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De-mystifying Grid Technologies
Continued from page: 3
Anindya Roy and Anadi Misra
Tuesday, April 03, 2007
Emerging trends Let's now consider some of the latest trends in this sphere.
P2P Grid: One of the newest technologies in grid computing is P2P
grids. We talked about it in the December issue of PCQuest in detail and also
showed how to implement it. P-Grid is essentially a grid that runs over P2P
connections. Both the data transfer and the CPU cycle migration are done over
P2P. Currently, the framework being used runs on Gnutella network.
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| Between Nov 97 and Feb 06,
PrimeNet Grid has handled 11,579,649,914 P90 machine-hours. Its throughput
rate can be characterized by a fitted, exponential trend line |
Although, there is no full-fledged application available which can leverage
such a concept, you can use an application called GPU (downloadable from http://gpu.sf.
net). This application is still an alpha and can only run some test applications
such as Image Rendering, Net Crawling, etc.
But imagine what will happen when this technology matures. Any one with a
machine and an Internet connection can become a part of a public Grid and share
processing power the same way as we share MP3 and music files today. So, in that
case we will truly be able to achieve Internet computing or rather Internet
Super Computing.
Grid management: You must have heard about many types of grids and
clusters and read about them in PCQuest, such as heterogeneous Grid Platform
called Condor, or Globus or some simple clustering middleware such as SSI-based
like OpenMosix and MPI-based ones like Oscar and Flash Mob etc. If you search
over the Net, you will find there are quite a few different kinds of grid
products available. Some have a graphical front end to monitor the nodes and
some even don't have one. Let's take a classic example, OpenMosix.
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| In a matter of 5 mins, we
were able to connect to a P2P grid with 10 GB of RAM and 10 GFlops of
processing power using GPU |
This one has a graphical monitoring application called OpenMosixView, but
have you ever noticed that if the number grows to something around a hundred
nodes, then how difficult it becomes to monitor? Plus, it only shows you the
current RAM and CPU utilization of the nodes. What about the disk usage? Or if
in case, you want to see what the CPU utilization was in the last one hour or
day, then?
These are things which are very difficult to monitor in case of large grids
or clusters. To make things worse, let's say you have multiple grids, one based
on Condor and the other one on Globas. Another one could just be a cluster using
Oscar or ROCKS with MPI support. And you want to monitor both of them from one
place. Then, what will you do?
Let's take a case of a cluster or a grid with hundreds and thousands of nodes
over a wide geographical distribution. Managing them all from one place can be
really difficult. So, this is one area that is picking up on the Grid technology
front. The most common and popular tool out there which solves this purpose is
Ganglia. We have talked about this in detail in our June 2006 issue. And
this is the one being used by most of the biggies using Grid technologies
such as NASA, CRAY, SUN, Boeing, US Air Force and Microsoft.
| Glossary |
| Cluster Interconnect: A very high speed connection
allowing computers in a cluster to interconnect. Enterprise Grid Alliance: A
vendor-neutral, open and independent organization that works as a consortium
for focusing on obstacles enterprises face in grid implementations, and
promoting open and interoperable solutions for problems. Enterprise
Grid: A collection of networked components including systems,
applications like CRM, ERP etc. usually managed by a distinct business
entity providing a set of services and assignment of resources to these
services for accomplishing business goals.
N1: Sun's architecture for next-generation data-center that makes
the entire data center work as one single, unified system. It reduces
management and costs, increases the data-center resource utilization,
infrastructure responsiveness, and agility.
Utility Computing: 'PAY-AS-YOU-GO' model of computing analogous
electricity usage. Instead of paying for computing resources to handle peak
load all the time it requires paying only for the computing used.
Utility Data-Center: An infrastructure solution proposed by HP
that allows virtualization of computing resources for the data center. The
Utility Data Center includes servers, storage, and networking products that
are integrated and deployed by intelligent management software that allows
them to be shared and dynamically re-provisioned to accommodate changing
workloads. |
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