GTC Japan—Fueling the growth of AI services
worldwide, NVIDIA today launched an AI data center platform that
delivers the industry’s most advanced inference acceleration for
voice, video, image and recommendation services.
The NVIDIA TensorRT™ Hyperscale Inference Platform features
NVIDIA® Tesla® T4 GPUs based on the company’s breakthrough NVIDIA
Turing™ architecture and a comprehensive set of new inference
software.
Delivering the fastest performance with lower latency for
end-to-end applications, the platform enables hyperscale data
centers to offer new services, such as enhanced natural language
interactions and direct answers to search queries rather than a
list of possible results.
“Our customers are racing toward a future where every product
and service will be touched and improved by AI,” said Ian Buck,
vice president and general manager of Accelerated Business at
NVIDIA. “The NVIDIA TensorRT Hyperscale Platform has been built to
bring this to reality — faster and more efficiently than had been
previously thought possible.”
Every day, massive data centers process billions of voice
queries, translations, images, videos, recommendations and social
media interactions. Each of these applications requires a different
type of neural network residing on the server where the processing
takes place.
To optimize the data center for maximum throughput and server
utilization, the NVIDIA TensorRT Hyperscale Platform includes both
real-time inference software and Tesla T4 GPUs, which process
queries up to 40x faster than CPUs alone.
NVIDIA estimates that the AI inference industry is poised to
grow in the next five years into a $20 billion market.
Industry’s Most Advanced AI Inference
PlatformThe NVIDIA TensorRT Hyperscale Platform includes a
comprehensive set of hardware and software offerings optimized for
powerful, highly efficient inference. Key elements include:
- NVIDIA Tesla T4 GPU – Featuring 320 Turing Tensor Cores and
2,560 CUDA® cores, this new GPU provides breakthrough performance
with flexible, multi-precision capabilities, from FP32 to FP16 to
INT8, as well as INT4. Packaged in an energy-efficient, 75-watt,
small PCIe form factor that easily fits into most servers, it
offers 65 teraflops of peak performance for FP16, 130 teraflops for
INT8 and 260 teraflops for INT4.
- NVIDIA TensorRT 5 – An inference optimizer and runtime engine,
NVIDIA TensorRT 5 supports Turing Tensor Cores and expands the set
of neural network optimizations for multi-precision workloads.
- NVIDIA TensorRT inference server – This containerized
microservice software enables applications to use AI models in data
center production. Freely available from the NVIDIA GPU Cloud
container registry, it maximizes data center throughput and GPU
utilization, supports all popular AI models and frameworks, and
integrates with Kubernetes and Docker.
Supported by Technology Leaders
WorldwideSupport for NVIDIA’s new inference platform comes
from leading consumer and business technology companies around the
world.
“We are working hard at Microsoft to deliver the most innovative
AI-powered services to our customers,” said Jordi Ribas, corporate
vice president for Bing and AI Products at Microsoft. “Using NVIDIA
GPUs in real-time inference workloads has improved Bing’s advanced
search offerings, enabling us to reduce object detection latency
for images. We look forward to working with NVIDIA’s
next-generation inference hardware and software to expand the way
people benefit from AI products and services.”
Chris Kleban, product manager at Google Cloud, said: “AI is
becoming increasingly pervasive, and inference is a critical
capability customers need to successfully deploy their AI models,
so we’re excited to support NVIDIA’s Turing Tesla T4 GPUs on Google
Cloud Platform soon.”
More information, including details on how to request early
access to T4 GPUs on Google Cloud Platform, is available here.
Additional companies, including all major server manufacturers,
voicing support for the NVIDIA TensorRT Hyperscale Platform
include:
“Cisco’s UCS portfolio delivers policy-driven, GPU-accelerated
systems and solutions to power every phase of the AI lifecycle.
With the NVIDIA Tesla T4 GPU based on the NVIDIA Turing
architecture, Cisco customers will have access to the most
efficient accelerator for AI inference workloads — gaining insights
faster and accelerating time to action.”— Kaustubh Das, vice
president of product management, Data Center Group, Cisco
“Dell EMC is focused on helping customers transform their IT
while benefiting from advancements such as artificial intelligence.
As the world’s leading provider of server systems, Dell EMC
continues to enhance the PowerEdge server portfolio to help our
customers ultimately achieve their goals. Our close collaboration
with NVIDIA and historical adoption of the latest GPU accelerators
available from their Tesla portfolio play a vital role in helping
our customers stay ahead of the curve in AI training and
inference.”— Ravi Pendekanti, senior vice president of product
management and marketing, Servers & Infrastructure Systems,
Dell EMC
“Fujitsu plans to incorporate NVIDIA’s Tesla T4 GPUs into our
global Fujitsu Server PRIMERGY systems lineup. Leveraging this
latest, high-efficiency GPU accelerator from NVIDIA, we will
provide our customers around the world with servers highly
optimized for their growing AI needs.”— Hideaki Maeda, vice
president of the Products Division, Data Center Platform Business
Unit, Fujitsu Ltd.
“At HPE, we are committed to driving intelligence at the edge
for faster insight and improved experiences. With the NVIDIA Tesla
T4 GPU, based on the NVIDIA Turing architecture, we are continuing
to modernize and accelerate the data center to enable inference at
the edge.”— Bill Mannel, vice president and general manager, HPC
and AI Group, Hewlett Packard Enterprise
“IBM Cognitive Systems is able to deliver 4x faster deep
learning training times as a result of a co-optimized hardware and
software on a simplified AI platform with PowerAI, our deep
learning training and inference software, and IBM Power Systems
AC922 accelerated servers. We have a history of partnership and
innovation with NVIDIA, and together we co-developed the industry’s
only CPU-to-GPU NVIDIA NVLink connection on IBM Power processors,
and we are excited to explore the new NVIDIA T4 GPU accelerator to
extend this state of the art leadership for inference workloads.”—
Steve Sibley, vice president of Power Systems Offering Management,
IBM
“We are excited to see NVIDIA bring GPU inference to Kubernetes
with the NVIDIA TensorRT inference server, and look forward to
integrating it with Kubeflow to provide users with a simple,
portable and scalable way to deploy AI inference across diverse
infrastructures.”— David Aronchick, co-founder and product manager
of Kubeflow
“Open source cross-framework inference is vital to production
deployments of machine learning models. We are excited to see how
the NVIDIA TensorRT inference server, which brings a powerful
solution for both GPU and CPU inference serving at scale, enables
faster deployment of AI applications and improves infrastructure
utilization.”— Kash Iftikhar, vice president of product
development, Oracle Cloud Infrastructure
“Supermicro is innovating to address the rapidly emerging
high-throughput inference market driven by technologies such as 5G,
Smart Cities and IOT devices, which are generating huge amounts of
data and require real-time decision making. We see the combination
of NVIDIA TensorRT and the new Turing architecture-based T4 GPU
accelerator as the ideal combination for these new, demanding and
latency-sensitive workloads and plan to aggressively leverage them
in our GPU system product line.”— Charles Liang, president and CEO,
Supermicro
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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
BrysonPR Director for Data Center AI, HPC and Accelerated
ComputingNVIDIA Corporation+1-203-241-9190kbryson@nvidia.com
Certain statements in this press release including, but not
limited to, statements as to: Tesla T4 GPU and TensorRT software
enabling intelligent voice, video, image and recommender services;
NVIDIA’s AI data center platform delivering the industry’s most
advanced inference acceleration for voice, video, image and
recommendation services; the benefits, performance and abilities of
the NVIDIA TensorRT Hyperscale Inference Platform, including Tesla
T4 GPUs based on Turing architecture and new inference software,
its ability to deliver faster performance at lower latency than
other offerings, and enabling hyperscale data centers to offer new
services; customers racing toward a future where every product and
service will be touched and improved by AI and the Tensor RT
Hyperscale Platform being built to bring this to a reality faster
and more efficiently than previously thought possible; the value
the estimated AI inference industry will grow to in the next five
years; the performance and features of Tesla T4 GPUs; NVIDIA
TensorRT 5 expanding the set of neural network optimizations for
mixed precision workloads; NVIDIA TensorRT inference server
enabling applications to use AI models, its availability from the
NVIDIA GPU Cloud container registry and its ability to maximize GPU
utilization; NVIDIA GPUs enabling Microsoft to reduce object
detection latency for images and Microsoft looking forward to
working with NVIDIA’s next-generation inference hardware and
software to expand the way people benefit from AI products and
services; Google Cloud planning to add support for Tesla T4 GPUs on
the Google Cloud Platform soon; AI becoming increasingly pervasive,
and inference being a critical capability customers need to deploy
AI models; major server manufacturers voicing their support for the
NVIDIA TensorRT Hyperscale Platform; NVIDIA Tesla T4 GPUs giving
Cisco customers access to the most efficient accelerator for AI
inference workloads; Dell EMC enhancing the PowerEdge server
portfolio to help customers and its collaboration with NVIDIA
playing a vital role in helping its customers; Fujitsu’s plan to
incorporate Tesla T4 GPUs into its systems lineup and providing its
customers with servers optimized for their growing AI needs; HPE
using Tesla T4 GPUs to continue to modernize and accelerate the
data center to enable inference at the edge; IBM’s plans to explore
the Tesla T4 GPU accelerator to extend its state of the art
leadership for inference workloads; Kubernetes integrating NVIDIA
products with Kubeflow and providing ways to deploy AI inference
across diverse infrastructures; NVIDIA TensorRT inference server
features enabling faster deployment of AI applications and
improving infrastructure utilization; Supermicro innovating in
markets which generate data and require real-time decision making
and their plans to leverage NVIDIA products in their GPU system
product line 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.
© 2018 NVIDIA Corporation. All rights reserved. NVIDIA, the
NVIDIA logo, CUDA, NVIDIA Turing, NVLink, TensorRT 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/31016d3d-3f4c-413b-874b-e770338718f0
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