GTC China 2016
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Kicking off the first in a series of global GPU Technology Conferences, NVIDIA co-founder and CEO Jen-Hsun Huang today at GTC China unveiled technology that will accelerate the deep learning revolution that is sweeping across industries. Huang spoke in front of a crowd of more than 2,500 scientists, engineers, entrepreneurs and press, gathered in Beijing for a day devoted to deep learning and AI. On stage he announced the Tesla P4 and P40 GPU accelerators for inferencing production workloads for AI services and, a small, energy-efficient AI supercomputer for highway driving — the NVIDIA DRIVE PX 2 for AutoCruise.
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GTC China 2016
- 1. GTC 2016 — China THE DEEP LEARNING AI REVOLUTION
- 2. 2 GPU DEEP LEARNING BIG BANG Deep Learning NVIDIA GPU NIPS (2012) ImageNet Classification with Deep Convolutional Neural Networks Alex Krizhevsky University of Toronto Ilya Sutskever University of Toronto Geoffrey e. Hinton University of Toronto
- 3. 3 74% 96% 2010 2011 2012 2013 2014 2015 DL GPU DEEP LEARNING ACHIEVES “SUPERHUMAN” RESULTS 2012: Deep Learning researchers worldwide discover GPUs 2015: DNN achieves superhuman image recognition 2015: Deep Speech 2 achieves superhuman voice recognition ImageNet — Accuracy % Human Hand-coded CV Microsoft, Google 3.5% error rate
- 4. 4 NVIDIA — “THE AI COMPUTING COMPANY” GPU Computing Computer Graphics Artificial Intelligence
- 5. 5 ANNOUNCING NEW GRAPHICS SDKS Funhouse VR Open Source 360 Video 1.0 Real-Time Panoramic VR Iray VR Photorealistic VR Ray Tracing GVDB Sparse Volumes for Special Effects Remote Rendering Video Compositing Ansel In-game Photography Volumetric Physical Light Models OptiX 4.0 Multi-GPU Ray-Tracing MDL 1.0 Physically Based Materials Mental Ray Now GPU-Accelerated!
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- 8. 8 NVIDIA SILICON VALLEY HEADQUARTERS
- 9. 9 GTC — 25X GROWTH IN GPU DL DEVELOPERS 4X Attendees 3X GPU Developers 25x Deep Learning Developers 2014 55,000400,00016,000 2,200 120,000 3,700 • Australia • China • Europe • India • Japan • Korea • United States (Silicon Valley, D.C.) 20162014 2016 • Japan • United States • Higher Ed 35% • Software 19% • Internet 15% • Auto 10% • Government 5% • Medical 4% • Finance 4% • Manufacturing 4% 2014 2016
- 10. 10 WHY DID AI RESEARCHERS ADOPT GPUs FOR DEEP LEARNING?
- 11. 11 BRAIN IS LIKE A GPU BRAIN CREATES MENTAL IMAGES WHEN WE THINK
- 12. 12 GPU IS LIKE A BRAIN
- 13. 13 GPU DEEP LEARNING IS A NEW COMPUTING MODEL Training Device Datacenter
- 14. 14 GPU DEEP LEARNING IS A NEW COMPUTING MODEL Training Device Datacenter TRAINING Billions of Trillions of Operations GPU train larger models, accelerate time to market
- 15. 15 GPU DEEP LEARNING IS A NEW COMPUTING MODEL Training Device Datacenter DATACENTER INFERENCING 10s of billions of image, voice, video queries per day GPU inference for fast response, maximize datacenter throughput
- 16. 16 GPU DEEP LEARNING IS A NEW COMPUTING MODEL Training Device Datacenter DEVICE INFERENCING Billions of intelligent devices GPU for real-time accurate response
- 17. 17 AI — THE ULTIMATE COMPUTING CHALLENGE IMAGE RECOGNITION SPEECH RECOGNITION Important Property of Neural Networks Results get better with more data + bigger models + more computation (Better algorithms, new insights and improved techniques always help, too!) 2012 AlexNet 2015 ResNet 152 layers 22.6 GFLOP/image ~3.5% error 8 layers 1.4 GFLOP/image ~16% Error 16X Model 2014 Deep Speech 1 2015 Deep Speech 2 2 ExaFLOPS 25M | 7,000 Hours ~8% Error 10X Training Ops 20 ExaFLOPS 100M | 12,000 Hours ~5% Error
- 18. 18 PASCAL “5 MIRACLES” BOOST DEEP LEARNING 65X Pascal — 5 Miracles NVIDIA DGX-1 Supercomputer 65X in 4 yrs Accelerate Every Framework PaddlePaddle Baidu Deep Learning Pascal 16nm FinFET CoWoS HBM2 NVLink cuDNN Chart: Relative speed-up of images/sec vs K40 in 2013. AlexNet training throughput based on 20 iterations. CPU: 1x E5-2680v3 12 Core 2.5GHz. 128GB System Memory, Ubuntu 14.04. M40 datapoint: 8x M40 GPUs in a node P100: 8x P100 NVLink-enabled. Kepler Maxwell Pascal X 10X 20X 30X 40X 50X 60X 70X 2013 2014 2015 2016
- 19. 19 ANNOUNCING NEW IBM SERVER POWER8 + NVIDIA TESLA P100 FOR THE AI ENTERPRISE “ Putting NVIDIA’s technology into the IBM system will speed up performance for such emerging workloads as AI, deep learning and data analytics.” — eWeek
- 20. 20 Andrew Ng, Chief Scientist
- 22. 22 ANNOUNCING TESLA P4 & P40 INFERENCING ACCELERATORS Pascal Architecture | INT8 P40: 250W | 40X Energy Efficient versus CPU P40: 250W | 40X Performance versus CPU
- 23. 23 ANNOUNCING TensorRT PERFORMANCE OPTIMIZING INFERENCING ENGINE FP32, FP16, INT8 | Vertical & Horizontal Fusion | Auto-Tuning VGG, GoogLeNet, ResNet, AlexNet & Custom Layers Available Today: developer.nvidia.com/tensorrt
- 24. 24
- 25. 25
- 26. 26 NVIDIA GPU DEEP LEARNING EVERYWHERE Alibaba/Aliyun iQIYI Shazam Amazon JD.com Skype Facebook Orange Twitter Flickr Periscope Yahoo Supermarket Google Pinterest Yandex iFLYTEK Qihoo 360 Yelp eBay Tencent Netflix Baidu Sogou Microsoft
- 27. 27 >1,500 AI STARTUPS AROUND THE WORLD Deep Learning for Cybersecurity Deep Learning for Genomics Deep Learning for Self-Driving Cars Deep Learning for Art
- 28. 28 AI STARTUPS IN CHINA Weather & Environment Forecast Eye-tracking for Human- machine Interaction Medical Imaging Face Recognition Product Recognition, Detection, Search Personal Concierge App
- 30. 30 “BILLIONS OF INTELLIGENT DEVICES” “Billions of intelligent devices will take advantage of DNNs to provide personalization and localization as GPUs become faster and faster over the next several years.” — Tractica
- 31. 31 AI CITY — 1B CAMERAS BY 2020 ~1 billion cameras worldwide by 2020 30 billion inferences/sec Tesla P40: 2,500 inferences/sec @ 720P AI City needs ~10M P40 servers DATA: 1B cameras, IHS “Video Surveillance Intelligence Service, Aug. 2016”
- 32. 32 1/20TH THE SPACE, 1/10TH THE POWER Hikvision Blade 16 Jetson TX1s NVIDIA DGX-1 Traditional Server Hikvision Blade ~21 1U Servers 42 CPUs ~4,000 W 1 Hikvision Blade 16 TX1 + 1 CPU >8 1080 streams ~300 W
- 33. 33 ANNOUNCING NVIDIA AI CITY PARTNERS
- 34. 34 AI TRANSPORTATION — $10T INDUSTRY PERCEPTION AI PERCEPTION AI LOCALIZATION DRIVING AI DEEP LEARNING
- 35. 35 FREE SPACE DETECTION CAR 3D DETECTION
- 36. 36 NVIDIA BB8 AI CAR
- 37. 37 NVIDIA DRIVE PX 2 AutoCruise to Full Autonomy — One Architecture Full Autonomy AutoChauffeur AutoCruise AUTONOMOUS DRIVING Perception, Reasoning, Driving AI Supercomputing, AI Algorithms, Software Scalable Architecture
- 38. 38 NVIDIA DRIVE PX 2 AUTOCRUISE 10W AI Car Computer | Passive Cooling | Automotive IO AI Highway Driving | Localization & Mapping
- 39. 39 NVIDIA & BAIDU PARTNER ON AI SELF-DRIVING CARS
- 40. 40 NVIDIA AI SELF-DRIVING CARS IN DEVELOPMENT Baidu nuTonomy Volvo WEpods NVIDIA
- 41. 41 NVIDIA END-TO-END DEEP LEARNING PLATFORM TRAINING PaddlePaddle Baidu Deep Learning DGX-1TESLA P100
- 42. 42 NVIDIA END-TO-END DEEP LEARNING PLATFORM TRAINING PaddlePaddle Baidu Deep Learning DGX-1TESLA P100 DATACENTER INFERENCING ANNOUNCING TESLA P4 & P40 ANNOUNCING TensorRT
- 43. 43 NVIDIA END-TO-END DEEP LEARNING PLATFORM TRAINING PaddlePaddle Baidu Deep Learning DGX-1TESLA P100 DATACENTER INFERENCING ANNOUNCING TESLA P4 & P40 ANNOUNCING TensorRT CUDA JETPACK DRIVEWORKS JETSON TX1 ANNOUNCING DRIVE PX 2 AUTOCRUISE INTELLIGENT DEVICES
- 44. 44 NVIDIA DEEP LEARNING PLATFORM PARTNERS AI ENTERPRISE AI CITY AI CAR
- 45. 45 AI FOR EVERYONE AI will Revolutionize Transportation AI will Revolutionize Healthcare AI will Revolutionize Society