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GTC Taiwan 2017 主題演說
Jensen Huang, Founder and CEO of NVIDIA, discusses the new era of AI and how GPU computing is driving innovations in deep learning. He highlights NVIDIA's role in accelerating scientific breakthroughs using AI, developing the Holodeck for virtual design collaboration, and powering autonomous machines and vehicles. Huang also announces that Taiwan's Ministry of Science and Technology has adopted NVIDIA's platform to develop AI capabilities in manufacturing, IoT, healthcare and more.
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GTC Taiwan 2017 主題演說
- 1. Jensen Huang, Founder& CEO, GTC Taiwan 2017 A NEW COMPUTING ERA
- 2. 2 THE ERA OFAI PC MOBILE CLOUD AI
- 3. 3 TWO FORCES DRIVING THEFUTURE OF COMPUTING Deep Learning Starts AI Revolution 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 CPU Performance Stalled Transistors (thousands) Single-threaded perf
- 4. 4 1980 1990 20002010 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 GPU Extends Performance Post-Moore’s Law Single-threaded perf RISE OF NVIDIA GPU COMPUTING GPU-Accelerated Computing 1.1X per year CUDA GPU Parallel Domain-Specialized Accelerator High Compute & Bandwidth High-Throughput GPU Plus Low-Latency CPU
- 5. 5 RISE OF NVIDIAGPU 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 RISE OF NVIDIAGPU COMPUTING Performance Reach 10-50X Roadmap CUDA Kepler Maxwell Pascal Volta Applications 500+ TOOLS & APPS
- 7. 7 NVIDIA GPU ACCELERATES 2017NOBEL 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
- 8. 8 NEW NVIDIA HOLODECK THE DESIGNLAB OF THE FUTURE Photorealistic Models Physically Simulated Interaction Virtual Team Collaboration GPU-accelerated AI
- 9.
- 10. 10 CREATE AND COLLABORATE INNVIDIA HOLODECK CATIA / Siemens NX Creo / Alias Maya / 3dsMAX
- 11. 11 NEW NVIDIA HOLODECK THE DESIGNLAB OF THE FUTURE Photorealistic Models Physically Simulated Interaction Virtual Team Collaboration GPU-accelerated AI Early Access NOW nvidia.com/holodeck
- 12. 12 AI — CUDAGPU’S NEXT KILLER APP NIPS RegistrationAI Startup Funding 10X in 5 Years Deep Learning Papers Published 10X in 3 Years 2017201420172012 $6.6B 3,000 -50 -25 0 25 1500 3000 4500 6000 2017 2016 2002
- 13. 13 SOLVING THE UNSOLVABLE NVIDIA InteractiveRay Tracing
- 14. 14 SOLVING THE UNSOLVABLE NVIDIA InteractiveRay Tracing NVIDIA / Remedy Audio-driven Facial Animation
- 15. 15 SOLVING THE UNSOLVABLE NVIDIA InteractiveRay Tracing NVIDIA / Remedy Audio-driven Facial Animation WRNCH Pose Estimation
- 16. 16 SOLVING THE UNSOLVABLE NVIDIA InteractiveRay Tracing NVIDIA / Remedy Audio-driven Facial Animation WRNCH Pose Estimation University of Edinburgh Character Animation
- 17. 17 SOLVING THE UNSOLVABLE NVIDIA InteractiveRay Tracing NVIDIA / Remedy Audio-driven Facial Animation WRNCH Pose Estimation University of Edinburgh Character Animation UC Berkeley / OpenAI One-shot Imitation Learning
- 18. 18 THE WORLD’S AIPLATFORM IT Services Automotive Healthcare Smart City Manufacturing Drones Fin. Services Other NVIDIA Inception: 2,000 DL Startups Every Cloud and Data CenterEvery Framework NVIDIA AI PLATFORM
- 19. 19 ANNOUNCING TAIWAN MINISTRY OFSCIENCE AND TECHNOLOGY ADOPTS NVIDIA FOR AI GRAND PLAN Top 25 Fastest Supercomputer in the World Training 3,000 Developers in AI for Manufacturing, IoT, Smart Cities, Healthcare Startup Innovation Center
- 20. 20 NVIDIA GPU CLOUD GPU-ACCELERATEDCLOUD PLATFORM OPTIMIZED FOR DEEP LEARNING Containerized in NVDocker Optimization Across the Full Stack Always Up-to-Date Fully Tested and Maintained by NVIDIA
- 21.
- 22. 22 NVIDIA GPU CLOUD GPU-ACCELERATEDCLOUD PLATFORM OPTIMIZED FOR DEEP LEARNING Containerized in NVDocker Optimization Across the Full Stack Always Up-to-Date Fully Tested and Maintained by NVIDIA Coming this Month Sign up now: www.nvidia.com/gpu-cloud
- 23. 23 AI INFERENCE IS THENEXT GREAT CHALLENGE Training InferenceDNN Model
- 24. 24 EXPLOSION OF INTELLIGENTMACHINES 20M Inference Servers Trillions of IoT Devices100s of Millions of Autonomous Machines
- 25. 25 EXPLOSION OF NETWORKDESIGN 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
- 26. 26 2014 2015 20162017 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
- 27. 27 NEW NVIDIA TENSORRT3 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
- 28. 28 NEW NVIDIA TENSORRT3 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
- 29. 29 NEW NVIDIA TENSORRT3 Programmable Inference Accelerator 40x Speed-up on ResNet-50 | 140x Speed-up on OpenNMT 4 550 0 150 300 450 600 CPU + Torch V100 + TensorRT 140 5,700 - 1,500 3,000 4,500 6,000 CPU + TensorFlow V100 + TensorRTCPU + TensorFlow V100 + TensorRT Images/Sec (ResNet-50) Sentences/Sec (OpenNMT)
- 30. 30 NVIDIA TENSORRT 10X BETTERDATA CENTER TCO 160 CPU Servers 45,000 Images / Second 65 KWatts
- 31. 31 NVIDIA TENSORRT 10X BETTERDATA 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
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- 34. 34 NVIDIA VOLTA INEVERY CLOUD, EVERY DATACENTER
- 35. 35 NVIDIA TESLA DATACENTERMARKETS HPC CSP TRAINING CSP INFERENCE PUBLIC CLOUD INDUSTRIES ENTERPRISE $25B Market20M Inference Servers 600M Amazon Packages / Yr$12B Market 80% of Apps by 2020 $3T IT Industry
- 36. 36 NVIDIA TESLA DATACENTERPLATFORM HPC CSP TRAINING CSP INFERENCE PUBLIC CLOUD INDUSTRIES ENTERPRISE CUDA ComputeWorks NVIDIA AI SDK cuDNN, NCCL, TensorRT, DIGITS Every Framework NGC GRID vPC Quadro vWS
- 37. 37 NVIDIA TESLA PLATFORMPARTNERS INVENTEC QUANTA GIGABYTE TYAN WISTRONSUPERMICRO GIGABYTEASUS GIGABYTE QUANTA TYAN FOXCONN 2-GPU 8-GPU4-GPU SUPERMICRO
- 38.
- 39. 39 NVIDIA DRIVE AV COMPUTINGPLATFORM 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
- 40.
- 41. 41 — Goldman Sachs UberLyft Waymo GM / Cruise Ford / Argo.ai Baidu Zoox nuTonomy Yandex “RIDE-HAILING INDUSTRY EXPECTED TO GROW EIGHTFOLD TO $285B BY 2030”
- 42.
- 43. 43 NEW “PEGASUS” ROBOTAXI DRIVEPX 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 Size of a License Plate
- 44. 44 NEW “PEGASUS” ROBOTAXI DRIVEPX 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 Size of a License Plate
- 45.
- 46. 46 NEW “PEGASUS” ROBOTAXI DRIVEPX 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 Size of a License Plate
- 47. 47 THE ERA OF AUTONOMOUSMACHINES
- 48. 48 A WORLD OFAUTONOMOUS MACHINES 10% of Manufacturing Tasks Are Automated 1M Pizzas Delivered Per Day by Domino’s 100M People 80+ Years Old Ag Tech: 70% Increase in Farm Yields by 2050 600K Bridges to Inspect in the U.S. 300M Operations per Year WW
- 49. 49 NVIDIA JETSON AUTONOMOUS MACHINEPLATFORM Jetson TX2 JetPack SDK DIGITS Isaac Robot Simulator Deep Learning Institute
- 50. 50 ADAPTING TO NEWUSE CASES Pre-Trained Network Optimized Network Optimized NetworkNVIDIA DGX Station NVIDIA Jetson NVIDIA DIGITS Pre-Trained Network 20’ Camera Indoor Camera 360° Camera Improved Improved TensorRT Improved
- 51.
- 52. 52 A NEW COMPUTINGERA Taiwan’s MOST Adopts NVIDIA for AI Grand Plan NVIDIA AUTONOMOUS MACHINES Jetson TX2 JetPack | DIGITS | Isaac Robot Simulator | Deep Learning Institute NVIDIA AI Volta in Every Cloud | NVIDIA GPU Cloud Registry TensorRT Programmable Inference Accelerator
- 53.