1. Panel on: DEFINING the “GRID” Moderator: Frederica Darema, NSF Panelists: Fabrizio Gagliardi, Microsoft Ian Foster, ANL & UofChicago Geoffrey Fox, Indiana U. Filia Makedon, NSF & Dartmouth Ed Seidel, Louisiana State U.

2. 2 Intent of this discussion This panel is intended as a venue to present some views and open a dialogue for discussion What is a “grid”? –what’s the fuss about it? –scope? several views of a grid? –past, present, emerging grids? Define a process for a comprehensive, concise definition of what’s a grid

3. 3 What is Grid Computing? coordinated problem solving on dynamic and heterogeneous resource assemblies IMAGING INSTRUMENTS COMPUTATIONAL RESOURCES LARGE-SCALE DATABASES DATA ACQUISITION,ANALYSIS ADVANCED VISUALIZATION Example: “Telescience Grid”, Courtesy of Ellisman & Berman /UCSD&NPACI

4. 4 A bit of history…and trends… The “grid concept” which in the mid-90’s was the purview of a few academics is now entrenching the industrial sector In some ways the grid started systematizing ideas that preceded it –like distributed computing environments (DCEs) The first demos of “grids” starting with the I-Way at SC’95 Followed by several demos (~97-…)of distributing a single application on multiple, geographically distributed nodes

5. 5 In the (recent) beginning.. The efforts that started in the mid-90’s had an emphasis more akin to the parallel, cluster, NOWs, and metacomputing environments. –they were a step beyond the high-end (supercomputer) parallel, or cluster, or NOW systems –placed emphasis on creating computational capabilities where a single application can be partitioned and deploy multiple, heterogeneous and geographically distributed platforms, –where each of these “nodes” could in itself be a high-end (supercomputer) system, in other words, the grid was originally viewed as a means of increasing the computational (mips & flops) power, –beyond the high-end or supercomputers of that time. The dominant term for such grids has been: computational grids.

6. 6 Revisiting and building on the past… Together with efforts that built upon the notions of DCEs, and as computational grids’ environments enabled larger applications to execute, few other aspects have become apparent: 1) larger capabilities also entailed larger and often distributed sets of data (consumed or produced by such applications) and 2) application models that incorporate multiple modalities of the application system (complex application models). These aspects, pointed to other modalities of “grids”, more akin to the notions of DCE’s, where grids enable executing the various models of complex applications on different (and perhaps specialized) platforms of such a grid. Notions like workflow, which were popular in the late 80’s and early 90’s for CIM (Computer Integrated Manufacturing) applications are again finding their way to the present grids. Notions of VMs also are brought again in the forefront Furthermore grids are becoming coupled with the notion of collaboratories, leading to notions of various grid communities….

7. 7 Moving forward… Dynamic Data Driven Application Systems (DDDAS) A new paradigm for applications/simulations and measurement methodologies PROGRAM SOLICITATION NSF05-570 Sponsored by NSF, NIH, NOAA Cooperating Programs: EU Grids & e-Infrastructure, and UK e-Sciences Solicitation announced on March 10, 2005 Proposals received: June 13, 2005 Awards made by end of Sept, 2005

8. 8 Measurements Experiments Field-Data User Theory (First Principles) Simulations (Math.Modeling Phenomenology) Experiment Measurements Field-Data (on-line/archival) User Theory (First Principles) Simulations (Math.Modeling Phenomenology Observation Modeling Design) OLD (serialized and static ) NEW PARADIGM (Dynamic Data-Driven Simulation Systems) Challenges : Application Simulations Development Algorithms Measurement Instruments Interfaces Computing Systems Support Dynamic Feedback & Control Loop What is DDDAS (Symbiotic Measurement&Simulation Systems)

9. 9 DDDAS: Beyond Grid Computing New Capabilities in Applications and Measurements --dynamic integration between applications&measurements--- COMPUTATIONAL RESOURCES DATA ACQUISITION,ANALYSIS ADVANCED VISUALIZATION

10. 10 Beyond Grid Computing “Extended Grid’: the Application Platform is the computational&measurement system Applications Computational Platforms Instruments Sensors Archival/ Stored Data MeasurementsComputational Grids

11. 11 Examples of Programmatic Support: Programs like –the DARPA QUORUM Program (1996-2002) were motivated to support grids along the directions of DCE, RT, &… also supported computational grids. While programs like –the DARPA Systems Environments (1996-1998), –the NASA Information Powergrid (IPG, 1996-2002), –and later DOE Science Grid - SciDAC program (2000 – present?) placed emphasis in enhanced computational capabilities provided by grids, More recently: –the NSF Next Generation Software Program (NGS, 1998-2004) –the NGS follow-up Computer Systems Research (AES&SMA) (2004-present) –and the NSF Middleware Initiative (2000-present) emphasize both aspects of the grids, the first two with research emphasis the later with infrastructure emphasis. Emerging and future directions, Dynamic Data Driven Applications Systems (DDDAS), (2000 -…) further extend the present notions of the “grid” PLUS several Programs in EU, UK, Asia, AU

12. 12 The challenge and the opportunity All these aspects and grid modalities give the impression of a non-coherent view of what is the “grid” it looks like the proverbial ‘parts of an elephant’. Furthermore, emerging technologies and concepts, such as: –sensors and sensor networks, –dynamically integrated computational and observational systems point to environments which further extend the grid notions Do we have multiple grid instantiations? an “amoeba grid”? But even so can we have a comprehensive all encompassing definition? For these reasons, it behooves us to have a discussion for defining a concerted notion of the “grid concept”

13. 13 This panel, consisting of developers and users of grid technologies advances, and notable visionaries, will discuss their views of what’s the “grid” and how to lay the foundation of a definition for the grid

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15. 15 Experiment Measurements Field-Data User Simulations (Math.Modeling Phenomenology Observation Modeling Design) Dynamic Feedback & Control Loop DDDAS has potential for significant impact in science, engineering, and commercial world, akin to the transformation effected since the ‘50s by the advent of computers NSF05-570 www.cise.nsf.gov/dddas Proposal Deadline: June 13, 2005 Enabling the DDDAS vision rests on the creativity and resourcefulness of the research community