In this paper, we present a parallel computing strategy for the detection of single scatterers in SAR tomography, specifically targeted to multi-node, multi-GPU platforms. In particular, we refer to an existing processing scheme based on the Generalized Likelihood Ratio Test (GLRT), which is considered a reference canonical problem for our investigation. To tackle this problem, a dedicated parallel algorithm is developed according to High-Performance Computing (HPC) methodologies. To quantitatively demonstrate the benefits of the multi-level parallelism incorporated into the proposed algorithm, an experimental analysis using real SAR data is conducted on a large distributed computational platform. The results show significant speedup, indicating that the proposed solution maintains excellent performance as both the problem size and computational resources increase.
Detection of Single Scatterers in SAR Tomography using Multi-GPU Platforms / Russo, Massimiliano; Nisar, Mehwish; Lapegna, Marco; Romano, Diego; Pauciullo, Antonio; Imperatore, Pasquale. - (2025), pp. 1-4. ( 2025 Joint Urban Remote Sensing Event, JURSE 2025 Tunisi (Tunisia) 2025) [10.1109/jurse60372.2025.11076025].
Detection of Single Scatterers in SAR Tomography using Multi-GPU Platforms
Russo, Massimiliano;Lapegna, Marco;Imperatore, Pasquale
2025
Abstract
In this paper, we present a parallel computing strategy for the detection of single scatterers in SAR tomography, specifically targeted to multi-node, multi-GPU platforms. In particular, we refer to an existing processing scheme based on the Generalized Likelihood Ratio Test (GLRT), which is considered a reference canonical problem for our investigation. To tackle this problem, a dedicated parallel algorithm is developed according to High-Performance Computing (HPC) methodologies. To quantitatively demonstrate the benefits of the multi-level parallelism incorporated into the proposed algorithm, an experimental analysis using real SAR data is conducted on a large distributed computational platform. The results show significant speedup, indicating that the proposed solution maintains excellent performance as both the problem size and computational resources increase.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


