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Published November 2009 | public
Book Section - Chapter

Plasma fusion code coupling using scalable I/O services and scientific workflows

Abstract

In order to understand the complex physics of mother nature, physicist often use many approximations to understand one area of physics and then write a simulation to reduce these equations to ones that can be solved on a computer. Different approximations lead to different equations that model different physics, which can often lead to a completely different simulation code. As computers become more powerful, scientists can either write one simulation that models all of the physics or they produce several codes each for different portions of the physics and then 'couple' these codes together. In this paper, we concentrate on the latter, where we look at our code coupling approach for modeling a full device fusion reactor. There are many approaches to code coupling. Our first approach was using Kepler workflows to loosely couple three codes via files (memory-to-disk-to-memory coupling). This paper describes our new approach moving towards using memory-to-memory data exchange to allow for a tighter coupling. Our approach focuses on a method which brings together scientific workflows along with staging I/O methods for code coupling. Staging methods use additional compute nodes to perform additional tasks such as data analysis, visualization, and NxM transfers for code coupling. In order to transparently allow application scientist to switch from memory to memory coupling to memory to disk to memory coupling, we have been developing a framework that can switch between these two I/O methods and then automate other workflow tasks. Our hybrid approach allows application scientist to easily switch between in-memory coupling and file-based coupling on-the-fly, which aids debugging these complex configurations.

Additional Information

© 2009 ACM. This work is part of the ongoing research activities within the Center for Plasma Edge Simulation (CPES), a SciDAC Fusion Si mulation Prototype center that is supported by the Office of Fusion Energy Sciences and the Office of Advanced Scientific Computing Research within the US Department of Energy. We are grateful to the National Center for Computational Science at Oak Ridge National Laboratory for access to and support of their computing resources. We thank to the Scientific Data Management (SDM) Center, another SciDAC center, which supports the development of Kepler and developed the Kepler Provenance Framework. We thank Zhih ong Lin and Yong Xiao, in the GPSC and GSEP projects, and Michael Booth from Sun Microsystems.

Additional details

Created:
August 19, 2023
Modified:
October 23, 2023