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Big Data: Thoughts from the perspective of the semiconductor industry

Big Data: Thoughts from the perspective of the semiconductor industry. Celia Merzbacher, SRC VP for Innovative Partnerships. Happy Data Innovation Day!. 2012. iPod(5G) 80GB. Hardware Advances Enable Big Data. 80Gb cost $9,000,000 !!! in 1982 dollars.

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Big Data: Thoughts from the perspective of the semiconductor industry

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  1. Big Data: Thoughts from the perspective of the semiconductor industry Celia Merzbacher, SRC VP for Innovative Partnerships

  2. Happy Data Innovation Day!

  3. 2012 iPod(5G) 80GB Hardware Advances Enable Big Data 80Gb cost $9,000,000 !!! in 1982 dollars 1982: Best available storage technology was the IBM 3350 126 IBM 3350’s = storage in 1 iPod • Each unit: • 635 MB • $70,000 80Gb cost <$100 in 2012 dollars

  4. Moore’s Law: # transistors/chip doubles every 24 months

  5. In 1982… Aug 17—the first compact disc goes on sale Oct 1—Sony launches the first compact disc player

  6. In 1982… Time magazine’s Man of the Year was… The Computer

  7. But in 1982 the U.S. semiconductor industry saw threats on the horizon.

  8. In the early 1980’s US semiconductor market share was dropping… Federal funding for academic research on silicon was declining… The pipeline of talent was drying up. US Research Talent Federal $ Market Share Japan

  9. In 1982… • Objectives: • Define relevant research directions • Explore potentially important new technologies • Generate a pool of experienced faculty & • relevantly educated students • STAY ON MOORE’S LAW The Semiconductor Research Corporation (SRC) was launched with the support of visionary industry leaders. Erich Bloch Robert Noyce Jack Kilby

  10. Moore’s Law: 1971-2011 FinFET Cu interconnects Pb-free packaging High-K gate insul. Dual Core Triple Core Quad Core Hex Core Eight Core

  11. Benchmark capability m (IPS) as a function of b (bit/s) ~100 W Power is the main issue for further scaling of high-performance computing

  12. Scaling up performance & power • IBM Watson supercomputer • The most recent and most impressive demonstration of an artificial intelligence computer system • Capable of answering questions posed in natural language • Winner of the Jeopardy! quiz show in 2011 • ~3000 processor cores (POWER7) • each consisting of 1.2B transistors and operating at 3.5GHz • approximate total binary throughput ~ 1022 bit/s. • ~200kW of power • EPA estimated data centers used 1.5% of total US electricity in 2007

  13. Benchmark capability m (IPS) as a function of b (bit/s) Estimates of computational power of human brain: Basic algorithms need to work in very few steps! (L.G Valiant, A quantitative theory of neural computation, Biol. Cybern. (2006) 95 1014 IPS 1019 bit/s 30 W • Binary information throughput: • b ~1019 bit/s • Gitt W, “information - the 3rd fundamental quantity”, Siemens Review 56 (6): 36-41 1989 • (Estimate made from the analysis of the control function of brain: language, deliberate movements, information-controlled functions of the organs, hormone system etc. 1000x algorithmic efficiency ~100 W • Number of instruction per second • m ~ 108 MIPS • H. Moravec, “When will computer hardware match the human brain?” J. Evolution and Technol. 1998. Vol. 1 • (Estimate made from the analysis brain image processing) How can we decrease the energy needed to move/store data? What can we learn about information processing from Nature?

  14. The IT Platform of Today: Mobiles at the Edge of the Cloud MobileAccess Mobile data growth [Source: Cisco VNI Mobile, 2011] Infrastructural core Mobile traffic grew 2.6x in 2010 (nearly tripling for 3rd year) Driven by Tablets The Cloud [J. Rabaey, ASPDAC’08]

  15. The Swarm at The Edge of the Cloud MobileAccess & Relay Infrastructural core The Swarm The Cloud [J. Rabaey, ASPDAC’08]

  16. New STARnet* Center: TerraSwarmDirector: Ed Lee, UC-Berkeley www.src.org/program/starnet/tsrc/ *STARnet is a subsidiary of SRC

  17. Si-mCell: A hypothetical 1-mm3Si computer 1mm Memory: 40 kbit Logic: 320 bit Exceeds capability of known cooling techniques Memory access is the most severe limiting factor of Si-Cell due to line charging

  18. Nanoelectronics Research InitiativeFinding the Next Switch (co-funds all centers) Notre Dame Purdue Penn State UT-Dallas SUNY-Albany Purdue U. Virginia Harvard GIT Columbia MIT Virginia Nanoelectronics Center (ViNC) University of Virginia Old Dominion University College of William & Mary UC Los Angeles UC Berkeley UC Irvine UC Riverside UC Santa Barbara Brown U. Alabama Northwestern Columbia Carnegie Mellon Illinois-UC MIT Stanford Notre Dame (2) Nebraska-Lincoln Columbia / U. Florida Penn State U. of Minnesota Princeton / UT-Austin Cornell / Princeton UC-Santa Barbara Drexel University / UI-UC / U. Penn UC-Riverside / Georgia Virginia Commonwealth / UC-R / Michigan / U. Virginia UC-Riverside / UC-I / UC-SD / Rochester / SUNY-Buffalo U. Pittsburgh / U. Wisconsin-Madison / Northwestern UT-Austin Rice UT-Dallas NCSU U. Maryland Texas A&M GIT Over 40 Universities in 19 States 20

  19. NRI Nanoelectronic Devices Tunnel Devices MIND HeterojunctionsNotre Dame, Penn State VGn Vn Insulators NanowiresPenn State Contacts Oxidation Vp VGp GrapheneNotre Dame Spin-Wave Device WIN - UCLA, UCSB Spin-Torque Device WIN - UCI Spin-FET WIN - UCLA Bilayer pseudoSpin SWAN - UT Austin Graphene Processes SWAN – UT Dallas Nanomagnet Logic MIND - Notre DameWIN - Berkeley Graphene PN Junction Device INDEX - SUNY Albany Graphene Integration INDEX – SUNY Albany All-Spin Logic INDEX - Purdue U. Device and Architecture Benchmarking MIND/WIN/INDEX/SWAN – Led by K. Bernstein, IBM 21

  20. Breakthrough Technology Challenges for next decades • From fundamental physics it seems likely that the scaling of current technology will end in the few nanometer regime. • NRI is working to develop replacement technologies • So far, a replacement technology has not been found • Are there other models for information processing technologies that offer the promise to sustain Moore’s Law? • Looking to organic systems, i.e., at the intersection of chemistry, biology, and information processing

  21. Specifications of a Human Cell AC BS • 10 mm overall size • - 0.36 nm between base pairs in DNA. Average protein is 5 nm. - 107 biochemical operations per second - 1 pWatts power consumption - 30,000 node gene-protein molecular network with nanoscale devices. - 20 kT per molecular operation (vs. 104–105 kT in advanced nanoelectronics) • Functions: sensing, communication, actuation, feedback regulation, molecular synthesis & transport, detoxification, defense, self assembles from a single embryonic cell. Biology computes efficiently and precisely with noisy and unreliable components on noisy real-world signals. Courtesy of Rahul Sarpeshkar, Analog Circuits and Biological Systems Group, MIT

  22. Nature Has Been Processing Information for a Billion Years M (DNA) L L L L L L L L L L L L S L L L L L L E E E Bio-mCell – A Living Cell Si-mCell E E About 500 of these cells would fit in the cross-section of a human hair Memory C C E Logic V=1mm3 Our studies show that the Si-mCell cannot match the Bio-µCell in the density of memory and logic elements, nor operational speed, nor operational energy: Memory: 1000x more Logic: >10x more Power: 1,000,000x less Algorithmic efficiency: 1000x more

  23. DNA-inspired memory • DNA volumetric memory density far exceeds (1000x) projected ultimate electronic memory densities • Potential for very low-energy memory access • Goal: Demonstrate a miniaturized, on-chip integrated DNA storage <10-11 1019bit/cm3

  24. DNA Memory http://www.wired.com/wiredscience/2012/08/dna-data-storage/ Researchers stored an entire genetics textbook in less than a picogram of DNA — one trillionth of a gram — an advance that could revolutionize our ability to save data. DNA: The Ultimate Hard Drive? 5.27×106 bit DNA memory can be stable 100+ years

  25. Encoded into DNA code computer files totaling 739 kilobytes of hard-disk storage and with an estimated 5.2 × 106 bits • Synthesized and sequenced the DNA, and reconstructed the original files with 100% accuracy. • Storage scheme is theoretically scalable beyond current global information volumes • Current trends in DNA synthesis costs should make the scheme cost-effective for sub-50-year archiving within a decade. European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK Agilent Technologies, Genomics–LSSU, 5301 Stevens Creek Boulevard, Santa Clara, California 95051, USA

  26. Possible New SRC Initiative: SemiSynBio Exploring potential benefits to the semiconductor industry arising from synthetic biology Meeting Date: February 22&23, 2013 Meeting Place: Cambridge, MA Organizing Committee: Rahul Sarpeshkar/MIT Timothy Lu/MIT Sami Issa / ATIC Andrew Hessel / Autodesk Eric Klavins / U. Washington Larry Sumney / SRC Steven Hillenius / SRC Ralph Cavin / SRC Victor Zhirnov / SRC

  27. Take Away Messages • Success of Big Data will depend on continued advances in computation hardware, aka semiconductors • Moore’s Law (for CMOS) is facing physical limits • Power is the main issue for further scaling of high-performance computing • There are no evident replacement technologies • Nanoelectronics research is seeking new devices • New research turns to biology • DNA-based memory • Using/mimicking Nature in other areas may allow Moore’s Law (for performance) to continue “beyond CMOS”. • Industry—through SRC—continues to fund leading edge university research in partnership with Government

  28. SRC Creates Value Through Partnerships Tactical Perspective, “Can-Do” Attitude, FUNDING Creativity, Faculty Expertise, Student Resources Strategic Perspective, National Needs, Credibility, FUNDING Government Universities Industry • Maximizes technological progress • Leverages investments • Utilizes the strengths of each sector • Expands and replenishes the professional community

  29. Semiconductor Research Corporation: A Family of Distinct, Related Program Entities Focus Center Research Program Phase VI STARnet Early research engagement of key long horizon semiconductor challenges Nanoelectronics Research Initiative Beyond CMOS –the next switch and associated architectures Education Alliance Attracting and educating the next generation of innovators and technology leaders Energy Research Initiative Emphasis on efficient/clean energy generation, storage and distribution Global Research Collaboration Ensuring vitality of current industry Each entity has a distinct set of member companies and Government partners. For more information go to www.src.org Updated January 2013

  30. Benefits of SRC Approach (to Univ & Govt) Value of research is enhanced • Provide insight on industry needs to researcher community • Input and feedback from industry at periodic reviews • E-seminars and e-workshops facilitate near real-time sharing of research results and tech transfer • Interactions and opportunities for personnel exchanges among universities and industry Student education is enhanced • Industry liaisons & mentors engage with students • Participation in TECHCON, SRC’s annual technical conference at which students present research and network with industry representatives. • Opportunities for student internships at SRC member companies. Explore new research directions • E.g., joint workshops, new program “spin offs”, etc.

  31. SRC created an industry-guided global university research ecosystem Since 1982… In 2012… • 1500 students • 500 faculty • 120 universities worldwide 20X increaseover 1982 • Over $1.6B invested by SRC participants • 9,195 students • 2,025 faculty members • 261 universities in 27 countries

  32. Current SRC Member Companies

  33. Backup

  34. Essential SRC Features • Industry-driven, consensus-based goals embodied in: • Moore’s Law • ITRS (International Technology Roadmap for Semiconductors) • Focus on pre-competitive university research (>5 yr time horizon) • Members have rights to resulting IP • Involves the current industry experts (provide input/ feedback/ oversight and tech transfer) • Managed by an independent entity (facilitates interactions among members and with universities & government agencies) • Nimble and adaptable (~1/3 of projects turn over annually) • Accountable; value-driven; efficient; effective • Attracts world-class researchers (faculty & students)

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