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ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization最新文献

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Automated In Situ Computational Steering Using Ascent’s Capable Yes-No Machine 自动原位计算转向使用上升的能力是-否机器
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-15 DOI: 10.1145/3490138.3490144
Margaret Lawson, C. Harrison, E. Brugger, A. Skinner, Matthew Larsen
{"title":"Automated In Situ Computational Steering Using Ascent’s Capable Yes-No Machine","authors":"Margaret Lawson, C. Harrison, E. Brugger, A. Skinner, Matthew Larsen","doi":"10.1145/3490138.3490144","DOIUrl":"https://doi.org/10.1145/3490138.3490144","url":null,"abstract":"The life of a multi-physics code user is complicated. Simulation crashes, efficient resource utilization, and simulation parameter choices are time consuming workflow issues that increase a user’s iteration time. Simulations often don’t provide general tools to support automatically adapting workflows to the diverse set of problems that multi-physics codes are capable of simulating. In situ visualization and analysis infrastructures are designed to be general. They are repositories of shared capability that support multiple simulation codes. Normally, the connection between simulation and in situ analysis is unidirectional (e.g., render an image or querying the mesh). In this work, we close the loop between an in situ infrastructure and a simulation, and we explore opportunities to leverage in situ triggers for automatic computational steering at runtime. We demonstrate using Ascent’s in situ trigger interface as a capable yes-no machine for controlling simulation choices.","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124825603","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
Developing and Evaluating In Situ Visualization Algorithms using Containers 基于容器的现场可视化算法的开发与评价
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-15 DOI: 10.1145/3490138.3490141
Michael Will, Quincy Wofford, J. Patchett, David Rogers, Jonas Lukasczyk, C. Garth
{"title":"Developing and Evaluating In Situ Visualization Algorithms using Containers","authors":"Michael Will, Quincy Wofford, J. Patchett, David Rogers, Jonas Lukasczyk, C. Garth","doi":"10.1145/3490138.3490141","DOIUrl":"https://doi.org/10.1145/3490138.3490141","url":null,"abstract":"Fundamental research into in situ visualization and analysis techniques is difficult to access for visualization researchers due to the overwhelming complexity and effort of constructing and managing in situ software stacks that allow reproducible evaluation of novel in situ visualization and analysis techniques. To address this problem, we describe EZ-ISAV, a work-in-progress towards a framework for easy construction of customizable in situ pipelines in container images. Designed for portability and ease of use, these images are intended to serve as proof-of-concept cases for in situ visualization and analysis research. Furthermore, we describe the EZ-ISAV repository, an open repository of turn-key, ready-made container images that can strongly reduce the overhead of developing and evaluating in situ techniques and provide improved reproducibility and portability of in situ visualization research.","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127944369","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
3D CFD In-situ Co-processing for Turbomachinery Design 涡轮机械设计的三维CFD原位协同处理
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138.3498572
A. Gerstenberger
{"title":"3D CFD In-situ Co-processing for Turbomachinery Design","authors":"A. Gerstenberger","doi":"10.1145/3490138.3498572","DOIUrl":"https://doi.org/10.1145/3490138.3498572","url":null,"abstract":"","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128639335","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
In-Situ Spatial Inference on Climate Simulations with Sparse Gaussian Processes 稀疏高斯过程气候模拟的原位空间推理
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138.3490140
M. Grosskopf, E. Lawrence, Ayan Biswas, Li Tang, Kelin Rumsey, L. V. Roekel, N. Urban
{"title":"In-Situ Spatial Inference on Climate Simulations with Sparse Gaussian Processes","authors":"M. Grosskopf, E. Lawrence, Ayan Biswas, Li Tang, Kelin Rumsey, L. V. Roekel, N. Urban","doi":"10.1145/3490138.3490140","DOIUrl":"https://doi.org/10.1145/3490138.3490140","url":null,"abstract":"As extreme-scale physics simulation becomes increasingly memory and storage expensive, the ability to access full simulation data for statistical analysis is becoming increasingly limited. The capability to perform in-situ statistical inference of state variables is becoming increasingly important for the comprehensive utilization of the huge amounts of information generated by these simulations. In this work, we report the first results fitting scalable Gaussian process regression to the state information of an expensive simulation in-situ. For this, spatial regression of upper atmosphere temperature data was performed using Julia coupled to the E3SM climate model. The resulting sparse Gaussian process model shows strong predictive performance using a small number of representative observations. These results provide the backbone for more general in-situ spatial inference with Gaussian process models in complex physics simulations.","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117328671","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
In Situ Climate Modeling for Analyzing Extreme Weather Events 分析极端天气事件的原位气候模式
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138.3490142
Soumya Dutta, Natalie Klein, L. Tang, J. Wolfe, L. V. Roekel, J. Benedict, Ayan Biswas, E. Lawrence, N. Urban
{"title":"In Situ Climate Modeling for Analyzing Extreme Weather Events","authors":"Soumya Dutta, Natalie Klein, L. Tang, J. Wolfe, L. V. Roekel, J. Benedict, Ayan Biswas, E. Lawrence, N. Urban","doi":"10.1145/3490138.3490142","DOIUrl":"https://doi.org/10.1145/3490138.3490142","url":null,"abstract":"The study of many extreme weather events requires simulations with high spatiotemporal data that can grow in size quickly. Storing all the raw data from such a large-scale simulation for traditional post hoc analyses is soon going to be prohibitive as the data generation speed is outpacing the data storage capability in supercomputers. In situ analysis has emerged as a solution to this problem; data is analyzed when it is being produced, bypassing the slower disk input/output (I/O). In this work, we develop a new in situ analysis pathway for Energy Exascale Earth System Model (E3SM) and propose an algorithm for analyzing the impacts of sudden stratospheric warmings (SSWs), which can cause extreme cold temperature outbreaks at the surface, resulting in hazardous weather and disrupting many socioeconomic sectors. We detect SSWs and model the surface temperature data distributions in situ and show that post hoc analysis using the distribution models can predict the impact of SSWs in the continental United States.","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130158098","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: 1
Lightweight Interface for In Situ Analysis and Visualization of Particle Data 用于粒子数据原位分析和可视化的轻量级接口
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138.3490143
Pascal Grosset, J. Ahrens
{"title":"Lightweight Interface for In Situ Analysis and Visualization of Particle Data","authors":"Pascal Grosset, J. Ahrens","doi":"10.1145/3490138.3490143","DOIUrl":"https://doi.org/10.1145/3490138.3490143","url":null,"abstract":"As simulations get larger and produce more data, domain scientists are increasingly using in situ methods to analyze and visualize data as they are being produced. Most tools for in situ, which allow domain scientists to monitor their simulations, such as ParaView Catalyst and VisIt Libsim, tend to be bulky and require the scientist to request and wait for compute nodes or download full datasets (of the order of terabytes or petabytes) on desktops/laptops for analysis. In this paper, we present a very lightweight framework that allows users to visualize snapshots of a simulation without having to request additional compute nodes from a supercomputer when analysis or visualization is needed or download full datasets. We extend the Seer framework, an open-source in situ framework, to sub-sample and store simulation data, which can then be accessed and manipulated from the user’s local machine using a dashboard created using Plotly’s Dash interface.","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116640640","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: 1
LOOM: Interweaving tightly coupled visualization and numeric simulation framework 交织紧密耦合的可视化和数值模拟框架
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138.3490139
J. Barbosa, P. Navrátil, Luís Paulo Santos, D. Fussell
{"title":"LOOM: Interweaving tightly coupled visualization and numeric simulation framework","authors":"J. Barbosa, P. Navrátil, Luís Paulo Santos, D. Fussell","doi":"10.1145/3490138.3490139","DOIUrl":"https://doi.org/10.1145/3490138.3490139","url":null,"abstract":"Traditional post-hoc high-fidelity scientific visualization (HSV) of numerical simulations requires multiple I/O check-pointing to inspect the simulation progress. The costs of these I/O operations are high and can grow exponentially with increasing problem sizes. In situ HSV dispenses with costly check-pointing I/O operations, but requires additional computing resources to generate the visualization, increasing power and energy consumption. In this paper we present LOOM, a new interweaving approach supported by a task scheduling framework to allow tightly coupled in situ visualization without significantly adding to the overall simulation runtime. The approach exploits the idle times of the numerical simulation threads, due to workload imbalances, to perform the visualization steps. Overall execution time (simulation plus visualization) is minimized. Power requirements are also minimized by sharing the same computational resources among numerical simulation and visualization tasks. We demonstrate that LOOM reduces time to visualization by 3 × compared to a traditional non-interwoven pipeline. Our results here demonstrate good potential for additional gains for large distributed-memory use cases with larger interleaving opportunities.","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133784177","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: 1
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization ISAV'21:实现极端尺度分析和可视化的现场基础设施
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138
{"title":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","authors":"","doi":"10.1145/3490138","DOIUrl":"https://doi.org/10.1145/3490138","url":null,"abstract":"","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122567283","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
In Situ Data-Driven Analysis and Learning of Turbulence Closures at Scale 大规模湍流闭包的原位数据驱动分析和学习
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1145/3490138.3498573
R. Balin
{"title":"In Situ Data-Driven Analysis and Learning of Turbulence Closures at Scale","authors":"R. Balin","doi":"10.1145/3490138.3498573","DOIUrl":"https://doi.org/10.1145/3490138.3498573","url":null,"abstract":"","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"2011 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125633389","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
Moderator 主持人
ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization Pub Date : 2021-11-10 DOI: 10.1002/9780470114735.hawley11054
S. Ziegeler
{"title":"Moderator","authors":"S. Ziegeler","doi":"10.1002/9780470114735.hawley11054","DOIUrl":"https://doi.org/10.1002/9780470114735.hawley11054","url":null,"abstract":"","PeriodicalId":256396,"journal":{"name":"ISAV'21: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116210128","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
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