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High Performance Computing and Artificial Intelligence for Solar System activities at SSDC

High Performance Computing and Artificial Intelligence for Solar System activities at SSDC. A. Zinzi, M. Giardino, G. Sindoni, A. Baraldi, D. Grassi, F. Tosi, G. Polenta angelo.zinzi@ssdc.asi.it INAF Science Archives & the Big Data Challenge 19th June 2019, INAF HQ, Rome. 6 years ago

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High Performance Computing and Artificial Intelligence for Solar System activities at SSDC

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  1. High Performance Computing and Artificial Intelligence for Solar System activities at SSDC A. Zinzi, M. Giardino, G. Sindoni, A. Baraldi, D. Grassi, F. Tosi, G. Polenta angelo.zinzi@ssdc.asi.it INAF Science Archives & the Big Data Challenge 19th June 2019, INAF HQ, Rome

  2. 6 years ago (Bormio 2013) MATISSE wasfirstlypresented to the Italianplanetological community, with a demo version

  3. Duringtheseyears the toolhasgrown up, improvingitsscientificcapabilities and includingseveral targets, missions It’snow time to release a brand new version of the tool A beta versiononline https://193.204.103.156/Matisse

  4. The PostgreSQL + PostGISsolutionallows to correctlymanagespatialqueries, alsoimprovingspatialinterpolationbetweenobservations and DTMs/shapemodels

  5. 3D JS9 + Planetary FITS

  6. Big data, featuring the 5 Vs of Variety, Veracity, Velocity, Volume and Value

  7. CPU cluster system based on Dell technology HPC dedicated HW infrastructure (to be acquired) HPC Primary task Develop a set of software engineering techniques to apply parallel computing to existing non-parallel retrieval algorithms Medium term goal Exploit commonalities between similar science cases to produce a single library dealing with platform portability issues

  8. The generalization task to be pursuedthrough a double path Programming languagelevel (Python environment and wrapping of native code) Platform abstractionlevel (distributed memory model / shared memory model) The referenceplatform for developmentis the Microsoft Azurecloud, usedas a suitableworkbench to define, test and profiledifferentscenarios

  9. HPC case study 1 JIRAM atmosphericretrieval codedevelopedat INAF IAPS (D. Grassi) for serial applications Going to be optimized for parallelcomputing, boostingits performances Resultingdatasetadded to MATISSE see Grassi et al., 2017, DOI: 10.1016/j.jqsrt.2017.08.008 Grassi et al., 2010, DOI: 10.1016/j.pss.2010.05.003

  10. Current ‘scientific’ serial approach Serial computing Serial computing Retrieval Spectrum Spectrum Retrieval Parallelapproach under development Parallelcomputing by launchingseveralindependentsimultaneousjobs Group of independentspectra Group of independentretrievals

  11. The achievement of goals from the first test case willpave a way for a number of differentscientificcasesthat can be treatedusing HPC in SSDC

  12. Artificial (general) Intelligence for Big Data analytics Qualitative/equivocalinformation-as-data-interpretation In SSDC we are integrating high-levelskills in the Computer Vision (CV) field, where CV is subset-of Artificial General Intelligence (AGI) Theseskillscould be extremelyuseful and versatile for a wide range of scientificcases, ranging from astronomy to Earth observation, passingthroughplanetarysciences

  13. A.I. case study 1 Detection of Jupiter White Ovals from JIRAM imagery (see Sindoni et al., 2017) Finding best colorimetric and spatialfeatures to extractcyclones and anticyclones from the «image background (clutter)» Makethis CV task automatic and robust to changes in a series of input test images

  14. Color Constancy + RGB Image Automatic Mapper RGB images Top Numberdensities of R: NH3, G: NH4SH, B:N2H4 Middle Heights of R: NH3, G: NH4SH, B:N2H4 Bottom R: NH3 VMR, G: NH3 RH, B: Temperature Color, Shape, Orientation, Size, Texture, Inter-Object SpatialTopologicalRelationships, Inter-Object Spatial non-topologicalrelationships

  15. Combination of selectedproperties from CV approach White Ovals detection and classification Detaileddiscussion of the task at EPSC/DPS (talk 1278 by Zinzi et al. in OPS4)

  16. Thisapproachiscompletelyhorizontal and could be applicable to extremelydifferentiatedcases. Itonlyrequires images and priorknowledge to be used

  17. … and …

  18. ExoplAn3T https://tools.ssdc.asi.it/exoplanet The new SSDC webtooldesigned to studyexoplanetarysystemsas a whole, starting from exoplanetary data present in different online archives Using a two-foldquerytotallytransparent to the user, itallows to find relation betweenexoplanetarysystemssharingatleastonesimilarplanet. The toolsalsoprovides a novel 3D visualization of the selectedexosystems, thusfacilitating the comparisonbetweenresults.

  19. Conclusions and future works • A powerful HPC machine isgoing to be acquired by SSDC and major activities to be fulfilled are now under development • Computer Vision techniquesapplied to scientific test cases are beingtested to acquireknowledgeaboutthem and to integrate theseskills in the SSDC tools Together with the development of the new version of MATISSE theseadvanced ICT solutions to be adopted by SSDC willconstitute a crucialmilestone for the advancement of solar systemexplorationactivities of the center

  20. Thankyou for yourattention angelo.zinzi@ssdc.asi.it

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