Evaluation of methods to integrate analysis into a large-scale shock shock physics code

Abstract

Exascale supercomputing will embody many revolutionary changes in the hardware and software of high-performance computing. For example, projected limitations in power and I/O-system performance will fundamentally change visualization and analysis workflows. A traditional post-processing workflow involves storing simulation results to disk and later retrieving them for visualization and data analysis; however, at Exascale, post-processing approaches will not be able to capture the volume or granularity of data necessary for analysis of these extreme-scale simulations. As an alternative, researchers are exploring ways to integrate analysis and simulation without using the storage system. In situ and in transit are two options, but there has not been an adequate evaluation of these approaches to identify strengths, weaknesses, and trade-offs at large scale. This paper provides a detailed performance and scaling analysis of a large-scale shock physics code using traditional post-processsing, in situ, and in transit analysis to detect material fragments from a simulated explosion.

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