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Technologies that will Change the World

John Cohn Ph. D. IBM Fellow Systems and Technology Group . Technologies that will Change the World. 1E+12. Integrated Circuit. Discrete Transistor. 1E+9. Vacuum Tube. 1E+6. Electro- Mechanical. $1000 Buys: Computations per second. 1E+3. Mechanical. 1E+0. 1E-3. 1E-5. 1900.

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Technologies that will Change the World

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  1. John Cohn Ph. D. IBM Fellow Systems and Technology Group Technologies that will Change the World

  2. 1E+12 Integrated Circuit Discrete Transistor 1E+9 Vacuum Tube 1E+6 Electro- Mechanical $1000 Buys: Computations per second 1E+3 Mechanical 1E+0 1E-3 1E-5 1900 1920 1940 1960 1980 2000 2020 Source: Kurzweil 1999 – Moravec 1998 Our Industry has been driven by Continual Improvementand Disruptive Innovation !

  3. Cognitive Computing • “Synapse” devices Compute+ Natural Language+ Analytics Learn Program BIG/Fast Deep Q&A Computers • Data + analytics (zettabytes + milli / microseconds 1,000  1,000,000 X Smarter Planet (Internet of Things + People) Big Data Exascale (Datacenter-in-a-box) • Massive parallelism • Flexible system optimization 1000X Workload Optimized Systems Nano Systems (Systems-on-a-chip) • Photonics • DNA Transistor 1000X 1B Transistors 1T Devices Nano Devices Power7 chip 4 Technologies that Will Change the World – and IBM Will Lead !

  4. Cognitive Computing • “Synapse” devices Compute+ Natural Language+ Analytics Learn Program BIG/Fast Deep Q&A Computers • Data + analytics (zettabytes + milli / microseconds 1,000  1,000,000 X Smarter Planet (Internet of Things + People) Big Data Exascale (Datacenter-in-a-box) • Massive parallelism • Flexible system optimization 1000X Workload Optimized Systems Nano Systems (Systems-on-a-chip) • Photonics • DNA Transistor 1000X 1B Transistors 1T Devices Nano Devices Power7 chip From Nano Devices to Nano Systems

  5. HfO2 Si NW Deposited Si Device Structure Research PipelineInnovation and Disruptive Technology at Each Node C Electronics Fully Depleted Devices Si Nano-Wire ETSOI FINFET Conventional Planar Device 8 nm & Beyond 22/20 nm 15/11 nm

  6. Light out for off-chip traffic Light Multiplexor Photo-detector Analog CMOS Digital CMOS Inter-layer3D vias Modulator Vision: >1 Tbps on a 3D Chip

  7. The Future of Medicine “Lab-on-a-Chip” • Requires pinhead size sample; takes only minutes • Tests for hundreds of diseases, viruses, bacteria and biohazards “DNA Transistor” • Goal: a personal genome for $1,000 • Could make possible customized medicine “Targeted Medicine at the Nanoscale” • Detects and destroys antibiotic-resistant bacteria • Fights infectious diseases like MRSA

  8. Cognitive Computing • “Synapse” devices Compute+ Natural Language+ Analytics Learn Program BIG/Fast Deep Q&A Computers • Data + analytics (zettabytes + milli / microseconds 1,000  1,000,000 X Smarter Planet (Internet of Things + People) Big Data Exascale (Datacenter-in-a-box) • Massive parallelism • Flexible system optimization 1000X Workload Optimized Systems Nano Systems (Systems-on-a-chip) • Photonics • DNA Transistor 1000X 1B Transistors 1T Devices Nano Devices Power7 chip From Petascale to Exascale

  9. BG/Q ~20PF From Disruptive HPC to Commercial Leadership HPC ~1000PF Roadrunner 1PF BG/P 1PF ~300PF BG/L 0.3PF Commercial Hybrid Architecture Relative Performance (log) Workload Optimized Fast Network Future Power and Z Systems Scalability High Efficiency Multicore SoC zEnterprise pSeries P7 z10 pSeries P6 z9 pSeries P5 Time

  10. Exascale ComputingA billion calculations in a billionth of a second Overall Performance = 1000X Performance / watt = 135X Performance / $ = 1000X Footprint = <2% Referenced to one-petaflop system 1 PetaFlop 72 BG/P Racks Silicon Photonics CPU Phase Change Memory 3D Software The Next Ten Years 1 PetaFlop = 1/3 rack 2009 2019

  11. Cognitive Computing • “Synapse” devices Compute+ Natural Language+ Analytics Learn Program BIG/Fast Deep Q&A Computers • Data + analytics (zettabytes + milli / microseconds 1,000  1,000,000 X Smarter Planet (Internet of Things + People) Big Data Exascale (Datacenter-in-a-box) • Massive parallelism • Flexible system optimization 1000X Workload Optimized Systems Nano Systems (Systems-on-a-chip) • Photonics • DNA Transistor 1000X 1B Transistors 1T Devices Nano Devices Power7 chip From Big Data to Big Analytics

  12. Electric Car Transmission Line Charge Points 430 locations Substation SynchroPhasor Sensors 30 measurements / sec Switch Gear 40 control points Feeder Line Intelligent Building Power Quality Sub-second feedback Automated Meters Demand Response 5 minute price signals Households 5.2 million Smarter Planet will Drive Creation of Big/Fast Data Millions of end points (e.g., meters, appliances, capacitors) Analytics requirements: 100K+ data elements,10ms latency Multiple feedback time-scales: sub-second, 4 sec, 5 min, …

  13. Exa Big Insights Peta Feedback Tera Integration Data Scale Giga yr mo wk day hr min sec … ms s System s Traditional Data Warehouse & Business Intelligence Mega Real-time Occasional Frequent Kilo Decision Frequency New Big/Fast Data Brings New Opportunities, Requires New Analytics Homeland Security 600,000 records/sec, 50B/day 1-2 ms/decision 320TB for Deep Analytics Up to 10,000 Times larger Big Telco Promotions 100,000 records/sec, 6B/day 10 ms/decision 270TB for Deep Analytics Data at Rest DeepQA 100s GB for Deep Analytics 3 sec/decision Fast Data in Motion Up to 10,000 times faster Smart Traffic 250K GPS probes/sec 630K segments/sec 2 ms/decision, 4K vehicles

  14. Cognitive Computing • “Synapse” devices Compute+ Natural Language+ Analytics Learn Program BIG/Fast Deep Q&A Computers • Data + analytics (zettabytes + milli / microseconds 1,000  1,000,000 X Smarter Planet (Internet of Things + People) Big Data Exascale (Datacenter-in-a-box) • Massive parallelism • Flexible system optimization 1000X Workload Optimized Systems Nano Systems (Systems-on-a-chip) • Photonics • DNA Transistor 1000X 1B Transistors 1T Devices Nano Devices Power7 chip From Programming to Systems that Learn

  15. Evidence Scoring Hypothesis Generation Problem Decomposition Confidence Ranking Question Analysis Solution Synthesis Watson ! – A Workload optimized system • Built on 90 x IBM Power 750 servers • 2880 POWER7 cores • 15 Terabytes of memory • Up to 80 Teraflops • 500 GB per sec on-chip bandwidth

  16. Research / Demo Commercialization Future Technologies Voice & Image Recognition Query & Dialogue Won Jeopardy! 2007 – 2011 2011 – 2012 2012 – 2015 Watson – a Roadmap

  17. Eg. This is the most common cause of unilateral decreased vocal fremitus. Deep Q&A: Progress on Medical Queries 100% 100% DeepQA Adapted for Medical Questions WatsonY/E 2010 “Winners Cloud” ~3 person-month effort Precision Precision Starting Point 2007 0% 0% 0% % Answered 100% 0% % Answered 100%

  18. Cognitive Computing Neuroscience Complexity Supercomputing Nanoelectronics Time

  19. Smart Systems Era Computing Era Tabulating Era We Are Entering a New Era Computer Intelligence Time

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