Towards a High Performance Computing Economy: Blue Collar Computing Presented by:

1. Towards a High Performance Computing Economy: Blue Collar Computing Presented by: Stanley C. Ahalt, Ph.D. Ohio Supercomputer Center Pittsburgh, PA November 6 – 12, 2004

2. IntroductionCommercial Forces Influence Technology

3. Example: The Automobile Market

4. Today’s Automotive Market

5. Today: commercialization of high-performance computing

6. The IT Sector must influence HPC! • From 1993 to 2000, IT added 1.8 million jobs. • Between 2000 and 2002 IT lost 600,000 jobs. • In 2003 IT equipment sector up 16.7 percent • In 2004 top 500 companies estimate average of $369 million spent on IT. • In 2004 U.S. federal government estimate $59 billion spent on IT. • Federal IT spending expected to grow at 6.6 percent, reaching $81 billion by 2009 Sources: The Digital Economy Fact Book, Information Week, and INPUT.

7. A Growing Awareness of HPC’s importance as a competitive tool July 2004 COC/IDC Survey of 33 CIO/CTOs: • Over 70% indicated their companies could not function without HPC; • Over 25% of companies could quantify HPC’s ROI to their businesses: - saved millions of dollars, or - shortened production development cycles, or - provided faster product-to-market timing.

8. Joseph Gardner: HPC as a critical tool

9. But industrial adoption of HPC lags… From the same Council on Competitiveness IDC report: • 65% of the reporting companies have important, but currently unsolved computational problems; • 35% need faster computers for their problems HPC has the potential to impact: • Workforce productivity • Engineering design • Manufacturing

10. Giorgio Rizzoni: HPC use in automotive industry. Pete Buca: HPC is integrated part of some industries.

11. Barriers to HPC entry • Workforce • Intellectual Property • ROI • Culture clashes • Imagination • Tools High performance computing gives you the ability to include additional information into the model that may have an impact on the long-term outlook of that product or service. It just gives you a more accurate reading of where that product or service will be twenty, thirty, forty years down the road. -Brandt Barlow IT Solutions Architect, Nationwide Services Co.

12. Workforce Issues: Lack of HPC Skills • Deficit of technical expertise among existing and emerging workforce • Need for sophisticated computational science curricula • Educational programs cater to the NOW, not the future • “The problems that need to be solved nowadays often require individuals with multidisciplinary experience and that is precisely what computational science education strives to achieve.” • - Leigh J. Little • Prof., Computational Science, SUNY Brockport

13. A Few Standouts in Education • Some Universities have degree programs • Graduate programs (36) • Undergraduate programs (6) • Some have minors or Certificate programs • Most are adds or minors rather than full integration • Some are trying to do it right • Capital University • Undergraduate and community college efforts • The Shodor Education Foundation, funded by NSF and Burroughs Wellcome, created the National Computational Science Institute (NCSI) “… there has been a lack of an effective language to communicate new ideas and results in computational science. This is in part due to the diversity of the computational science community.” -Ken Wilson (1982 Nobel Prize winner in Physics )

14. The importance of Computational Science to University faculty, High School teachers, and… … to high school students!

15. Forecast for Software Engineers: Good “Computer software engineers will be among the ten fastest growing occupations over the decade between 2002 and 2012, with those focusing on applications growing by 46 percent and those in systems software growing by 45 percent.” -Bureau of Labor Statistics Forecast for Computational Scientists: Excellent! "One of my students combined his studies in the computational science program at Capital University with a finance degree, then received a master's degree in computational finance at Carnegie Mellon.  After over 10 offers from New York city firms mostly, he came back to Ohio to work for American Electric Power in Cincinnati, with all of his college loans paid and a starting salary of $96,000 per year.” -Ignatios Vakalis, Capital Univ., Nov. , 2004

16. Other Barriers… • Intellectual Property – security and confidentiality • ROI calculations • Because of the short term goals of industry, HPC can appear unattractive because the rewards of HPC are longer-term • Culture clashes between industrial and HPC communities • Industry viewpoint: Speed, quality, cost – pick two • Academic and Government viewpoint: Grand Challenges • A lack of experience, and therefore imagination, with HPC “High performance computing gives you the ability to include additional information into the model that may have an impact  on the long-term outlook of that product or service.  It just gives you a more accurate reading of where that product or service will be twenty, thirty, forty years down the road.” - Brandt Barlow, IT Solutions Architect, Nationwide Financial Services Co.

17. Tools – The Biggest Barrier • GUI made desktop computing broadly accessible, and, • Web browsers made networking popular. • HPC hardware and software are hard to use, but, • HPC companies have little reason to forge new tools and utilities, although • Industry needs to tackle more complex models in a much wider context, • Cost of developing HPC tools versus other business investments is problematic….

18. Computation Science Wizard • Modeling and simulation require expertise • Standard models could be codified • Novices could use standardized tools while experts push the envelope

19. Refocusing HPC: Usability and Productivity • HPC industry has benefited from bigger memory chips, faster switching speeds, and far greater storage capacity • Usability of HPC software HAS NOT TRACKED the improvements in hardware. There are some hopeful signs: • The European Union plans to spend $63 million into universities and research labs to make grid computing work for industrial projects. • “Expert makes move from U.S. to China to lead supercomputing effort” The Chinese government is seizing upon supercomputing to help speed the nation's transition from low-cost manufacturing to becoming a more powerful force in the world economy.

20. High End of the Spectrum • Grand Challenges bring federal resources and funds to bear on high-end computational problems, for example: • Astrophysics • Computational biology/Life Sciences • Condensed matter physics • Nanoscale materials • Aerospace vehicles • Solutions to Grand Challenges usually represent several orders of magnitude improvement over previous capabilities

21. A “typical” job distribution at OSC

22. A Proposed Goal: Full-Spectrum HPC, aka, “Blue Collar Computing™” • Full spectrum focus – from small jobs to large jobs. • Large jobs of today must become small jobs tomorrow • Need scalable applications – scale up AND scale down! • Industrial application focus • Emphasis on productivity

23. Blue-Collar Computing 8 Ideal Market for HPC Increased Productivity Gains In Industry and Engineering Blue-Collar HPC Increased Gains in Scientific Discovery Number of Tasks Number of Users Number of Applications Easy Pickings Competitive Necessity Business ROI Current Market for HPC Programmer Productivity Heroes 1 2 4 64 DoD NSF DoE Amount of Computing Power , Storage , & Capability # of Dollars

24. Blue Collar(High-Performance) Computing The goals of Blue Collar Computing: • Move the bulk of everyday research, science, and engineering tasks from single-processor desktops to everyday HPC platforms. • Drive the use of parallel computing into the mainstream of computing!

25. Leslie Southern on Blue Collar Computing

26. Is the time right for Blue Collar Computing? Absolutely!

27. Reason 1: Large, forward thinking firms already making investments • Use HPC for production and process design • Use simulation to save money and time • Improve product quality with virtual prototypes “Because we have not had high performance computing in the past, and because the models are very complex and take a long time to run, our actuaries try to skinny down the models.  That means that the results might not be as accurate as you would like them to be.” - Brandt Barlow, IT Solutions Architect, Nationwide Services Co. • “We are significantly expanding capabilities in computational modeling and computer-aided engineering, so we can do an increasing percentage of product and process design through virtual simulation.” • - A.G. Lafley, President and CEO, Procter & Gamble

28. Irene Qualters: HPC’s role in drug design

29. Reason 2: Democratization of HPC HPC hardware is becoming more ... Personal.

30. Multi-Core Microprocessors Two factors: • Physics: heat dissipation increasingly difficult. • Economics: production yields increasingly problematic. “A Split at the Core”, by W. Wayt Gibbs, Scientific American, November, 2004 Are compelling microprocessor manufacturers to offer multi-core (2,4,8, 16,…?) microprocessors. • IBM • Hewlett-Packard • Sun • Intel • AMD • Issues: • Costs/Licenses: • Number of cores? • Number of processors? • Number of sockets? • Microsoft, Novell, Oracle, IBM, BEA, AMD • Virtualization • Software

31. DARPA High Productivity Computing Systems (HPCS) High-End Computing Revitalization Task Force (HECRTF) Workshop on High-Productivity Languages and Models (Hans Zima) Reason 3: Momentum

32. How to accelerate the Blue-Collar revolution A public-private partnership: The HPC Software Institute • Shared investments • Shared benefits An increased focus on highly reliable, sustained software, high-productivity languages, and HPC tools • Common software methods • Sustain research tools long enough to allow them to become viable in the marketplace A new emphasis on Computational Science curricula at all levels, that is, K-16 • All undergrads should be exposed to computational science and engineering • AP courses should be made available for wide distribution at the high school level

33. Griorgio Rizzoni: HPC in automotive industry Add fastest electric car picture!

34. Pete admonishes us to use HPC to “Think Faster”

35. Conclusions • A fundamental shift in our industry is underway – a shift to Blue Collar HPC. The shift is inevitable, but can be accelerated. • Blue Collar HPC will move everyday research, science, and engineering tasks from the desktop onto everyday HPC platforms. • Eventually, parallel computing will become the dominant form of mainstream computing! • The entire spectrum of the HPC industry will reap the benefit – including the very highest end of the spectrum. • This shift is compelled by: • Industrial needs and receptivity • Technology changes • Criticality of computational science to the many complex problems we face today