This topic provides a forum for the
presentation of the latest research results and practical experience in the
development of parallel programs. Advances in algorithmic and programming
models, design methods, languages, and interfaces are needed to produce
correct, portable parallel software with predictable performance on different
parallel and distributed architectures.
The topic emphasises results that improve the
process of developing high-performance programs, including high-integrity
programs that are scalable with both problem size and complexity. Of
particular interest are novel techniques by which parallel software can be
assembled from reusable parallel components without compromising efficiency.
Related to this is the need for parallel software to adapt, both to available
resources and to the problem being solved.
appropriate, contributions should demonstrate quantitative performance
results in support of their claims, and address applications not adequately
handled by well-established approaches.
libraries and interfaces for different parallel programming models
(e.g. data-parallelism, task-parallelism, functional, object-oriented,
logic, component-based, etc.).
and optimisation techniques for innovative parallel languages and
programming models (e.g. threads, dataflow, tiling, skeletons,
declarative languages, and generalised data-parallel approaches, etc.).
models and their integration into the design of efficient parallel
algorithms and programs (e.g. BSP, LogP, CGM, N-half and their
alternatives, cost calculi and static performance prediction,
programming paradigms and tools, their comparison and integration (e.g.
data-parallel vs. task-parallel, coordination programming, performance
analysis and debugging).
aspects of developing, optimizing and validating parallel programs
(formalisms, semantics, specification, design, transformations,
- Software engineering
for parallel and distributed systems (design patterns, portability,
robustness, standardization, etc.).
approaches and programming models to support effective program development
in grid environments.
parallel libraries and languages (e.g. for simulation, irregular and
unstructured meshes, computational geometry, etc.).
Prof. José C. Cunha
New University of Lisbon, Portugal
Dr. Christoph Herrmann
Universität Passau, Germany