Scalable computing with parallel tasks

  • Authors:

  • Jörg Dümmler;Thomas Rauber;Gudula Rünger

  • Affiliations:

  • Chemnitz University of Technology, Chemnitz, Germany;Bayreuth University, Bayreuth, Germany;Chemnitz University of Technology, Chemnitz, Germany

  • Venue:
  • Proceedings of the 2nd Workshop on Many-Task Computing on Grids and Supercomputers
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recent and future parallel clusters and supercomputers use SMPs and multi-core processors as basic nodes, providing a huge amount of parallel resources. These systems often have hierarchically structured interconnection networks combining computing resources at different levels, starting with the interconnect within multi-core processors up to the interconnection network combining nodes of the cluster or supercomputer. The challenge for the programmer is that these computing resources should be utilized efficiently by exploiting the available degree of parallelism of the application programs and by structuring the application in a way which is sensitive to the heterogeneous interconnect. In this article, we present an approach to structure the computations of an application as parallel tasks which can interact with other parallel tasks in communication phases. In particular, we consider how these parallel tasks can be mapped onto the computing resources provided by parallel clusters or supercomputers. We show that the scalability can be significantly improved by a suitable task-based organization and a corresponding structuring of the communication within tasks as well as between tasks. We evaluate the impact of different mappings of tasks to cores for different application programs on a variety of parallel machines.