Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization最新文献

In situ particle advection via parallelizing over particles 通过平行于粒子的原位粒子平流

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364235

R. Binyahib, D. Pugmire, H. Childs

引用次数: 3

The challenges of elastic in situ analysis and visualization 弹性原位分析和可视化的挑战

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364234

Matthieu Dorier, Orcun Yildiz, T. Peterka, R. Ross

引用次数: 11

The impact of work distribution on in situ visualization: a case study 工作分布对现场可视化的影响:一个案例研究

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364233

Tobias Rau, P. Gralka, Oliver Fernandes, G. Reina, S. Frey, T. Ertl

{"title":"The impact of work distribution on in situ visualization: a case study","authors":"Tobias Rau, P. Gralka, Oliver Fernandes, G. Reina, S. Frey, T. Ertl","doi":"10.1145/3364228.3364233","DOIUrl":"https://doi.org/10.1145/3364228.3364233","url":null,"abstract":"Large-scale computer simulations generate data at rates that necessitate visual analysis tools to run in situ. The distribution of work on and across nodes of a supercomputer is crucial to utilize compute resources as efficiently as possible. In this paper, we study two work distribution problems in the context of in situ visualization and jointly assess the performance impact of different variants. First, especially for simulations involving heterogeneous loads across their domain, dynamic load balancing can significantly reduce simulation run times. However, the adjustment of the domain partitioning associated with this also has a direct impact on visualization performance. The exact impact of this side effect is largely unclear a priori as generally different criteria are used for balancing simulation and visualization load. Second, on node level, the adequate allocation of threads to simulation or visualization tasks minimizes the performance drain of the simulation while also enabling timely visualization results. In our case study, we jointly study both work distribution aspects with the visualization framework MegaMol coupled in situ on node level to the molecular dynamics simulation ls1 Mardyn on Stampede2 at TACC.","PeriodicalId":400017,"journal":{"name":"Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115304902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A new approach for in situ analysis in fully coupled earth system models 全耦合地球系统模型的原位分析新方法

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364231

U. Turuncoglu, Baris Önol, M. Ilıcak

{"title":"A new approach for in situ analysis in fully coupled earth system models","authors":"U. Turuncoglu, Baris Önol, M. Ilıcak","doi":"10.1145/3364228.3364231","DOIUrl":"https://doi.org/10.1145/3364228.3364231","url":null,"abstract":"This work focuses on enabling the use of existing in situ analysis and visualization methods within the model coupling framework, which is specially designed software layer to combine physical components of Earth system (i.e., atmosphere, ocean) through a standardized calling interface to simplify common tasks such as interpolation among different numerical grids and synchronization of the model components. The new approach enables simultaneous analysis of the vast amount of data produced by a multi-component Earth system model in an integrated way and facilitates efficient, interoperable, and optimized data analysis and visualization workflows for Earth system science applications. To demonstrate the flexibility and the capability of the new approach, a fully coupled regional atmosphere-ocean modeling application that aims to investigate air-sea interaction in a very high spatial and temporal resolution has been implemented. In the use case application, both the simulation and in situ visualization application run in parallel on a large-scale HPC platform with both software and hardware rendering support through the use of accelerators.","PeriodicalId":400017,"journal":{"name":"Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134181224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HDF5 as a vehicle for in transit data movement HDF5作为传输数据移动的载体

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364237

Junmin Gu, B. Loring, Kesheng Wu, E. W. Bethel

引用次数: 4

In situ adaptive timestep control and visualization based on the spatio-temporal variations of the simulation results 基于仿真结果时空变化的现场自适应时间步长控制与可视化

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364230

Yoshiaki Yamaoka, Kengo Hayashi, Naohisa Sakamoto, J. Nonaka

{"title":"In situ adaptive timestep control and visualization based on the spatio-temporal variations of the simulation results","authors":"Yoshiaki Yamaoka, Kengo Hayashi, Naohisa Sakamoto, J. Nonaka","doi":"10.1145/3364228.3364230","DOIUrl":"https://doi.org/10.1145/3364228.3364230","url":null,"abstract":"Effective visualization of time-varying volumetric data is considered challenging, since in addition to the traditional visualization parameter selections, there is also the need to take care about the dynamic changings between the timesteps. In situ adaptive sampling based on the amount of change between the simulation timepsteps might be helpful for the I/O and visualization cost savings. In this paper, we propose the use of Kernel Density Estimation (KDE) and Kullback-Leibler (KL) divergence, in order to estimate the amount of internal variations between the timesteps, and use this as a parameter for controlling the sampling rate. Needless to say that these selected timesteps should be sufficient to enable the understanding of the underlying phenomena without missing important data features. We confirmed the effectiveness on reducing the number of timepsteps, by using an OpenFOAM CFD simulation with irregular volume data. However, we could also observe that the user-defined parameter selection can highly influence the amount of data size reduction as well as the smoothness of the visualization results, and an optimal parameter selection method remains as a future work.","PeriodicalId":400017,"journal":{"name":"Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114461021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Interactive in situ visualization and analysis using Ascent and Jupyter 使用Ascent和Jupyter的交互式原位可视化和分析

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364232

Seif Ibrahim, T. Stitt, Matthew Larsen, C. Harrison

{"title":"Interactive in situ visualization and analysis using Ascent and Jupyter","authors":"Seif Ibrahim, T. Stitt, Matthew Larsen, C. Harrison","doi":"10.1145/3364228.3364232","DOIUrl":"https://doi.org/10.1145/3364228.3364232","url":null,"abstract":"There is a gap in interactive in situ solutions for HPC simulations. While we have access to fully-featured visualization UIs through tools like ParaViewCatalyst and VisItLibSim,we lack in situ infrastructure to access more general interactive environments like Jupyter. The Jupyter ecosystem of tools provides a rich paradigm for interactive data analysis and is well-suited to help expand interactive use of in situ. Both the complexity of the Jupyter ecosystem and the security requirements of HPC centers pose challenges to developing software infrastructure that enables direct use of Jupyter in simulation codes. With this work, we developed a system enabling simulations instrumented with Ascent to connect to Jupyter. This system allows simulation users to interact with their data in situ using Jupyter Notebooks. The system combines Ascent's embedded Python filter infrastructure with a Client/Server Jupyter Bridge Kernel to simplify both deployment and security considerations on HPC systems. We describe the design of this system, demonstrate basic usage, and describe a prototype of an Ascent rendering UI built on top of this system.","PeriodicalId":400017,"journal":{"name":"Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115281703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization 实现极端尺度分析和可视化的现场基础设施研讨会论文集

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228

引用次数: 0

In-situ visualization for the large scale computing initiative milestone 大规模计算计划里程碑的现场可视化

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364229

Jeff Mauldin, Thomas J. Otahal, A. Agelastos, S. Domino

引用次数: 1

Spack meets singularity: creating movable in-situ analysis stacks with ease Spack满足奇点:轻松创建可移动的原位分析堆栈

Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2019-11-18 DOI: 10.1145/3364228.3364682

Sergei Shudler, N. Ferrier, J. Insley, M. Papka, S. Rizzi

引用次数: 2