NVIDIA HPC
2022/12/9(@_ksasaki)

NVIDIA HPC

HOLOSCANMODULUSNVIDIA HPC

HPC SDKCUQUANTUMQODA

NVIDIA AI

NVIDIA Omniverse

OMNIVERSE

RTX

CUDA-X

PHYSX

DOCA

FLEET
COMMAND

CLOUD
NATIVE

H100

GRACE HOPPER
SUPERCHIPGRACE CPUSUPERCHIP

QUANTUM-2

BLUEFIELD-3

SPECTRUM-4

Exascale AI

HPC

LiU
Cambridge-1
NERSC

Bristol
NVIDIA ANL
LANL

BSC

18 EFLOPS AI Perf
Quantum-2 400Gb/s InfiniBand

Naver

TACC
UoF

NVIDIA (EOS)

JülichCSCS
CINECALANL (Venado)
10 EFLOPS AI Perf

KAUST

BSC (MareNostrum 5)
18 EFLOPS AI PerfQuantum-2 400Gb/s InfiniBand

CSCS (ALPS)
20 EFLOPS AI PerfC-DAC

CINECA (Leonardo)
10 EFLOPS

KAUST (Shaheen-III)
7 EFLOPS AI PerfNVIDIA H100AI

AI/HPC
4PF FP8 (6X)| 2PF FP16 (3X)| 1PF TF32 (3X)| 67TF FP64 (3X)
3.35TB/s (1.5X), 80GB HBM3 memory

TRANSFORMER
6X faster on largest transformer models

7 Fully isolated & secured instances, guaranteed QoS
2nd Gen MIG | Confidential Computing

900 GB/s GPU-2-GPU connectivity (1.5X) | 128GB/s PCI Gen5Custom TSMC 4N Process | 4.9 TB/s Total External B/W

https://resources.nvidia.com/en-us-tensor-core/nvidia-tensor-core-gpu-datasheet

FP8, FP16, TF32 performance include sparsity. X-factor compared to A100

MULTI-INSTANCE GPU (MIG)

GPC
1c.4g.40gb

1H100 GPU

GPC

GPC

7GPC

GPC

GPC

GPC

コンピュート
インスタンスコンピュート
インスタンス

メモリ

メモリ

メモリ

GPU インスタンス
4g.40gb

GPU インスタンス
2g.20gb

GPU インスタンス

1c.4g.40gb

1c.4g.40gb

1c.4g.40gb

GPU

1g.10gb

H100 GPU 搭載 DGX H100
GPU

8 x NVIDIA H100 Tensor Core GPUs

GPU memory

640 GB total

Performance

32 petaFLOPs FP8NVswitches

4CPUs

2 x x86

System Memory

2 TB

Networking
4 x OSFP ports provide connectivity to 8 x NVIDIA
connectivity and speed ConnectX-7s
8 x 400Gb/s InfiniBand/Ethernet*
2 x dual-port NVIDIA ConnectX-7
1 x 400Gb/s InfiniBand/Ethernet and1 x 200Gb/s InfiniBand/Ethernet*
Cache Storage

8 x U.2 3.84TB NVMe Secure Erase Drives

Boot Storage

2 x 1.92TB M.2 NVMe (software encryptable)

Host Management

On-board 10Gb/s RJ-45 Ethernet
Optional 50Gb/s QSFP Ethernet NIC

Remote SystemManagement

Baseboard Management Controller (BMC)
1Gb/s RJ-45 network connectivity
Remote Keyboard, Video, Mouse (KVM)
Remote Storage
RedFish, IPMI management

Operating System

DGX OS based on Ubuntu
Additional support for Ubuntu and Red Hat EnterpriseLinuxNVIDIA DGX H100
The world’s first AI system with the NVIDIA H100 Tensor Core GPU* Subject to Change

DGX H100

NVIDIA H100 PCIE

AI/HPC
3.2PF FP8 (5X) | 1.6PF FP16 (2.5X) | 800TF TF32 (2.5X) | 48TF FP64 (2.5X)
6X faster Dynamic Programming with DPX Instructions
2TB/s , 80GB HBM2e memory

Configurable TDP - 200W to 350W
2 Slot FHFL mainstream form factor

7 Fully isolated & secured instances, guaranteed QoS
2nd Gen MIG | Confidential Computing

128GB/s PCI Gen5600 GB/s GPU-2-GPU connectivity (5X PCIe Gen5)
up to 2 GPUs with NVLink Bridge

FP8, FP16, TF32 performance include sparsity. X-factor compared to A100

H100

GREEN500

https://blogs.nvidia.co.jp/2022/11/16/green/NVIDIA RTX 6000 Ada

NVIDIAL40
Ada for the Data Center

Ada for the Enterprise Desktop• Up to 2x Faster than RTX A6000• Up to 2x Faster than A40• 48GB GDDR6 w/ECC Memory• 48GB GDDR6 w/ECC Memory• 4x DP1.4 Display Outputs• 4x DP1.4 Display Outputs• PCIe Gen 4• PCIe Gen 4• vGPU Support

Ada is incredibly energy efficient – over twice the performance at the same power compared to Ampere.

• vGPU Support• Available from channel partners
starting in December 2022, OEMpartners early 2023

• Availability starting in December 2022

*Specifications, availability dates subject to change. vGPU support in Q1 2023

Ada Lovelace
RTX

GPU
AI HPC
Unprecedented Performance,
Scalability, Security

High Compute Perf AI, HPC,
Data Processing

AI Inference & Mainstream
ComputeUnprecedented VisualComputing PerformanceHigh Performance
Graphics

DL Training

DL Training

Scientific ResearchOmniverse

Cloud Rendering

Scientific Research

Scientific ResearchConversational AIRendering and 3D Graphics

Cloud XR and vWS

Data Analytics

Data Analytics

Recommender Systems

AI Training and Data ScienceOmniverse

Highest Compute,Transformer Engine,
Confidential Computing

FP64, TF32
up to 7 MIG instances

Versatile Mainstream
ComputeFP64, Up to 4 MIG instances

Fastest RT Graphics
Largest render models

4K Resolution
Max # of encode/decodestreams

H100

A100

A30

L40

A40

SXM/PCIe | 700W | 80GB
FP64 67TF | FP16 1979TF
Mem BW 3.35TB/s | Liquid

SXM/PCIe | 400W | 80GB
FP64 19.5TF | FP16 624TF
Mem BW 2.04TB/s | Liquid

Compute165W | 24GB
FP32 88TF | RT Core 202TF
Mem BW 864GB/s

300W | 48GB
FP32 88TF | RT Core 202TF
Mem BW 864GB/s | 4x DisplayPort

300W | 48GB
FP32 37.4TF | RT Core 73.1TF
Mem BW 696GB/s | 3x DisplayPort

Compute & Graphics

Graphics

Grace CPU
HPC
GRACE CPU SUPERCHIP

3.0X

HPC APPLICATION PERFORMANCE
Up to 1.8X Speedup with 2.4X Better Efficiency
Performance

Efficiency

2.5X2.4X

2.0X
2.0X

1.8X
1.5X

1.5X

1X

1.0X

x86 CPU

144-core Arm Neoverse V2 cores in a Superchip
NVLink-C2C, 900 GB/s Bi-Directional BW

0.5X

LPDDR5X With ECC, 1TB/s Memory BW
0.0X

Available 1H 2023​

Genomics
BWA-MEM2ClimateNEMO

Grace CPU Superchip Pre-silicon ESTIMATES ONLY, Subject to change: | AMD Milan CPU baseline| BWA-MEM2 (Single Socket/Chip) | NEMO GYRE_PISCES nn_GYRE=25(Dual Socket/Chip)

Grace Hopper
AIHPC

GRACE HOPPER SUPERCHIP

Grace 72-core Arm Neoverse V2 CPUHopper H100 GPU

Relative Performance

x86+H100LPDDR5X & HBM3 memory – 3.5TB/s memory BW
Almost 600GB of Fast Memory for GPU

5.3X

Grace Hopper

4.1X

2.2X

1.4X

1.5X

1.5X

1Xx86+A100

NVLink-C2C - 900GB/s coherent CPU to GPU interconnect
Dynamic power sharing between CPU and GPU

MD
GROMACS

CFD
OpenFOAMMD
CP2K

Available 1H 2023​

Grace Hopper Superchip performance comparisons are Pre-silicon ESTIMATES ONLY and are subject to change. Configurations: 2x86 + 4x A100, 2x86 + 4x H100, 4x
Grace Hopper Superchip single nodes. Benchmarks comparing throughput: GROMACS dataset STMV 1066628 atoms | OpenFOAM dataset Lid driven cavity flow | CP2K
dataset RPA

GRACEGRACE HOPPERHPC
1.8

1 MW Data Center with 20% of power for CPU nodes and 80% power for accelerated system.
X86 Data Center consists of 2S Milan CPU and Dual Milan and 4xH100 GPU nodes. Grace CPU Super Node and Grace Hopper Nodes.
CPU workload consisting of a mix of HPC applications . GPU workloads consisting of a mix of HPC applications (including LAMMPS, GROMACS, and CP2K)
Projected data center workload performance, subject to change.

X86 CPU AND X86 + H100 DATA CENTERGRACE AND GRACE HOPPER DATA CENTER

180 2x86 CPU nodes

250 Grace CPU Superchip nodes

168 2x86 + 4xH100 nodes

570 Grace Hopper Superchip nodes

IB Networking

IB Networking

1 MW total power

1 MW total power

NVIDIA Networking

In-Network Computing
Zero Trust Security

NVIDIA CLOUD-NATIVE
SUPERCOMPUTING PLATFORM

Performance Isolation
Computational Storage
Enhanced Telemetry

QUANTUM-2 INFINIBAND SWITCHCONNECTX-7 SMARTNIC

BLUEFIELD-3 / -X DPU

SPECTRUM-3 ETHERNET SWITCHUFM

SHARP In-Network Computing
Higher Scalability

Intelligent Offloads
Data-path Acceleration Engines

Programmable In-Network Computing
Software Defined Networking

Secure Data AccessConsistent Performance

Monitoring, Management, Orchestration
Predictive Maintenance, Anomaly Detection

BlueField Data Processing Unit
SOFTWARE DEFINED NETWORKINGSOFTWARE DEFINED SECURITY

SOFTWARE DEFINED STORAGE

Infrastructure Services

Data Center on a Chip
16 Arm 64-Bit Cores
16 Core / 256 Threads Datapath Accelerator
ConnectX InfiniBand / Ethernet
DDR memory interface
PCIe switch

BlueField Infrastructure
Compute Platform

Higher Application PerformanceWith BlueField DPU and Quantum In-Network Computing

1.26X
1.24X
1.2X

Barcelona
Supercomputing CenterDurhamUniversity​

Georgia Instituteof TechnologyJapan
Meteorological Agency

Los Alamos
National Laboratory

Ohio State
University

Sandia National
Laboratory

Technical University
MunichUniversity CollegeLondon

NVIDIA Software Enabling ScienceNVIDIA HPC SDKDEVELOPMENT
Programming
ModelsStandard C++ & FortranCore
Libraries

Compilers

nvcc

nvc

libcu++ANALYSIS
Math
Libraries

cuBLAS

Communication
Libraries
HPC-X

cuTENSOR

Profilers

DebuggerNsightcuda-gdb

Systems

Host

ComputeDeviceMPIOpenACC & OpenMP

nvc++

ThrustcuSPARSE

cuSOLVER

UCX

SHMEM

SHARP

HCOLL

NVSHMEM
CUDA

nvfortran

CUB

cuFFT

cuRAND

NCCL

Available Everywhere: developer.nvidia.com/hpc-sdk, on NGC catalog, via Spack, and in the CloudHPC SDK 22.11
Multi-node Libraries | Standard Language Parallelism

MULTI NODE CUFFT

MULTI NODE MAGNUM IO

Nearly 3X VASP Performance Increase Using NCCL

Relative Speedup (2 nodes - Fall 2021)

140X
120X

100X
80X
60X

16X

4.5X

14X

4.0X

12X
Speedup Relative to 32 GPUs

768 - NCCL OFF

160X

Relative SPEEDUP

Using cuFFT
No cuFFT

768 - NCCL ON

180X

PALABOS Strong Scaling

5X Performance for Multi-Node GROMACS

5.0X

200X

MULTI NODE C++ STDPAR WITH NVC++

3.5X

3.0X

2.5X

Ideal

Speedup

200

400

10X

8X

6X

2.0X

4X

1.5X

2X

1.0X

0X

40X
20X
0X
0100200# Nodes

30001020# Nodes

30400600# A100 GPUs

Left Panel: VASP 6.3.2 with MAGNUM IO (NCCL On) vs OpenMPI+UCX (NCCL Off) on DGX-A100 SuperPOD for Hafnia (HfO2) testcase of 4x4x4: 768 atoms, 3840 orbitals | Center Panel: GROMACS Performance on DGX-A100 SuperPOD (4 GPUs and 4 HDR IB connections) using versions 2022.3 and development branch2023-dev-20220927-4b826f6c6f-dirty plotted relative 2021.1 on 2 Nodes 4 GPUs each | Right Panel: PALABOS version 2.3.0++ compiled with unreleased HPC-SDK run on Selene 8x A100 80 GB & 8x HDR IB per node

NVIDIA Grace HPC/AI
Full support for the broad Arm software ecosystem, both open source and commercial

Compilers
NVIDIA, GCC, Clang/Flang(LLVM), Arm, Cray, Fujitsu

Libraries
ArmPL, FFTW, BLIS, OpenBLAS,
NumPy, Hypre, SuperLU,
ScaLAPACK, MUMMPS, HDF5,NetCDF…

Filesystems
NFS (pNFS), Lustre, BeeGFS

Admin Tools & Packaging
Spack, EasyBuild, RPM, apt, Ganglia, modulefiles, Lmod, LosF, Nagios, pdsh, ClusterShell,…

OS
All major Linux distributions

Arm SystemReady SR
Standard firmware and RAS

Containers & Orchestration

Frameworks, Libraries,
SDKs, Toolkits, etc.

OFED, OpenUCX, HPC-X, OpenMPI, MPICH, MVAPICH2, OpenSHMEM, HPE MPI, …

Cluster Management

Communication Libraries

Schedulers

NVIDIA
SoftwareDocker, Apptainer, Sylabs.io SingularityCE, Kubernetes, KVM, …

AI, HPC, General Compute

Forge, Totalview, HPC Toolkit,Scalasca, Vampir, TAU, PAPI …

NVIDIA Bright, HPE CMU, xCat, Warewulf, puppets, Ansible, Open Stack,…

Applications

Slurm, Altair PBS Pro & Grid Engine, IBM Spectrum LSF, …

Developer Tools

NVIDIA Modulus

RENEWABLE ENERGY

CLIMATE CHANGE

Siemens Gamesa
Up to 4000X Speedup of Wind
Turbine Wake Optimization

45,000X Speedup of
Extreme weather Prediction
with FourCastNet

RENEWABLE ENERGY

INDUSTRIAL HPC

SGTC Plasma Fusion

NVIDIA LaunchPad

RTX Workstation Digital Twin

LaunchPad | NGC | DLI

GPU(QIS)(:)+••
•

HPC

•()

••

QPU

HPCGPU25

CUQUANTUM26

NVIDIA HPC
HOLOSCANMODULUSNVIDIA HPC

HPC SDKCUQUANTUMQODANVIDIA AI

NVIDIA Omniverse

OMNIVERSE

RTX

CUDA-X

PHYSX

DOCA

FLEET
COMMAND

CLOUD
NATIVE

H100

GRACE HOPPER
SUPERCHIPGRACE CPUSUPERCHIP

QUANTUM-2

BLUEFIELD-3

SPECTRUM-4