LBVis: Interactive Dynamic Load Balancing Visualization for Parallel Particle Tracing

被引:0
作者
Zhang, Jiang [1 ,2 ]
Yang, Changhe [1 ,2 ]
Li, Yanda [1 ,2 ]
Chen, Li [4 ]
Yuan, Xiaoru [1 ,2 ,3 ]
机构
[1] Peking Univ, Minist Educ, Key Lab Machine Percept, Beijing, Peoples R China
[2] Peking Univ, Sch EECS, Beijing, Peoples R China
[3] Peking Univ, Beijing Engn Technol Res Ctr Virtual Simulat & Vi, Beijing, Peoples R China
[4] Tsinghua Univ, Sch Software, Inst CG&CAD, Beijing, Peoples R China
来源
2020 IEEE PACIFIC VISUALIZATION SYMPOSIUM (PACIFICVIS) | 2020年
关键词
Parallel particle tracing; load balancing; performance analysis; visual analytics; COMMUNICATION;
D O I
10.1109/PacificVis48177.2020.1029
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose an interactive visual analytical approach to exploring and diagnosing the dynamic load balance (data and task partition) process of parallel particle tracing in flow visualization. To understand the complex nature of the parallel processes, it is necessary to integrate the information of the behaviors and patterns of the computing processes, data changes and movements, task status and exchanges, and gain the insight of the relationships among them. In our proposed approach, the data and task behaviors are visualized through a graph with a fine-designed layout, in which node glyphs are dedicated to showing the status of processes and the links represent the data or task transfer between different computation rounds and processes. User interactions are supported to facilitate the exploration of performance analysis. We provide a case study to demonstrate that the proposed approach enables users to identify the bottlenecks during this process, and thus help optimize the related algorithms.
引用
收藏
页码:91 / 95
页数:5
相关论文
共 21 条
[21]   Dynamic Data Repartitioning for Load-Balanced Parallel Particle Tracing [J].
Zhang, Jiang ;
Guo, Hanqi ;
Yuan, Xiaoru ;
Peterka, Tom .
2018 IEEE PACIFIC VISUALIZATION SYMPOSIUM (PACIFICVIS), 2018, :86-95