
By:
Oscar Andersson 820923-4817
Glenn Eliasson 821012-4890
Table of contents
FOREWORD ................................................................................................................................... 3
INTRODUCTION ............................................................................................................................ 4
WHY USE GRID COMPUTING? .................................................................................................. 5
HOW DOES GRID COMPUTING WORK? .................................................................................. 7
SUMMARY ................................................................................................................................... 10
SOURCES ...................................................................................................................................... 10
FOREWORD
Before we started with this project we asked ourselves some questions, because none of us know
much about grids;
What is a grid?
What does it do?
Why do we use grids? Advantages / disadvantages
These are the main questions we want to get answered after we are finished with this project.
INTRODUCTION
In 1800 Alessandra Volta invented the electrical battery. This invention would be the ground for the
future evolvement into our modern electrical society, and made a future of demand for dependable
and consistent access to utility power, resulting in the electrical power grid.
It was first in the mid of 1990s the computer scientists were inspired by the electrical power grids
and began to design and develop an analogous infrastructure called the computational power grid for
wide-area and distributed computing. The reason why the power grid was so interesting was that the
scientist required more resources than a single computer could provide in a single administrative
domain. Connecting several computers and running software in parallel, a practice known as
distributed computing had been done long before, but designing a system were each user can take
advantage of the collective computing resources in the network was new ground.
Just like the invention of the battery eventually led to information exchange through telegraphs,
and later the construction of power grids, the computer gave us the Internet and will perhaps lead
us into an era were computer power can be tapped through a global computer grid. (It is in fact the
many similarities to the power grid that resulted in the word “computing grid”).
These abilities of the grids enable sharing, selection and aggregation with computers and storage
systems over wide areas. This is perfect when the users solve large-scale resource problems in
science, engineering and commerce.
WHY USE GRID COMPUTING?
It is a well known fact that the computing power of the typical workstation or PC is very poorly
utilised. Most of the time only a fraction of the systems resources are used (writing Matlab code,
running screensavers..), but sometimes the system will be bogged down with work for long periods of
time (running a Matlab simulation..). The traditional solution to this has been to build ever faster
computers and supercomputers, however investing in this kind of computational resources can be
prohibitively expensive. There exists perhaps a more elegant solution to the problem; using
networking technologies it is theoretically possible to dynamically share the computational resources
among a large group of users, hence improving the usage of computational resources of the involved
systems. Ideally the net result for all users would be a dramatic gain in peak computational power as
there would be substantially more resources available for the average user at the particular times
when large computations are necessary. Again theoretically this would empower users with vast
amounts of available computational power, theoretically far beyond that of expensive
supercomputers. To this date it is foremost the prospect of relatively cheap access to huge amounts
of computing power that has sparked the interest in grid computing within organisations such as
CERN;
“When the Large Hadron Collider (LHC) comes online at the CERN in 2007 it will produce more data
than any other experiment in the history of physics. Particle physicists have now passed another
milestone in their preparations for the LHC by sustaining a continuous flow of 600 megabytes of
data per second (MB/s) for 10 days from the Geneva laboratory to seven sites in Europe and the US.
CERN plans to use a worldwide supercomputing "Grid" -- similar to the World Wide Web but much
more powerful -- of computing centres to handle the data from the collider, which will then be
analyzed by more than 6000 scientists all over the world”. -Belle Dumé, PhysicsWeb
Also some pharmaceutical companies have shown great interest in using grids for computer aided
drug design because of the immense scalability of such systems;
“A drug design problem that requires screening 180,000 compounds at three hours each would take
a single PC about 61 years to process, and would tie-up a typical 64-node supercomputer for about a
year.. The problem can be solved with a large scale grid of hundreds of supercomputers in a
day" -Rajkumar Buyya B.E. (Mysore Univ.) and M.E. (Bangalore Univ.).
However there exists far longer reaching visions for the applications of grid computing. One such
vision is that instead of the smaller corporate and government grids of today, in the future there
will be a global grid system that will replace the Internet (which is just an information exchange
network) of today. The users of this grid would not only be able to access information and services
as before, but also invest into computing power on a pay for use basis in a similar way as we today
buy electrical energy thorough the power grid. In addition, the users would be able to access
powerful remote services. Another key benefit of a global grid is better load balancing by using
available resources in off-peak time zones.
One area of debate is whether the average micro-consumer in such a grid would also act as a
producer of computing power. The answer to this question seems to depend on if future applications
can exploit these small, loosely coupled computational resources. Some claim that in a grid based
future there is little need for any significant computing performance in the machines of the average
consumers as it would be cheaper to buy this performance through the grid anyway, so the benefit
from such a scheme would be questionable.
Although there are already several grid systems in use around the world today, most are relatively
small and are used within individual companies and organizations in order to efficiently connect and
utilize the company resources. This is mainly because of security concerns, many companies are
worried about the possibility of theft of sensitive information within larger grids. But there are
other problems as well. For a large multi company grid to function there needs to be a good system
in place to divide the resources rightfully. This problem seems relatively easy to solve on paper but
implementing such rules has proved to be more difficult than previously thought.
Another interesting commercial use of
grids is for “computer brokers” to lease
grid resources to companies. Companies
hiring such resources would not have to
make the large investments in
supercomputers. This system would offer a
much more dynamical access to computing
power than before, making it cheaper and
faster for companies to adapt to changes in
computing demand within the organization.
One such “computer broker” is Sun
Microsystems, who has recently entered
the market with its “Sun Grid Compute
Utility”, selling grid computing resources to
companies on a pay per use basis (as seen in
the figure to the right). Of course such a
business model would only pay off in the
long run for companies with certain
resource usage patterns. Another use would
be for companies to offload parts of their
workload to these leased grids at times of
unusually high computational activity to
speed up the computational times.
.
“Compute resources—they must be available and
accessible whenever you need them, 24x7.
Many organizations are faced with resource utilization
issues—they need vast amounts of
compute power, but only at certain times. The rest of the
time, resources are underutilized.”
“The Solution: Sun™ Grid Pay-Per-Use Computing
Sun has defined and developed a better solution:
pay-per-using computing. This model
changes the game—enabling you to purchase
computing power as you need it, without
owning and managing the assets.”
“Simple, Affordable Compute Utility:
$1/Hour/CPU
The first in the Sun Grid family of offerings is
Compute Utility, a $1 per CPU per hour payperuse offering for batch workloads such as
Monte Carlo simulations, protein modeling,
geologic exploration, and mechanical CAD
simulations, among others. This offering
meets the needs of our customers for agile,
highly available, affordable compute resources
on a pay-per-use basis.”
HOW DOES GRID COMPUTING WORK?
Grids are very complex systems, in order to get a clear view of how grids work we have divided this
subject into smaller individual parts.
 Grid hardware:
On the hardware level, a grid system should be very familiar to most people as the hardware
building blocks of a grid system is the same as that of the Internet; computer resources and
network interconnections connecting them. However as the network of the grid will transfer not
only pure information but computations (instructions) as well, it is required to have far greater
network transmission rates than what is typical over the Internet. Interestingly however,
networking technologies are developing at a far greater rate than processor technologies, as
shown by the following slide from [www.globus.org]:
This fact is of great importance, as applications that process over a grid will have to be
processed in parallel across a large number of geographically separated resources. Many types
of computation workloads however require a fair amount of information exchange between each
other. The resulting amount of required information exchange between geographically separated
resources in the grid and the capability of the network interconnects connecting them is often
the performance limiting metric in grid systems today. As networking technologies continue to
evolve at much higher rates than processing technologies computing grids will become
increasingly effective and useful for new kinds of computational loads.
 Grid software:
Just like the Internet, a grid is built from standardised protocols that enable systems of
various hardware and operative systems to function together in the grid. These protocols are
commonly divided into 2 parts depending on how close to the end-system they work;
Lowlevel services: security, information, directory, resource management (resource trading and
resource allocation.
High-level services: tools for application development, resource management and scheduling
Naturally the most challenging parts of the complex grid software platform is the high-level
services and of those resource management and scheduling are especially complicated to
implement. It is after all in the control software that all the complexities of grid computing
reside. Lets consider some important aspects of software impact on grid operation:
Performance:
Customized application development tools (SDKs) are needed for application development for the
grid systems, as the user applications processed over the grid will have to execute using the
protocol framework of the grid system. These SDKs are built to extract maximum application
parallelism from the code of the applications in order for the application to be able to execute
in a highly parallel fashion across as high number of machines in the grid as practically possible.
Ideally the job would be divided into a large amount of “subjobs” that would require as little
communication between each other as possible. These “subjobs” would then be distributed to
resources across the grid by the high level system services. Of course the extent of parallelism
that can be extracted from an application depends highly on the characteristics of the code,
and because of this certain types of workloads are far more suitable for grid computations than
others. The amount of communication required between the “subjobs” tells how “scalable” the
application is. The more scalable an application is the less communication is required and the
more efficiently each subjob will be processed. However writing efficient code for grid
computation is a hard task and often requires considerable use of complicated mathematics and
programming tricks to extract good performance. For instance the programmer might want to
implement code algorithms that counter intuitively takes more processing power to process a
certain problem, if this measure ensures that the program can run more parallel or scale better
than before. Making these kind of decisions can be very hard as the programmer can only guess
what kind of resources will be available to the finished program on the grid. There are other
sources of performance problems in the grid as well, for instance if many of the subjobs would
need to access a certain storage resource in the grid for data, the network traffic of that
resource might become congested. There are many such potential problems in the grid that the
complicated scheduling software will have to handle properly to keep the grid processing
efficiently.
Security:
Security is rightfully of large concern for grid users. As data is moved around and processed
much more freely than over the Internet it is clear that there needs to be strong protection in
place to prevent that for instance virus can spread along the workloads. There are more grid
specific problems as well, such as preventing other users from examining each others data (data
confidentiality) that is processing remotely on their machines in the grid, or manipulate the
results of such computations (data integrity). The grid solution to data confidentiality problems
is generally the extensive use of encryption techniques. We will not discuss encryption
techniques here as the techniques used in most current grids are similar to those currently in
use on the Internet. Data integrity when especially important is sometimes tested by running
the computations multiple times at different resources. Further, all grid resources are
authenticated (identified) after which they are granted certain permissions or access to
resources within the grid.
 Grid layers:
The software of the grid is often divided into layers to show the layered architecture of the
underlying protocols:
Starting at the bottom we have the
grid fabric that consists of the
distributed resources of the grid
which could be computers, storage
devices databases or even clusters,
supercomputers, sensors or
instruments etc. The range of
hardware has few constraints and is
only defined by the connectivity
protocols used.
Next the security infrastructure
layer provides secure and
authorized access to grid resources
as discussed above.
The core grid middleware performs
middle level tasks between the
resources.
The user level middleware consists of schedulers responsible for aggregating the resources.
Grid programming environments are used by application developers to enable applications to run
on the grid.
At the very top is the Grid Applications which of course constitute the applications that run on
the grid.
SUMMARY
Although one might get the impression that grids might soon replace supercomputers, this is not
exactly true. Although grids represent an interesting new way of harnessing vast amounts of unused
computing power, it is also important to understand the inherent performance limitations of grid
computing. Grids require very complicated control software and many types of software is very hard
or impossible to program to run efficiently on grids. So at least in a shorter perspective grids will
only be able to successfully replace traditional supercomputers in very specific types of tasks. But
there is a lot of grid related activity and development currently going on among research
organizations. Also networking technologies are evolving at a very high pace, so perhaps more
efficient and capable grids might be closer in the future than most expect.
Some anticipate that grid computing will soon start to slowly make its way out onto the Internet and
eventually absorb it. As both grids and the Internet is based on similar hardware and standardised
use of protocols it is likely that grid elements will be introduced as additional protocols and services
that extend the ones currently in use on the Internet. As networking, virtualization and security
technology continues to evolve many of the problems inherent in the current generation of grids
could be solved and the possibility of another “Internet revolution” based on grid services seems
possible.
SOURCES
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This article by Ted Smalley Bowen appeared in the Technology Review News, September 12, 2001.
IBM’s Grid Computing website: http://www-136.ibm/ibm/developerworks/grid
The Grid: A new infrastructure for 21 century science, physics today, February 2002
Globus website www.globus.org
Introduction to Grid computing with Globus, IBM redbook:
http://www.redbooks.ibm.com/abstracts/sg246895.html