I risultati scientifici del progetto SCoPE SCoPE Scientific Results L. Merola Workshop finale dei Progetti Grid del PON "Ricerca" 2000-2006 - Avviso 1575.

Presentazione sul tema: "I risultati scientifici del progetto SCoPE SCoPE Scientific Results L. Merola Workshop finale dei Progetti Grid del PON "Ricerca" 2000-2006 - Avviso 1575."— Transcript della presentazione:

1 I risultati scientifici del progetto SCoPE SCoPE Scientific Results L. Merola Workshop finale dei Progetti Grid del PON "Ricerca" 2000-2006 - Avviso 1575 Catania, 10-12 febbraio 2009

2 Summary The University of Napoli Federico II The SCoPE Project and Research Areas The SCoPE Data Center & Metropolitan Network Results from Material Sciences Results from Life Sciences Results from MicroCosm and MacroCosm Sciences Results from Middleware applications Beyond SCoPE

3 Founded in 1224 Second largest university in Italy More tha 3.000 professors and researchers More than 10.000 new student per year Involved in the most strategic areas of scientific research, e-Science and technology The University of Napoli Federico II

4 The SCoPE project and Research Areas SCoPE : SCoPE : Sistema Cooperativo distribuito ad alte Prestazioni per Elaborazioni Scientifiche Multidisciplinari (Distributed Cooperative High Performance System for Multidisciplinary Applications) Objectives: Innovative and original software for fundamental scientific research. High performance Data & Computing Centre for multidisciplinary applications. Grid infrastructure and middleware INFNGRID LCG/gLite: Compatibility with EGEE middleware Interoperability with the other three PON 1575 projects and SPACI in GRISU Integration in the Italian and European Grid Infrastructure.

5 5 Research areas: MicroCosm and MacroCosm Sciences MicroCosm and MacroCosm Sciences Materials and Environment Sciences Materials and Environment Sciences Life Sciences Life Sciences Social Sciences Social Sciences Middleware Middleware 19 Departments and Research Institutes 128 Professors and Senior researchers from UniNA + many others from Research Institutes (INFN, etc.) 35Young researchers (assegni di ricerca) 28 Technology specialists (co.co.co.)

6 Macro area Scie nze M.F.N. Macro area Medi cina Struttura centrale (CSI) Area delle Scienze MM.FF.NN. (Campus – GRID) Area delle Scienze Ingegneristiche Area delle Scienze Mediche e Biotecnologie Dip.Informatica e Sistemistica Dip. Ingegneria Elettrica Dip.Ingegneria Elettronica e delle Telecomunicazioni Dip. Biochimica e Biotecnologie mediche Macro area Medi cina Area delle Scienze Umane e Sociali Dip. Matematico- Statistico Dip. di Scienze Fisiche Dip.Ingegneria Chimica Organizzazioni esterne ma collegate INFN Sezione di Napoli CNR-SPACI Napoli INFM Unità di Napoli CEINGE CRIAI ARPA CINI Dip. di Analisi e Progettazione Strutturale Dipartimento di Sociologia Centro di Eccellenza per lo Studio delle Malattie Genetiche Dip. di Matematica Dip. di Chimica

7 Astrophysics group Search for gravitational waves Data mining and visualization of astronomical massive data sets http://virgo.infn.ithttp://virgo.infn.it and http://www.eurovotech.org/http://www.eurovotech.org/ Particle Physics (subnuclear physics) group Study of proton-proton interactions at the CERN-LHC Large Hadron Collider and implementation of a Tier2 Data Centre for large scale, data intensive Montecarlo simulations and data analysis http://lxatlas.na.infn.it

8 Bioinformatics group Study of genome sequence analysis and image analyses for cell motility and other dynamical phenomena http://bioinfo.ceinge.unina.it/http://bioinfo.ceinge.unina.it/ and http://www.ceinge.unina.ithttp://www.ceinge.unina.it Numerical Mathematics and Scientific computing group Study and design of algorithms for distributed scientific applications and implementation on HPC infrastructures Statistical mechanics group Study of applications of statistical mechanics to complex systems http://smcs.na.infn.it/

9 9 Electromagnetism and Telecommunication group Study of models and measurements of electromagnetic field in the Napoli metropolitan area http://www.diet.unina.it/gruppoCE/GruppoEl.html Material Science group Study of molecular dynamics and optical properties of nano- structured materials http://lsdm.campusgrid.unina.it/http://lsdm.campusgrid.unina.it/ and http://www.nanomat.unina.it Soft Matter Engineering group Study of models and simulations of the flux of micro-structured materials http://wpage.unina.it/p.maffettonehttp://wpage.unina.it/p.maffettone

10 The SCoPE Data Center 33 Racks (of which 10 for Tier2 ATLAS) 304 Servers for a total of 2.432 processors 130 TeraByte storage 2 remote sites: Fac. Medicine: 60 TB storage Dep. Chemistry: 8 server multiCPU (4-proc)

11 INGRESSO Data Center SCOPE Control Room SCOPE Biologia Fisica

12 SCoPE DataCenter & Tier2 ATLAS 1 MW Cabina elettrica 1 MW

13 Control room Chem. Med. Data Center Low latency network 2432 core

14 CAMPUS GRID Monte SantAngelo DMA DiCh i DSF INFN C.S.I. GARR Fibra ottica S.CO.P.E. GARR 2.4 Gb/s Centro S.CO.P.E. Centro S.CO.P.E. Dipartimento di Scienze Fisiche Sezione INFN Cabina elettrica G.E. 1 MW Control room S.CO.P.E. The Metropolitan Network

15 SUSPENSION OF PARTICLES IN LIQUIDS SUSPENSION OF PARTICLES IN LIQUIDS Intensive simulations in 2D & 3D FEM Motivation Suspensions of particles in liquids are a class of materials relevant in a huge variety of applications, e.g. – Polymer melts with fillers – Biomedical materials – Food – Cosmetics – Detergents This variegate spectrum is due to the differences in particle concentration, mechanical properties, shape, and size. Particles suspended in viscoelastic media are known to develop structures when sheared at sufficiently high shear rates. Results from Material Sciences (Dip. Ingegneria Chimica – Dip. Matematica e Applicazioni

16 Aim Characterize the flow behavior of dilute and semidilute suspensions of rigid spheres in viscoelastic media in confined geometries. Sw libraries: – BLAS/LAPACK – METIS To solve linear systems emerging from FEM, following solvers have been used/compared: – HSL library (commercial, direct solver, sequential) – MKL Gmres (included in MKL, iterative solver, sequential) – Sparsekit (free, iterative solver, sequential) – Pardiso (included in MKL, direct solver, OpenMP) – Mumps (free, direct solver, MPI) – Petsc (free, iterative solver, MPI)

17 3D Two Particles flux in confined geometries Newtonian Fluid Non Newtonian FluidNewtonian Fluid Non Newtonian Fluid

18 Results from Material Sciences (Dip. Scienze Fisiche) From single-particle energy levels Tight-Binding sw package to study optical properties (absorbance, reflectivity, refraction index, photoluminescence) of semiconductor nanocrystals vs. shape and dimensions. Intensive computing and RAM requirements (10^3-10^5 rows matrix diagonalization). Medintz et al. Quantum dot bioconjugates for imaging, labelling and sensing, Nat. Mat. 4, 435 (2005)

19 Problem H.Hofmeister, F.Huisken and B.Kohn, Eur. Phys. J. D 9, 137 (1999). Nanocrystal (real) Nanocrystal (model) 3 nm Tight Binding = wave functions as linear combination of atomic orbitals. Advantages: 1) Hamiltonian Matrix of small dimension: only 4 orbitals per single Si atom; 2) High level of sparsity (>95%): the diagonalization time scales linearly with dimension ; 3) Symmetries: Hamiltonian Matrix decomposed in independent blocks according to the irriducible representations of the simmetry group.

20 Results Absorbance of InAs colloidal nanocrystals vs. dimensions Line: this model (Trani et al. Phys. Rev. B 76, 085302 2007) Points: experiment (Yu et al. J. Phys. Chem. B 109, 7084 2005)

21 Workshop SCoPE - Stato del progetto e dei Work Packages Sala Azzurra - Complesso universitario Monte SantAngelo 21-2-2008 Language: Fortran 90 Libraries: BLAS, LAPACK, math lib (MKL) for matrix manipulation Package tested on: linux AMD Athon a 1.6 GHz, AMD64 a 3.2 GHz, Alpha True64, Intel Xeon. Compilers: Intel, PGI, Gfortran HPC needed: Parallelization under development Web interface: http://www.nanomat.unina.it SCoPE portal http://www.nanomat.unina.it Software

22 Computational modelling of molecular and supra-molecular systems theory Recent developments: theory: both classical (MM) and quantistic algorithmstechnology (QM); algorithms (linear scaling methods) and technology. Intensive simulation processes. Efficient description for: Average dimension structures Periodic systems Problematic areas: large non periodic systems: large non periodic systems: -- Nanoparticles -- biomacromolecules -- defects of materials Results from Material (and Life) Sciences (Dip. Chimica) Soft Matter

23 Application (example) Dynamic ADMP (Atom centered Density Matrix Propagation)/ ONIOM (Our own N-layered Integrated molecular Orbital + Molecular Mechanicson ionic channel of the gramicidine A. Dynamic ADMP (Atom centered Density Matrix Propagation) / ONIOM (Our own N-layered Integrated molecular Orbital + Molecular Mechanics) on ionic channel of the gramicidine A. In ADMPthe electronic degrees of freedom have a unreal mass and propagate from step to step. In ADMP the electronic degrees of freedom have a unreal mass and propagate from step to step. nella dinamica ADMP (come nella congenere dinamica Car-Parrinello), anche i gradi di libertà elettronici hanno associata una massa fittizia e vengono propagati da uno step allaltro (Lagrangiana estesa). - nella dinamica ADMP (come nella congenere dinamica Car-Parrinello), anche i gradi di libertà elettronici hanno associata una massa fittizia e vengono propagati da uno step allaltro (Lagrangiana estesa). - nellADMP, i gradi di libertà elettronici sono codificati da una matrice densità espressa in termini di funzioni di base centrate sugli atomi. nella dinamica classica, le posizioni e i momenti dei nuclei vengono propagati da uno step al successivo: il campo di forze consente di calcolare lenergia e le accelerazioni punto per punto. - nella dinamica classica, le posizioni e i momenti dei nuclei vengono propagati da uno step al successivo: il campo di forze consente di calcolare lenergia e le accelerazioni punto per punto.

24 24 Real-time forecast of the e.m. field on the metropolitan area (Napoli) Numerical solvers for the optimization of planning of wireless mobile phones networks. Interpolation on the metropolitan area of the e.m. exposure, starting from a limited number of sensors. Application to a project for a call- center for public information Livello del campo Results from Material & Environment Sciences (Dip. Ingegneria Elettronica e delle Telecomunicazioni) P.zza Plebiscito Palazzo Reale Study of the environmental impact of e.m. field

25 Interests of UniNA towards a Virtual Organization in MATerIal Science Simulation and Engineering (MATISSE) (ref. Prof. Domenico Ninno) STRUTTURATEMAMETODI E CODICI Dip. Scienze FisicheFisica delle nanostrutture, ossidi, grafeni e sistemi ibridi organico inorganico Teoria del funzionale densit à – Basi localizzate di Wannier- Codici open source: Quantum Espresso, Wannier 90 Dip. Scienze FisicheSistemi a forte correlazione elettronica (ossidi di metalli di transizione) Diagonalizzazione esatta Lanczos e/o Jacobi-Davidson – Quantum Montecarlo diagrammatico Dip. Scienze FisicheMeccanica Statistica dei vetri, mezzi granulari, superconduttori e sistemi biologici Montecarlo e dinamica molecolare – Codici propri Dip. Scienze FisicheMeccanica Statistica dei vetri di spin, vetri strutturali, gel e colloidi, materiali granulari Montecarlo e dinamica molecolare – Codici propri Dip. Scienze Fisiche Modelli d interazione tra biomolecole e laser Dinamica molecolare Molpro, Gaussian Dip. Chimica Propriet à chimico-fisiche di materiali nanostrutturati, solidi e superfici Teorie ab initio, teoria del funzionale della densit à, basi localizzate e onde piane, metodi multiscala Codici non open source: Gaussian, Crystal, Molpro, Materials studio, Vasp, dlpoly. Codici open source: Gamess-us, quantum espresso, gulp Dip. Ingegneria ChimicaReologia e fluidodinamica di sospensioni solide in fluidi viscoelastici Simulazioni agli elementi finiti – Codice proprio (TFEM) Dip. Ingegneria dei Materiali e della ProduzioneDiffusione di sostanze a basso peso molecolare in sistemi macromolecolari Dinamica molecolare (Materials studio) Dip. Ingegneria dei Materiali e della ProduzioneNucleazione e crescita di microparticelle per precipitazione in fluido supercritico Codici propri interfacciatI con FLUENT Dip. Ingegneria dei Materiali e della ProduzioneNanofluidica. Moto di particelle e macromolecole in nanochannels Codici propri Dip. Ingegneria dei Materiali e della Produzione e Dipartimento di Ingegneria strutturale Comportamenti meccanici di polimeri e compositi e problemi di omogeneizzazione Codici propri interfacciati con ANSYS

26 Results from Life Sciences Results from Life Sciences (Fac. Medicine & CEINGE - Biotecnologie Avanzate) Large DataBase for genomic sequences of bacteria, vertebrates, trees. Applications CPU & Data intensive: Identification and characterization of nucleotide sequences H. Sapiens M. Musculus CSTs DG-CST (DISEASE GENE CONSERVED SEQUENCE TAGS), A DATABASE OF HUMAN–MOUSE CONSERVED ELEMENTS ASSOCIATED TO DISEASE GENES. More than 60.000 sequences identified associated to diseases.

27 DNA Proteina RNA Strutturato mRNA biological function Applications CPU & Data intensive: Gene mining

28 G. Paolella Napoli, 28/5/ 2008 28 Gene mining Execution time on GRID 1 WN Grid Large DataBase for genomic sequences of bacteria, vertebrates, trees.

29 G. Paolella Napoli, 28/5/ 2008 29 Length46,944,323 bps Total genes392 > miRNA Genes10 > rRNA Genes3 > snRNA Genes7 > snoRNA Genes8 > miscRNA8 Found known RNAs9 Transcriptome length14,609,025 Automatic annotation of genomic sequences: Search for functional RNA structures Sequences potentially transcribed has been split in overlapping fragments of 150 bp length. 290,904 sequences Results

30 G. Paolella Napoli, 28/5/ 2008 30 Bioinfo portal

31 G. Paolella Napoli, 28/5/ 2008 31 HPC on Cluster nodes GatewayGateway iPage image area data + images page iPane proc- steps IPROC architecture

32 32 Grid-aware HPC for medical images: management processing visualization Problem Solving Environment MedIGrid Results from Middleware for applications Results from Middleware for applications (Dip. Matematica e Applicazioni) (see talk by Vania Boccia)

33 Multilevel adaptive algorithms on MP multicore architectures (poster; abstract no. 92) (Dip. Matematica e Applicazioni) 1 st level: message passing among CPUs of a blade server 2 nd level: multithreading among cores of a single multicore CPU memory cores CPU memory cores CPU memory cores CPU memory cores CPU Message passing level Multithreading level While (local error > local tolerance) refine subdomains on the cores rearrange subdomains among CPUs Endwhile Parallel out-of-order task scheduling without synchronization and idle time Better efficiency on the single CPUs Subdomains reorganization without global communications Better scalability on the blade system

34 VO-Neural Project Implementation of a web application (WA), of Data Mining and visualization methodologies for complex scientific data in distributed systems. WA is intended to be a service for both astronomical and bioinformatic international communities. Virtual Observatory: objective: federation and interoperability of worldwide astronomical data archives according to the standards of the International Virtual Observatory Alliance (IVOA). Large astronomical surveys (from 100 TB to 1000 TB) requirements: patterns, trends etc in high dimensionality parametric spaces. Results from MacroCosm Sciences Results from MacroCosm Sciences (Dip. Scienze Fisiche & INAF)

35 http://nesssi.cacr.caltech.edu/dmtest/index.html International Collaboration : Università Federico II INAF - Napoli Caltech Pennsylvania State University Pune IUCAA - India Applications: Astrophysics Biology e Bioinformatics Enterprises MIRROR sites: SCOPE - UNINA NESSSI - Caltech S.Co.P.E. at Caltech DAME – Data Mining & Exploration

36 DAME offers user friendliness task for Data mining tasks. DM models now available: MLP: Multi Layer Perceptron SVM: Support Vector Machines PPS: Probabilistic Principal Surfaces DM models under developments: Bregmann co-clustering SVM-C: SVM per clustering Reti Bayesiane PCA & ICA Access to the GRID through robot-certificates (e-Token) Specific applications are offered to the user as web – applications. Photometric redshifts for galaxies and quasar Search for quasar candidates Automatic classification of AGN (Active Galactic Nuclei) by photometric multiband surveys. Talk by M. Brescia Poster by Laurino Poster by Riccio

37 Ex: Automatic classification of AGN lg 2 (gamma) lg 2 (C) Base di conoscenza spettroscopica (per addestramento SVM) 30380 objects Superficie dei parametri delle SVM Ottenuta su 110 nodi di S.Co.P.E. e = 79.69% e Seyfert: e sey = 74.76% e LINER : e LIN = 81.09% c Seyfert: c sey = 52.77% c LINER : c LIN = 91.69%

38 VIRGO interferometer at Cascina (PI) DATA INTENSIVE ALGORITHMS TO SEARCH FOR GRAVITATIONAL WAVES 1 TB /day MORE THAN 1 TB /day to be analyzed Signals from: - periodic systems (Pulsar) - coalescent binary systems (Chirp) - impulsive systems (Burst) VERY LOW SNR (SIGNAL to NOISE RATIO) HIGH COMPUTATIONAL CHALLENGE Results from Gravitational waves research Results from Gravitational waves research (Dip. Scienze Fisiche & INFN – Istituto Nazionale di Fisica Nucleare)

39 Merlino The online analysis in Virgo has been tackled via Merlino, a SMFT-based (Static Matched Filter Technique) framework, whose architecture is sketched below. Merlino: Data Analysis via Matched Filters Bosis Merlino computes the correlation between the data series and a number of signal templates, obtained by simulating the chirp signals emitted by pairs of coalescing stars with solar masses within a given range. Precision and efficiency are strongly influenced by the number of considered working points, i.e. the granularity of the search in the space of the star masses. A Grid-based Evolution of Merlino

40 Adaptive Filters for Detection of Gravitational Waves in Virgo Data Size and Computational Cost of the Analysis Data from VIRGO are characterized by a very low SNR, and thus need to be accurately filtered to actually detect the presence of the signal. However an on-line analysis requires roughly 300 Gflops to retrieve the 90 per cent of the SNR. Approach to the Analysis via Adaptive Filters The aim is to implement a rough analysis with: small signal losses (w.r.t. the use of matched filters); robustness against false detections; low computational costs (for use in real-time). The idea is to use the adaptive IIR ALE filter to reconstruct at the output the coherent component at the input. The reconstruction can then be used as (noisy) template for building a correlation detector for the analysis. infinite impulse response adaptive line enhancer (IIR ALE)

41 A Genetic Parallel Evolution of the Price's Controlled Random Search Algorithm As most of the others, the Prices algorithm is based on a matched filter approach. However, instead of adopting a fixed grid of templates, it heuristically explores the search space via a controlled random search. Parallel Genetic Price Price algorithm has been modified to improve the performances and better ensure the thoroughness of the exploration of the search space - without having to consider a too high number of working points. To these aims we parallelized the software, and introduced a genetic modification of the search procedure, which introduce some randomness in the generation of new working points, thus making the software more resilient to local minima. Furthermore more than one trial point is now generated at each step. A number of different population members are randomly chosen, and each of them is reflected through the centroid of the others, generating a new trial point. These trial points are then compared to the worst population members, and substitute them in case of better behaviour.

42 p p Large Hadron Collider (proton-proton interactions) Centre of mass energy: 14 TeV Accelerator circumference: 27 km Physics objectives: – Particle physics in the TeV energy domain – Search for Higgs boson – Search for Physics Beyond the Standard Model (supersimmetry etc.) – Precision measurements for konwn (and unkown) physics. ATLAS ALICE CMS LHCb Bunch crossing every 25 ns rate 10 9 Hz 25 interactions/b.c. High granularity detectors: 10 8 electronic channels event size ~1 MB Input data rate: 1PB/s ! But only ~100 MB/s to tape. High selectivity triggersystem (rejection power 10 7 ) Max\size of single files 2 GB, 16k files/day 10 TB/day ! Napoli in exp.ATLAS e CMS Results from Subnuclear Physics @CERN-LHC Results from Subnuclear Physics @CERN-LHC (Dip. Scienze Fisiche & INFN) (see talk by G. Carlino)

43 ATLAS Huge international effort (scientific and tecnological) 37 nations 167 institutions 2000 scientists 22 m 46 m

44 First events at the LHC (10-09-2008) (10-09-2008) ATLAS CMS Reconstructed events with HPC & Grid computing

45 Dissemination Meetings, workshops, events for dissemination of the results to research and industry communities: Le idee della ricerca al lavoro (26-27/2/08) Networking Day (15/4/08) Incontro con le imprese (16/4/08) Italian e-science2008 (27-29/5/08) Inaugurazione di SCoPE (1/12/08)

46 Beyond SCoPE High bandwidth network and services Cloud computing Scientific and industrial applications High Performance Computing e Grid Computing. Data Mining Development of algorithms and software Aerospace, Automobile Telecommunications, Informatics, Elettronics Security Chemistry, Farmaceutica, Biomedicine Transportation e logistics Finance and Economy Services for Public Cooperation with Science and Industry Cooperation with Science and Industry Interoperability and Integration in GriSù IGI EGI Interoperability and Integration in GriSù IGI EGI

47 GRISU GARR PI2S2 GARR Altri Enti e realtà SPACI OGNI INFRASTUTTURA IMPLEMENTA ALMENO UN SITE (CE+SE+WN) E REPLICA I SERVIZI COLLECTIVE SERVIZI COLLECTIVE E CORE DI OGNI INFRASTRUTTURA SUPPORTANO TUTTE LE VO 1 VO PER PROGETTO cybersar cresco cometa scope spaci

48 PORTICI BRINDISILECCE TRISAIA GRISU EGI European GRID Infrastructure DEISA IGI Italian GRID Infrastructure INFN-GRID ENEA-GRID