IO for Data Management in Multi-physics Simulations

Date and Time: 
2013 Monday, April 1
CG1 Auditoriums
William W. Dai

Authors: William W. Dai

A library for parallel IO and data management has been developed for multi-physics simulations. The goal of the library is to provide sustainable, interoperable, efficient, scalable, and convenient tools for parallel IO and data management for high-level data structures in numerical simulations, and to provide tools for the connection between applications. The high-level data structures include one- and multi-dimensional arrays, structured meshes, unstructured meshes, the meshes generated through (block-based, patch-based, and cell-based) adaptive mesh refinement, variables associated with these meshes, and data defined on particles in particle simulations. The IO mechanism can be collective and non-collective. The library is typically used for restarting files, visualization files, and files connecting different applications. The library is based on MPI-IO. Compared with the IO performance of MPI-IO, the overhead to write the explicit users’ data structures are less than five percent. To further improve IO performance, in addition to the bookkeeping data, the library could buffer problem-size data before calling MPI-IO while keeping users’ explicit high-level data structures. The buffering mechanism improves IO performance by a factor 10 to 20 in multi-physics simulations involving AMR and unstructured meshes.

Speaker Description: 

William Dai received his Ph.D. degree in physics in University of Minnesota in 1993. After that he joined Laboratory for Computational Science and Engineering as a research scientist in the University, focusing on numerical methods for hydrodynamics, magnetohydrodynamics, radiation, and diffusion. William joined the Los Alamos National Laboratory in 2001 as a staff member in High Performance Computing Division. In 2002 he became a team leader and project leader responsible for software development and their integration to several multi-physics codes. Currently, William is a scientist in Computer, Computational, and Statistical Sciences Division, and he is one of the key developers of a large-scale multi-physics code, responsible for new physics capabilities, numerical solvers, and modernization of the code on future computer platforms.

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