The effective exploitation of the available huge SAR data archives in reasonable time-frames has motivated the development of P-SBAS, a parallel computing solution for the SBAS (Small BAseline Subset) processing chain. Hence, P-SBAS parallel solution represents a valuable tool for the analysis of the complex phenomena characterizing the surface deformation dynamics of Earth large areas, since it permits to exploit the parallelism offered by the modern computational platforms. In this paper, the performance of the parallel algorithm P-SBAS is investigated. The quantitative evaluation of the computational efficiency of the implemented parallel prototype in terms of achieved speedup is addressed to demonstrate the effectiveness of the proposed approach. An experimental analysis has been carried out on real data by employing a computational platform comprising 32 processors. In particular, the performance analysis has been conducted by exploiting different SAR datasets pertinent to different sensors (Envisat and Cosmo Sky-Med) and the factors limiting the inherent scalability are discussed.
Scalable performance analysis of the parallel SBAS-DInSAR algorithm
Imperatore Pasquale;Zinno Ivana;Elefante Stefano;De Luca Claudio;Casu Francesco
2014
Abstract
The effective exploitation of the available huge SAR data archives in reasonable time-frames has motivated the development of P-SBAS, a parallel computing solution for the SBAS (Small BAseline Subset) processing chain. Hence, P-SBAS parallel solution represents a valuable tool for the analysis of the complex phenomena characterizing the surface deformation dynamics of Earth large areas, since it permits to exploit the parallelism offered by the modern computational platforms. In this paper, the performance of the parallel algorithm P-SBAS is investigated. The quantitative evaluation of the computational efficiency of the implemented parallel prototype in terms of achieved speedup is addressed to demonstrate the effectiveness of the proposed approach. An experimental analysis has been carried out on real data by employing a computational platform comprising 32 processors. In particular, the performance analysis has been conducted by exploiting different SAR datasets pertinent to different sensors (Envisat and Cosmo Sky-Med) and the factors limiting the inherent scalability are discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.