Icme Stanford 20110507 Final

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How parallel computing and mathematics is driving the 21st century industrial revolution

How parallel computing and mathematics is driving the 21st century industrial revolution

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  • 1. Mathematics and Parallel Computing: Powering the 21st Century Industrial Revolution Shanker Trivedi, Vice President (Business Development) - NVIDIA CorporationNVIDIA Confidential 1
  • 2. Super Phones to Super ComputersNVIDIA Confidential 2
  • 3. Tesla in 3 of Top 5 Super Computers 2500 2000 1500 Gigaflops 1000 500 0 Tianhe-1A Jaguar Nebulae Tsubame Hopper IINVIDIA Confidential 3
  • 4. Tesla “Green” Supercomputing 2500 8 7 2000 6 1500 5 Megawatts Gigaflops 4 1000 3 2 500 1 0 0 Tianhe-1A Jaguar Nebulae Tsubame Hopper IINVIDIA Confidential 4
  • 5. Super Computing Across Industries Drug Design Seismic Imaging Automotive Design Medical Imaging Molecular Dynamics Reverse Time Migration Computational Fluid Dynamics Computed Tomography Astrophysics Options Pricing Product Development Weather Forecasting n-body Monte Carlo Finite Difference Time Domain Atmospheric PhysicsNVIDIA Confidential 5
  • 6. Gene Sequencing NVIDIA Confidential 6
  • 7. DiagnosticImaging NVIDIA Confidential 7
  • 8. SeismicProcessing NVIDIA Confidential 8
  • 9. Defense and Intelligence NVIDIA Confidential 9
  • 10. Financial Risk Management NVIDIA Confidential 10
  • 11. Automobile Design – CFD NVIDIA Confidential 11
  • 12. CUDA Ecosystem Applications Developer Tools Languages & APIs Cloud Computing Partners Microsoft, Dell CUDA C/C++ HP, IBM, ASUS, SuperMicro DirectX11 Fortran OpenCL Accelereyes, Acceleware, EM Photonics, MAGMA, PGI, Rogue Wave, pyCUDA GPU.NET EC2 StoneRidge Research & Education CUDA ZoneNVIDIA Confidential 12
  • 13. [Industrial Light and Magic video]NVIDIA Confidential 13
  • 14. NVIDIA Confidential 14
  • 15. Better Science @ Lower Cost Using Industry Standard Parallel ComputingNVIDIA Confidential 15
  • 16. [Three Pillars of Science video] http://www.nvidia.com/object/race-for-better-science.htmlNVIDIA Confidential 16
  • 17. NVIDIA Confidential 17
  • 18. Additional Materials!   “Illumination Effect in Reverse Time Migration”, Bruno Kaelin et al ! http://www.fusiongeo.com/publications/k3d/3DGeo- IlluminationEffects_EAGE2007.pdf!   “Implementing 3D Finite Difference Codes on the GPU” by P. Micikevicius !   Slides: http://www.nvidia.com/content/GTC/documents/1006_GTC09.pdf !   Video : http://developer.download.nvidia.com/compute/cuda/docs/ GTC09Materials.htm (talk 1006P
  • 19. CUDA Resources!   Introduction (basics, assume no GPU knowledge): !   Video: http://developer.download.nvidia.com/CUDA/training/cudaintrowebinar.mp4 !   Slides: http://www.nvidia.com/content/PDF/sc_2010/CUDA_Tutorial/SC10_CUDA_C_Basics.pdf!   Fundamental optimization: !   The two presentations are largely the same, the second one has some updates but no audio/video !   Slides/video: http://www.nvidia.com/object/gtc2010-presentation-archive.html#session2011 ! http://www.nvidia.com/content/PDF/sc_2010/CUDA_Tutorial/SC10_Fundamental_Optimizations.pdf!   Advanced optimization: !   The two presentations are largely the same, the second one has some updates but no audio/video !   Slides/video: http://www.nvidia.com/object/gtc2010-presentation-archive.html#session2012 ! http://www.nvidia.com/content/PDF/sc_2010/CUDA_Tutorial/SC10_Analysis_Driven_Optimization.pdf!   Miscellaneous: !   all NVIDIA webinars: http://developer.nvidia.com/object/gpu_computing_online.html#Previously !   all NVIDIA tutorials from Supercomputing 2010: http://www.nvidia.com/object/sc10_cuda_tutorial.html
  • 20. ICME Stanford May 7, 2011 Shanker TrivediVP, Business Development