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Low-Overhead in Situ Visualization Using Halo Replay

Publication ,  Conference
Ames, J; Rizzi, S; Insley, J; Patel, S; Hernández, B; Draeger, EW; Randles, A
Published in: 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019
October 1, 2019

In situ visualization and analysis is of increasing importance as the compute and I/O gap further widens with the advance to exascale capable computing. Yet, in situ methods impose resource constraints leading to the difficult task of balancing simulation code performance and the quality of analysis. Applications with tightly-coupled in situ visualization often achieve performance through spatial and temporal downsampling, a tradeoff which risks not capturing transient phenomena at sufficient fidelity. Determining a priori visualization parameters such as sampling rate is difficult without time and resource intensive experimentation. We present a method for reducing resource contention between in situ visualization and stencil codes on heterogeneous systems. This method permits full resolution replay through recording halos and the communication-free reconstruction of interior values uncoupled from the main simulation. We apply this method in the computational fluid dynamics (CFD) code HARVEY [1] on the Summit supercomputer. We demonstrate minimal-overhead, in situ visualization relative to simulation alone, and compare the Halo Replay performance to tightly-coupled in situ approaches.

Duke Scholars

Published In

2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019

DOI

ISBN

9781728126050

Publication Date

October 1, 2019

Start / End Page

16 / 26
 

Citation

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Ames, J., Rizzi, S., Insley, J., Patel, S., Hernández, B., Draeger, E. W., & Randles, A. (2019). Low-Overhead in Situ Visualization Using Halo Replay. In 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019 (pp. 16–26). https://doi.org/10.1109/LDAV48142.2019.8944265
Ames, J., S. Rizzi, J. Insley, S. Patel, B. Hernández, E. W. Draeger, and A. Randles. “Low-Overhead in Situ Visualization Using Halo Replay.” In 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019, 16–26, 2019. https://doi.org/10.1109/LDAV48142.2019.8944265.
Ames J, Rizzi S, Insley J, Patel S, Hernández B, Draeger EW, et al. Low-Overhead in Situ Visualization Using Halo Replay. In: 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019. 2019. p. 16–26.
Ames, J., et al. “Low-Overhead in Situ Visualization Using Halo Replay.” 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019, 2019, pp. 16–26. Scopus, doi:10.1109/LDAV48142.2019.8944265.
Ames J, Rizzi S, Insley J, Patel S, Hernández B, Draeger EW, Randles A. Low-Overhead in Situ Visualization Using Halo Replay. 2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019. 2019. p. 16–26.

Published In

2019 IEEE 9th Symposium on Large Data Analysis and Visualization, LDAV 2019

DOI

ISBN

9781728126050

Publication Date

October 1, 2019

Start / End Page

16 / 26