WTEC International Assessment of Simulation-Based Engineering and Science: Education Celeste Sagui North Carolina State University Sharon Glotzer University

WTEC International WTEC International

Assessment ofAssessment of

Simulation-Based Simulation-Based

Engineering and Science: Engineering and Science:

EducationEducation

Celeste SaguiCeleste SaguiNorth Carolina State UniversityNorth Carolina State University

Sharon GlotzerSharon GlotzerUniversity of MichiganUniversity of Michigan

Sponsors: NSF, DOE, DOD, NIH, NASA, NIST SIAM, CSE09www.wtec.org/sbes

Simulation-Based Simulation-Based Engineering & ScienceEngineering & Science

SBE&S involves the use of computer modeling and simulation to solve mathematical formulations of physical models of engineered and natural systems

SBE&S – or computational science & engineering – is an established (though not mature) field.

C. Sagui and S. Glotzer SIAM, CSE09www.wtec.org/sbes

SBE&S: Why now?SBE&S: Why now?

A tipping point in SBE&S Computer simulation is more pervasive today, and having more impact, than ever before - hardly a field untouched

Fields are being transformed by simulation

Reached a useful level of predictiveness; complements traditional pillars of science

C. Sagui and S.C. Glotzer

SIAM, CSE09www.wtec.org/sbes


A tipping point in SBE&S Computers are now affordable and accessible to researchers in every country around the world.

The near-zero entry-level cost to perform a computer simulation means that anyone can practice SBE&S, and from anywhere.

“Flattening world” of computer simulation that will continue to flatten - everyone can do it.

C. Sagui and S. Glotzer SIAM, CSE09www.wtec.org/sbes

SBE&SBE&S: Why now?S: Why now?

A tipping point in SBE&S US, Japanese, EU companies are building the next generation of computer architectures, with the promise of thousand-fold or more increases of computer power coming in the next half-decade.

These new massively multicore computer chip architectures will allow unprecedented accuracy and resolution, as well as the ability to solve the highly complex problems that face society today.




A tipping point in SBE&S The toughest scientific and technological problems facing society today are big problems: alternative energy sources and global warming sustainable infrastructures mechanisms of life, curing disease and personalizing

medicine.

These problems are complex and messy, and their solution requires a partnership among experiment, theory and simulation, and among industry, academia and government, working across disciplines.




Simulation is key to scientific discovery and engineering innovation. Recent reports argue the United States is at risk at losing of its competitive edge.

Our continued capability as a nation to lead in simulation-based discovery and innovation is key to our ability to compete in the 21st century.



Previous SBES studyPrevious SBES study

Our study builds upon previous efforts: Workshops run by NSF

Engineering Directorate NSF Blue Ribbon Panel

report chaired by J. Tinsley Oden, May 2006 - lays out intellectual arguments for SBES

SBES broadened to SBE&S

& many previous reports on computational science

http://www.nsf.gov/pubs/reports/sbes_final_report.pdf

WTEC SBE&S Study WTEC SBE&S Study SponsorsSponsors

To inform program managers in U.S. research agencies and decision makers of the status, trends and activity levels in SBE&S research abroad, these agencies sponsored this study: National Science Foundation (NSF) Department of Energy Department of Defense National Institutes of Health NASA National Institute of Standards and Technology

SIAM, CSE09

Overall Scope & Overall Scope & Objectives of WTEC Objectives of WTEC International StudyInternational Study

Study designed to: Gather information on the worldwide status and trends of SBE&S research State of the art, regional levels of activities US leadership status Opportunities for US leadership

Disseminate this information to government decision makers and the research community

Findings, not recommendations



Primary thematic areas Life sciences and medicine Materials Energy and sustainability

Core cross-cutting issues Next-generation algorithms and high

performance computing Multiscale simulation Simulation software Validation, verification, and quantifying

uncertainty Engineering systems Big data and data-driven simulations Education and training Funding

Structure of StudyStructure of Study



The SBE&S Study TeamThe SBE&S Study Team

Panelists

Sharon Glotzer (Chair), U Michigan

Sangtae Kim, NAE (Vice-chair), Purdue

Peter Cummings, Vanderbilt/ORNL

Abhi Deshmukh, Texas A&M

Martin Head-Gordon, UC Berkeley

George Karniadakis, Brown U

Linda Petzold, (NAE) UC Santa Barbara

Celeste Sagui, NC State U

Matsunoba Shinozuko, (NAE) UC Irvine

Advisors

Tomas de la Rubia, LLNL

Jack Dongarra, (NAE) UTK/ORNL

James Duderstadt (NAE), U Michigan

David Shaw, D.E. Shaw Research

Gilbert Omenn (IOM), U Michigan

J. Tinsley Oden (NAE), UT Austin

Marty Wortman, Texas A&M

Study Process & TimelineStudy Process & Timeline

US Baseline Workshop November 2007 Bibliometrics analysis Panel visited 57 sites in Europe, Asia

Universities, national labs, industrial labs Also: conversations, reports, research papers, bibliometric analysis provided basis for assessment

Public workshop on study findings in April 2008 Final report now in review Research directions planning workshop in April 2009



Major Trends in Major Trends in SBE&S ResearchSBE&S Research


Life sciences & medicine, Life sciences & medicine, materials, and energy & materials, and energy &

sustainability are among most sustainability are among most likely sectors to be likely sectors to be transformed by SBE&Stransformed by SBE&S

SBE&S is changing the way disease is treated, the way surgery is performed and patients are rehabilitated, the way we understand the brain

SBE&S is changing the way materials & components are designed, developed, and used in all industrial sectors E.g. ICME (National Academies Report 2008, T. Pollock, et al)

SBE&S is aiding in the recovery of untapped oil, the discovery & utilization of new energy sources, and the way we design sustainable infrastructures


IAM, CSE09www.wtec.org/sbes

Findings: Top FourFindings: Top FourMajor Trends in SBE&S Major Trends in SBE&S

ResearchResearch

1. Data-intensive applications (esp Switzerland and Japan)1. Integration of (real-time) experimental and observational

data with modeling and simulation to expedite discovery and engineering solutions

2. Millisecond timescales for proteins and other complex matter with molecular resolution

3. Science-based engineering simulations (US slight lead)1. Increased fidelity through inclusion of physics and chemistry

4. Multicore for petascale and beyond: not just faster time to solution - increased problem complexity1. Cheap GPUs today give up to 200x speed up on hundreds of

apps!



Threats to Threats to United States United States Leadership in Leadership in

SBE&SSBE&S

SIAM, CSE09C. Sagui and S.C. Glotzer

Some general trends: R&D Some general trends: R&D “map”“map”

Figure from the council on Competitiveness Competitiveness Index: Where America stands (2007). Data from Main Science and Technology Indicators

2006 (OECD 2006).

US share of global US share of global output in S&Toutput in S&T

Figure from the council on Competitiveness Competitiveness Index: Where America stands (2007). Data from Main Science and Technology Indicators 2006 (OECD 2006); NSF’s Science and Engineering Indicators (NSB 2006), and the U.S. Patent and Trademark Office.

Threats to US leadership Threats to US leadership in SBE&Sin SBE&S

Education ImpactsEducation Impacts

Finding 1: The world of computing is flat, and anyone can do it. We must do it better, and exploit new architectures before those architectures become ubiquitous crucial to train next generations of SB engineers and scientists.



Threats to US Threats to US leadership leadership in SBE&Sin SBE&S

Top 500 list: US at top today. But Japan, France, Germany have world-class resources, faculty and students and are committed to HPC/SBE&S for long haul. Japan has an industry-university-govt roadmap out to 2025 (exascale)

Germany investing nearly US$1B in new HPC push, also with EU Cheap to start up, hire in SBE&S (e.g. India)

100M NVIDIA GPUs w/CUDA compilers worldwide Every desktop, laptop, etc. with NVIDIA card in last two years Speed-ups of factors up to 1000. Applications from every sector.



Threats to US leadership in Threats to US leadership in SBE&SSBE&S

Education ImpactsEducation Impacts

Finding 2: A persistent pattern of subcritical funding overall for SBE&S threatens US leadership and continued needed advances amidst a recent surge of strategic investments in SBE&S abroad. The surge reflects recognition by those countries of the role of simulations in advancing national competitiveness and its effectiveness as a mechanism for economic stimulus.



Threats to US Threats to US leadership leadership in SBE&Sin SBE&S

Finding 3: Inadequate education and training of the next generation of computational scientists threatens global as well as US growth of SBE&S. This is particularly urgent for the US, since such a small percentage of its youths go into S&E.



US has most citations and top-cited publications but EU has surpassed in number of articles

Education and Training: Education and Training: some statisticssome statistics

S&E articles and citations in all fields. From Science and Engineering Indicators 2008

(NSB 2008).

US has been surpassed in number of PhDs in S&E


Number of PhDs earned in Europe, Asia and North America (2004). From Science and

Engineering Indicators 2008 (NSB 2008).

Left: Foreign students enrolled in tertiary education, 2004. Right: S&E doctoral degrees earned by foreign students


S&E Indicators

(2008)

Academic R&D share of all R&D, for selected countries (S&E Indicators, 2008)


Natural Sciences and Engineering degrees per hundred 24-year olds, by country (S&E Indicators, 2008)


S&E postdoctoral students at US universities, by citizenship (S&E Indicators, 2008)

Percentage of visa post-docs:

-Biological Sciences: 59%

-Computer Sciences: 60%

-Engineering: 66%

-Physical Sciences: 64%


Education and Education and Training:Training:

Key FindingsKey Findings


Finding 1: (a) Increasing Asian leadership due to funding allocation and industrial participation in education

Japan committed to HPC, and leads US in bridging physical systems modeling to social-scale engineered systems Japan Earth Simulation Center (Life Simulation Center): developing new algorithms, specially

multiscale and multiphysics. Govt investing in software; innovation in algorithms will drive hardware.

Systems Biology Institute (Japan): funded by Japanese government for 10 years. Software infrastructure: Systems Biology Markup Language (SBML), Systems Biology Graphical Notation (SBGN), CellDesigner, and Web 2.0 Biology. Difficult to publish software, the merit system in this lab values software contributions as well as publications.

University of Tokyo: “21st Century Center of Excellence (COE) Program” 28 worldclass research and education center in Japanese Universities Global COE

Singapore and Saudi Arabia – $$$ in S&E (KAUST university, with $80B endowment)

Increased China and India presence in scientific simulation software R&D and SBE&S over next decade due to new academic & industry commitment, new government $$ Institute of Process Engineering (P.R. China): 50% of research funding comes from industry

(domestic and international; significant funding from the petro-chemical industry). Significant government funding through the National Natural Science Foundation of China and the Ministry of Science and Technology (main focus: multiscale simulations for multiphase reactors ).

Tsinghua University Department of Engineering Mechanics: Strong interaction of R&D centers with industry and multinational companies.

Fudan University, Shanghai: strong emphasis on education, first analytical work then computational. Prof. Yang is director of leading computational polymer physics group and Vice Minister of Education; has allocated funding for SBE&S and for 2000 students/year to study abroad.

Finding 1: (a) Increasing Asian leadership due to funding allocation and industrial participation in education

China not yet a strong US competitor, but SBE&S “footprint” changing rapidly China contributes 13% of the world’s output in simulation papers, second to US at

27% and growing (but publish in <1st tier journals and cited less) Non-uniform quality overall, but many high quality examples

Strategic change towards innovation, and recognition by industry and State that innovation requires simulation China’s S&T budget has doubled every 5 years since 1990

70% to top 100 universities (80% all PhDs, 70% all , 50% all international,30% all UGs)

Recognition of need to train new generation of “computationally-savvy” students, and new State $$$ to do this under new VM of Education

>211 Fund: US$1B/year, all projects must have integrated simulation component

Finding 1: (b) Increasing European leadership due to funding allocation and industrial participation in education

Center for Biological Sequence Analysis (Bio-Centrum-DTU, Denmark): Danish Research Foundation, the Danish Center for Scientific Computing, the Villum Kann Rasmussen Foundation and the Novo Nordisk Foundation (US$100M), other institutions in European Union, industry and the American NIH (bioinformatics, systems biology).

CIMNE –– International Center for Numerical Methods in Engineering (Barcelona, Spain): independent research center, now as a consortium between Polytechnic University of Catalonia, the government of Catalonia, and the federal government; annual funding 10M€ from external sources, focused on SBE&S research, training activities and technology transfer.

Germany restructuring universities; new univ-industry partnerships. German research foundation (DFG) has provided support for collaborative research centers (SBF), transregion projects (TR), transfer units (TBF), research units (FOR), Priority programs, and “Excellence Initiatives”. Many of these are based on or have major components in SBE&S (Stuttgart, Karlsruhe, Munich) and strong connections with industry

Fraunhofer Institute for the Mechanics of Materials (Germany): 15.5M€/year, 44% from industry and 25-30% from government. Significant growth recently (10% per year). Fully 50% of funding goes to SBE&S (up from 30% 5 years ago) (applied materials modeling), 50,000 euro projects awarded to PhDs to work in the institute in topic of their choice.

Finding 1: (b) Increasing European leadership due to funding allocation and industrial participation in education

Partnership for Advanced Computing in Europe (PRACE): coalition of 15 countries led by Germany and France, based on the infrastructure roadmap outlined in the 2006 report of the European Strategy Forum for Research Infrastructures. This roadmap aims to install five petascale systems around Europe beginning in 2009, in addition to national HPC facilities and regional centers.

TALOS: Industry-govmt alliance to accelerate the development in Europe of new-generation HPC solutions for large-scale computing systems.

DEISA: consortium of 11 leading European national supercomputing centers to operate a continent-wide distributed supercomputing network, similar to TeraGrid in the United States.


SIAM, CSE09

CBS (BioCentrum-DTU): MSc in Systems Biology and in Bioinformatics loosely structured, not linked to any department in particular. Real-time internet training (all lectures, exercises and exams), with typically 50:50 students onsite:internet. International exchange highly encouraged, students can take their salary and move anywhere in the globe for half a year.

CIMNE (Barcelona): main especiality is courses and seminars on the theory and application of numerical methods in engineering. In last 20 years, CIMNE has organized 100 courses, 300 seminars, 80 national and international conferences, published 101 books, 15 educational software + 100s of research and technical reports and journal papers.

ETH Zurich: pioneering CSE program (MSc and BSc) combining several departments, successful with grads and postdocs taking the senior level course.

Technical University of Munich and Leibnitz Supercomputing Center: Many CSE programs (i) BGCE, a Bavaria-wide MSc honors program; (ii) IGSSE postgraduate school; (iii) Center for Simulation Technology in Engineering; (iv) Centre for Computational and Visual Data exploration; (v) International CSE Master program multidisciplinary involving 7 departments; also allows for industrial internship; (iv) Software project promotes development of software for HPC/CSE as an educational goal; (v) many, many other programs with other universities and industry.

Finding 2: New centers and programs for education and training in SBE&S ––all of interdisciplinary nature

Finding 3: EU and Asian Centers are attracting more international students from all over the world (including US)

Japan: International Center for Young Scientists (Comp. Mat. Science Center & Nat. Inst. Mat. Sc.); English, interdisciplinary, independent research, high salary, research grant support (5M yen/year). COE aimed at attracting international students. Below 120,000 international students enrolled in Japanese universities, PM wants to increase number to 300,000.

China: “211” and “985” programs to build world-class universities. ~200,000 international students from 188 countries came in 2007. Main “donors”: Korea, Japan, US, Vietnam, Thailand

King Abdullah University of Science and Technology (KAUST): recruiting computational scientists and engineers at all levels, attracting best and brightest from Middle East, India and China.

Australia: targeting Malaysia and Taiwan

Finding 3: EU and Asian Centers are attracting more international students from all over the world (including US)

CBS (BioCentrum-DTU): The internet courses are used to attract international students (cost 20% more effort but bring lots of money, always oversubscribed).

CIMNE (Barcelona): (i) introduced an international course for masters in computational mechanics for non-European students. This is 1st year with 30 students. Four universities involved in this course (Barcelona, Stuttgart, Swansea and Nantes). (ii) Web environment for distance learning, also hosting a Master Course in Numerical methods in Engineering and other postgraduate courses. (iii) the “classrooms”: physical spaces for cooperation in education, research and technology located in Barcelona, Spain, Mexico, Argentina, Colombia, Cuba, Chile, Brazil, Venezuela and Iran.

ETH Zurich: number of international students has increased dramatically (Asian, Russian).

Vrije University Amsterdam: 50% graduate students come from outside the Netherlands (mainly Eastern Europe).

LRZ in TUM Munich: 80% SBE&S students in MSc programs come from abroad: Near East, Asia, Eastern Europe, Central and South America.

United Kingdom: ranks 2nd in world (after US) in attracting international students

Spain, Germany and Italy among others are capturing more and more of the latin american student market, which has shifted its traditional preference for the US in favor of Europe.

Finding 4: Pitfall of interdisciplinary education: breadth vs depth

Educational breadth comes at the expense of educational depth. e.g., in ETH Zurich the CSE faculty choose physics or chemistry students when dealing with research issues and CS majors for software development. General feeling that CSE students can spend too much time on the “format” of the program, without really thinking the underlying science beneath. To solve “grand challenges” in a field, solid knowledge of core

discipline is crucial.

Appropriate evaluation of scientific performance: difficult to come up with credit assignation in an interdisciplinary endeavor. Also, “hidden innovation phenomena” (who gets credit when code is run by other than author).

Finding 5: Demand exceeds supply: academia vs industry

Huge demand for qualified SBE&S students who get hired immediately after MSc, don’t go into PhDs. Good to maintain a dynamical market force but academia would like to see more students that continue a tradition of “free” research. Pharmaceutical, chemical, oil, (micro)electronics, IT,

communications, software companies; automotive and aerospace engineering; finance, insurance, environmental institutions, etc.

Insufficient exposure to computational science & engineering and underlying core subjects at high school and undergraduate level, particularly in the US

Increased topical specialization beginning with graduate school Insufficient training in HPC – an educational “gap”

Gap b/t domain science courses and CS courses; insufficient “continued learning” opportunities related to programming for performance

Most students use codes as black boxes; who will be innovators? Exception: “pockets of excellence”, ie, TUM, Stuttgart,

Karlsruhe No real training in software engineering for sustainable codes Little training in Uncertainty Quantification, Validation &

Verification, risk assessment & decision making

Finding 6: Inadequate education & training Finding 6: Inadequate education & training threatens global advances in SBE&S – threatens global advances in SBE&S –

a worldwide concerna worldwide concern



Finding 1: The many orders-of-magnitude in speedup required to make significant progress in many disciplines will come from a combination of synergistic advances in hardware, algorithms, and software, and thus investment and progress in one will not pay off without concomitant investments in the other two.

Finding 2: The US leads both in computer architectures (multicores, special-purpose processors, interconnects) and applied algorithms (e.g., ScaLAPACK, PETSC), but aggressive new initiatives around the world may undermine this position.

At present the EU leads the US in theoretical algorithm development.

Finding 3: The US leads in the development of next-generation supercomputers, but Japan, Germany committed, and China now investing in supercomputing infrastructure.

Education and Training are crucial:Education and Training are crucial:Next-generation Architectures and Next-generation Architectures and

AlgorithmsAlgorithms



Finding 1: Around the world, SBE&S relies on leading edge (supercomputer class) software used for the most challenging HPC applications, mid-range computing used by most scientists and engineers, and everything in between.

Finding 2: Software development leadership in many SBE&S disciplines remains largely in US hands, but in an increasing number of areas it has passed to foreign rivals, with Europe being particularly resurgent in software for mid-range computing, and Japan particularly strong on high-end supercomputer applications. In some cases, this leaves the US without

access to critical scientific software. Finding 3: The greatest threats to US leadership in SBE&S come from the

lack of reward, recognition and support concomitant with the long development times and modest numbers of publications that go hand-in-hand with software development; the steady erosion of support for first rate, excellence-based single investigator or small-group research in the US; and the inadequate training of today’s computational science and engineering students – the would-be scientific software developers of tomorrow..

Education and Training are crucial:Education and Training are crucial:Scientific and Engineering software Scientific and Engineering software

developmentsdevelopments



Opportunities for the US Opportunities for the US to gain or reinforce lead to gain or reinforce lead

in SBE&Sin SBE&S

Finding 1: There are clear and urgent opportunities for industry-driven partnerships with universities and national laboratories to hardwire scientific discovery to engineering innovation through SBE&S. This would lead to new and better products, as well as development savings both financially and in terms of time. National Academies’ report on Integrated Computational

Materials Engineering (ICME), which found a reduction in development time from 10-20 yrs to 2-3 yrs with a concomitant return on investment of 3:1 to 9:1.

www.wtec.org/sbes


in SBE&Sin SBE&S

Finding 2: There is a clear and urgent opportunity for new mechanisms for supporting SBE&S R&D. Support and reward for long-term development of algorithms, middleware, software, code maintenance and interoperability. Although scientific advances achieved through the use

of a large complex code is highly lauded, the development of the code itself often goes unrewarded.

Community code development projects are much stronger within the EU than the US, with national strategies and long-term support.

investment in math, software, middleware development always lags behind investment in hardwarewww.wtec.org/sbes


in SBE&Sin SBE&S

Finding 3: There is a clear and urgent opportunity for a new, modern approach to educating and training the next generation of researchers in high performance computing for scientific discovery and engineering innovation. Must teach fundamentals, tools, programming for performance, verification and validation, uncertainty quantification, risk analysis and decision making, and programming the next generation of massively multicore architectures. Also, students must gain deep knowledge of their core discipline.

For more For more information and information and final reportfinal report

www.wtec.org/sbeswww.wtec.org/sbes



The growth of number of publications in SBE&S worldwide is double the number of all S&E publications (5% vs 2.5%).

In 2007, US dominated the world SBE&S output at 27%, but China moved 2nd place at (13%).

EUR-12 have larger SBE&S output than US, with difference increasing over time.

Education and Training: Education and Training: WTEC bibliometrics studyWTEC bibliometrics study

C. Sagui and S.C. Glotzer www.wtec.org/sbes SIAM, CSE09

Threats to US leadership Threats to US leadership in SBE&Sin SBE&S

We found healthy levels of SBE&S funding for company-internal projects, underscoring industry’s recognition of the cost-effectiveness and timeliness of SBE&S research.

The mismatch vis a vis the public-sector’s investment level in SBE&S hinders workforce development.

We saw many examples of companies (including US auto and chemical companies) working with EU groups rather than US groups for “better IP agreements”.C. Sagui and S.C.

GlotzerSIAM, CSE09www.wtec.org/sbes

Hurdles: There are three systemic barriers to HPC: 1) Lack of application software, 2) access to talent, 3) Cost constraints (capital, software, expertise).

Most of firms revealed they have important problems they can not solve on their desktop systems. Over 60% of firms would be willing to pay outside organizations (non-profits, engineering services companies, or major universities) for realizing the benefits of HPC.

The survey implications are sobering: critical U.S. supply chains and the leadership of many U.S. industries may be at risk if more companies do not embrace modeling and simulation with HPC.

Drivers and barriers for Drivers and barriers for HPC usage in industryHPC usage in industry

US Council on Competitiveness Report, 2008US Council on Competitiveness Report, 2008



Key Study Key Study Findings: Major Findings: Major Thematic AreasThematic Areas


1. Predictive biosimulation is here.

2. Pan-SBE&S synergy argues for a focused investment of SBE&S as a discipline.

3. Worldwide SBE&S capabilities in life sciences and medicine are threatened by lack of sustained investment and loss of human resources.

Key Findings: Key Findings: Life Sciences & MedicineLife Sciences & Medicine



1. Computational MSE is changing how new materials are discovered, developed, and applied, from the macroscale to the nanoscale.

2. World-class research exists in all areas of materials simulation in the US, EU, and Asia; the US leads in some, but not all, of the most strategic of these.

3. The US ability to innovate and develop the most advanced materials simulation codes and tools in strategic areas is eroding.

Key Findings: Key Findings: MaterialsMaterials


SIAM, CE09www.wtec.org/sbes

1. In the area of transportation fuels, SBE&S is critical to stretch the supply and find other sources.

2. In the discovery and innovation of alternative energy sources – including biofuels, batteries, solar, wind, nuclear – SBE&S is critical for the discovery and design of new materials and processes.

3. Petascale computing will allow unprecedented breakthroughs in sustainability and the simulation of ultra-large-scale sustainable systems, from ecosystems to power grids to whole societies.

Key Findings: Key Findings: Energy & SustainabilityEnergy & Sustainability



Key Study Key Study Findings: Cross-Findings: Cross-

Cutting IssuesCutting Issues


Finding 1: The many orders-of-magnitude in speedup required to make significant progress in many disciplines will come from a combination of synergistic advances in hardware, algorithms, and software, and thus investment and progress in one will not pay off without concomitant investments in the other two.

Key Findings: Key Findings: Next-generation Next-generation

Architectures and Architectures and AlgorithmsAlgorithms



Finding 2: The US leads both in computer architectures (multicores, special-purpose processors, interconnects) and applied algorithms (e.g., ScaLAPACK, PETSC), but aggressive new initiatives around the world may undermine this position.

Already, the EU leads the US in theoretical algorithm development, and has for some time.

Finding 3: The US leads in the development of next-generation supercomputers, but Japan, Germany committed, and China now investing in supercomputing infrastructure.

Key Findings: Key Findings: Next-generation Next-generation

Architectures and Architectures and AlgorithmsAlgorithms



European InitiativesEuropean Initiatives

A new European initiative called Partnership for Advanced Computing in Europe (PRACE) has been formed based on the infrastructure roadmap outlined in the 2006 report of the European Strategy Forum for Research Infrastructures (ESFRI 2006). This roadmap involves 15 different countries and aims to install five petascale systems around Europe beginning in 2009 (Tier-0), in addition to national high-performance computing (HPC) facilities and regional centers (Tiers 1 and 2, respectively). The estimated construction cost is €400 million, with running costs estimated at about €100–200 million per year. The overall goal of the PRACE initiative is to prepare a European structure to fund and operate a permanent Tier-0 infrastructure and to promote European presence and competitiveness in HPC. Germany and France appear to be the leading countries.


SIAM, CSE09

European InitiativesEuropean Initiatives

Recently, several organizations and companies, including Bull, CEA, the German National High Performance Computing Center (HLRS), Intel, and Quadrics, announced the creation of the TALOS alliance (http://www.talos.org/) to accelerate the development in Europe of new-generation HPC solutions for large-scale computing systems. In addition, in 2004 eleven leading European national supercomputing centers formed a consortium, DEISA, to operate a continent-wide distributed supercomputing network. Similar to TeraGrid in the United States, the DEISA grid (http://www.deisa.eu) in Europe connects most of Europe’s supercomputing centers with a mix of 1-gigabit and 10-gigabit lines.


SIAM, CSE09

Finding 1: Around the world, SBE&S relies on leading edge (supercomputer class) software used for the most challenging HPC applications, mid-range computing used by most scientists and engineers, and everything in between.

Key Findings: Key Findings: Scientific & Engineering Scientific & Engineering

Software DevelopmentSoftware Development



Finding 2: Software development leadership in many SBE&S disciplines remains largely in US hands, but in an increasing number of areas it has passed to foreign rivals, with Europe being particularly resurgent in software for mid-range computing, and Japan particularly strong on high-end supercomputer applications. In some cases, this leaves the US without access to critical scientific software.





Finding 3: The greatest threats to US leadership in SBE&S come from the lack of reward, recognition and support concomitant with the long development times and modest numbers of publications that go hand-in-hand with software development; the steady erosion of support for first rate, excellence-based single investigator or small-group research in the US; and the inadequate training of today’s computational science and engineering students – the would-be scientific software developers of tomorrow.





Finding 2: The lack of code interoperability is a major impediment to industry’s ability to link single-scale codes into a multiscale framework.

Finding 3: Although U.S. on par with Japan and Europe, MMS is diffuse, lacking focus and integration, and federal agencies have not traditionally supported the development of codes that can be distributed, supported, and successfully used by others.

Contrast with Japan and Europe, where large, interdisciplinary teams are supported long term to distribute codes either in open-source or commercial form.

Key Findings: Key Findings: Multiscale Modeling and Multiscale Modeling and

SimulationSimulation

Finding 1: Software and data interoperability, visualization, and algorithms that outlast hardware obstruct more effective use of engineering simulation.

Finding 2: Links between physical and system level simulations remain weak. There is little evidence of atom-to-enterprise models that are coupled tightly with process and device models and thus an absence of multi-scale SBE&S to inform strategic decision-making directions.

Key Findings: Key Findings: Engineering SimulationEngineering Simulation



Finding 3: Although US academia and industry are, on the whole, ahead (marginally) of their European and Asian counterparts in the use of engineering simulation, pockets of excellence exist in Europe and Asia that are more advanced than US groups, and Europe is leading in training the next generation of engineering simulation experts.

Key Findings: Key Findings: Engineering SimulationEngineering Simulation



Finding 1: Overall, the United States leads the research efforts today, at least in terms of volume, in quantifying uncertainty; however, there are similar recent initiatives in Europe.

Key Findings: Key Findings: Validation, Verification Validation, Verification

& Uncertainty & Uncertainty QuantificationQuantification

www.wtec.org/sbes

Finding 2: Although the U.S. DOD and DOE are been leaders in V&V and UQ efforts, they have been limited primarily to high-level systems engineering and computational physics & mechanics, with most of the mathematical developments occurring in universities by small numbers of researchers. In contrast, several large European initiatives stress UQ-related activities.

Finding 3: Existing graduate level curricula, worldwide, do not teach stochastic modeling and simulation in any systematic way.

Key Findings: Key Findings: Validation, Verification Validation, Verification

& Uncertainty & Uncertainty QuantificationQuantification

www.wtec.org/sbes

Finding 1: The biological sciences and the particle physics communities are pushing the envelope in large-scale data management and visualization methods. In contrast, the chemical and material science communities lag in prioritization of investments in data infrastructure. Bio appreciates importance of integrated, community-wide

infrastructure for massive amounts of data, data provenance, heterogeneous data, analysis of data and network inference from data. Great opportunities for the chemical and materials communities to move in a similar direction, with the promise of huge impacts on the manufacturing sector.

Key Findings: Key Findings: Big Data, Visualization, Big Data, Visualization,

and Data-Driven and Data-Driven SimulationSimulation

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Finding 2: Industry is significantly ahead of academia with respect to data management infrastructure, supply chain, and workflow.



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Most universities lack campus-wide strategy for big data. Widening gap between the data infrastructure needs of the current generation of students and the campus IT infrastructure.

Industry active in consortia to promote open standards for data exchange – a recognition that SBE&S is not a series of point solutions but integrated set of tools that form a workflow engine.

Companies in highly regulated industries, e.g., biotechnology and pharmaceutical companies, are also exploring open standards and data exchange to expedite the regulatory review processes for new products.



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Finding 3: Big data and visualization capabilities are inextricably linked, and the coming “data tsunami” made possible by petascale computing will require more extreme visualization capabilities than are currently available, as well as appropriately trained students who are adept with data infrastructure issues.

Finding 4: Big data, visualization and dynamic data-driven simulations are crucial technology elements in “grand challenges,” including production of transportation fuels from the last remaining giant oil fields.



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Insufficient exposure to computational science & engineering and underlying core subjects at high school and undergraduate level

Increased topical specialization beginning with graduate school

Insufficient training in HPC – an educational “gap” Gap b/t domain science courses and CS courses; insufficient “continued

learning” opportunities related to programming for performance Major worry for multicore/gpu architectures in US

Students use codes as black boxes; who will be innovators? No real training in software engineering for sustainable codes

Little training in UQ, V&V, risk assessment & decision making Necessary for atoms to enterprise – US lead slim

Inadequate education & Inadequate education & training threatens global training threatens global

advances in SBE&S – advances in SBE&S – a worldwide concerna worldwide concern

S.C. Glotzer 01/29/09

MASI Conference, Helsinki, Finland

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Opportunities Opportunities for the US to for the US to

gain or gain or reinforce lead reinforce lead

in SBE&Sin SBE&S



in SBE&Sin SBE&S

Finding 1: There are clear and urgent opportunities for industry-driven partnerships with universities and national laboratories to hardwire scientific discovery to engineering innovation through SBE&S. This would lead to new and better products, as well as development savings both financially and in terms of time. National Academies’ report on Integrated Computational

Materials Engineering (ICME), which found a reduction in development time from 10-20 yrs to 2-3 yrs with a concomitant return on investment of 3:1 to 9:1.

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in SBE&Sin SBE&S

Finding 2: There is a clear and urgent opportunity for new mechanisms for supporting SBE&S R&D. Support and reward for long-term development of algorithms, middleware, software, code maintenance and interoperability. Although scientific advances achieved through the use

of a large complex code is highly lauded, the development of the code itself often goes unrewarded.

Community code development projects are much stronger within the EU than the US, with national strategies and long-term support.

investment in math, software, middleware development always lags behind investment in hardwarewww.wtec.org/sbes


in SBE&Sin SBE&S

Finding 3: There is a clear and urgent opportunity for a new, modern approach to educating and training the next generation of researchers in high performance computing for scientific discovery and engineering innovation. Must teach fundamentals, tools, programming for performance, verification and validation, uncertainty quantification, risk analysis and decision making, and programming the next generation of massively multicore architectures. Also, students must gain deep knowledge of their core discipline.

For more For more information and information and final reportfinal report

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Documents

WTEC International Assessment of Simulation-Based Engineering and Science: Education Celeste Sagui North Carolina State University Sharon Glotzer University