Jen-Hsun Huang, Founder & CEO | SC’16 | Nov. 14, 2016

THE GREATEST CHALLENGES CAN’T WAIT

2

Pascal — 5 Miracles Pascal Supercomputers3x Developers in 2 Years10 of Top 10 HPC

Applications Accelerated

Pascal

16nm FinFET

CoWoS HBM2

NVLink

cuDNN

120,0002014

400,0002016

Gaussian

ANSYS Fluent

GROMACS

Simulia Abaqus

NAMD

WRF

VASP

OpenFOAM

LS-DYNA

AMBER

>400HPC Apps

A GREAT YEAR FOR GPU COMPUTING

3

Numerical models to understand and predict physical and biological behavior

Based on the laws of physics —motion, gravity, mass-energy, thermodynamics, electrostatics

Computational methods like PDE, FEM, MC, LA

Turbulent Flow

Structural Analysis

Molecular Dynamics

N-body Simulation

COMPUTATIONAL SCIENCE

4

Combinatorial explosion

Incomplete information

No laws-of-physics equations exist

Deep learning extracts multi-dimensional features from data

Breakthrough for AI

“What’s the next move?” “Is there cancer?”

“What’s happening” “What does she mean?”

DATA SCIENCE

5

DEEP LEARNING IS A SUPERCOMPUTING CHALLENGE

INFERENCING

RECOGNIZE

CLASSIFY

PREDICT

GENERATE

TRAINING

PIPELINE

MODEL CONFIGURATION

HYPERPARAMETER TUNING

MODEL TRAINING

100’s OF PETAFLOPS TO

EXAFLOPS MACHINES

DATA

PIPELINE

PROCESS

AUGMENT

AUTO LABEL

MANUAL LABEL

CURATE

PETABYTES OF DATA

PETAFLOPS MACHINE

100’s OF GIGAFLOPS

TO TERAFLOPS

6

Future supercomputers designed for computational and data science

Strong CPU – Variable Precision Computation – High-Speed Links

4X 5.3 TF FP644X 10.6 TF FP324X 21.2 TF FP16

640GB/s NVLink

CPU

THE ENGINE FOR AI SUPERCOMPUTING

7

GPU Boosts HPC GPU Boosts AIGPU Boosts AI

ImageNet — Accuracy Speech Recognition — AccuracyProcessor Trends

AI IS THE PATH TO EXASCALE

8

Accelerating Targeted Drug Development

Reducing Cancer DiagnosisError Rate by 85%

Predicting Disease from Medical Records

AI IS REVOLUTIONIZING HEALTHCARE

9

2014 2016

Higher Ed

Internet

Healthcare

Finance

Automotive

Others

EVERY INDUSTRY HAS AWOKEN TO AIOrganizations Engaged with NVIDIA on Deep Learning

1,549

19,439

Government

Developer Tools

10

GTC, DLI, Inception

One Architecture Everywhere

Advance GPU Deep Learning Accelerate Every Framework

PaddlePaddleBaidu Deep Learning

GPU DL-as-a-Service

NVIDIA AI COMPUTING PLATFORM

11

NVIDIA Tesla GPU

NVIDIA DGX-1

ANNOUNCING NVIDIA & MICROSOFTCognitive Toolkit Optimized for DGX-1 & Azure Cloud

Azure Data Center

NVIDIA GPUDL Toolkit

12

CortanaPersonal Assistant

SkypeLanguage Translator

BingSearch Engine

HololensAugmented Reality

MICROSOFT COGNITIVE TOOLKITEngine Behind Microsoft Products, Now Democratizing AI for All

13

170x Faster (AlexNet images/sec)

78

13,000

CPU Server DGX-1

170X SPEED-UP OVER COTS SERVER MICROSOFT COGNITIVE TOOLKIT SUPERCHARGED ON NVIDIA DGX-1

AlexNet training batch size 128, Dual Socket E5-2699v4, 44 cores CNTK 2.0b2 for CPU.

CNTK 2.0b3 (to be released) includes cuDNN 5.1.8, NCCL 1.6.1, NVLink enabled

8x Tesla P100 | 170TF FP16 | NVLink hybrid cube mesh

14

CANDLECancer Distributed Deep Learning Environment

ANNOUNCING NVIDIA, DOE, NCI BUILDAI PLATFORM FOR CANCER MOONSHOT

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Accelerate Discovery of Cancer Therapies

Automate Analysisof Treatment Effectiveness

Predict Drug Responseof Cancer Patients

June 2016 NCI Genomic Data Commons = 3PB Data

CANDLE FOR EXASCALE DEEP LEARNING PRECISION MEDICINE FOR CANCER

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Fastest AI Supercomputer in TOP5004.9 Petaflops Peak FP6419.6 Petaflops Peak FP16

Most Energy Efficient Supercomputer#1 Green5009.5 GFLOPS per Watt

Rocket for Cancer MoonshotCANDLE Development Platform Common platform with DOE labs — ANL, LLNL,

ORNL, LANL

INTRODUCING DGX SATURNV124 NVIDIA DGX-1 “Rocket for Cancer Moonshot”

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AI EnterpriseAI Transportation AI Factory AI Healthcare

PowerAI ToolkitMinsky

CANDLE

NVIDIA AI COMPUTING FOR EVERY INDUSTRY