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Gallo, Giovanni
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Gallo, Giovanni
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- PublicationOpen AccessPorting and optimizing MAGFLOW on CUDA(2011)
; ; ; ; ; ; ; ;Bilotta, G.; Università di Catania, Dipartimento di Matematica e Informatica, Catania, Italy ;Rustico, E.; Università di Catania, Dipartimento di Matematica e Informatica, Catania, Italy ;Herault, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Vicari, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Russo, G.; Università di Catania, Dipartimento di Matematica e Informatica, Catania, Italy ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Gallo, G.; Università di Catania, Dipartimento di Matematica e Informatica, Catania, Italy; ; ; ; ; ; The MAGFLOW lava simulation model is a cellular automaton developed by the Sezione di Catania of the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and it represents the peak of the evolution of cellbased models for lava-flow simulation. The accuracy and adherence to reality achieved by the physics-based cell evolution of MAGFLOW comes at the cost of significant computational times for long-running simulations. The present study describes the efforts and results obtained by porting the original serial code to the parallel computational platforms offered by modern video cards, and in particular to the NVIDIA Compute Unified Device Architecture (CUDA). A number of optimization strategies that have been used to achieve optimal performance on a graphic processing units (GPU) are also discussed. The actual benefits of running on the GPU rather than the central processing unit depends on the extent and duration of the simulated event; for large, long-running simulations, the GPU can be 70-to-80-times faster, while for short-lived eruptions with a small extents the speed improvements obtained are 40-to-50 times.449 254 - PublicationRestrictedSpatial vent opening probability map of Etna volcano (Sicily, Italy)(2012-09-02)
; ; ; ; ; ; ;Cappello, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Neri, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Acocella, V.; Dipartimento di Scienze Geologiche, Università RomaTre, Rome, Italy ;Gallo, G.; Dipartimento di Matematica e Informatica, Università di Catania, Catania, Italy ;Vicari, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; ; ; ; We produce a spatial probability map of vent opening (susceptibility map) at Etna, using a statistical analysis of structural features of flank eruptions of the last 2 ky. We exploit a detailed knowledge of the volcano structures, including the modalities of shallow magma transfer deriving from dike and dike-fed fissure eruptions analysis on historical eruptions. Assuming the location of future vents will have the same causal factors as the past eruptions, we converted the geological and structural data in distinct and weighted probability density functions, which were included in a non-homogeneous Poisson process to obtain the susceptibility map. The highest probability of new eruptive vents opening falls within a N-S aligned area passing through the Summit Craters down to about 2,000 ma.s.l. on the southern flank. Other zones of high probability follow the North-East, East-North-East, West, and South Rifts, the latter reaching low altitudes (∼400 m). Less susceptible areas are found around the faults cutting the upper portions of Etna, including the western portion of the Pernicana fault and the northern extent of the Ragalna fault. This structuralbased susceptibility map is a crucial step in forecasting lava flow hazards at Etna, providing a support tool for decision makers.311 22 - PublicationRestrictedA texton-based cloud detection algorithm for MSG-SEVIRI multispectral images(2011)
; ; ; ; ; ;Ganci, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Vicari, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Bonfiglio, S.; Dipartimento di Matematica e Informatica, University of Catania, Italy ;Gallo, G.; Dipartimento di Matematica e Informatica, University of Catania, Italy ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; ; ; A new statistical texton-based method for cloud detection through satellite image analysis is presented. The ultimate goal is to improve the performance of remote sensing techniques used to support the observations of active volcanic processes. The proposed method is a supervised classifier that exploits radiance spatial correlation in satellite images using a statistical descriptor of texture called texton. Cloudy and clear-sky models are determined using cluster analysis over the image features. The pixels to be classified are compared with the estimated models and assigned to the closest model. The cloud detection algorithm has been tested on a data set of MSG-SEVIRI images acquired during 2008 (about 35,000 images) of the Sicily area. Results show that the texton-based approach is robust in terms of percentage of correctly classified pixels, reaching more than 85% of success in both daytime and nighttime images.246 38 - PublicationRestrictedImprovements of data analysis and self-consistent monitoring methods for the MEV telescope(2020-04)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; The MEV project is running for a long-term muography measurement at the North-East crater of the Etna Volcano, after the successful conclusion of the test phase in July 2017. Two sets of data were already acquired during 2017, during the last months of the summer, and 2018. Data analysis is currently ongoing in order to extract a two-dimensional density map of the target from the measured muon flux. But before, a major improvement on data pre-processing was required. It regards in particular the algorithm for event reconstruction and filtering and the introduction of a method to extract the telescope efficiency from data themselves. The main steps of this pre-analysis and their application to the test data set is described in this paper.510 4 - PublicationOpen AccessLAV@HAZARD: A Web-Gis interface for volcanic hazard assessment(2011)
; ; ; ; ; ; ; ; ; ;Vicari, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Bilotta, G.; Università di Catania, Dipartimento di Matematica e Informatica ;Bonfiglio, S.; Università di Catania, Dipartimento di Matematica e Informatica ;Cappello, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Ganci, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Herault, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Rustico, E.; Università di Catania, Dipartimento di Matematica e Informatica ;Gallo, G.; Università di Catania, Dipartimento di Matematica e Informatica ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia; ; ; ; ; ; ; ; Satellite data, radiative power of hot spots as measured with remote sensing, historical records, on site geological surveys, digital elevation model data, and simulation results together provide a massive data source to investigate the behavior of active volcanoes like Mount Etna (Sicily,Italy) over recent times. The integration of these eterogeneous data into a coherent visualization framework is important for their practical exploitation. It is crucial to fill in the gap between experimental and numerical data, and the direct human perception of their meaning. Indeed, the people in charge of safety planning of an area need to be able to quickly assess hazards and other relevant issues even during critical situations. With this in mind, we developed LAV@HAZARD, a web-based geographic information system that provides an interface for the collection of all of the products coming from the LAVA project research activities. LAV@HAZARD is based on Google Maps application programming interface, a choice motivated by its ease of use and the user-friendly interactive environment it provides. In particular, the web structure consists of four modules for satellite applications (time-space evolution of hot spots, radiant flux and effusion rate), hazard map visualization, a database of ca. 30,000 lava-flow simulations, and real-time scenario forecasting by MAGFLOW on Compute Unified Device Architecture.363 448 - PublicationRestrictedThe MEV project: design and testing of a new high-resolution telescope for Muography of Etna Volcano(2018-05-29)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ;; ; ; ;The MEV project aims at developing a muon telescope expressly designed for the muography of Etna Volcano. In particular, one of the active craters in the summit area of the volcano would be a suitable target for this experiment. A muon tracking telescope with high imaging resolution was built and tested during 2017. The telescope is a tracker based on extruded scintillating bars with WLS fibres and featuring an innovative read-out architecture. It is composed of three XY planes with a sensitive area of \SI{1}{m^2}; the angular resolution does not exceeds \SI{0.4}{\milli\steradian} and the total angular aperture is about $\pm$\SI{45}{\degree}. A special effort concerned the design of mechanics and electronics in order to meet the requirements of a detector capable to work in a hostile environment such as the top of a tall volcano, at a far distance from any facility. The test phase started in January 2017 and ended successfully at the end of July 2017. An extinct volcanic crater (the Monti Rossi, in the village of Nicolosi, about 15km from Catania) is the target of the measurement. The detector acquired data for about 120 days and the preliminary results are reported in this work.734 3 - PublicationOpen AccessScalable multi-GPU implementation of the MAGFLOW simulator(2011)
; ; ; ; ; ;Rustico, E.; Università di Catania, Dipartimento di Matematica e Informatica, Catania, Italy ;Bilotta, G.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Herault, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Del Negro, C.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Catania, Catania, Italia ;Gallo, G.; Università di Catania, Dipartimento di Matematica e Informatica, Catania, Italy; ; ; ; We have developed a robust and scalable multi-GPU (Graphics Processing Unit) version of the cellular-automaton-based MAGFLOW lava simulator. The cellular automaton is partitioned into strips that are assigned to different GPUs, with minimal overlapping. For each GPU, a host thread is launched to manage allocation, deallocation, data transfer and kernel launches; the main host thread coordinates all of the GPUs, to ensure temporal coherence and data integrity. The overlapping borders and maximum temporal step need to be exchanged among the GPUs at the beginning of every evolution of the cellular automaton; data transfers are asynchronous with respect to the computations, to cover the introduced overhead. It is not required to have GPUs of the same speed or capacity; the system runs flawlessly on homogeneous and heterogeneous hardware. The speed-up factor differs from that which is ideal (#GPUs×) only for a constant overhead loss of about 4E−2 · T · #GPUs, with T as the total simulation time.187 155