E ducational Applications of Supercomputing and Cyberinfrastructure KAUST Economic Development International Symposium at ISC'11, 21 June 2011, Hamburg.

Educational Applications of Supercomputing and Cyberinfrastructure

KAUST Economic Development International Symposium at ISC'11, 21 June 2011, Hamburg

Supercomputing in Science and Engineering:Economic and Technological Opportunities and Challenges

Dr. Craig A. StewartAssociate Dean, Research Technologies

Executive Director, Pervasive Technology InstituteIndiana [email protected]

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Outline

• Too many people, too few people• Inspiring young people• Examples of interesting educational activities

(roughly scaling up by participant count)• New opportunities for cyberinfrastructure at the

campus, national, and international levels (campus bridging)

• Conclusions: Education, technology, economic development

NB: License terms for slides at end

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Some definitions• Supercomputer – large, monolithic, tightly integrated computer • High Performance Computer – a more general term than

supercomputer including a wider variety of cluster types • High Throughput Computing – systems of computers that work on

nicely parallel problems with (very) low bandwidth connections• Cyberinfrastructure consists of computing systems, data storage

systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high performance networks to improve research productivity and enable breakthroughs not otherwise possible.

• eScience – large scale science increasingly carried out by global collaborations enabled by the Internet.

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Technology assertions…“…results of this discovery upon society will be greater than the imagination of the most sanguine can now distinctly conceive.”

“… will tremendously influence our national elections, will promote world understanding of social, racial, and economic problems, will influence our daily lives to a degree yet undreamed of.”

“… is becoming the town square for the global village of tomorrow.”

“The world is poised on the cusp of an economic and cultural shift as dramatic as that of the Industrial Revolution.”

“We have technology, finally, that for the first time in human history allows people to really maintain rich connections with much larger numbers of people.”

The telegraph

The television

The Internet

The WWW

The Internet

The American Biblical Repository, 1838

Franklin Dunham, 1956

Bill Gates, 1996

Steven Levy, 1997

Pierre Omidyar, 2005

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A.D.2000

A.D.1000

A.D.1

1000B.C.

2000B.C.

3000B.C.

4000B.C.

5000B.C.

6000B.C.

7000B.C.

1+ million years

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7

6

5

2

1

4

3

OldStoneAge New Stone Age

BronzeAge

IronAge

MiddleAges

ModernAge

Black Death — The Plague

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10

11

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A.D.3000

A.D.4000

A.D.5000

18001900

1950

1975

2000

2100

Future

Billions

Source: © Population Reference Bureau; and United Nations, World Population Projections to 2100 (1998).

World population growth (history & predicted)

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© Schnabel, R. 2011. ACM’s engagement in education policy.CRA Leadership Meeting. 28 Feb 2011.

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Analytics market $76B market by 2015

Information & Analytics Market$60B in 2011; 6.4% CGR 10′ - 15′

Data Mgmt & IDM$18.9B 11; ′4.2% CGR 10- 15′ ′

Content Management$6.9B 11; ′6.7% CGR 10- 15′ ′

Info Integration & MDM$4.9B 10; ′8.3% CGR 10-’15′

Analytic Applications$7.3B 11; ′7.0% CGR 10- 15′ ′

DW DBMS$6.9B 11; ′7.1% CGR 10- 15′ ′

Source: GMV 2H10 (incl. analytic applications)

BI Platform & PM$15.0B 11; ′7.7% CGR 10- 15′ ′

SPSS

© IBM, Inc.

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The conundrum

• Technology will not solve our problems by itself• We do not have enough knowledge workers• People in many parts of the globe do not have

access to education that will enable them to fill the jobs of today and tomorrow

• Colleges and universities are not recruiting and retaining enough students to fulfill demand for students with CSTEM skills in general and advanced computing skills in particular

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We need people comfortable with critical thinking and computational thinking

• Critical thinking skills • Computational thinking skills– Conceptualizing, not programming– Fundamental, not rote skill– A way that humans, not computers, think– Complements and combines mathematical and

engineering thinking– Ideas, not artifacts– For everyone, everywhere

From: Wing, J.M. Computational thinking. 2006. Communications of the ACM. 49(3): 33-35

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Inspiration matters!

© Estes-COX Inc. www.estesrockets.com

Two young model and model rocket builders, shortly after claiming world record for continuous model building at 37 hours and 40 minutes (quickly surpassed by others) April, 1973

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Ready, Set Robots! Camp @ PTI 2010

Mike Boyles, AVL, Research Technologies, UITS / PTI giving demo

From 3D movie What is Cancer? by Albert WilliamIUPUI, SOIC, AVL, Research Technologies, UITS / PTI

© Matthew King, student in IU professorMargaret Dolinsky's Digital Art class

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Games are not reality

PolarGrid

Photos courtesy of Keith Lehigh and Matt Link, Indiana UniversityGeoffrey Fox, PI. PolarGrid 13

Je’aime Powell, Elizabeth City State University graduate researcher on Greenland expedition, 2009.

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SC ‘08 Cluster Challenge

IU / Dresden team – organized within IU side by Dr. Andrew Lumsdaine, Director, Open Systems Lab and Center for Scalable Computing, PTI, and Professor, School of Informatics and Computing; and Matt Link and D. Scott McCaulay, Directors, Research Technologies, UITS / PTI

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Guitar workshop

Photos courtesy of Rebecca Lowe, Open Systems Lab, SOIC and PTI, Indiana University. Guitar workshop sponsored by Dr. Andrew Lumsdaine, Director, Open Systems Lab and Center for Scalable Computing, PTI; and Professor, School of Informatics and Computing

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Minority Engineering Advancement Program @ IUPUI

Use the Bootable Cluster CD with the “Game of Life” to demonstrate speedup

LittleFe - small integrated cluster

Matt Link, Director, Research Technologies,UITS; and Associate Director, Center forScalable Computing, PTI

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LittleFe“LittleFe is a complete 6 node Beowulf style portable computational cluster. The entire package weighs less than 50 pounds; easily travels; and sets-up in 5 minutes. Current generation LittleFe hardware includes multi-core processors and GPGPU support enabling support for shared memory parallelism, distributed memory parallelism, and hybrid models. By leveraging the Bootable Cluster CD project, and the Computational Science Education Reference Desk LittleFe is a powerful, ready-to-run, computational science and parallel programming educational platform for the price of a high-end laptop.”http://LittleFe.net

Photo courtesy Charlie Peck, Earlham College. © Earlham College.

18Images © Beth Plale, Professor, School of Informatics & Computing; Director, Data to Insight Center, PTI

LEAD (Linked Environments for Atmospheric Discovery) & LEAD II – an example Science Gateway

Meteorology researchers used data and images generated by LEAD II while chasing tornadoes.

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WxChallenge & LEAD II

www.wxchallenge.com. Screen image © University of Oklahoma.

In support of the 2010 Vortex2 campaign, LEAD II successfully executed 214 workflows, used 109,568 CPU hours, generated 215 GB of data and over 9,100 2D products.

http://pti.iu.edu/d2i/leadii-vortex2 Image © Trustees of Indiana University

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nanoHUB

Screen Image © Network for Computational Nanotechnology (nanohub.org/groups/ncn).

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nanoHUB usage

nanoHUB usage, September 2010. Red dots: tutorial and seminar use. Yellow dots: online simulation use. Size of dot indicates number of users from location. Annually nanoHUB serves over 170,000 users in 172 countries.

© Gerhard Klimeck, Network for Computational Nanotechnology (nanohub.org/groups/ncn). Used by permission. May not be reused without permission.

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@home projects (based on BOINC)

docking.cis.udel.edu Image Courtesy of Michela Taufer, GCLab, U. Delaware. © U. Deleware

http://escatter11.fullerton.edu/nfs/. Image courtesy Dr. Greg Childers, and © California State University, Fullerton.

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You don’t need access to a supercomputer to teach parallel computing… or data-intensive computing

• Multicore & GPUs• LittleFe• Cloud providers• Citizen Science – access to

and participation in authentic science

Photograph © Chris Eller, Advanced VisualizationLab, Research Technologies, UITS; and PTI

physicsworld.com/cws/article/news/2738© Institute of Physics. Reused underLicensing terms @ physicsworld.com/cws/copyright

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Campus bridging• Campus bridging is the seamlessly integrated use of

cyberinfrastructure operated by a scientist or engineer with other cyberinfrastructure on the scientist’s campus, at other campuses, and at the regional, national, and international levels as if they were proximate to the scientist, and when working within the context of a Virtual Organization (VO) make the ‘virtual’ aspect of the organization irrelevant (or helpful) to the work of the VO.

• Campus bridging material: http://pti.iu.edu/campusbridging/

• ACCI Taskforce final reports: http://www.nsf.gov/od/oci/taskforces/

Commercial cloud (Iaas and Paas)

Volunteer computing

Workstations at Carnegie research

universities

Campus HPC/ Tier 3 systems

Track 2 and other major facilities

NSF Track 1

0 2000 4000 6000 8000 10000 12000

Estimated Computing Capacity (TFLOPS)

Data at http://hdl.handle.net/2022/13136

TFLOPS

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Single lab biological instrumentsType of instrument Model Raw image

dataData products

Light Microscopy BD Pathway 855 Bioimager N/A 7 GB/day

Genome sequencing

Roche 454 Life Sciences genome analyzer system

39 GB/day 9 GB/day

Illumina-Solexa genome analyzer system

367 GB/day 100 GB/day

ABI SOLID 3 238 GB/day 150 GB/day

Microarray Gene Expression Chip Reader

Molecular Devices GenePix Professional 4200A Scanner

N/A 8 MB/day

Microarray Gene Expression Chip Reader

NimbleGen Hybridization System 4 (110V)

N/A 300 MB/day

Several Task Force recommendations to the NSF re Hardware and networking: Much more attention to data and networking challenges!

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Cyberinfrastructure is infrastructure

Strategic Recommendation to the NSF: NSF must lead the community in establishing a blueprint for a National CI

CI software must be mademore robust

National Science Foundation. Investing in America’s Future: Strategic Plan FY 2006-2011. September 2006. Available from: http://www.nsf.gov/pubs/2006/nsf0648/nsf0648.jsp

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Examples of mature and maturing systems & software

DEISA

UK eScience Grid

NSF CIF 21 (CyberinfrastructureFramework for 21st Century Science and Engineering

ROCKS (www.rocksclusters.org)

Condor (www.condor.org)

© DEISA. http://www.deisa.eu/usersupport/user-documentation/unicore-5-in-deisa/job-submission-through-unicore-5/DEISA-UNICORE-Figure01.png/image_preview

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Critical challenge: curriculum materials

http://ocw.mit.edu/index.htm Used under Creative Commons License – Attribution-NonCommercial-ShareAlike 3.0 United States (CC BY-NC-SA 3.0) http://creativecommons.org/licenses/by-nc-sa/3.0/us/

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Existing curriculum resources• MIT Computer Science & Engineering curriculum –

web.mit.edu/catalog/degre.engin.ch6.html• ACM – www.acm.org/education/curricula-recommendations• TCPP (Technical Committee on Parallel Programming) tcpp.cs.gsu.edu/

– CORE COURSES: • CS1 Introduction to Computer Programming (First Courses) • CS2 Second Programming Course in the Introductory Sequence • Systems Intro Systems/Architecture Core Course • DS/A Data Structures and Algorithms • DM Discrete Structures/Math ADVANCED

– ELECTIVE COURSES: • Arch 2 Advanced Elective Course on Architecture• Algo 2 Elective/Advanced Algorithm Design and Analysis• Lang Programming Language/Principles (after introductory sequence) • SwEngg Software Engineering • ParAlgo Parallel Algorithms • ParProg Parallel Programming • Compilers Compiler Design

– IMHO: The TCPP curriculum demonstrates the need for more attention to computational thinking in K-12 education

University ofArkansas

Indiana University

University ofCalifornia atLos Angeles

Penn State

Iowa

Univ.Illinois at Chicago

University ofMinnesota Michigan

State

NotreDame

University of Texas at El Paso

IBM AlmadenResearch Center

WashingtonUniversity

San DiegoSupercomputerCenter

Universityof Florida

Johns Hopkins

July 26-30, 2010 NCSA Summer School Workshophttp://salsahpc.indiana.edu/tutorial

300+ Students learning about Twister & Hadoop MapReduce technologies, supported by FutureGrid.

Slide © Judy Qiu, SOIC and SALSA Lab, PTI

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Economies of scale in training

Image from TeraGridEOT: Education, Outreach, and Training 2010. https://www.teragrid.org/web/news/news#2010scihigh

Photo courtesy Robert Quick,Research Technologies & PTI.OSG Grid School in Sao Paulo Brazil, January 2011

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Great challenges, great opportunities

• Challenges– Matters such as human impact on the global environment will

be most successfully addressed with fact-based consensus approaches.

– More countries must have the skill and access to technology to do their own modeling

• Cyberinfrastructure and education opportunities – If we can treat cyberinfrastructure more like infrastructure …

we can focus on the challenging / important / fun work– Robust cyberinfrastructure => reusable educational materials– Data-intensive science creates tremendous need and

opportunity in education and application– While we are busy improving the pipeline of talent, involving

undergrads in research may greatly improve the % of the existing pipeline that pursues an advanced technology career

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New economic growth opportunities

• VOs and opportunities they provide for research• Digital manufacturing (new opportunities in a

different approach to globalization)• Sustainable societies• With better education in supercomputing, and all

forms of high performance computing, people may enable us to achieve some of the technology nirvana described at beginning of talk

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This talk is dedicated to the memory of Truman O. Stewart

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Additional information• Droegemeier, K., B. Plale, M. Ramamurthy, and C. Mattocks, "A New

Approach for Using Web Services, Grids, and Virtual Organizations in Mesoscale Meteorological Research" 25th Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology (IIPS), 01/2009.

• Stewart, C.A., S. Simms, B. Plale, M. Link, D. Hancock and G. Fox. 2010. What is Cyberinfrastructure? In: Proceedings of SIGUCCS 2010 (Norfolk, VA, 24-27 Oct, 2010). http://portal.acm.org/citation.cfm?doid=1878335.1878347

• http://www.computinginthecore.org/ − “a non-partisan advocacy coalition … to elevate computer science education to a core academic subject in K-12 education …

• http://hubzero.org/resources/408/ Exploring the Impact of nanoHUB.org on Research and Education

• Cohen, D. 2006. Globalization and Its Enemies. MIT Press

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Acknowledgments• Thanks to King Abdullah University of Science and Technology for

the opportunity to present today (Through Inspiration, Discovery indeed!)

• Malinda Lingwall for editing, graphical work, and fact-finding/checking

• Ready, Set, Robots! Camp: Daphne Siefert-Herron, Kurt Seiffert, Kristy Kallback-Rose, Danko Antolovic, Jenett Tillotson, Therese Miller

• MEAP: David Hancock, Andrew Arenson, Rich Knepper, Kurt Seiffert, Matt Link (Research Technologies, UITS, Research Technologies, PTI); Patrick Gee, Mark Russell

• Thanks to all of the IU Research Technologies staff and Pervasive Technology Institute students, staff, and faculty who have led or been involved in the IU projects described here

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Acknowledgments• Many of the scientific workflow examples here use the IU Data Capacitor – project led by

Steve Simms, Research Technologies, UITS, & PTI. http://pti.iu.edu/dc/ NSF CNS 05-21433• LEAD: Beth Plale, IU (SOIC-PTI) funded by NSF 0331480• PolarGrid: NSF 0723054 (G. Fox, PI)• FutureGrid: NSF 0910812 (G. Fox, PI)• nanoHUB: nanoHUB.org is operated by Network for Computational Nanotechnology (NCN).

NCN was funded by the National Science Foundation (NSF) under various grants. • Development and support of nanoHUB is also supported in part by the HUBzero consortium,

of which IU is a member. • Campus Bridging: NSF 040777, 1059812, 0948142, 1002526, 0829462• LittleFe: Support from TeraGrid, SC Conference, Intel Corporation and Earlham College.• Lilly Endowment for its support of IU through INGEN, METACyt, and the Pervasive

Technology Institute• Tevfik Kosar, who as Chair of DIDC ‘10 invited me to present the Keynote presentation at the

Third International Workshop on Data Intensive Distributed Computing (DIDC'10). “It’s not a data deluge – it’s worse than that.” Several slides from that talk are reused here. That original talk is available : http://hdl.handle.net/2022/13195

• Thanks to those individuals who gave permission to use images presented in this talk• Any opinions presented here are those of the presenter and do not necessarily represent the

opinions of the National Science Foundation, the Lilly Endowment, the NSF ACCI, NSF ACCI Task Force on Campus Bridging, or any other funding agencies or organizations

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License terms• Items indicated with a © are under copyright and used here with permission. Such

items may not be reused without permission from the holder of copyright except where license terms noted on a slide permit reuse.

• Please cite this presentation as: Stewart, C.A. “Educational Applications of Supercomputing and Cyberinfrastructure.” Presentation at KAUST Economic Development International Symposium at ISC'11, 21 June 2011. Available from: http://hdl.handle.net/2022/13365

• Except where otherwise noted, contents of this presentation are copyright 2011 by the Trustees of Indiana University.

• This document is released under the Creative Commons Attribution 3.0 Unported license (http://creativecommons.org/licenses/by/3.0/). This license includes the following terms: You are free to share – to copy, distribute and transmit the work and to remix – to adapt the work under the following conditions: attribution – you must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). For any reuse or distribution, you must make clear to others the license terms of this work.

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Questions?

And thank you for your kind attention….