CRII: III: Scalable and Interactive Dependency Visualization to Accelerate Parallel Program Analysis

CRII：III：可扩展和交互式依赖关系可视化，以加速并行程序分析

• 批准号: 1656958
• 负责人: Katherine Isaacs
• 金额: $ 17.45万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2021-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1656958&HistoricalAwards=false
• 关键词: CRII; III; Scalable; Interactive; Dependency

Computer simulations allow scientists and engineers to explore and analyze processes that would be infeasible to observe experimentally such as the physics leading to fusion, possible future climate scenarios, and the aerodynamics of new vehicle designs. Computing larger, more accurate, and more realistic simulations requires large clusters of computing devices working in parallel. Using these parallel computing resources efficiently is difficult. By analyzing the behavior of the simulation programs, scientists and programmers can achieve significant efficiency improvements enabling better simulations and more useful results. This program analysis often involves visualizing the graph of dependencies between different parts of the program and different parallel computing resources. However, there may be hundreds of thousands of parallel devices and thousands of computer instructions involved. Current visualizations are difficult to interpret at this size. This project develops visualization approaches that overcome this limitation, giving programmers the support to analyze and optimize large-scale simulations and ultimately accomplish more science. At the same time, this project furthers the understanding of how to design scalable visualizations which may then be applied to other large and complex data. The objective of this research is the creation of visual encodings and interaction techniques supporting the exploration and analysis of computing dependencies at scale. This project will study how visual design factors affect the interpretability of visual depictions as well as how parallel computing experts interact with the data during exploration. As dependency graphs are generated programmatically, they often exhibit a high degree of regularity. This project will test the efficacy of different depictions of this regularity through controlled user studies. In determining the interactivity needs of program analysts, this project will conduct a design study resulting in an interactive visual approach for exploring program control and data flow. The expected results of this project are a set of validated design guidelines for representing and interacting with program dependency data and an interactive visual tool for analyzing program dependency graphs. All products resulting from this project will be linked from the project website (http://hdc-arizona.github.io/projects/dependencies).

计算机模拟允许科学家和工程师探索和分析在实验上观察到的过程，例如导致融合的物理，可能的未来气候场景以及新车辆设计的空气动力学。计算更大，更准确，更现实的模拟需要并联运行的大量计算设备。有效地使用这些并行计算资源很困难。通过分析模拟程序的行为，科学家和程序员可以实现重大效率提高，从而可以更好地模拟和更有用的结果。该程序分析通常涉及可视化程序不同部分与不同平行计算资源之间的依赖关系图。但是，可能涉及数十万平行设备和数千台计算机说明。当前的可视化很难以这种大小解释。该项目开发了可视化方法，从而克服了这一限制，从而为程序员提供了分析和优化大规模仿真并最终完成更多科学的支持。同时，该项目进一步了解如何设计可扩展的可视化，然后将其应用于其他大型且复杂的数据。这项研究的目的是创建视觉编码和交互技术，以大规模探索和分析计算依赖性。该项目将研究视觉设计因素如何影响视觉描述的解释性以及平行计算专家如何与探索过程中的数据相互作用。由于依赖图是通过编程生成的，因此它们通常表现出很高的规律性。该项目将通过受控的用户研究来测试这种规律性不同描述的功效。在确定计划分析师的交互性需求时，该项目将进行设计研究，从而实现一种探索程序控制和数据流的交互式视觉方法。该项目的预期结果是一组经过验证的设计指南，用于表示和与程序依赖性数据进行交互，以及用于分析程序依赖图图的交互式视觉工具。该项目产生的所有产品将链接在项目网站（http://hdc-arizona.github.io/projects/deppencesies）中。

项目成果

Distributed Asynchronous Array Computing with the JetLag Environment

• DOI: 10.1109/pyhpc51966.2020.00011
• 发表时间: 2020-11
• 期刊: 2020 IEEE/ACM 9th Workshop on Python for High-Performance and Scientific Computing (PyHPC)
• 作者: Steven R. Brandt;Bita Hasheminezhad;Nanmiao Wu;Sayef Azad Sakin;Alex Bigelow;Katherine E. Isaacs;K. Huck;Hartmut Kaiser

Materia: A Data Quality Control Embedded Domain Specific Language in Python

Materia：Python 中的数据质量控制嵌入式领域特定语言

• DOI: 10.1007/978-3-030-61146-0_23
• 发表时间: 2020
• 期刊: BIS 2020: Business Information Systems Workshops
• 作者: Scully-Allison, Connor

Usability and Performance Improvements in Hatchet

Hatchet 的可用性和性能改进

• DOI: 10.1109/hustprotools51951.2020.00013
• 发表时间: 2020
• 期刊: 2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST
• 作者: Brink, Stephanie;Lumsden, Ian;Scully-Allison, Connor;Williams, Katy;Pearce, Olga;Gamblin, Todd;Taufer, Michela;Isaacs, Katherine E.;Bhatele, Abhinav
• 通讯作者: Bhatele, Abhinav

Visualizing a Moving Target: A Design Study on Task Parallel Programs in the Presence of Evolving Data and Concerns

可视化移动目标：存在不断变化的数据和关注点的任务并行程序的设计研究

• DOI: 10.1109/tvcg.2019.2934285
• 发表时间: 2019
• 期刊: IEEE Transactions on Visualization and Computer Graphics
• 影响因子: 5.2
• 作者: Williams, Katy;Bigelow, Alex;Isaacs, Katherine E.
• 通讯作者: Isaacs, Katherine E.

JetLag: An Interactive, Asynchronous Array Computing Environment

• DOI: 10.1145/3311790.3396657
• 发表时间: 2020-07
• 期刊: Practice and Experience in Advanced Research Computing
• 作者: Steven R. Brandt;Alex Bigelow;Sayef Azad Sakin;Katy Williams;Katherine E. Isaacs;K. Huck;R. Tohid;Bibek Wagle;S. Shirzad;Hartmut Kaiser