High Performance Linux Clusters with OSCAR, Rocks, OpenMosix, and MPI [Electronic resources] نسخه متنی

2.3 Architecture and Cluster Software

Once
you have established the mission for your cluster, you can focus on
its architecture and select the software. Most high-performance
clusters use an architecture similar to that shown in Figure 1-5. The software described in this book is
generally compatible with that basic architecture. If this does not
match the mission of your cluster, you still may be able to use many
of the packages described in this book, but you may need to make a
few adaptations.

Putting together a cluster involves the selection of a variety of
software. The possibilities are described briefly here. Each is
discussed in greater detail in subsequent chapters in this book.

2.3.1 System Software

One of the first selections
you will probably want to make is the operating system, but this is
actually the final software decision you should make. When selecting
an operating system, the fundamental question is compatibility. If
you have a compelling reason to use a particular piece of software
and it will run only under a single operating system, the choice has
been made for you. For example, openMosix uses extensions to the
Linux kernel, so if you want openMosix, you must use Linux. Provided
the basic issue of compatibility has been met, the primary reasons to
select a particular operating system are familiarity and support.
Stick with what you know and what's supported.

All the software described in this
book is compatible with Linux. Most, but not all, of the software
will also work nicely with other Unix systems. In this book,
we'll be assuming the use of Linux. If
you'd rather use BSD or Solaris,
you'll probably be OK with most of the software, but
be sure to check its compatibility before you make a commitment. Some
of the software, such as MPICH, even works with Windows.

There is a natural human tendency to want to go with the latest
available version of an operating system, and there are some obvious
advantages to using the latest release. However, compatibility should
drive this decision as well. Don't expect clustering
software to be immediately compatible with the latest operating
system release. Compatibility may require that you use an older
release. (For more on Linux, see Chapter 4.)

In addition to the operating system itself, you may need additional
utilities or extensions to the basic services provided by the
operating system. For example, to create a cluster
you'll need to install the operating system and
software on a large number of machines. While you could do this
manually with a small cluster, it's an error-prone
and tedious task. Fortunately, you can automate the process with
cloning software. Cloning is described in detail in Chapter 8.

High-performance systems frequently require extensive I/O. To
optimize performance, parallel file systems may be used. Chapter 12 looks at the Parallel Virtual
File System (PVFS), an open source
high-performance file system.

2.3.2 Programming Software

There are two basic decisions
you'll need to make with respect to programming
softwarethe programming languages you want to support and the
libraries you want to use. If you have a small user base, you may be
able to standardize on a single language and a single library. If you
can pull this off, go for it; life will be much simpler. However, if
you need to support a number of different users and applications, you
may be forced to support a wider variety of programming software.

The
parallel programming libraries provide
a mechanism that allows you to easily coordinate computing and
exchange data among programs running on the cluster. Without this
software, you'll be forced to rely on operating
system primitives to program your cluster. While it is certainly
possible to use sockets to build parallel programs, it is a lot more
work and more error prone. The most common libraries are the

Message Passing Interface
(MPI) and

Parallel
Virtual Machine (PVM) libraries.

The choice of program languages depends on the parallel libraries you
want to use. Typically, the libraries provide bindings for only a
small number of programming languages. There is no point in
installing Ada if you can't link it to the parallel
library you want to use. Traditionally, parallel programming
libraries support C and FORTRAN, and C++ is growing in popularity.
Libraries and languages are discussed in greater detail in Chapter 9.

2.3.3 Control and Management

In addition to the
programming software, you'll need to keep your
cluster running. This includes scheduling and management software.

Cluster management includes both routine system administration tasks
and monitoring the health of your cluster. With a cluster, even a
simple task can become cumbersome if it has to be replicated over a
large number of systems. Just checking which systems are available
can be a considerable time sink if done on a regular basis.
Fortunately, there are several packages that can be used to simplify
these tasks. Cluster Command and Control
(C3) provides a
command-line interface that extends across a cluster, allowing easy
replication of tasks on each machine in a cluster or on a subset of
the cluster.
Ganglia
provides web-based monitoring in a single interface. Both C3 and
Ganglia can be used with federated clusters as well as simple
clusters. C3 and Ganglia are described in Chapter 10.

Scheduling software determines when your users' jobs
will be executed. Typically,
scheduling software can allocate
resources, establish priorities, and do basic accounting. For Linux
clusters there are two likely
choices

Condor and

Portable
Batch System (PBS) . If you have needs for an advanced
scheduler, you might also consider

Maui . PBS is
available as a commercial product, PBSPro, and
as open source software, OpenPBS. OpenPBS is
described in Chapter 11.