3,152 research outputs found
High-Performance Cloud Computing: A View of Scientific Applications
Scientific computing often requires the availability of a massive number of
computers for performing large scale experiments. Traditionally, these needs
have been addressed by using high-performance computing solutions and installed
facilities such as clusters and super computers, which are difficult to setup,
maintain, and operate. Cloud computing provides scientists with a completely
new model of utilizing the computing infrastructure. Compute resources, storage
resources, as well as applications, can be dynamically provisioned (and
integrated within the existing infrastructure) on a pay per use basis. These
resources can be released when they are no more needed. Such services are often
offered within the context of a Service Level Agreement (SLA), which ensure the
desired Quality of Service (QoS). Aneka, an enterprise Cloud computing
solution, harnesses the power of compute resources by relying on private and
public Clouds and delivers to users the desired QoS. Its flexible and service
based infrastructure supports multiple programming paradigms that make Aneka
address a variety of different scenarios: from finance applications to
computational science. As examples of scientific computing in the Cloud, we
present a preliminary case study on using Aneka for the classification of gene
expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape
An Approach to Ad hoc Cloud Computing
We consider how underused computing resources within an enterprise may be
harnessed to improve utilization and create an elastic computing
infrastructure. Most current cloud provision involves a data center model, in
which clusters of machines are dedicated to running cloud infrastructure
software. We propose an additional model, the ad hoc cloud, in which
infrastructure software is distributed over resources harvested from machines
already in existence within an enterprise. In contrast to the data center cloud
model, resource levels are not established a priori, nor are resources
dedicated exclusively to the cloud while in use. A participating machine is not
dedicated to the cloud, but has some other primary purpose such as running
interactive processes for a particular user. We outline the major
implementation challenges and one approach to tackling them
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