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Opportunities for CyberInfrastructure at the Cornell Nanoscale Facility Garnet Kin-Lic Chan Department of Chemistry and Chemical Biology Cornell University.

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Presentation on theme: "Opportunities for CyberInfrastructure at the Cornell Nanoscale Facility Garnet Kin-Lic Chan Department of Chemistry and Chemical Biology Cornell University."— Presentation transcript:

1 Opportunities for CyberInfrastructure at the Cornell Nanoscale Facility Garnet Kin-Lic Chan Department of Chemistry and Chemical Biology Cornell University

2 Who I am Modeling at the Cornell Nanoscale Facility Opportunities for CyberInfrastructure for Nanoscale modeling  Software Infrastructure Random ideas about the Web

3 Who am I? Ab-initio Quantum Chemistry / Electronic Structure theory Method development for large systems  Renormalization Group methods for multi- scale phenomena  Ab-initio DMRG, Canonical Transformation Theory Correlated materials problems  Conjugated Polymers, Surface chemistry Quantum transport in nanoscale structures User of CCMR and CNF modeling facilities Conjugated Polymers Low-temperature Kondo regime in Metal complexes

4 Experimental facilities are not data-intensive Primary use of computing/cyberinfrastructure is materials modeling Secondary use is for social aspects e.g. education / communication / documentation The Cornell Center for Materials Research and the Cornell Nanoscale Facility

5 Cornell Nanoscale Modeling Facility The National Nanostructure Infrastructure Network (http://www.nnin.org)http://www.nnin.org Computational mission of CNF: Develop modeling resources that complement and expand on the current experimental capabilities. Development of new computing clusters. Acquisition of commercial software packages. Construction of new codes to address user needs. Expansion and distribution of localized programs to user network. Web based access – truly remote research Main Computation Nodes Cornell Harvard Stanford University of Texas, Austin University of Michigan Courtesy Derek Stewart

6 Computing Power  Cornell Nanoscale Facility 48 node dual processor Xeon (3.06 GHz) cluster 16 AMD 64 bit Opteron workstations  Harvard University 48 node dual processor Xeon (3.06 GHz) cluster 4 4-way 32 GB Opterons from Sun Microsystems (coming soon!)  University of Texas, Austin Access to 600 processor Xeon cluster 224 (1.3 GHz) Power4 processor cluster  Stanford and University of Michigan (resources coming soon!) Computational Resources available across the country Duffield Hall

7 A Platform for more than just computation… Services to encourage collaboration and enhance existing tools.  Web based discussion groups that allow new users to learn from existing users.  A conduit for codes developed by localized groups to reach a larger audience (beta testing, optimizing, streamlining)  Creation of input file libraries for different programs

8  Develop modeling resources that complement and expand on the current experimental capabilities.  Services to encourage collaboration and enhance existing tools 1.Software infrastructure 2.Web-based initiatives How can we use CI for the CNF’s mission?

9 Software infrastructure for nanoscale modeling Multiscale Inhomogeneous  Neither periodic nor isolated Multiple energy scales  Electronic, vibrational, electromagnetic Fundamental algorithms, but also enabling software infrastructure Interoperable components

10 Interoperabilitiy Many levels of theory Each level has multiple algorithms implemented in different packages  Continuum models  Force-field Tinker, NAMD, Moldy etc.  Kinetic Monte Carlo  Density Functional Theory ABINIT, SIESTA, PWSCF, DFT++  Ab-initio quantum chemistry Gaussian, QCHEM, GAMESS, MOLPRO Any successful multiscale method cannot adopt a monolithic approach but must reuse components Scientific issues: different choice of basis Computer science issues: e.g. conversion of formats

11 Where can we look? Software industry  CORBA, DCOM, SOAP, XML, RPC  Standard interfaces e.g. BLAS, LAPACK But - cultural challenges  Scientific modeling companies are notoriously competitive  No motivation for academic scientists  Deciding on an implementation is not enough: it has to be implemented (and free).

12 Example 1: OpenBabel http://openbabel.sourceforge.net/ “Open Babel is a community-driven scientific project including both cross-platform programs and a developer library designed to support molecular modeling, chemistry, and many related areas, including interconversion of file formats and data.” Over 70 different formats babel [OPTIONS] [-i input-type] infile [-o output-type] outfile But only for structural and geometric information For true multiscale modeling, require more sophisticated conversion e.g. wavefunctions, orbitals, density matrices, potentials Data-intensive e.g. many-particle wavefunctions

13 Example 2: EMSL Gaussian Basis Set Order Form (PNNL) http://www.emsl.pnl.gov/forms/basisform.h tml Standardised repository for basis sets for quantum chemistry calculations Produces outputs for essentially every QC package Used by 100% of quantum chemists

14 Issues Where is the boundary between CyberInfrastructure and traditional materials modeling algorithm development?

15 The Web Web-based frontends (“enhancing existing tools”)  e.g. WebMO frontend to Gaussian / GAMESS  http://www.webmo.net/ http://www.webmo.net/  Users draw structures in browser, submit to remote server, used successfully e.g. in Cornell CHEM765  Essentially Web-mail as opposed to mail-client  Convenient, but really necessary?

16 The thing of the moment: Flickr, MySpace, Facebook Set up Facebook for Nanoscale scientists  “Experts” database  But cultural barriers Virtual conferences?  Useful – but NSF funding? Social networking (“collaboration”)

17 Wikis (“collaboration”) Accessible web-pages, anyone can edit simply by clicking and typing Used in my lab for announcements, electronic workbooks, research notes, paper repository Highly recommended! Several people have made suggestions already e.g. for material specific wikis

18 Issues: Global vs specific To what extent should we create specialized sites with a restricted user community? To what extent should we control the content? Many of the revolutionary aspects of cyberinfrastructure revolve around a truly global community  E.g. Google – one place to search, do not search by categories as in early engines  Wikipedia, one stop place for all information  Should we make an official contribution to these sites rather than set up our own?


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