A Multi-Level Parallel Algorithm for Detection of Single Scatterers in SAR Tomography
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| Titel: | A Multi-Level Parallel Algorithm for Detection of Single Scatterers in SAR Tomography |
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| Autoren: | Russo, Massimiliano, Nisar, Mehwish, Pauciullo, Antonio, Imperatore, Pasquale, Lapegna, Marco, Romano, Diego |
| Quelle: | 2025 33rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP). :544-551 |
| Verlagsinformationen: | IEEE, 2025. |
| Publikationsjahr: | 2025 |
| Schlagwörter: | Synthetic Aperture Radar (SAR), Parallel Algorithms, Electromagnetic Scattering, Graphical Processing Unit (GPU), High Performance Computing (HPC), Tomography |
| Beschreibung: | Synthetic Aperture Radar (SAR) tomography is an advanced technique for monitoring deformations of the Earth's surface. However, the computational complexity of SAR tomography algorithms often restricts their application to large-scale datasets. To address this issue, we introduce a multi-level parallel implementation of a single scatterer detection algorithm specifically designed to exploit the capabilities of modern heterogeneous High-Performance Computing (HPC) systems. By efficiently distributing the computational workload at different levels across multiple processing units, our parallel approach significantly reduces processing time, facilitating the analysis of extensive SAR datasets. We assess the performance of our parallel implementation using real-world SAR data, showcasing its effectiveness in enhancing both the efficiency and scalability of SAR tomography. Our work contributes to advancing remote sensing techniques and offers valuable insights into the application of HPC for large-scale environmental monitoring. |
| Publikationsart: | Article Part of book or chapter of book |
| DOI: | 10.1109/pdp66500.2025.00083 |
| Zugangs-URL: | https://hdl.handle.net/11588/1005864 https://hdl.handle.net/11588/1005864 https://doi.org/10.1109/pdp66500.2025.00083 |
| Rights: | STM Policy #29 |
| Dokumentencode: | edsair.doi.dedup.....49c2cf4c990b9e3c31ff093a4dd7557e |
| Datenbank: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | Synthetic Aperture Radar (SAR) tomography is an advanced technique for monitoring deformations of the Earth's surface. However, the computational complexity of SAR tomography algorithms often restricts their application to large-scale datasets. To address this issue, we introduce a multi-level parallel implementation of a single scatterer detection algorithm specifically designed to exploit the capabilities of modern heterogeneous High-Performance Computing (HPC) systems. By efficiently distributing the computational workload at different levels across multiple processing units, our parallel approach significantly reduces processing time, facilitating the analysis of extensive SAR datasets. We assess the performance of our parallel implementation using real-world SAR data, showcasing its effectiveness in enhancing both the efficiency and scalability of SAR tomography. Our work contributes to advancing remote sensing techniques and offers valuable insights into the application of HPC for large-scale environmental monitoring. |
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| DOI: | 10.1109/pdp66500.2025.00083 |