The Green500 List: Encouraging Sustainable Supercomputing

Feng, Wu-chun; Cameron, Kirk W.

doi:10.1109/mc.2007.445

Cited by 185 publications

(72 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Clusters are able to handle complex and large computations by simultaneously working on multiple computers on the same problem or a portion of it [6] [7]. Cluster systems are capable of competing with the performance of supercomputers at lower costs [8].…”

Section: Clusteringmentioning

confidence: 99%

Green Cloud Computing: A Review

Masoud¹,

AlShamrani²,

AlGhamdi³

et al. 2017

IJCA

View full text Add to dashboard Cite

Cloud computing has revolutionized the way large data is stored and handled by the virtualization of servers and data centers to make them more efficient. However, these IT resources consume huge amounts of power and energy, ultimately becoming a vital source of CO2 emission. This has brought upon the need for Green Cloud Computing to make IT resources both energy efficient and operating at a low cost. In order to reach optimal solutions for green cloud computing, the power efficiency of the Cloud needs to be thoroughly analyzed. The aim of this review is to underscore some of the most effective ways to achieve green cloud computing such as scheduling, clustering, virtualization, proportional computing, and other energy conserving methods.Although the environmental impact is high for green cloud computing, it still faces challenges with regards to security and connectivity.

show abstract

Section: Clusteringmentioning

confidence: 99%

Green Cloud Computing: A Review

Masoud¹,

AlShamrani²,

AlGhamdi³

et al. 2017

IJCA

View full text Add to dashboard Cite

show abstract

“…By lowering processor clock speed and supply voltage during both idle times and compute intensive application phases, large reductions in power consumption can be achieved with modest performance loss. High-end computing communities, for example, cluster computing and supercomputing in large data centers, have applied DVFS techniques to reduce power consumption and achieve high reliability and availability [13], [14], [15], [16]. A power-aware cluster is defined as a compute cluster where compute nodes support multiple power/performance modes, for example, processors with frequencies that can be turned up or down.…”

Section: A Power-aware Cluster Computingmentioning

confidence: 99%

Power-aware scheduling of virtual machines in DVFS-enabled clusters

Laszewski

Wang

Younge

et al. 2009

2009 IEEE International Conference on Cluster Computing and Workshops

227

136

View full text Add to dashboard Cite

Abstract-With the advent of Cloud computing, large-scale virtualized compute and data centers are becoming common in the computing industry. These distributed systems leverage commodity server hardware in mass quantity, similar in theory to many of the fastest Supercomputers in existence today. However these systems can consume a cities worth of power just to run idle, and require equally massive cooling systems to keep the servers within normal operating temperatures. This produces CO2 emissions and significantly contributes to the growing environmental issue of Global Warming. Green computing, a new trend for high-end computing, attempts to alleviate this problem by delivering both high performance and reduced power consumption, effectively maximizing total system efficiency. This paper focuses on scheduling virtual machines in a compute cluster to reduce power consumption via the technique of Dynamic Voltage Frequency Scaling (DVFS). Specifically, we present the design and implementation of an efficient scheduling algorithm to allocate virtual machines in a DVFS-enabled cluster by dynamically scaling the supplied voltages. The algorithm is studied via simulation and implementation in a multi-core cluster. Test results and performance discussion justify the design and implementation of the scheduling algorithm.

show abstract

“…In procurement situations the access to actual cost data allows ranking competing offers with econometric measures such as life-time costs and costperformance. New approaches for metrics, which include other aspects of computers, include the Green500 [7], where actual installed high performance computing (HPC) systems from the Top500 are re-ranked by power-efficiency (performance/power). Another interesting concept developed by Tsugio Makimoto is the " Figure of Merit" for nomadic devices, which inspired the work presented here [8].…”

Section: Current Practice For Ranking Computersmentioning

confidence: 99%

Generalized utility metrics for supercomputers

Strohmaier

2009

Comp. Sci. Res. Dev.

View full text Add to dashboard Cite

The problem of ranking the utility of supercomputer systems arises frequently in situations such as procurements and other types of evaluations of architectures. It is also central for any general ranking of supercomputers such as the Top500. Rankings of computer systems have traditionally solely focused on performance aspects. In recent years restrictions due to power and space requirements of large supercomputers have become very noticeable, which has increased the importance of including these factors in generalized rankings. In this paper we present an overview of the current practice for utility metrics and analyze their shortcomings. We then present and discuss in detail a new concept for a parameterized utility metric for supercomputers, which is based on effective performance, available memory size, actual power consumption, and (if desired) the floor space required for supercomputers. This metric is designed and proposed for augmenting the current Top500 ranking.

show abstract

The Green500 List: Encouraging Sustainable Supercomputing

Cited by 185 publications

References 6 publications

Green Cloud Computing: A Review

Green Cloud Computing: A Review

Power-aware scheduling of virtual machines in DVFS-enabled clusters

Generalized utility metrics for supercomputers

Contact Info

Product

Resources

About