Jensen Huang on a New Computing Era with NVIDIA GPUs
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NVIDIA founder and CEO Jensen Huang took the stage in Munich — one of the hubs of the global auto industry — to introduce a powerful new AI computer for fully autonomous vehicles and a new VR application for those who design them.
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Jensen Huang on a New Computing Era with NVIDIA GPUs
- 1. Jensen Huang, Founder & CEO, GTC Europe 2017 A NEW COMPUTING ERA
- 2. 2 1980 1990 2000 2010 2020 Original data up to the year 2010 collected and plotted by M. Horowitz, F. Labonte, O. Shacham, K. Olukotun, L. Hammond, and C. Batten New plot and data collected for 2010-2015 by K. Rupp 103 105 107 1.5X per year 1.1X per year TWO FORCES DRIVING THE FUTURE OF COMPUTING 40 Years of CPU Trend Data Transistors (thousands) Single-threaded perf
- 3. 3 TWO FORCES DRIVING THE FUTURE OF COMPUTING The Big Bang of Deep Learning 1980 1990 2000 2010 2020 Original data up to the year 2010 collected and plotted by M. Horowitz, F. Labonte, O. Shacham, K. Olukotun, L. Hammond, and C. Batten New plot and data collected for 2010-2015 by K. Rupp 103 105 107 1.5X per year 1.1X per year 40 Years of CPU Trend Data Transistors (thousands) Single-threaded perf
- 4. 4 1980 1990 2000 2010 2020 Original data up to the year 2010 collected and plotted by M. Horowitz, F. Labonte, O. Shacham, K. Olukotun, L. Hammond, and C. Batten New plot and data collected for 2010-2015 by K. Rupp 103 105 107 1.5X per year 40 Years of CPU Trend Data Single-threaded perf RISE OF NVIDIA GPU COMPUTING NVIDIA Volta GPU | 21B xtors | 120 TFLOPS GPU-Computing perf 1.5X per year 1.1X per year
- 5. 5 RISE OF NVIDIA GPU COMPUTING CUDA Downloads 5X in 5 Years Global GTC Attendees 10X in 5 Years GPU Developers 15X in 5 Years 20172012 2012 1.8M645,000 201720172012 22,000
- 6. 6 NVIDIA GPU-ACCELERATED APPLICATIONS Scientific Computing Deep LearningComputer Graphics Data Science NVIDIA CUDA AMBER Molecular Dynamics COSMO Climate Weather ChaNGa Astrophysics Gaussian Quantum Chemistry Schlumberger WG Seismic Processing PowerGrid Medical Imaging ANSYS Fluent Computational Fluid Dynamics SIMULIA Abaqus Finite-Element Analysis K-Means Clustering Gradient Boosting Support Vector MachineGeneralized Linear Model DATABASES ANALYTICS
- 7. 7 NVIDIA GPU-ACCELERATED INDUSTRIES HPC INTERNET SERVICES TRANSPORTATION MEDICAL IMAGING LOGISTICS Ride Sharing Self-Driving Cars Design & Simulation Radiology Volumetric Rendering 3D CT AV Truck Route Management Warehouse Automation Photo Album Recommendations Social Media Weather Molecular Dynamics Materials Science
- 8. 8 NVIDIA GPU ACCELERATES 2017 NOBEL PRIZES IN CHEMISTRY AND PHYSICS Cryogenic Electron Microscopy Jacques Dubochet, Joachim Frank, Richard Henderson Detection of Gravitational Waves Rainer Weiss, Barry Barish, Kip Thorne Resolution before 2013 Resolution at present
- 9. 9 ANNOUNCING NVIDIA HOLODECK THE DESIGN LAB OF THE FUTURE Photorealistic Models Physically Simulated Interaction Virtual Team Collaboration GPU-accelerated AI
- 10. 10 CREATE AND COLLABORATE IN NVIDIA HOLODECK CATIA / Siemens NX Creo / Alias Maya / 3dsMAX
- 11. 11
- 12. 12 ANNOUNCING NVIDIA HOLODECK THE DESIGN LAB OF THE FUTURE Photorealistic Models Physically Simulated Interaction Virtual Team Collaboration GPU-accelerated AI Early Access NOW nvidia.com/holodeck
- 13. 13 THE ERA OF AI NIPS RegistrationAI Startup Funding 12X in 5 Years Deep Learning Papers Published 13X in 3 Years 2017201420172012 $6.6B 3,000 -50 -25 0 25 1500 3000 4500 6000 2017 2016 2002
- 14. 14 SOLVING THE UNSOLVABLE NVIDIA Interactive Ray Tracing
- 15. 15 SOLVING THE UNSOLVABLE NVIDIA Interactive Ray Tracing NVIDIA / Remedy Audio-driven Facial Animation
- 16. 16 SOLVING THE UNSOLVABLE NVIDIA Interactive Ray Tracing NVIDIA / Remedy Audio-driven Facial Animation WRNCH Pose Estimation
- 17. 17 SOLVING THE UNSOLVABLE NVIDIA Interactive Ray Tracing NVIDIA / Remedy Audio-driven Facial Animation WRNCH Pose Estimation University of Edinburgh Character Animation
- 18. 18 SOLVING THE UNSOLVABLE NVIDIA Interactive Ray Tracing NVIDIA / Remedy Audio-driven Facial Animation WRNCH Pose Estimation University of Edinburgh Character Animation UC Berkeley / OpenAI One-shot Imitation Learning
- 19. 19 THE WORLD’S AI PLATFORM NVIDIA AI PLATFORM IT Services Automotive Healthcare Smart City Manufacturing Drones Fin. Services Other NVIDIA Inception: 1,900 DL Startups Every Cloud and Data CenterEvery Framework
- 20. 20 AI INFERENCE IS THE NEXT GREAT CHALLENGE Training InferencingDNN Model
- 21. 21 EXPLOSION OF INTELLIGENT MACHINES 20M Inference Servers Trillions of IoT Devices100s of Millions of Autonomous Machines
- 22. 22 EXPLOSION OF NETWORK DESIGN Recurrent Networks Generative Adversarial NetworksConvolution Networks Reinforcement Learning GRU HighwayLSTM Embedding BiDirectionalProjection ReLuPRelu Dropout PoolingConcat BatchNorm A3C Dueling DQNDQNConditional GAN Latent space GAN 3D-GAN Coupled GAN Rank GAN Speech Enhancement GAN
- 23. 23 2014 2015 2016 2017 20182013 2014 2015 2016 2017 20182011 2013 2015 2017 EXPLOSION OF NETWORK COMPLEXITY Translation Network Complexity GOPS * Bandwidth Image Network Complexity GOPS * Bandwidth Speech Network Complexity GOPS * Bandwidth 2012 2014 2016 ResNet-50 Inception-v2 Inception-v4 AlexNet GoogLeNet 350X 30X DeepSpeech 3 DeepSpeech 2 DeepSpeech 10X GNMT OpenNMT MoE
- 24. 24 NEW NVIDIA TENSORRT 3 DRIVE PX 2 JETSON TX2 NVIDIA DLA TESLA P4 TensorRT TESLA V100 Programmable Inference Accelerator Compile and Optimize Neural Networks | Support for Every Framework Optimize for Each Target Platform
- 25. 25 NEW NVIDIA TENSORRT 3 Programmable Inference Accelerator Weight & Activation Precision Calibration | Layer & Tensor Fusion Kernel Auto-Tuning | Multi-Stream Execution concat batch nm batch nm batch nm batch nm max pool input relu relu relu relu 1x1 conv 3x3 conv 5x5 conv 1x1 conv relu batch nm 1x1 conv relu batch nm 1x1 conv next input next input max pool input copy 3x3 CR 5x5 CR 1x1 CR 1x1 CR
- 26. 26 NEW NVIDIA TENSORRT 3 Programmable Inference Accelerator 40x Speed-up on ResNet-50 | 140x Speed-up on OpenNMT 4 25 550 0 150 300 450 600 CPU + Torch V100 + Torch V100 + TensorRT 140 300 5,700 - 1,500 3,000 4,500 6,000 CPU + TensorFlow V100 + TensorFlow V100 + TensorRTCPU + TensorFlow V100 + TensorFlow V100 + TensorRT Images/Sec (ResNet-50) Sentences/Sec (OpenNMT)
- 27. 27 NEW NVIDIA TENSORRT 3 Programmable Inference Accelerator 40x Speed-up on ResNet-50 | 140x Speed-up on OpenNMT | Half the Latency 0 150 300 450 600 CPU + Torch V100 + Torch V100 + TensorRT - 1,500 3,000 4,500 6,000 CPU + TensorFlow V100 + TensorFlow V100 + TensorRTCPU + TensorFlow V100 + TensorFlow V100 + TensorRT Images/Sec (ResNet-50) Sentences/Sec (OpenNMT) 14ms 7ms 7ms 280ms 153ms 117ms
- 28. 28 NVIDIA TENSORRT 10X BETTER DATA CENTER TCO 160 CPU servers 45,000 images / second 65 KWatts
- 29. 29 NVIDIA TENSORRT 10X BETTER DATA CENTER TCO 1 NVIDIA HGX with 8 Tesla V100 GPUs 45,000 images / second 3 KWatts 1/6 the Cost | 1/20 the Power 4 Racks in a Box
- 31. 31
- 33. 33
- 34. 34 VINCENT AI
- 35. 35
- 37. 37 NVIDIA DRIVE AV COMPUTING PLATFORM Sensor Fusion: RADAR, LIDAR, Camera | Deep Learning, CV, Parallel Computing Diversity of Algorithms | ASIL-D Functional Safety | Fully Integrated into NVIDIA BB8 DRIVE PX — AI CAR COMPUTER DRIVEWORKS SDK DRIVE AV DRIVE OS RADAR Fusion LIDAR Point-Cloud Processing Camera Deep Learning (Detection) Camera Deep Learning (Freespace) Camera Computer Vision (SLAM) HD Map (Localizing to Map) Path Planning
- 38. 38
- 39. 39 — Goldman Sachs Uber Lyft Waymo GM / Cruise Ford / Argo.ai Baidu Zoox nuTonomy Yandex “RIDE-HAILING INDUSTRY EXPECTED TO GROW EIGHTFOLD TO $285B BY 2030”
- 40. 40 ROBOTAXI DEMANDS EXTREME COMPUTING + 10X camera resolution + Surround LIDAR point-cloud processing + Camera & LIDAR localization to HD map + Tracking all surrounding objects + New map generation + Sophisticated path planning & control + Algorithm diversity + Sensor & computing fail-operate + Excess computing capacity Level 2 Level 5
- 42. 42 ANNOUNCING “PEGASUS” ROBOTAXI DRIVE PX 320 TOPS CUDA TensorCore | 16x GMSL | 4x 10G | 8x 1G | 16x 100M | Auto-grade | ASIL D 500W | Late Q1 Early Access Partners Supercomputing Data Center in your Trunk
- 43. 43 ANNOUNCING “PEGASUS” ROBOTAXI DRIVE PX 320 TOPS CUDA TensorCore | 16x GMSL | 4x 10G | 8x 1G | 16x 100M | Auto-grade | ASIL D 500W | Late Q1 Early Access Partners Supercomputing Data Center in your Trunk
- 45. 45 ANNOUNCING “PEGASUS” ROBOTAXI DRIVE PX 320 TOPS CUDA TensorCore | 16x GMSL | 4x 10G | 8x 1G | 16x 100M | Auto-grade | ASIL D 500W | Late Q1 Early Access Partners Supercomputing Data Center in your Trunk
- 46. 46 ANNOUNCING NVIDIA DRIVE IX SDK Intelligent Experience Toolkit Sense Inside & Outside the Vehicle | Deep Learning Powered | Early Access Q4 Your Car is an AI Customer Application DRIVE OS DRIVE AV Object, Path, Wait Perception DRIVE IX Gaze, Head Pose, Gestures, Recognize Face, Voice Recognition & Lip Reading Exterior Driver Recognition Automatic Personalization Inattentive Driver Alert Cyclist Alert Distracted Driver Alert Driver/Passenger Recognition
- 47. 47 NVIDIA DRIVE AI CAR PLATFORM From Training to Driving | From Processor to AI to AV Stack | From AV to IX From 3D Simulation to Super-Real-Time Testing | Open Platform for Partners SILHIL Data Factory DRIVE AV on DPXTraining on DGX 3D-SIM on DGX RE-SIM on DGX
- 48. 48 SUPER REAL-TIME SIMULATION WITH DGX AND NEW TENSORRT 3 With 8 NVIDIA DGX Re-Sim 300,000 miles in 5 hours Virtually Drive Every Paved Road in U.S. in 2 Days
- 49. 49
- 50. 50 145 AV STARTUPS ON NVIDIA DRIVE
- 51. 51 THE ERA OF AUTONOMOUS MACHINES
- 52. 52 XAVIER WORLD’S FIRST AUTONOMOUS MACHINE PROCESSOR Deep Learning, CV, Parallel Computing Rich High-Speed Sensor IOs Extreme Energy Efficiency 30 TOPS at 30W
- 53. 53 PROJECT ISAAC — AI ROBOT SIMULATOR SIMULATION TRAINING AUTONOMOUS Project Isaac
- 54. 54
- 55. 55 A NEW COMPUTING ERA NVIDIA Holodeck Design Lab of the Future NVIDIA The World’s AI Computing Platform NVIDIA Drive Open AV Platform for the Transportation Industry NVIDIA DRIVE PX Pegasus Robotaxi AI Computer Project Isaac AI Robot Simulator
- 56. 56