Computex -- NVIDIA today announced
NVIDIA EGX, an accelerated computing platform that enables
companies to perform low-latency AI at the edge — to perceive,
understand and act in real time on continuous streaming data
between 5G base stations, warehouses, retail stores, factories and
beyond.
NVIDIA EGX was created to meet the growing demand to perform
instantaneous, high-throughput AI at the edge — where data is
created – with guaranteed response times, while reducing the amount
of data that must be sent to the cloud.
By 2025, 150 billion machine sensors and IoT devices will stream
continuous data that will need to be processed(1) — orders of
magnitude more than produced today by individuals using
smartphones. Edge servers like those in the NVIDIA EGX platform
will be distributed throughout the world to process data in real
time from these sensors.
“Enterprises demand more powerful computing at the edge to
process their oceans of raw data — streaming in from countless
interactions with customers and facilities — to make rapid,
AI-enhanced decisions that can drive their business,” said Bob
Pette, vice president and general manager of Enterprise and Edge
Computing at NVIDIA. “A scalable platform like NVIDIA EGX allows
them to easily deploy systems to meet their needs on premises, in
the cloud or both.”
Scalability EGX starts with the tiny NVIDIA
Jetson Nano™, which in a few watts can provide one-half trillion
operations per second (TOPS) of processing for tasks such as image
recognition. And it spans all the way to a full rack of NVIDIA T4
servers, delivering more than 10,000 TOPS for real-time speech
recognition and other real-time AI tasks.
Enterprise-Grade NVIDIA has partnered with Red
Hat to integrate and optimize NVIDIA Edge Stack with OpenShift, the
leading enterprise-grade Kubernetes container orchestration
platform.
NVIDIA Edge Stack is optimized software that includes NVIDIA
drivers, a CUDA® Kubernetes plugin, a CUDA container runtime,
CUDA-X™ libraries and containerized AI frameworks and applications,
including TensorRT™, TensorRT Inference Server and DeepStream.
NVIDIA Edge Stack is optimized for certified servers and
downloadable from the NVIDIA NGC™ registry.
“Red Hat is committed to providing a consistent experience for
any workload, footprint and location, from the hybrid cloud to the
edge,” said Chris Wright, chief technology officer at Red Hat. “By
combining Red Hat OpenShift and NVIDIA EGX-enabled platforms,
customers can better optimize their distributed operations with a
consistent, high-performance, container-centric environment.”
An “On-Prem AI Cloud-in-a-Box” EGX combines the
full range of NVIDIA AI computing technologies with Red Hat
OpenShift and NVIDIA Edge Stack together with Mellanox and Cisco
security, networking and storage technologies. This enables
companies in the largest industries — telecom, manufacturing,
retail, healthcare and transportation — to quickly stand up
state-of-the-art, secure, enterprise-grade AI infrastructures.
“Mellanox Smart NICs and switches provide the ideal I/O
connectivity for data access that scale from the edge to hyperscale
data centers,” said Michael Kagan, chief technology officer at
Mellanox Technologies. “The combination of high-performance,
low-latency and accelerated networking provides a new
infrastructure tier of computing that is critical to efficiently
access and supply the data needed to fuel the next generation of
advanced AI solutions on edge platforms such as NVIDIA EGX.”
“Cisco is excited to collaborate with NVIDIA to provide
edge-to-core full stack solutions for our customers, leveraging
Cisco’s EGX-enabled platforms with Cisco compute, fabric, storage,
and management software and our leading Ethernet and IP-based
networking technologies,” said Kaustubh Das, vice president of
Cisco Computing Systems.
Enables Hybrid-Cloud and Multi-Cloud IoT NVIDIA
AI computing is offered by major clouds and is architecturally
compatible with NVIDIA EGX. AI applications developed in the cloud
can run on NVIDIA EGX and vice versa. NVIDIA Edge Stack connects to
major cloud IoT services, and customers can remotely manage their
service from AWS IoT Greengrass and Microsoft Azure IoT Edge.
“Azure IoT Edge helps customers deploy cloud service to their
IoT devices quickly and securely,” said Sam George, director of
Azure IoT Edge. “We look forward to supporting NVIDIA’s EGX edge
platform on Azure IoT Edge devices so that customers can deploy AI
workloads targeting EGX-compatible hardware.”
Widespread Developer Support NVIDIA EGX is
optimizing AI at the edge for a growing ecosystem of software
solutions.
These include video analytics applications, which are ideal for
large retail chains and smart cities, from software vendors such as
AnyVision, DeepVision, IronYun and Malong Technologies, as well as
healthcare-specific software offerings from 12 Sigma, Infervision,
Qunatib and Subtle Medical.
Adoption by World’s Top Computer MakersEGX
servers are available from global enterprise computing providers
ATOS, Cisco, Dell EMC, Fujitsu, Hewlett Packard Enterprise, Inspur
and Lenovo. They are also available from major server and IoT
system makers Abaco, Acer, ADLINK, Advantech, ASRock Rack, ASUS,
AverMedia, Cloudian, Connect Tech, Curtiss-Wright, GIGABYTE,
Leetop, MiiVii, Musashi Seimitsu, QCT, Sugon, Supermicro, Tyan,
WiBase and Wiwynn.
NVIDIA EGX servers are tuned for NVIDIA Edge Stack and NGC-Ready
validated for CUDA-accelerated containers.
Support from 40+ Companies, Organizations Early
adopters include more than 40 industry-leading companies and
organizations.
Among them is BMW Group Logistics. Drawing from NVIDIA’s EGX
edge computing and Isaac robotic platforms, they are able to bring
the power of AI directly to the edge of its logistics processes and
handle increasingly complex logistics with real-time
efficiency.
Other industry leaders adopting EGX include:
“Foxconn PC production lines are limited by the speed of
inspection because it currently requires four seconds to manually
inspect each part. Our goal is to increase the throughput of the PC
production line by over 40 percent using the NVIDIA EGX platform
for real-time intelligent decision-making at the edge. Our model
detects and classifies 16 defect types and locations simultaneously
using fast neural networks running on NVIDIA GPUs, achieving 98
percent accuracy at a superhuman throughput rate.”— Mark Chien,
general manager, Foxconn D Group
“AI is fundamental to achieving precision health and must be
pervasively available from the cloud to the edge and directly on
medical devices. NVIDIA’s EGX enables GE Healthcare to deliver
rapid MR acquisition times, improves image quality and reduces
variability by embedding NVIDIA T4 GPUs directly into our medical
devices — all to further our goal of improving patient outcomes.
Real-time, critical-care use cases demand AI at the edge. This is
why we created our Edison intelligence offering and partnered with
NVIDIA to bring AI into our medical devices and Edison edge
appliances — and why we are working with ACR AI-LAB to democratize
AI.”— Jason Polzin, Ph.D., general manager of MR Applications, GE
Healthcare
“Hospitals are increasingly using AI to predict adverse patient
events, support clinical decision-making and operate more
efficiently. However, these AI applications rely on patient data.
NVIDIA’s EGX AI edge computing platform provides hospitals easy AI
infrastructure to keep patient data secure, deliver real-time AI
and scale to thousands of AI applications that are needed to
improve patient care and reduce the cost of care delivery.”— Keith
Dreyer, D.O., Ph.D., chief data science officer at Partners
Healthcare and associate professor of radiology, Harvard Medical
School
“At Seagate we have deployed an intelligent edge GPU-based
vision solution in our manufacturing plants to inspect the quality
of our hard disk read-and-write heads. The NVIDIA EGX platform
dramatically accelerates inference at the edge, allowing us to see
subtle defects that human operators haven’t been able to see in the
past. We expect to realize up to a 10 percent improvement in
manufacturing throughput and up to 300 percent ROI from improved
efficiency and better quality.”— Bruce King, senior principal data
scientist, Seagate Technology
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, AI and Accelerated ComputingNVIDIA
Corporation+1-203-241-9190kbryson@nvidia.com
- IDC white paper, sponsored by Seagate, “Data Age 2025: The
Digitization of the World from Edge to Core,” November 2018.
Certain statements in this press release including, but not
limited to, statements as to: NVIDIA launching an edge computing
platform to bring real-time AI to global industries; leading
computer makers adopting the NVIDIA EGX platform, and it offering
GPU Edge servers for instant AI on real-time streaming data in
industries; the benefits, performance, features, abilities and
impact of NVIDIA EGX, NVIDIA Jetson Nano, NVIDIA AI computing and
NVIDIA T4 servers; NVIDIA EGX enabling companies to perform
low-latency AI at the edge and it being able to perceive,
understand and act in real time on continuous data streaming;
NVIDIA EGX meeting the growing demand to perform AI at the edge and
its abilities; the year by which 150 billion machine sensors and
IoT devices streaming continuous data that will need to be
processed; edge servers being distributed throughout the world to
process data; enterprises demanding more powerful computing at the
edge to process data and drive their business and NVIDIA EGX
allowing them to deploy systems to meet their needs; the ability to
use EGX to deploy AI quickly and securely from edge to cloud; the
benefits of combining NVIDIA EGX, Red Hat OpenShift and NVIDIA Edge
Stack and its performance for customers; EGX, Red Hat OpenShift,
NVIDIA Edge Stack, and Mellanox and Cisco security enabling
companies to stand up AI infrastructures; NVIDIA EGX working with
Mellanox technologies to fuel the next generation of advanced AI
solutions on the edge; Cisco’s excitement to collaborate with
NVIDIA and its impacts; Azure IoT looking forward to supporting
NVIDIA’s EGX platform on its devices so customers can deploy AI
workloads targeting EGX-compatible hardware; the software solutions
enabling AI at the edge; the top computer makers adopting NVIDIA
EGX and its availability; the goals, impact and support of
customers planning to use NVIDIA EGX; AI being fundamental to
achieving precision health and needing to be pervasively available
from the cloud to the edge and directly on medical devices; NVIDIA
EGX enabling the delivery of rapid MR acquisition times, improving
image quality and reducing variability by embedding NVIDIA T4 GPUs
directly into medical devices; critical-care use cases demanding AI
at the edge; NVIDIA and GE Healthcare partnering to bring AI to
devices and working to democratize AI; high-performance,
low-latency and accelerated networking providing a new
infrastructure tier of computing that is critical to efficiently
access and supply the data needed for the next generation of
advanced AI solutions; hospitals increasingly using AI to predict
adverse patient events, support clinical decision-making and
operate more efficiently; NVIDIA EGX AI providing hospitals easy AI
infrastructure to keep patient data secure, deliver real-time AI
and scale to thousands of AI applications; and NVIDIA EGX
accelerating inference at the edge and allowing the detection of
defects humans haven’t been able to see in the past 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, CUDA, CUDA-X, Jetson Nano, NGC and TensorRT are
trademarks and/or registered trademarks of NVIDIA Corporation in
the U.S. and other countries. Red Hat and OpenShift are trademarks
or registered trademarks of Red Hat, Inc. or its subsidiaries 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.
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