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Performance Characterization for Fusion Co-design Applications

  • Author(s): Narayanan, P;
  • Koniges, A;
  • Oliker, L;
  • Preissl, R;
  • Williams, S;
  • Wright, N;
  • Umansky, M;
  • Xu, X;
  • Ethier, S;
  • Wang, W;
  • Candy, J;
  • Cary, J
  • et al.
Abstract

ABSTRACT: Magnetic fusion is a long-term solution for producing electrical power for the world, and the large thermonuclear international device (ITER) being constructed will produce net energy and a path to fusion energy provided the computer modeling is accurate. To effectively address the requirements of the high-end fusion simulation community, application developers, algorithm designers, and hardware architects must have reliable simulation data gathered at scale for scientifically valid configurations. This paper presents detailed benchmarking results for a set of magnetic fusion applications with a wide variety of underlying mathematical models including both particle-in-cell and Eulerian codes using both implicit and explicit numerical solvers. Our evaluation on a petascale Cray XE6 platform focuses on profiling these simulations at scale identifying critical performance characteristics, including scalability, memory/network bandwidth limitations, and communication overhead. Overall results are a key in improving fusion code design, and are a critical first step towards exascale hardware-software co-design — a process that tightly couples applications, algorithms, imple- mentation, and computer architecture.

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