GTC Taiwan—NVIDIA today introduced NVIDIA HGX-2™,
the first unified computing platform for both artificial
intelligence and high performance computing.
The HGX-2 cloud server platform, with multi-precision computing
capabilities, provides unique flexibility to support the future of
computing. It allows high-precision calculations using FP64 and
FP32 for scientific computing and simulations, while also enabling
FP16 and Int8 for AI training and inference. This unprecedented
versatility meets the requirements of the growing number of
applications that combine HPC with AI.
A number of leading computer makers today shared plans to bring
to market systems based on the NVIDIA HGX-2 platform.
“The world of computing has changed,” said Jensen Huang, founder
and chief executive officer of NVIDIA, speaking at the GPU
Technology Conference Taiwan, which kicked off today. “CPU scaling
has slowed at a time when computing demand is skyrocketing.
NVIDIA’s HGX-2 with Tensor Core GPUs gives the industry a powerful,
versatile computing platform that fuses HPC and AI to solve the
world’s grand challenges.”
HGX-2-serves as a “building block” for manufacturers to create
some of the most advanced systems for HPC and AI. It has achieved
record AI training speeds of 15,500 images per second on the
ResNet-50 training benchmark, and can replace up to 300 CPU-only
servers.
It incorporates such breakthrough features as NVIDIA NVSwitch™
interconnect fabric, which seamlessly links 16 NVIDIA Tesla® V100
Tensor Core GPUs to work as a single, giant GPU delivering two
petaflops of AI performance. The first system built using HGX-2 was
the recently announced NVIDIA DGX-2™.
HGX-2 comes a year after the launch of the original NVIDIA
HGX-1, at Computex 2017. The HGX-1 reference architecture won broad
adoption among the world’s leading server makers and companies
operating massive datacenters, including Amazon Web Services,
Facebook and Microsoft.
OEM, ODM Systems Expected Later This YearFour
leading server makers — Lenovo, QCT, Supermicro and Wiwynn —
announced plans to bring their own HGX-2-based systems to market
later this year.
Additionally, four of the world’s top original design
manufacturers (ODMs) — Foxconn, Inventec, Quanta and Wistron — are
designing HGX-2-based systems, also expected later this year, for
use in some of the world’s largest cloud datacenters.
Family of NVIDIA GPU-Accelerated Server
PlatformsHGX-2 is a part of the larger family of NVIDIA
GPU-Accelerated Server Platforms, an ecosystem of qualified server
classes addressing a broad array of AI, HPC and accelerated
computing workloads with optimal performance.
Supported by major server manufacturers, the platforms align
with the datacenter server ecosystem by offering the optimal mix of
GPUs, CPUs and interconnects for diverse training (HGX-T2),
inference (HGX-I2) and supercomputing (SCX) applications. Customers
can choose a specific server platform to match their accelerated
computing workload mix and achieve best-in-class performance.
Broad Industry SupportTop OEMs and ODMs have
voiced strong support for HGX-2:
“Foxconn has long been dedicated to hyperscale computing
solutions and successfully won customer recognition. We’re glad to
work with NVIDIA for the HGX-2 project, which is the most promising
solution to fulfill explosive demand from AI/DL.”
— Ed Wu, corporate
executive vice president at Foxconn and chairman at Ingrasys
“Inventec has a proven history of delivering high-performing and
scalable servers with robust innovative designs for our customers
who run some of the world’s largest datacenters. By rapidly
incorporating HGX-2 into our future designs, we’ll infuse our
portfolio with the most powerful AI solution available to companies
worldwide.”
— Evan Chien, head of IEC White Box Product Center,
China Business Line Director, Inventec
“NVIDIA’s HGX-2 ups the ante with a design capable of delivering
two petaflops of performance for AI and HPC-intensive workloads.
With the HGX-2 server building block, we’ll be able to quickly
develop new systems that can meet the growing needs of our
customers who demand the highest performance at
scale.”
— Paul Ju, vice president and general manager of Lenovo DCG
“As a leading cloud enabler, Quanta is committed to developing
solutions for the next generation of clouds for a variety of
innovative use cases. As we have seen a multitude of AI
applications on the rise, Quanta works closely with NVIDIA to
ensure our clients benefit from the latest and greatest GPU
technologies. We are thrilled to broaden our GPU compute portfolio
with this critical enabler for AI clouds as an HGX-2 launch
partner.”
— Mike Yang, senior vice president, Quanta Computer,
and president, QCT
“To help address the rapidly expanding size of AI models that
sometimes require weeks to train, Supermicro is developing cloud
servers based on the HGX-2 platform. The HGX-2 system will enable
efficient training of complex models.”
— Charles Liang, president and CEO
of Supermicro
“We are very honored to work with NVIDIA as a partner. The
demand for AI cloud computing is emerging in today’s modern
technology environment. I strongly believe the high performance and
modularized flexibility of the HGX-2 system will make great
contributions to various computing areas, ranging from academics
and science to government applications.”
— Jeff Lin, president of
Enterprise Business Group, Wistron
“Wiwynn specializes in delivering hyperscale datacenter and
cloud infrastructure solutions. Our collaboration with NVIDIA and
the HGX-2 server building block will enable us to provide our
customers with two petaflops of computing for computationally
intensive AI and HPC
workloads.”
— Steven Lu, Vice President, Wiwynn
About NVIDIANVIDIA’s (NASDAQ:NVDA) invention of
the GPU in 1999 sparked the growth of the PC gaming market,
redefined modern computer graphics and revolutionized parallel
computing. More recently, GPU deep learning ignited modern AI — the
next era of computing — with the GPU acting as the brain of
computers, robots and self-driving cars that can perceive and
understand the world. More information at
http://nvidianews.nvidia.com/.
For further information, contact:Kristin
BrysonPR Director for Data Center AI, HPC and Accelerated
ComputingNVIDIA Corporation(203) 241-9190kbryson@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: the benefits, impact, performance and
abilities of the NVIDIA HGX-2 cloud server platform; HGX-2
providing flexibility and versatility to support the future of
computing and ability to meet the requirements of applications
combining HPC with AI; computer makers’ plans to bring to market
systems based on the HGX-2 platform; CPU scaling slowing while
computing demand is skyrocketing; HGX-2 giving the industry a
powerful and versatile platform to solve the world’s grand
challenges; HGX-2 serving as a building block for manufacturers to
create one of the most advanced systems for HPC and AI and its
ability to replace up to 300 CPU-only servers; HGX-1 winning broad
adoption among the world’s leading server makers and companies
operating datacenters; leading server makers’ and top original
design manufacturers’ plans to bring HGX-2-based systems to market
later this year; the benefits, performance and abilities of the
NVIDIA GPU-Accelerated Server Platforms; HGX-2 being the most
promising solution to fulfill demand from AI/DL; HGX-2 being
incorporated into Inventec’s future designs and it infusing
Inventec’s portfolio with the most powerful AI solution available;
HGX-2’s ability to help Lenovo’s systems to meet the growing needs
of their customers; HGX-2 systems enabling the efficient training
of complex models; the demand for AI cloud computing emerging in
today’s modern technology environment; HGX-2’s ability to make
great contributions to various computing areas; and HGX-2 enabling
Wiwynn to provide customers with two petaflops of computing for AI
and HPC workloads are forward-looking statements that are subject
to risks and uncertainties that could cause results to be
materially different than expectations. Important factors that
could cause actual results to differ materially include: global
economic conditions; our reliance on third parties to manufacture,
assemble, package and test our products; the impact of
technological development and competition; development of new
products and technologies or enhancements to our existing product
and technologies; market acceptance of our products or our
partners’ products; design, manufacturing or software defects;
changes in consumer preferences or demands; changes in industry
standards and interfaces; unexpected loss of performance of our
products or technologies when integrated into systems; as well as
other factors detailed from time to time in the reports NVIDIA
files with the Securities and Exchange Commission, or SEC,
including its Form 10-Q for the fiscal period ended April 29, 2018.
Copies of reports filed with the SEC are posted on the company’s
website and are available from NVIDIA without charge. These
forward-looking statements are not guarantees of future performance
and speak only as of the date hereof, and, except as required by
law, NVIDIA disclaims any obligation to update these
forward-looking statements to reflect future events or
circumstances.
© 2018 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo, DGX, HGX-2, NVSwitch and Tesla are trademarks and/or
registered trademarks of NVIDIA Corporation in the U.S. and other
countries. Other company and product names may be trademarks of the
respective companies with which they are associated. Features,
pricing, availability and specifications are subject to change
without notice.
A photo accompanying this announcement is available at
http://www.globenewswire.com/NewsRoom/AttachmentNg/63489cd6-cead-478b-a92c-8a441e50e2dc
NVIDIA (NASDAQ:NVDA)
Historical Stock Chart
From Mar 2024 to Apr 2024
NVIDIA (NASDAQ:NVDA)
Historical Stock Chart
From Apr 2023 to Apr 2024