TiECon Florida keynote - New opportunities for entrepreneurs using GPU & CUDA

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This is a presentation that I gave at TiEcon Florida on 20 Sept 2013. I spoke about the new opportunities that are emerging for entrepreneurs caused by the disruptive innovation potential of GPU, CUDA and parallel computing technologies.

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TiECon Florida keynote - New opportunities for entrepreneurs using GPU & CUDA

  1. 1. SHANKER TRIVEDI Vice President, Worldwide Sales (PSG) | September 2013
  2. 2. NVIDIA THE VISUAL COMPUTING COMPANY
  3. 3. NVIDIA Growth Drivers ~$800M / 15% CAGR~$1B / 9% CAGR ~$200M / 68% CAGR ~$2B / 32% CAGR CUDA & GRID 20M Artists & Designers 100M PLM users SHIELD & GRID 400M Gamers TESLA & GRID 5-10M Servers GPU, TEGRA & IP Billions of Devices PRO-VISUALIZATION & DESIGN GAMING HPC & BIG DATA ANALYTICS OEM Revenue based on current run rates. CAGR from FY10-FY13.
  4. 4. From A Modest Beginning
  5. 5. To Almost Unbelievable Reality
  6. 6. The March of GPUs 0   50   100   150   200   250   2007   2008   2009   2010   2011   2012   GBytes/s   Peak  Memory  Bandwidth     M1060   Nehalem     3  GHz   Westmere   3  GHz   8-­‐core     Sandy  Bridge   3  GHz   Fermi   M2070   Fermi+   M2090   0   200   400   600   800   1000   1200   1400   2007   2008   2009   2010   2011   2012   Gflops/s   Peak  DP  FP    Performance   Nehalem   3  GHz   Westmere   3  GHz   Fermi   M2070   Fermi+   M2090   M1060   8-­‐core   Sandy  Bridge   3  GHz   NVIDIA  GPU  (ECC  off)   x86  CPU  Double  Precision:  NVIDIA  GPU   Double  Precision:  x86  CPU   Kepler   Kepler  
  7. 7. GPUs Enable Next Generation Graphics (with Computing) Deferred Lighting, Depth of Field and Post-Processing | Facial Performance | Wave and Fire Simulation | Interactive Global Illumination | Volumetric Lighting | iRAY on CUDA
  8. 8. CPU GPU + CPU MotionDSP – Example Image Stabilization & Rectification
  9. 9. Aerodynamics/CFD Electromagnetics Satellite Imaging Computer Vision Video Enhancement Signal Processing GPU Apps Run 10x-100x Faster
  10. 10. Traditional CPU Cluster GPU Workstation Nodes Required 12 1 (4 GPUs) Interconnect QDR IB None Time to complete 4.98 days 2.25 days Power Consumption 5.7 kW (681.3 kWh) 1.0 kW (54.0 kWh) System Cost (per day) $96,800 ($88.40) $5200 ($4.75) Simulation Cost (681.3 * 0.18) + (88.40 * 4.98) (54.0 * 0.18) + (4.75 * 2.25) $562.87 $20.41 AMBER 4 simultaneous simulations, 23,000 atoms, 250ns each GPU Apps are 5-25X Cheaper To Deploy Source: San Diego Supercomputing Center
  11. 11. Better Simulation - Toto Example
  12. 12. MEDIA & ENT. OIL AND GAS RESEARCH MANUFACTURINGGOVERNMENT The buyer plans for including accelerators in their next technical computing server purchase has more than doubled from 29% to over 65% in last 20 months. IDC Market Research April, 2013 “ ” GPUs becoming mainstream in the Data Center For Scientific & Technical Computing
  13. 13. CUDA Developer Momentum 2008 2013 4,000 Academic Papers 150K CUDA Downloads 60 University Courses 100M CUDA –Capable GPUs 1 Supercomputer 430M CUDA-Capable GPUs 50 Supercomputers 1.6M CUDA Downloads 640 University Courses 37,000 Academic Papers
  14. 14. Easiest Way to Learn CUDA 50K Registered 127 Countries $$ Learn from the Best Anywhere, Any Time It’s Free! Engage with an Active Community
  15. 15. Big Data Analytics Machine Learning Computer Vision Visual Shopping Real-time Video Delivery Searching Audio Analyzing Twitter Beyond Scientific & Technical Computing
  16. 16. The New Enterprise Mobile | BYOD | Massive Data
  17. 17. NVIDIA GRID Virtualized GPU Servers Visual Computing Appliances
  18. 18. Meet Ira! The Next Generation of Visual Computing http://www.youtube.com/watch?v=Vx0t-WJFXzo
  19. 19. Console Games Can Now Target Mobile
  20. 20. What’s the Next Big Thing?
  21. 21. Augmented Reality
  22. 22. Healthcare
  23. 23. Autonomous Vehicles, Drones, Robots
  24. 24. Deep Machine Learning
  25. 25. Visual Analytics of Big Data
  26. 26. GPU & CUDA Easy & Cheap What’s the Next Big Thing? Augmented Reality Autonomous Robots Computer Vision Deep Machine Learning Visual Analytics Biological Computing
  27. 27. Resources http://www.slideshare.net/shankert/nvidia-intro-0513 http://blogs.nvidia.com/ https://www.facebook.com/gpucomputing http://www.nvidia.com/object/race-for-better-science.html http://www.nvidia.com/object/gpuventures.html http://www.gputechconf.com/page/home.html http://www.gputechconf.com/page/gtc-learning-center.html http://www.slideshare.net/shankert/nvidia-gtc-computerecapbrochure http://sarahtariq.com/presentations.html http://www.slashgear.com/nvidia-shield-hands-on-with-parrot-ar-drone-2-0-26288075/ https://developer.nvidia.com/ http://www.nvidia.com/object/tesla_software.html http://gpu.meetup.com/ http://gpgpu.org/ https://www.udacity.com/course/cs344 https://www.coursera.org/course/hetero

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