Topic 9: Parallel and Distributed Programming

Description

Developing parallel or distributed applications is a difficult task and it requires adequate programming abstractions and models, efficient design tools, high performance languages and libraries, and experimental validation. This topic provides a forum for presentation of new results and practical experience in this domain. It emphasizes research that facilitates the design and development of high-performance, correct, portable, and scalable parallel programs.

Related to these central needs, we also welcome contributions that assess programming abstractions, models and methods for reusability, performance prediction, scalability, self-adaptation, rapid prototyping and fault-tolerance, as needed, for instance, in dynamic heterogeneous parallel and distributed infrastructures. We urge authors to include quantitative evaluations to substantiate their claims.

Focus

  • Innovative paradigms, programming models, languages and libraries for parallel and distributed applications
  • Programming paradigms for novel infrastructures like accelerators, exascale systems and Clouds
  • Design and implementation, performance analysis and performance portability of programming models across parallel and distributed platforms
  • Programming models and techniques for heterogeneity, self-adaptation and fault tolerance
  • Programming tools for application design, implementation, and performance-tuning
  • Application case-studies for benchmarking and comparative studies of parallel programming models
  • Domain-specific libraries and languages (e.g., for graph algorithms, map-reduce applications, stream processing)
  • Parallel and distributed programming productivity, reusability, and component-based parallel programming

Topic Committee

Global Chair
Henri Bal, Vrije Universiteit Amsterdam, Netherlands

Local Chair
João Luís Sobral, University of Minho, Portugal

Further Members
Ana Varbanescu, University of Amesterdam, Netherlands
Christian Perez, INRIA, ENS-Lyon, France
Fabrice Huet, University of Nice Sophia Antipolis, France
Marco Danelutto, University of Pisa, Italy
Peter Kilpatrick, Queen's University Belfast, UK