New Statistical Algorithms for the Analysis of Mass - FU Berlin, FB MI ...

5.1. INTRODUCTION 105
� A node is not exclusively used for the Grid whereas in a cluster it is
completely used by the cluster Application - it follows that even office
computers or laptops can be integrated into a Grid.
� A node can be at any physical location in the whole world as long as it
can connect to the Grid (e.g. by the Internet) whereas they need to be
in the same local network in the cluster case and use the same access
policies (for control reasons).
� Nodes can be added dynamically on demand opposed to a cluster that
usually has a fixed size (until new nodes are bought and manually integrated).
In this project we have focused on the Grid approach. In a university
setting this follows almost automatically from the fact that there is usually
a large number of (heterogeneous) computing resources available within the
university or other partner institutes. The resources are idle most of the time.
With the Grid approach resources can be added (when they are unused) or
excluded (when a user starts using them) from the Grid dynamically and even
resources from an existing cluster can be integrated.
However, as pointed out in section 5.1.3 using the power of Grid computing
these days is still very complicated. This is due to quite complex Grid
frameworks needed to be set up and used for the computations. There is still
no easy and quick way to set up such a system crossing organizational borders
to work mutually on a problem. Projects such as SETI@HOME (see section
5.7) have made a remarkable step towards this direction but they are highly
specialized on one particular problem domain. To the best of our knowledge
there is still nothing that allows users to set up a Grid spontaneously and
compute any (suited) large problem on many different resources in an easy
way.
In this thesis we have developed an approach we call the Quasi ad-hoc
Grid fulfilling these requirements. Additionally to the commonly available
functions of a Grid platform, namely
� easily set up a Grid Infrastructure with distributed heterogeneous resources
� integrate thousands of working nodes working mutually together on
(suited) large scale problems (opposed to systems like the SETI@HOME
project where only one particular problem can be analyzed)
it allows users to
� do this almost instantaneously (ad hoc) without the need of installing
client software prior to computation (see section 5.3.3 on page 126)
� use almost any programming language for the computations - even Matlab�(see
section 6.2.5 on page 159)
� use almost any hardware platform - even Sony’s Playstation 3�(see section
6.2.4 on page 158)
� hot deploy new services into an existing structure (see section 5.5.4 on
page 140)