Information Technology Reference
In-Depth Information
INTRODUCTION
Grid production environment. The simpler the
Grid infrastructure, and the easier to use, and the
sharper its focus, the bigger is its chance for suc-
cess. And it is for a good reason (which we will
explain in the following) that currently Clouds
are becoming more and more popular (Amazon,
2007 and 2010).
Over the last ten years, hundreds of applica-
tions in science, industry and enterprises have
been ported to Grid infrastructures, mostly pro-
totypes in the early definition of Foster & Kes-
selman (1998). Each application is unique in that
it solves a specific problem, based on modeling,
for example, a specific phenomenon in nature
(physics, chemistry, biology, etc.), presented as
a mathematical formula together with appropri-
ate initial and boundary conditions, represented
by its discrete analogue using sophisticated nu-
merical methods, translated into a programming
language computers can understand, adjusted to
the underlying computer architecture, embedded
in a workflow, and accessible remotely by the user
through a secure, transparent and application-
specific portal. In just these very few words, this
summarizes the wide spectrum and complexity we
face in problem solving on Grid infrastructures.
The user (and especially the developer) faces
several layers of complexity when porting applica-
tions to a computing environment, especially to
a compute or data Grid of distributed networked
nodes ranging from desktops to supercomputers.
These nodes, usually, consist of several to many
loosely or tightly coupled processors and, more and
more, these processors contain few to many cores.
To run efficiently on such systems, applications
have to be adjusted to the different layers, taking
into account different levels of granularity, from
fine-grain structures deploying multi-core archi-
tectures at processor level to the coarse granularity
found in application workflows representing for
example multi-physics applications. Not enough,
the user has to take into account the specific re-
quirements of the grid, coming from the different
components of the Grid services architecture, such
Over the last 40 years, the history of computing
is deeply marked of the affliction of the applica-
tion developers who continuously are porting and
optimizing their applications codes to the latest
and greatest computing architectures and environ-
ments. After the von-Neumann mainframe came
the vector computer, then the shared-memory
parallel computer, the distributed-memory par-
allel computer, the very-long-instruction word
computer, the workstation cluster, the meta-
computer, and the Grid (never fear, it continues,
with SOA, Cloud, Virtualization, Many-core, and
so on). There is no easy solution to this, and the
real solution would be a separation of concerns
between discipline-specific content and domain-
independent software and hardware infrastructure.
However, this often comes along with a loss of
performance stemming from the overhead of the
infrastructure layers. Recently, users and devel-
opers face another wave of complex computing
infrastructures: the Grid.
Let's start with answering the question: What
is a Grid? Back in 1998, Ian Foster and Carl
Kesselman (1998) attempted the following defi-
nition: “A computational Grid is a hardware and
software infrastructure that provides dependable,
consistent, pervasive, and inexpensive access to
high-end computational capabilities.” In a sub-
sequent article (Foster, 2002), “The Anatomy of
the Grid,” Ian Foster, Carl Kesselman, and Steve
Tuecke changed this definition to include social
and policy issues, stating that Grid computing is
concerned with “coordinated resource sharing and
problem solving in dynamic, multi-institutional
virtual organizations.” The key concept is the
ability to negotiate resource-sharing arrangements
among a set of participating parties (providers
and consumers) and then to use the resulting
resource pool for some purpose. This definition
seemed very ambitious, and as history has proven,
many of the Grid projects with a focus on these
ambitious objectives did not lead to a sustainable
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