in the virtual extension
DOI: 10.1145/1965724.1965727
In the Virtual Extension
To ensure the timely publication of articles, Communications created the Virtual Extension (VE)
to expand the page limitations of the print edition by bringing readers the same high-quality
articles in an online-only format. VE articles undergo the same rigorous review process as those
in the print edition and are accepted for publication on merit. The following synopses are from
articles now available in their entirety to ACM members via the Digital Library.
contributed article
DOI: 10.1145/1965724.1965751
The Case for RAMCloud
John Ousterhout, Parag Agrawal,
David Erickson, Christos Kozyrakis,
Jacob Leverich, David Mazières,
Subhasish Mitra, Aravind Narayanan,
Diego Ongaro, Guru Parulkar,
Mendel Rosenblum, Stephen M. Rumble,
Eric Stratmann, and Ryan Stutsman
For the past four decades magnetic disks
have been the primary storage location for
online information in computer systems.
over that period, disk technology has
undergone dramatic improvements while
being harnessed by higher-level storage
systems (such as file systems and relational
databases). However, disk performance has
not improved as quickly as disk capacity,
and developers find it increasingly difficult
to scale disk-based systems to meet the
needs of large-scale Web applications.
Many computer scientists have proposed
new approaches to disk-based storage
as a solution, and others have suggested
replacing disks with flash memory devices.
In contrast, we say the solution is to shift
the primary locus of online data from disk
to DRAM, with disk relegated to a backup/
archival role.
A new class of storage called
RAMCloud will provide the storage
substrate for many future applications.
RAMCloud stores all of its information in
the main memories of commodity servers
and uses hundreds or thousands of these
servers to create a large-scale storage
system. Because all data is in DRAM at all
times, RAMCloud promises 100x– 1,000x
lower latency than disk-based systems
and 100x– 1,000x greater throughput.
Though individual memories are
volatile, RAMCloud can use replication
and backup techniques to provide data
durability and availability equivalent to
disk-based systems.
The combination of latency and
scale offered by RAMCloud will change
the storage landscape in three ways:
simplify development of large-scale Web
applications by eliminating many of
the scalability issues that sap developer
productivity today; enable a new class
of applications that manipulate data
100x– 1,000x more intensively than
is possible today; and provide the
scalable storage substrate needed for
cloud computing and other data-center
applications.
review article
DOI: 10.1145/1965724.1965752
Workload Management
for Power Efficiency in
Virtualized Data Centers
Gargi Dasgupta, Amit Sharma,
Akshat Verma, Anindya Neogi,
and Ravi Kothari
By most estimates, energy-related costs will
become the single largest contributor to
the overall cost of operating a data center.
Ironically, several studies have shown that
a typical server in a data center is seriously
underutilized. For example, Bohrer et al.
find the average server utilization to vary
between 11% and 50% for workloads from
sports, e-commerce, financial, and Internet
proxy clusters. This underutilization is the
consequence of provisioning a server for
the infrequent though inevitable peaks
in the workload. Power-aware dynamic
application placement can simultaneously
address underutilization of servers as well
as the rising energy costs in a data center
by migrating applications to better utilize
servers and switching freed-up servers to a
lower power state.
Though the concept of dynamic
application placement is not new, the
two recent trends of virtualization and
energy management technologies in
modern servers have made it possible
for it to be widely used in a data center.
While virtualization has been the key
enabler, power minimization has been
the key driver for energy-aware dynamic
application placement.
Server virtualization technologies
first appeared in the 1960s to enable
timesharing of expensive hardware
between multiple users. As hardware
became less expensive, virtualization
gradually lost its charm. However, since
the late 1990s there has been renewed
interest in server virtualization and is now
regarded as a disruptive business model to
drive significant cost reductions. Advances
in system management allow the benefits
of virtualization to be now realized without
any appreciable increase in the system
management costs.
The benefits of virtualization include
more efficient utilization of hardware
(especially when each virtual machine,
or VM, on a physical server reaches peak
utilization at different points in time or
when the applications in the individual
VMs have complementary resource
usage), as well as reduced floor space and
facilities management costs. Additionally,
virtualization software tends to hide the
heterogeneity in server hardware and make
applications more portable or resilient to
hardware changes. Virtualization Planning
entails sizing and placing existing or fresh
workloads as VMs on physical servers.
In this article, the authors simplify
resource utilization of a workload to
be captured only by CPU utilization.
However in practice, multiple parameters,
such as memory, disk, and network I/o
bandwidth consumption, among others,
must be considered.
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And the latest news on supercomputers, Monte Carlo tree search,
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