Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data
With the increasing demand for high precision in numerical simulations using computational fluid dynamics (CFD), the use of large-scale grids for discretized solutions has become a trend, resulting in an explosive growth of flow-field data size. To address the challenges posed by large-scale flow-fi...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/16/9092 |
| _version_ | 1797585709726433280 |
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| author | Zhouqiao He Cheng Chen Yadong Wu Xiaokun Tian Qikai Chu Zhengbin Huang Weihan Zhang |
| author_facet | Zhouqiao He Cheng Chen Yadong Wu Xiaokun Tian Qikai Chu Zhengbin Huang Weihan Zhang |
| author_sort | Zhouqiao He |
| collection | DOAJ |
| description | With the increasing demand for high precision in numerical simulations using computational fluid dynamics (CFD), the use of large-scale grids for discretized solutions has become a trend, resulting in an explosive growth of flow-field data size. To address the challenges posed by large-scale flow-field data for real-time interactive visualization, this paper proposes novel strategies for data partitioning and communication management. Firstly, we propose a data-partitioning strategy based on grid segmentation. This approach constructs metadata to create file viewports for each process and performs grid partitioning. Subsequently, it reconstructs sub-grids within each process and utilizes a coordinate-mapping algorithm to map global coordinates to local process coordinates, facilitating access to attribute variables through a lookup table. Secondly, we introduce a real-time interactive method for large-scale flow fields. This method leverages the system architecture of high-speed interconnection among compute nodes in a cluster environment and low-speed interconnection between service nodes and rendering nodes. It enables coordinated management of parallel rendering and synchronized rendering methods. The experimental results on typical flow-field data demonstrate that the proposed data-partitioning strategy improves the loading speed of millions of grid-level data by a factor of 7, surpassing ParaView’s performance by 1.5 times. Furthermore, it achieves system load balancing. Real-time interaction experiments with datasets containing 500 million and 800 million grid cells exhibit millisecond-level latencies, demonstrating the effectiveness of the proposed communication management method in meeting the real-time interactive visualization demands of large-scale flow-field data. |
| first_indexed | 2024-03-11T00:09:57Z |
| format | Article |
| id | doaj.art-cf6593d14612408cbcd4a34bf4646d1d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T00:09:57Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-cf6593d14612408cbcd4a34bf4646d1d2023-11-19T00:04:09ZengMDPI AGApplied Sciences2076-34172023-08-011316909210.3390/app13169092Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field DataZhouqiao He0Cheng Chen1Yadong Wu2Xiaokun Tian3Qikai Chu4Zhengbin Huang5Weihan Zhang6School of Computer Science and Engineering, Sichuan University of Science and Engineering, Yibin 644002, ChinaChina Aerodynamics Research and Development Center, Mianyang 621050, ChinaSchool of Computer Science and Engineering, Sichuan University of Science and Engineering, Yibin 644002, ChinaSchool of Computer Science and Engineering, Sichuan University of Science and Engineering, Yibin 644002, ChinaSchool of Computer Science and Engineering, Sichuan University of Science and Engineering, Yibin 644002, ChinaChina Aerodynamics Research and Development Center, Mianyang 621050, ChinaSchool of Computer Science and Engineering, Sichuan University of Science and Engineering, Yibin 644002, ChinaWith the increasing demand for high precision in numerical simulations using computational fluid dynamics (CFD), the use of large-scale grids for discretized solutions has become a trend, resulting in an explosive growth of flow-field data size. To address the challenges posed by large-scale flow-field data for real-time interactive visualization, this paper proposes novel strategies for data partitioning and communication management. Firstly, we propose a data-partitioning strategy based on grid segmentation. This approach constructs metadata to create file viewports for each process and performs grid partitioning. Subsequently, it reconstructs sub-grids within each process and utilizes a coordinate-mapping algorithm to map global coordinates to local process coordinates, facilitating access to attribute variables through a lookup table. Secondly, we introduce a real-time interactive method for large-scale flow fields. This method leverages the system architecture of high-speed interconnection among compute nodes in a cluster environment and low-speed interconnection between service nodes and rendering nodes. It enables coordinated management of parallel rendering and synchronized rendering methods. The experimental results on typical flow-field data demonstrate that the proposed data-partitioning strategy improves the loading speed of millions of grid-level data by a factor of 7, surpassing ParaView’s performance by 1.5 times. Furthermore, it achieves system load balancing. Real-time interaction experiments with datasets containing 500 million and 800 million grid cells exhibit millisecond-level latencies, demonstrating the effectiveness of the proposed communication management method in meeting the real-time interactive visualization demands of large-scale flow-field data.https://www.mdpi.com/2076-3417/13/16/9092data partitioningscientific visualizationlarge-scale flow-field dataEnSight Gold data formatreal-time interactionparallel visualization |
| spellingShingle | Zhouqiao He Cheng Chen Yadong Wu Xiaokun Tian Qikai Chu Zhengbin Huang Weihan Zhang Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data Applied Sciences data partitioning scientific visualization large-scale flow-field data EnSight Gold data format real-time interaction parallel visualization |
| title | Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data |
| title_full | Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data |
| title_fullStr | Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data |
| title_full_unstemmed | Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data |
| title_short | Real-Time Interactive Parallel Visualization of Large-Scale Flow-Field Data |
| title_sort | real time interactive parallel visualization of large scale flow field data |
| topic | data partitioning scientific visualization large-scale flow-field data EnSight Gold data format real-time interaction parallel visualization |
| url | https://www.mdpi.com/2076-3417/13/16/9092 |
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