Abstract In the coming era of exascale supercomputing, in-situ visualization will be a crucial approach for reducing the output data size. A problem of in-situ visualization is that it loses interactivity if a steering method is not adopted. In this paper, we propose a new method for the interactive analysis of in-situ visualization images produced by a batch simulation job. A key idea is to apply numerous (thousands to millions) in-situ visualizations simultaneously. The viewer then analyzes the image database interactively during postprocessing. If each movie can be compressed to 100 MB, one million movies will only require 100 TB, which is smaller than the size of the raw numerical data in exascale supercomputing. We performed a feasibility study using the proposed method. Multiple movie files were produced by a simulation and they were analyzed using a specially designed movie player. The user could change the viewing angle, the visualization method, and the parameters interactively by retrieving an appropriate sequence of images from the movie dataset.
Many in-situ visualizations, with or without steering, have been designed and developed for particular simulation problems. However, general visualization frameworks with high parallel scalability have also become available recently. @cite_7 developed a library that facilitates in-situ visualizations using VisIt, which is one of the most sophisticated parallel visualization tools available today. Their paper also contained a concise review of the history and the latest status of the in-situ visualization research. @cite_1 reported the development of a coprocessing library for , which is another sophisticated parallel visualization tool. Using that library, it is possible to utilize the various visualization functions provided by during runtime, which is decoupled from the simulation. The latest case studies of in-situ visualization using and can be found in @cite_5 .
@cite_5 @cite_1 @cite_7
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As high performance computing approaches exascale, CPU capability far outpaces disk write speed, and in situ visualization becomes an essential part of an analyst's workflow. In this paper, we describe the ParaView Coprocessing Library, a framework for in situ visualization and analysis coprocessing. We describe how coprocessing algorithms (building on many from VTK) can be linked and executed directly from within a scientific simulation or other applications that need visualization and analysis. We also describe how the ParaView Coprocessing Library can write out partially processed, compressed, or extracted data readable by a traditional visualization application for interactive post-processing. Finally, we will demonstrate the library's scalability in a number of real-world scenarios. There is a widening gap between compute performance and the ability to store computation results. Complex scientific codes are the most affected since they must save massive files containing meshes and fields for offline analysis. Time and storage costs instead dictate that data analysis and visualization be combined with the simulations themselves, being done in situ so data are transformed to a manageable size before they are stored. Earlier approaches to in situ processing involved combining specific visualization algorithms into the simulation code, limiting flexibility. We introduce a new library which instead allows a fully-featured visualization tool, VisIt, to request data as needed from the simulation and apply visualization algorithms in situ with minimal modification to the application code.