Hierarchical task mapping of cell-based AMR cosmology simulations

  • Authors:

  • Jingjin Wu;Zhiling Lan;Xuanxing Xiong;Nickolay Y. Gnedin;Andrey V. Kravtsov

  • Affiliations:

  • Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL;Illinois Institute of Technology, Chicago, IL;Fermi National Accelerator Laboratory, Batavia, IL and The University of Chicago, Chicago, IL;The University of Chicago, Chicago, IL

  • Venue:
  • SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
  • Year:
  • 2012

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Abstract

Cosmology simulations are highly communication-intensive, thus it is critical to exploit topology-aware task mapping techniques for performance optimization. To exploit the architectural properties of multiprocessor clusters (the performance gap between inter-node and intra-node communication as well as the gap between inter-socket and intra-socket communication), we design and develop a hierarchical task mapping scheme for cell-based AMR (Adaptive Mesh Refinement) cosmology simulations, in particular, the ART application. Our scheme consists of two parts: (1) an inter-node mapping to map application processes onto nodes with the objective of minimizing network traffic among nodes and (2) an intra-node mapping within each node to minimize the maximum size of messages transmitted between CPU sockets. Experiments on production supercomputers with 3D torus and fat-tree topologies show that our scheme can significantly reduce application communication cost by up to 50%. More importantly, our scheme is generic and can be extended to many other applications.