GTCx 2016 — Seoul

THE DEEP LEARNING AI REVOLUTION

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NEW ERA OF COMPUTING

PC INTERNET

AI & INTELLIGENT DEVICES

MOBILE-CLOUD

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GPU DEEP LEARNING BIG BANG

Deep Learning NVIDIA GPU

NIPS (2012)

ImageNet Classification with Deep ConvolutionalNeural Networks

Alex KrizhevskyUniversity of Toronto

Ilya SutskeverUniversity of Toronto

Geoffrey e. HintonUniversity of Toronto

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74%

96%

2010 2011 2012 2013 2014 2015

Deep Learning

THE STAGE IS SET FOR THE AI REVOLUTION

2012: Deep Learning researchersworldwide discover GPUs

2015: ImageNet — Deep Learning achievessuperhuman image recognition

2016: Microsoft’s Deep Learning system achieves new milestone in speech recognition

Human

Hand-coded CV

Microsoft, Google3.5% error rate

Microsoft09/13/16

“The Microsoft 2016 Conversational Speech Recognition System.” W. Xiong, J. Droppo, X. Huang, F. Seide, M.

Seltzer, A. Stolcke, D. Yu, G. Zweig. 2016

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NVIDIA — “THE AI COMPUTING COMPANY”

GPU Computing Computer Graphics Artificial Intelligence

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SCI-FI NO LONGERThe Near Future with VR, AR and AI

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GTC — 25X GROWTH IN GPU DL DEVELOPERS

4X Attendees 3X GPU Developers 25x Deep Learning Developers

2014

55,000400,00016,000

2,200120,000

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

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WHY DID AI RESEARCHERS ADOPT GPUs FOR DEEP LEARNING?

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BRAIN IS LIKE A GPU

BRAIN CREATES MENTAL IMAGES WHEN WE THINK

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GPU IS LIKE A BRAIN

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GPU DEEP LEARNING IS A NEW COMPUTING MODEL

Training

Intelligent Devices

Datacenter

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GPU DEEP LEARNING IS A NEW COMPUTING MODEL

TRAINING

Billions of Trillions of Operations

GPU train larger models,accelerate time to market

Training

Intelligent Devices

Datacenter

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GPU DEEP LEARNING IS A NEW COMPUTING MODEL

DEEP NEURAL NETWORK

Modern neural network with hundreds of hidden layers

Generalize representations by learning hierarchy of features

Billions of operations

Training

Intelligent Devices

Datacenter

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GPU DEEP LEARNING IS A NEW COMPUTING MODEL

DATACENTER INFERENCING

10s of billions of image, voice, video queries per day

GPU inference for fast response, maximize datacenter throughput

Training

Intelligent Devices

Datacenter

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GPU DEEP LEARNING IS A NEW COMPUTING MODEL

DEVICE INFERENCING

Billions of intelligent devices

GPU for real-time accurate response

Training

Intelligent Devices

Datacenter

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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!)

2012AlexNet

2015ResNet

152 layers

22.6 GFLOP

~3.5% error8 layers

1.4 GFLOP

~16% Error

16XModel

2014Deep Speech 1

2015Deep Speech 2

80 GFLOP7,000 hrs of Data

~8% Error

10XTraining Ops

465 GFLOP

12,000 hrs of Data

~5% Error

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PASCAL “5 MIRACLES” BOOST DEEP LEARNING 65X

Pascal — 5 Miracles NVIDIA DGX-1 Supercomputer 65X in 4 yrs Accelerate Every Framework

PaddlePaddleBaidu 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

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NEW IBM SERVER FOR THE AI ENTERPRISEPOWER8 + NVIDIA TESLA P100

“Putting NVIDIA’s technology into the IBM system will

speed up performance for such emerging workloads as AI,

deep learning and data analytics.” — eWeek

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Training

Intelligent Devices

Datacenter

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TESLA P4 & P40 INFERENCING ACCELERATORS

Pascal Architecture | INT8

P40: 250W | 40X Energy Efficient versus CPU

P40: 250W | 40X Performance versus CPU

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TensorRTPERFORMANCE OPTIMIZING INFERENCING ENGINE

FP32, FP16, INT8 | Vertical & Horizontal Fusion | Auto-Tuning

VGG, GoogLeNet, ResNet, AlexNet & Custom Layers

Available Today: developer.nvidia.com/tensorrt

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NVIDIA AI COMPUTING ECOSYSTEM

AI-powered Consumer Services AI-as-a-Service AI for Enterprise GPU Server Builders

iQIYI JD.comGoogleFlickr

Amazon FacebookeBayBaidu

ShazamQihoo 360 Skype Sogou

Periscope PinterestNetflixMicrosoft

TwitterTencent Yandex Yelp

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>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

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Training Datacenter

Intelligent Devices

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“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

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JETSON TX1 EMBEDDED AI SUPERCOMPUTER

10W | 1 TF FP16 | >20 images/sec/W

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NVIDIA EMBEDDED AI COMPUTING PLATFORM

Best AI Development Environment New Training Courses for AI Developers Worldwide Partnerships

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AI TRANSPORTATION — $10T INDUSTRY

PERCEPTION AI PERCEPTION AI LOCALIZATION DRIVING AI

DEEP LEARNING

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NVIDIA DRIVE PX 2AutoCruise to Full Autonomy — One Architecture

Full Autonomy

AutoChauffeur

AutoCruise

AUTONOMOUS DRIVINGPerception, Reasoning, Driving

AI Supercomputing, AI Algorithms, Software

Scalable Architecture

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NVIDIA DRIVE PX 2 AUTOCRUISE

10W AI Car Computer | Passive Cooling | Automotive IO

AI Highway Driving | Localization & Mapping

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3D CAR DETECTION FREE SPACE DETECTION

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NVIDIA BB8 AI CAR

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UDACITY SELECTS DRIVE PX 2 FOR SELF-DRIVING CAR

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ANNOUNCING TOMTOM SELECTS DRIVE PX 2 FOR SELF-DRIVING CAR

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NVIDIA & TOMTOM SELF-DRIVING CAR

NVIDIA DRIVEWORKS OS

MAPPING

AI

PERCEPTION

AI

LOCALIZATION

CV

DRIVING

AI

NVIDIA DRIVE PX 2 AUTOCRUISE

TESLA FOR CLOUD HD MAP PROCESSING

DRIVE PX 2 FOR IN-CAR HD MAP PROCESSING

OPEN “CLOUD-TO-CAR” SDC PLATFORM —HD MAP, AI ALGORITHMS, AI SUPERCOMPUTER

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ANNOUNCING DRIVEWORKS ALPHA 1OS FOR SELF-DRIVING CARS

DRIVEWORKS

PilotNet

OpenRoadNet

DriveNet

Localization

Path Planning

Traffic Prediction

Action Engine

Occupancy Grid

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NVIDIA AI SELF-DRIVING CARS IN DEVELOPMENT

Baidu nuTonomy Volvo WEpodsTomTom

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VISUALCOMPUTING

AI

HPC

AI COMPUTING FOR INTELLIGENT MACHINES

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INTRODUCING XAVIERAI SUPERCOMPUTER SOC

7 Billion Transistors 16nm FF

8 Core Custom ARM64 CPU

512 Core Volta GPU

New Computer Vision Accelerator

Dual 8K HDR Video Processors

Designed for ASIL C Functional Safety

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DRIVE PX 2

2 PARKER + 2 PASCAL GPU | 20 TOPS DL | 120 SPECINT | 80W

XAVIER

20 TOPS DL | 160 SPECINT | 20W

INTRODUCING XAVIERAI SUPERCOMPUTER SOC

ONE ARCHITECTURE

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AI FOR EVERYONE

AI will Revolutionize Transportation AI will Revolutionize Healthcare AI will Revolutionize Society