NVIDIA DGX A100/ NVIDIA DGX SUPERPOD最新情報
JLUG 2021, 2021/12/10 エヌビディア合同会社, シニアソリューションアーキテクト, 森野 慎也

A NEW COMPUTING LAW

MACHINELEARNING

109
108

SCALE
UP & OUT

107
106
105
Accelerated Computing

AI

Data Center Scale104
ACCELERATEDCOMPUTING

103
102

1.1X per year

101

1.5X per year
Single-threaded perf

1980

1990

2000

2010

2020

GPUDIRECT STORAGE GA
AVAILABLE WITH CUDA 11.4
6.6X perf benefit in DL inference
Low latency, high throughput
Multi-node storage acceleration library
Supported by a strong ecosystem
Available on DGX
OS: DGX BASEOS 5.0, Ubuntu 18.04, 20.04, RHEL 8.3
DL frameworks: PyTorch, MXNet
Data analytics frameworks: DALI, RAPIDS cuDF
CUDA 11.4 toolkit integration

Magnum IO GPUDirect Storage | NVIDIA DeveloperNVIDIA QUANTUM-2400G NDR InfiniBand
Cloud-Native Supercomputing

Multi-Tenant
Bare-Metal Secure

Performance
Isolation

Congestion
Control

SHARP Gen 3In-Network Computing

Precision
TimingNVIDIA QUANTUM-2400G NDR InfiniBand
Cloud-Native Supercomputing

QUANTUM-2 SWITCHCONNECTX-7 INFINIBAND

BLUEFIELD-3 INFINIBAND

64-Ports of 400 Gbps or 128-Ports of 200 Gbps

4X In-Network Computing Performance

16 Arm 64-Bit Cores | 400 Gbps Crypto Accelerations

32X More AI Acceleration Engines

2X GPUDirect Throughput

4X In-Network Computing Performance

3X Higher Switching Throughput

Sampling Jan ‘22

2X GPUDirect Throughput

Sampling Now

Sampling May ‘22

LEADING QUANTUM SIMULATORSNVIDIA CUQUANTUM BETA

Research the Computer of Tomorrow on theMost Powerful Computer Today

INDUSTRY PARTNERS

Libraries for State Vector and Tensor
Network Simulation
World-Class Performance on Multiple
Quantum Algorithms
Integrated In Leading Quantum Computing Frameworks
from Google and IBM

cuQuantum Available Now for Download
developer.nvidia.com/cuquantum

Oak Ridge National Laboratory and the oak leaf symbol are registered trademarks of the U.S. Department of Energy. Use of this mark does not constitute or imply its
endorsement, recommendation, or favoring by the United States Government or any agency thereof or its contractors or subcontractors.

RESEARCH COMMUNITY PARTNERSNVIDIA Python Data Science and Machine Learning Ecosystem

NVIDIA CUNUMERICTransparently Accelerates and Scales
NumPy Workflows
Zero Code Changes
Automatic Parallelism and Acceleration forMulti-GPU, Multi-Node Systems
Scales to 1,000s of GPUs

Performance ScalabilityAccelerated Computing At-Scalefor PyData and NumPy Ecosystem

cuDF

cuML

cuGraphcuNumericPandasScikit-Learn

NetworkX

NumPy

1,000,000100,00010,0001,0001001011

Available Now on GitHub and Conda
cuNumeric Library Download | NVIDIA Developer

2481632

GPUs64

128

256

512

1,024 2,048

NVIDIA MODULUS

SymPy Equation

Model Library(SiREN, PINO, PINN, MESHFREE)

Physics-ML Neural Simulation Framework
Computational Graph Compiler

Geometry
ICs & BCs

Numerical
Optimization
Plans

Framework for Developing Physics-ML Models
Train Physics-ML Models Using Governing Physics,Simulation, and Observed Data
Multi-GPU, Multi-Node Training
1,000-100,000X Speed Models – Ideal for Digital Twins

Available Now
developer.nvidia.com/modulus

Observations

Multi-Node Multi-GPU Training Engine

EARTH DIGITAL TWIN IN OMNIVERSE

Satellite

Wind Energy
Forecasting

Ocean
Fourier Neural Operator

AI
EARTH
EMULATOR

Extreme
Weather
Prediction

Ecosystem
Disaster
Mitigation

Atmosphere

ERA5 ECMWF
Atmospheric Winds & Geopotential
10 TB | 30km | 5 Atmos Layers

0.25 Seconds for 7-Day Forecast
Training: 4 Hours on 128 A100 GPUs

RAPIDS

Modulus100,000X Speed-Up

Omniverse

EARTH-2 SUPERCOMPUTER

1 Million X Acceleration for Climate Research

World’s largest digital twin
Running Modulus-created AI physics models
Designed to run Omniverse

More details in 2022