SCHEDULE: NOV 10-16, 2012
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Hierarchical Task Mapping of Cell-Based AMR Cosmology Simulations
SESSION: Cosmology Applications
EVENT TYPE: Papers
TIME: 11:30AM - 12:00PM
SESSION CHAIR: Subhash Saini
AUTHOR(S):Jingjin Wu, Zhiling Lan, Xuanxing Xiong, Nickolay Y. Gnedin, Andrey V. Kravtsov
ROOM:255-EF
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.
Chair/Author Details:
Subhash Saini (Chair) - NASA Ames Research Center
Jingjin Wu - Illinois Institute of Technology
Zhiling Lan - Illinois Institute of Technoloy
Xuanxing Xiong - Illinois Institute of Technology
Nickolay Y. Gnedin - Fermi National Laboratory
Andrey V. Kravtsov - University of Chicago
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Hierarchical Task Mapping of Cell-Based AMR Cosmology Simulations
SESSION: Cosmology Applications
EVENT TYPE:
TIME: 11:30AM - 12:00PM
SESSION CHAIR: Subhash Saini
AUTHOR(S):Jingjin Wu, Zhiling Lan, Xuanxing Xiong, Nickolay Y. Gnedin, Andrey V. Kravtsov
ROOM:255-EF
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.
Chair/Author Details:
Subhash Saini (Chair) - NASA Ames Research Center
Jingjin Wu - Illinois Institute of Technology
Zhiling Lan - Illinois Institute of Technoloy
Xuanxing Xiong - Illinois Institute of Technology
Nickolay Y. Gnedin - Fermi National Laboratory
Andrey V. Kravtsov - University of Chicago
Click here to download .ics calendar file