Iraqi Kurdistan All in the Timing

Recent Advances in Technology
Supercomputers
for Beginners PART II
LASSE AMUNDSEN, Statoil,
MARTIN LANDRØ and BØRGE ARNTSEN, NTNU Trondheim
Energy companies need ever larger computers. This article
is the second of three articles giving an introduction to
supercomputers . Here, we look at the design of parallel software.
Beta: Software undergoes
beta testing shortly before
it’s released. Beta is Latin
for ‘still doesn’t work’.
Unknown
Most supercomputers are multiple
computers that perform parallel
processing, which is well suited for
modelling, simulating and understanding
many complex, real world phenomena.
Historically, parallel computing has been
considered ‘the high end of computing’,
referring to high capability and high
capacity computing, communication and
storage resources. It has been used to
model difficult problems in many areas of
science and engineering. Today, however,
a greater driving force in the development
of faster computers is provided by
commercial applications that require
processing of large amounts of data in
very advanced ways.
Embarrassingly Parallel Solutions
In parallel computing the problem
is divided up among a number of
processors. The figure opposite shows
the basic computer layout.
The art of parallel programming
is identifying the part of the problem
which can be efficiently parallelised. In
many cases this can be straightforward
and simple, such as in the processing
of seismic data. Seismic data consists
of a (large) number of records, and very
often a single or a small number of
records can be processed independently.
A simplistic example of this kind of
processing is the application of various
filter operations. The problem is solved
by distributing a small number of records
to each processor which performs the
filtering. This is usually refered to as an
embarrassingly parallel solution and, as
the name suggests, does not require much
sophistication, but a suprisingly large
number of problems can be solved by
this approach. The gain in computer time
needed to solve this kind of problem can
be measured by the speedup, which is the
ratio of computer time needed to solve
the problem using a single processor to
the time needed to solve the problem on
N processors. For embarrassingly parallel
problems the speedup is largely equal to
the number of processors used. If each
filter operation takes 0.001 second and we
want to filter one million records, then a
single processor would use 1,000 seconds,
while a small supercomputer system
with 1,000 processors would need only
one second. This way of solving parallel
problems is thus highly efficient and
simple to implement.
Message Passing Interface
However, in many cases the problem
at hand cannot be split into completely
Titan is a supercomputer built by Cray at Oak Ridge National Laboratory. In November 2012, Titan held
number one position on the TOP500 list with 18,688 nodes and 552,960 processors. It relies on a combination
of GPUs and traditional CPUs to make it today the world’s second most powerful supercomputer, with peak
performance of more than 27 petaflops. Titan also has more than 700 terabytes of memory.
30 GEOExPro November 2015