Annual Conference: Communicating Process Architectures
Communicating Process Architectures 2015,
the 37th. WoTUG conference on concurrent and parallel systems, takes place from
Sunday August 23rd. to Wednesday August 26th. 2015 and is hosted by the
School of Computing,
University of Kent.
Accommodation and evening Fringe sessions will be at
a few minutes walk from the School.
WoTUG provides a forum for the discussion and promotion of concurrency ideas,
tools and products in computer science.
It organises specialist workshops and annual conferences that address
key concurrency issues at all levels of software and hardware granularity.
WoTUG aims to progress the leading state of the art in:
and to stimulate discussion and ideas on the roles concurrency will play in the future:
theory (programming models, process algebra, semantics, ...);
practice (multicore processors and run-times, clusters, clouds, libraries, languages, verification, model checking, ...);
education (at school, undergraduate and postgraduate levels, ...);
applications (complex systems, modelling, supercomputing, embedded systems, robotics, games, e-commerce, ...);
Of course, neither of the above sets of bullets are exclusive.
for the next generation of scalable computer infrastructure (hard and soft) and application,
where scaling means the ability to ramp up functionality (stay in control as complexity increases)
as well as physical metrics (such as absolute performance and response times);
for system integrity (dependability, security, safety, liveness, ...);
for making things simple.
A database of papers and presentations from WoTUG conferences is here.
The Abstract below has been randomly selected from this database.
Performance modelling of a parallel meural network simulator
A model program structure is presented for parallel applications with local interactions between the data elements, such as neural networks simulations and the solution of partial differential equations. The performance of this model program is analyzed both theoretically by means of classical performance models, and experimentally using a parallel neural network simulator program. The program runs on a Meiko transputer array, and uses the Meiko CSTools libraries for its communications. The comparison of both analyses allows to predict applications performance on new and other machines, and indicate what parts of an application are worth optimizing. Moreover, it is shown that classical theoretical models not always capture the behavior of a real machine.