2016 06 nvidia-isc_supercomputing_car_v02
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The document discusses advancements in supercomputing for self-driving cars, highlighting the role of deep learning and NVIDIA's Drive PX platform as essential components for autonomous vehicle technology. It outlines key developments by companies like Uber, Tesla, and Volvo in the self-driving sector, alongside a description of NVIDIA's hardware capabilities for AI processing. The text emphasizes the importance of high-performance computing and deep learning frameworks for achieving advancements in vehicle autonomy and safety.
2016 06 nvidia-isc_supercomputing_car_v02
- 1. SUPERCOMPUTING IN A CAR Carlo Nardone, Senior Solution Architect EMEA Enterprise ISC 2016
- 2. 2 ENTERPRISE AUTOGAMING DATA CENTERPRO VISUALIZATION THE WORLD LEADER IN VISUAL COMPUTING
- 5. 5 SIMULATION MEANS BETTER PRODUCTS, FASTER ACTUAL CRASH SIMULATED CRASH
- 6. 6 THE SELF DRIVING REVOLUTION Safer Driving New Mobility Services Urban Redesign
- 7. 7 AUTONOMOUS DRIVING IS HARD
- 8. 8 Uber Enters the Race Toyota Invests $1B in AI Lab Volvo Drive Me on Public Roads in 2017 NHTSA: Computer Counts as Driver Tesla Model 3: 300K pre-orders 2016: AN AMAZING YEAR FOR SELF-DRIVING CARS Audi, BMW, Daimler Buy HERE Tesla Model S Auto-pilot Baidu Enters the Race Honda, Nissan, Toyota Team Up GM Buys Cruise
- 9. 9 DEEP LEARNING FOR SELF-DRIVING CARS
- 10. 10 NVIDIA PILOTNET VIDEO Paper on http://arxiv.org/abs/1604.07316
- 11. 11 THE BIG BANG IN MACHINE LEARNING DNN GPUBIG DATA “The GPU is the workhorse of modern A.I.”
- 12. 12 Image “Volvo XC90” Image source: “Unsupervised Learning of Hierarchical Representations with Convolutional Deep Belief Networks” ICML 2009 & Comm. ACM 2011. Honglak Lee, Roger Grosse, Rajesh Ranganath, and Andrew Ng. WHAT IS DEEP LEARNING?
- 14. DEEP LEARNING EVERYWHERE NVIDIA Titan X NVIDIA Jetson NVIDIA Tesla NVIDIA DRIVE PX
- 15. 15NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. NVIDIA DGX-1 WORLD’S FIRST DEEP LEARNING SUPERCOMPUTER 170 TFLOPS FP16 8x Tesla P100 16GB NVLink Hybrid Cube Mesh Accelerates Major AI Frameworks Dual Xeon 7 TB SSD Deep Learning Cache Dual 10GbE, Quad IB 100Gb 3RU – 3200W
- 16. 16 NVIDIA END-TO-END AUTONOMOUS DRIVING PLATFORM NVIDIA DRIVE PX 2NVIDIA DGX-1 NVIDIA DRIVENET Localization Planning Visualization Perception DRIVEWORKS
- 17. 17 NVIDIA DRIVE PX 2 World’s First AI Supercomputer for Self-Driving Cars 12 CPU cores | Pascal GPU | 8 TFLOPS | 24 DL TOPS | 16nm FF | 250W | Liquid Cooled
- 19. 19 SELF DRIVING COMPUTER I/O NVIDIA Drive PX 2: 70 Gbps aggregate I/O DISPLAY DATA LOGGING DRIVE TRAIN POWER TRAIN Ethernet GMSL Ethernet FlexRay/Ethernet TEGRA TEGRA SMART CAMERAS CAMERAS LIDAR RADAR CANBus LVDS USB/PCIE
- 20. 20 DRIVE™ PX 2 COMPUTATION ENGINES 24 DL TOPS, 8 TFLOPS, high performance CPU/GPU complex
- 21. 21 NVIDIA DRIVE PX SW STACK A full stack of rich software components
- 22. 22 GPU INFERENCE ENGINE High-performance framework makes it easy to develop GPU-accelerated inference Production deployment solution for deep learning inference Optimized inference for a given trained neural network and target GPU Solutions for Hyperscale, ADAS, Embedded Supports deployment of 32-bit or 16-bit inference Maximum Performance for Deep Learning Inference developer.nvidia.com/gpu-inference-engine GPU Inference Engine for Automotive Pedestrian Detection Lane Tracking Traffic Sign Recognition --- NVIDIA DRIVE PX 2
- 23. ACTIVE LEARNING Data Scientist Vehicle Drive PX - Deploy Model Classification Detection Segmentation DIGITS / Tesla - Train Network Solver Dashboard
- 24. 24 A COMPLETE DEEP LEARNING PLATFORM MANAGE TRAIN DEPLOY DIGITS DATA CENTER AUTOMOTIVE TRAINTEST MANAGE / AUGMENT EMBEDDED GPU INFERENCE ENGINE
- 25. NVIDIA DRIVE™ PX 2 Selected by Volvo on Journey Towards a Crash-Free Future
- 26. 26 WORLD’S FIRST AUTONOMOUS CAR RACE 10 teams, 20 identical cars | DRIVE PX 2 as “brain” in every car | 2016/17 Formula E season
- 27. THANK YOU! cnardone@nvidia.com +39 335 5828197 www.nvidia.com/drive
- 28. 28 DEEP LEARNING & ARTIFICIAL INTELLIGENCE Sep 28-29, 2016 | Amsterdam www.gputechconf.eu #GTC16 SELF-DRIVING CARS VIRTUAL REALITY & AUGMENTED REALITY SUPERCOMPUTING & HPC GTC Europe is a two-day conference designed to expose the innovative ways developers, businesses and academics are using parallel computing to transform our world. GTC EUROPE 2 Days | 800 Attendees | 50+ Exhibitors | 50+ Speakers | 15+ Tracks | 15+ Workshops | 1-to-1 Meetings
- 29. BACKUP SLIDES
- 30. 30 MANY THINGS TO LEARN
- 31. 31 THE BASIC SELF-DRIVING LOOP LOCALIZE MAP CONTROLSENSE PLAN PERCEIVE
- 32. 32 INTERFACES 70 Gigabits per second of I/O Sensor Fusion Interfaces: GMSL Camera, CAN, GbE, BroadR-Reach, FlexRay, LIN, GPIO Displays and Cockpit Computer Interfaces HDMI, FPDLink III and GMSL Development and Debug Interfaces HDMI, GbE, 10GbE, USB3, USB 2 (UART/debug), JTAG Auto Grade connectors Debug/Lab interfaces
- 33. 33 GPU INFERENCE ENGINE Optimizations • Fuse network layers • Eliminate concatenation layers • Kernel specialization • Auto-tuning for target platform • Select optimal tensor layout • Batch size tuningTRAINED NEURAL NETWORK OPTIMIZED INFERENCE RUNTIME developer.nvidia.com/gpu-inference-engine
- 34. OPEN PLATFORM FOR ALL DEVELOPERS
- 35. 37 AUTOMOTIVE PARTNERS Self Driving Vehicles
- 36. “Using NVIDIA DIGITS deep learning platform, in less than four hours we achieved over 96% accuracy using Ruhr University Bochum’s traffic sign database. While others invested years of development to achieve similar levels of perception with classical computer vision algorithms, we have been able to do it at the speed of light.” Matthias Rudolph, Director of Architecture, Driver Assistance Systems, Audi
- 37. “Deep learning on NVIDIA DIGITS has allowed for a 30x enhancement in training pedestrian detection algorithms, which are being further tested and developed as we move them onto the NVIDIA DRIVE PX.” Dragos Maciuca, Technical Director, Ford Research and Innovation Center
- 39. 41
- 40. 42 DGX-1 GPU CLUSTER Two fully connected quads, connected at corners 160GB/s per GPU bidirectional to Peers Load/store access to Peer Memory Full atomics to Peer GPUs High speed copy engines for bulk data copy PCIe to/from CPU