4,325 research outputs found
Towards Energy-Proportional Computing for Enterprise-Class Server Workloads
Massive data centers housing thousands of computing nodes
have become commonplace in enterprise computing, and the
power consumption of such data centers is growing at an
unprecedented rate. Adding to the problem is the inability
of the servers to exhibit energy proportionality, i.e., provide
energy-ecient execution under all levels of utilization,
which diminishes the overall energy eciency of the data
center. It is imperative that we realize eective strategies
to control the power consumption of the server and improve
the energy eciency of data centers. With the advent of
Intel Sandy Bridge processors, we have the ability to specify
a limit on power consumption during runtime, which creates
opportunities to design new power-management techniques
for enterprise workloads and make the systems that they run
on more energy-proportional.
In this paper, we investigate whether it is possible to achieve
energy proportionality for an enterprise-class server workload,
namely SPECpower ssj2008 benchmark, by using Intel's
Running Average Power Limit (RAPL) interfaces. First,
we analyze the power consumption and characterize the instantaneous
power prole of the SPECpower benchmark at
a subsystem-level using the on-chip energy meters exposed
via the RAPL interfaces. We then analyze the impact of
RAPL power limiting on the performance, per-transaction
response time, power consumption, and energy eciency of
the benchmark under dierent load levels. Our observations
and results shed light on the ecacy of the RAPL interfaces
and provide guidance for designing power-management techniques
for enterprise-class workloads
A Note on Disk Drag Dynamics
The electrical power consumed by typical magnetic hard disk drives (HDD) not
only increases linearly with the number of spindles but, more significantly, it
increases as very fast power-laws of speed (RPM) and diameter. Since the
theoretical basis for this relationship is neither well-known nor readily
accessible in the literature, we show how these exponents arise from
aerodynamic disk drag and discuss their import for green storage capacity
planning.Comment: 5 pages, 3 figure
Dynamic Physiological Partitioning on a Shared-nothing Database Cluster
Traditional DBMS servers are usually over-provisioned for most of their daily
workloads and, because they do not show good-enough energy proportionality,
waste a lot of energy while underutilized. A cluster of small (wimpy) servers,
where its size can be dynamically adjusted to the current workload, offers
better energy characteristics for these workloads. Yet, data migration,
necessary to balance utilization among the nodes, is a non-trivial and
time-consuming task that may consume the energy saved. For this reason, a
sophisticated and easy to adjust partitioning scheme fostering dynamic
reorganization is needed. In this paper, we adapt a technique originally
created for SMP systems, called physiological partitioning, to distribute data
among nodes, that allows to easily repartition data without interrupting
transactions. We dynamically partition DB tables based on the nodes'
utilization and given energy constraints and compare our approach with physical
partitioning and logical partitioning methods. To quantify possible energy
saving and its conceivable drawback on query runtimes, we evaluate our
implementation on an experimental cluster and compare the results w.r.t.
performance and energy consumption. Depending on the workload, we can
substantially save energy without sacrificing too much performance
Architecting Efficient Data Centers.
Data center power consumption has become a key constraint in continuing to scale Internet services. As our society’s reliance on “the Cloud” continues to grow, companies require an ever-increasing amount of computational capacity to support their customers. Massive warehouse-scale data centers have emerged, requiring 30MW or more of total power capacity. Over the lifetime of a typical high-scale data center, power-related costs make up 50% of the total cost of ownership (TCO). Furthermore, the aggregate effect of data center power consumption across the country cannot be ignored. In total, data center energy usage has reached approximately 2% of aggregate consumption in the United States and continues to grow.
This thesis addresses the need to increase computational efficiency to address this grow- ing problem. It proposes a new classes of power management techniques: coordinated full-system idle low-power modes to increase the energy proportionality of modern servers. First, we introduce the PowerNap server architecture, a coordinated full-system idle low- power mode which transitions in and out of an ultra-low power nap state to save power during brief idle periods. While effective for uniprocessor systems, PowerNap relies on full-system idleness and we show that such idleness disappears as the number of cores per processor continues to increase. We expose this problem in a case study of Google Web search in which we demonstrate that coordinated full-system active power modes are necessary to reach energy proportionality and that PowerNap is ineffective because of a lack of idleness. To recover full-system idleness, we introduce DreamWeaver, architectural support for deep sleep. DreamWeaver allows a server to exchange latency for full-system idleness, allowing PowerNap-enabled servers to be effective and provides a better latency- power savings tradeoff than existing approaches. Finally, this thesis investigates workloads which achieve efficiency through methodical cluster provisioning techniques. Using the popular memcached workload, this thesis provides examples of provisioning clusters for cost-efficiency given latency, throughput, and data set size targets.Ph.D.Computer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91499/1/meisner_1.pd
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Applying the Full Protection and Security Standard of International Investment Law to Digital Assets
This article considers the possibility that digital assets of foreign investors such as websites and computer systems could be protected by the full protection and security (‘FPS’) standard common to many bilateral investment treaties. Such assets can properly be described as investments and the flexible nature of the FPS standard observed in recent arbitration practice could be extended to cover civil disturbances such as 'cyber attacks' against companies. The article considers host state liability with respect to the prevention of harm to digital assets as well as failure to enforce laws that prohibit it. The lack of governmental control over websites suggests that it would be difficult to ascribe state liability under an FPS clause, except possibly in situations of large scale internet infrastructure collapse. A duty to prosecute attacks against digital assets, while common to many jurisdictions and seen in international instruments, is inappropriate as an investment treaty claim because of difficulties in compensation. The FPS standard further appears to incorporate a degree of contextual proportionality linked to the host state’s resources and this may prevent successful claims against Developing States where many cyber attacks occur
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