MC.2009.84}, 
ISSN={0018-9162},
}