Abstract
Although K computer has been operational for more than five years, it is still ranked in the top 10 of the Top500 list, and in active use, especially in Japan. One of the peculiarity of this system is the use of SPARC64fx CPU, with no instruction set compatibility with other traditional CPU architecture, and the use of a two-staged parallel file system, where the necessary data is moved from the user accessible GFS (Global File System) to a faster LFS (Local File System) for enabling high performance I/O during the simulation run. Since the users have no access to the data during the simulation run, the tightly coupled (co-processing) in-situ visualization approach seems to be the most suitable approach for this HPC system. For the visualization purposes, the hardware developer (Fujitsu) did not provide or support the traditional Mesa 3D graphics library on their SPARC64fx CPU, and in exchange, it provided a non-OSS (Open Source Software) and non-OpenGL visualization library with Particle-Based Volume Rendering (PBVR) implementation, including an API for in-situ visualization. In order to provide a more traditional in-situ visualization alternative for the K computer users, we focused on the Mesa 3D graphics library, and on an OpenGL-based KVS (Kyoto Visualization System) library. We expect that this approach can also be useful on other SPARC64fx HPC environments because of the binary compatibility.
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Acknowledgement
Some of the results were obtained using the K computer at RIKEN Center for Computational Science (R-CCS) in Kobe, Japan. This work is partially supported by the “Joint Usage/Research Center for Interdisciplinary Large-scale Information Infrastructures” in Japan (Project ID: jh180060-NAH), JSPS KAKENHI Grant Number JP17K00169 and Social Implementation Program on Climate Change Adaptation Technology (SI-CAT) from the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan.
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Hayashi, K., Sakamoto, N., Nonaka, J., Matsuda, M., Shoji, F. (2018). An In-Situ Visualization Approach for the K Computer Using Mesa 3D and KVS. In: Yokota, R., Weiland, M., Shalf, J., Alam, S. (eds) High Performance Computing. ISC High Performance 2018. Lecture Notes in Computer Science(), vol 11203. Springer, Cham. https://doi.org/10.1007/978-3-030-02465-9_21
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