|| ||Justin Riley <justin.t.riley-AT-gmail.com> |
|| ||python-announce-list-AT-python.org |
|| ||ANN: StarCluster 0.90beta Released - HPC Clusters on Amazon's EC2 |
|| ||Wed, 16 Sep 2009 15:34:41 -0400|
|| ||Article, Thread
I'd like to announce the first beta release of StarCluster, a utility
for creating and managing general purpose computing clusters hosted on
Amazon's Elastic Compute Cloud (EC2).
>From the PyPI Page:
StarCluster minimizes the administrative overhead associated with
obtaining, configuring, and managing a traditional computing cluster
used in research labs or for general distributed computing applications.
StarCluster is built on top of EC2 which enables dynamically creating
and destroying clusters of virtual machines and only paying for the time
used. The amount per hour varies depending on the instance type and the
number of virtual machines.
StarCluster consists of a library and set of scripts that use the
library. For end-users, the scripts are the main user interface and
provide simple intuitive options for getting started with distributed
computing on EC2 (i.e. starting/stopping clusters, managing software
configurations, etc). For developers, the library wraps the EC2 API to
provide a simplified interface for launching/terminating nodes,
executing commands on the nodes, copying files to/from the nodes, etc.
To get started, the user creates a simple configuration file with their
account details and a few preferences (i.e. number of machines, instance
type, EBS volumes to be mounted, etc). After creating the configuration
file and starting the software, a cluster of Linux machines configured
with a queuing system (Sun Grid Engine), a nfs shared /home directory,
and OpenMPI is created and ready to go out of the box.
StarCluster has been targeted for computational research labs and to
support classrooms with computational requirements.
For research labs, StarCluster is a way for graduate students and
faculty to have an on-demand cluster. This means students can access
their research with the same hardware and software configurations
wherever they go; even if they move to another institution. StarCluster
also provides a way for students to experiment with a computational
model on a cheap budget before running on local dedicated resources.
In the classroom, StarCluster provides a cost effective, reliable way of
managing the software configurations for a particular course. It also
removes the majority of system administration concerns since the initial
setup procedures have been captured in StarCluster and in the user's
software configurations (i.e. AMI images, EBS volumes, etc). This means
that each semester the exact computing cluster configuration can be
recalled with more or less nodes. With this model there is also the
benefit that if hardware problems occur it's easy to request a new set
of machines in the cloud.
ComputerWorld (AU) Article:
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