NVIDIA Announces Scalable GPU-Accelerated Supercomputer in the Microsoft Azure Cloud
November 18 2019 - 6:20PM
SC19 --
NVIDIA today
announced the availability of a new kind of GPU-accelerated
supercomputer in the cloud on Microsoft Azure.
Built to handle the most demanding AI and high performance
computing applications, the largest deployments of Azure’s new NDv2
instance rank among the world’s fastest supercomputers, offering up
to 800 NVIDIA V100 Tensor Core GPUs interconnected on a single
Mellanox InfiniBand backend network. It enables customers for the
first time to rent an entire AI supercomputer on demand from their
desk, and match the capabilities of large-scale, on-premises
supercomputers that can take months to deploy.
“Until now, access to supercomputers for AI and high performance
computing has been reserved for the world’s largest businesses and
organizations,” said Ian Buck, vice president and general manager
of Accelerated Computing at NVIDIA. “Microsoft Azure’s new offering
democratizes AI, giving wide access to an essential tool needed to
solve some of the world’s biggest challenges.”
Girish Bablani, corporate vice president of Azure Compute at
Microsoft Corp., added, “As cloud computing gains momentum
everywhere, customers are seeking more powerful services. Working
with NVIDIA, Microsoft is giving customers instant access to a
level of supercomputing power that was previously unimaginable,
enabling a new era of innovation.”
Dramatic Performance, Cost BenefitsThe new
offering — which is ideal for complex AI, machine learning and HPC
workloads — can provide dramatic performance and cost advantages
over traditional CPU-based computing. AI researchers needing fast
solutions can quickly spin up multiple NDv2 instances and train
complex conversational AI models in just hours.
Microsoft and NVIDIA engineers used 64 NDv2 instances on a
pre-release version of the cluster to train BERT, a popular
conversational AI model, in roughly three hours. This was achieved
in part by taking advantage of multi-GPU optimizations provided by
NCCL, an NVIDIA CUDA X™ library and high-speed Mellanox
interconnects.
Customers can also see benefits from using multiple NDv2
instances to run complex HPC workloads, such as LAMMPS, a popular
molecular dynamics application used to simulate materials down to
the atomic scale in such areas as drug development and discovery. A
single NDv2 instance can deliver an order of magnitude faster
results than a traditional HPC node without GPU acceleration for
specific types of applications, such as deep learning. This
performance can scale linearly to a hundred instances for
large-scale simulations.
All NDv2 instances benefit from the GPU-optimized HPC
applications, machine learning software and deep learning
frameworks like TensorFlow, PyTorch and MXNet from the NVIDIA NGC
container registry and Azure Marketplace. The registry also offers
Helm charts to easily deploy the AI software on Kubernetes
clusters.
Availability and PricingNDv2 is available now
in preview. One instance with eight NVIDIA V100 GPUs can be
clustered to scale up to a variety of workload demands. See more
details here.
About NVIDIA NVIDIA’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
UchiyamaNVIDIASenior PR
Manager+1-408-313-0448kuchiyama@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: the benefits, impact, performance and
availability of the Microsoft Azure NDv2 with NVIDIA V100 Tensor
Core GPUs; and cloud computing gaining momentum everywhere 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 most recent reports NVIDIA files with the
Securities and Exchange Commission, or SEC, including, but not
limited to, its annual report on Form 10-K and quarterly reports on
Form 10-Q. 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.
© 2019 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo and CUDA-X 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
https://www.globenewswire.com/NewsRoom/AttachmentNg/e50b1594-b6d1-40cd-b1fc-d1a4ba09c6bd
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