SMP (Symmetric Multi-Processors) hardware technologies are very popular
with vendors and end-users alike for a number of reasons. However, true
shared memory parallelism has experienced somewhat slower to take up
amongst the scientific-programming community. NAG has been at the
forefront of SMP technology for a number of years, and the NAG SMP
Library has shown the potential of SMP systems.
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At the very high end, SMP hardware technologies are used as building
blocks of modern supercomputers, which truly consist of clusters of SMP
systems, for which no dedicated model of parallelism yet exists.
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The aim of this talk is to introduce SMP systems and their potential.
Results from our work at NAG will also be introduced to show how SMP
parallelism, based on a shared memory paradigm, can be used to very
good effect and can produce high performance, scalable software. The
talk also aims to discuss some aspects of the apparent slow take up of
shared memory parallelism and the potential competition from PC (i.e.
Intel)-based cluster technology. The talk then aims to explore the
potential of SMP technology within "hybrid parallelism", i.e. mixed
distributed and shared memory modes, illustrating the point with some
preliminary work carried out by the author and others. Finally, a
number of potential future challenges to numerical analysts will be
discussed.
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The talk is aimed at all who are interested in SMP technologies for
numerical computing, irrespective of any previous experience in the
field. The talk aims to stimulate discussion, by presenting some ideas,
backing these with data, not to stifle it in an ocean of detail!