New accelerated computing instances feature
NVIDIA T4 Tensor Core GPUs to provide the most cost-effective
compute in the cloud for running machine learning inference and
graphics-intensive applications
Clarifai and Electronic Arts among customers
using Amazon EC2 G4 instances
Today, Amazon Web Services, Inc. (AWS), an Amazon.com company
(NASDAQ: AMZN), announced the general availability of G4 instances,
a new GPU-powered Amazon Elastic Compute Cloud (Amazon EC2)
instance designed to help accelerate machine learning inference and
graphics-intensive workloads, both of which are computationally
demanding tasks that benefit from additional GPU acceleration. G4
instances provide the industry’s most cost-effective machine
learning inference for applications, like adding metadata to an
image, object detection, recommender systems, automated speech
recognition, and language translation. G4 instances also provide a
very cost-effective platform for building and running
graphics-intensive applications, such as remote graphics
workstations, video transcoding, photo-realistic design, and game
streaming in the cloud. To get started with G4 instances visit
https://aws.amazon.com/ec2/instance-types/g4.
Machine learning involves two processes that require compute –
training and inference. Training entails using labeled data to
create a model that is capable of making predictions, a
compute-intensive task that requires powerful processors and
high-speed networking. Inference is the process of using a trained
machine learning model to make predictions, which typically
requires processing a lot of small compute jobs simultaneously, a
task that can be most cost-effectively handled by accelerating
computing with energy-efficient NVIDIA GPUs. With the launch of P3
instances in 2017, AWS was the first to introduce instances
optimized for machine learning training in the cloud with powerful
NVIDIA V100 Tensor Core GPUs, allowing customers to reduce machine
learning training from days to hours. However, inference is what
actually accounts for the vast majority of machine learning’s cost.
According to customers, machine learning inference can represent up
to 90% of overall operational costs for running machine learning
workloads.
New G4 instances feature the latest generation NVIDIA T4 GPUs,
custom 2nd Generation Intel Xeon Scalable (Cascade Lake)
processors, up to 100 Gbps of networking throughput, and up to 1.8
TB of local NVMe storage, to deliver the most cost-effective GPU
instances for machine learning inference. And with up to 65 TFLOPs
of mixed-precision performance, G4 instances not only deliver
superior price/performance for inference, but also can be used
cost-effectively for small-scale and entry-level machine learning
training jobs that are less sensitive to time-to-train. G4
instances also provide an ideal compute engine for
graphics-intensive workloads, offering up to a 1.8x increase in
graphics performance and up to 2x video transcoding capability over
the previous generation G3 instances. These performance
enhancements enable customers to use remote workstations in the
cloud for running graphics-intensive applications like Autodesk
Maya or 3D Studio Max, as well as efficiently create
photo-realistic and high-resolution 3D content for movies and
games.
“We focus on solving the toughest challenges that hold our
customers back from taking advantage of compute intensive
applications,” said Matt Garman, Vice President, Compute Services,
AWS. “AWS offers the most comprehensive portfolio to build, train,
and deploy machine learning models powered by Amazon EC2’s broad
selection of instance types optimized for different machine
learning use cases. With new G4 instances, we’re making it more
affordable to put machine learning in the hands of every developer.
And with support for the latest video decode protocols, customers
running graphics applications on G4 instances get superior graphics
performance over G3 instances at the same cost.”
Customers with machine learning workloads can launch G4
instances using Amazon SageMaker or AWS Deep Learning AMIs, which
include machine learning frameworks such as TensorFlow, TensorRT,
MXNet, PyTorch, Caffe2, CNTK, and Chainer. G4 instances will also
support Amazon Elastic Inference in the coming weeks, which will
allow developers to dramatically reduce the cost of inference by up
to 75% by provisioning just the right amount of GPU performance.
Customers with graphics and streaming applications can launch G4
instances using Windows, Linux, or AWS Marketplace AMIs from NVIDIA
with NVIDIA Quadro Virtual Workstation software preinstalled. A
bare metal version will be available in the coming months. G4
instances are available in the US East (N. Virginia, Ohio), US West
(Oregon, N. California), Europe (Frankfurt, Ireland, London), and
Asia Pacific (Seoul and Tokyo) Regions, with availability in
additional regions planned in the coming months. G4 instances are
available to be purchased as On-Demand, Reserved Instances, or Spot
Instances.
Clarifai is a leading artificial intelligence company that
excels in visual recognition to solve real-world challenges. “We
apply machine learning to image and video recognition, helping
customers better understand their media assets and apply it across
a broad set of applications, such as providing personalized online
shopping experience or measuring in-store shopper behaviors,” said
Robert Wen, Head of Engineering at Clarifai. “We provide our
customers with a full-featured API that allows them to utilize our
pre-trained machine learning models and make predictions on their
data. G4 instances offer a highly cost-effective solution that will
enable us to make it more economical for our customers to use AI
across a broader set of use cases.”
Electronic Arts (EA) is a global leader in digital interactive
entertainment, delivering games, content, and online services to
hundreds of millions of players around the world through
Internet-connected consoles, mobile devices, and personal
computers. “Leveraging the power of the cloud with providers such
as Amazon Web Services has revolutionized how we create games and
how players experience them,” said Erik Zigman, EA’s Vice President
of Cloud, Social, Marketplace, and Cloud Gaming Engineering.
“Working with AWS’s G4 instance has enabled us to build
cost-effective and powerful services that are optimized for
bringing online gaming to a wide range of devices.”
GumGum is an artificial intelligence company with deep expertise
in computer vision. “We use our proprietary computer vision
technology to identify content relevant to marketers to deliver
highly visible advertising campaigns and rich insights to brands
and agencies,” said Brian Fuller, Engineering Manager, at GumGum.
“GumGum scans millions of images and videos each day across the
web, social media, and broadcast television using AI. The new
Amazon EC2 G4 instances provide us with the ideal balance of price
and performance, allowing us to optimize our content processing
pipelines, lower our costs to generate data insights, and provide
our clients the ability to precisely target audiences and deliver
contextually relevant advertising.”
PureWeb’s interactive streaming technology enables users to
publish, collaborate, and interact with massive data files,
including photo-real 3D simulations and game engine projects. “Our
Reality product, deployed on AWS, is a fully managed, secure, and
scalable service that provides on-demand access to 3D
photorealistic renderings built using Unity or Unreal Engine,” said
Barry Allen, CEO, PureWeb. “With their low cost and latest NVIDIA
T4 GPUs, AWS G4 instances are perfect for our graphics-intensive
workloads, as they provide the right balance of performance and
cost, allowing us to stream at scale to anyone on any device.”
About Amazon Web Services
For 13 years, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud platform. AWS offers over
165 fully featured services for compute, storage, databases,
networking, analytics, robotics, machine learning and artificial
intelligence (AI), Internet of Things (IoT), mobile, security,
hybrid, virtual and augmented reality (VR and AR), media, and
application development, deployment, and management from 69
Availability Zones (AZs) within 22 geographic regions, spanning the
U.S., Australia, Brazil, Canada, China, France, Germany, Hong Kong
Special Administrative Region, India, Ireland, Japan, Korea, Middle
East, Singapore, Sweden, and the UK. Millions of
customers—including the fastest-growing startups, largest
enterprises, and leading government agencies—trust AWS to power
their infrastructure, become more agile, and lower costs. To learn
more about AWS, visit aws.amazon.com.
About Amazon
Amazon is guided by four principles: customer obsession rather
than competitor focus, passion for invention, commitment to
operational excellence, and long-term thinking. Customer reviews,
1-Click shopping, personalized recommendations, Prime, Fulfillment
by Amazon, AWS, Kindle Direct Publishing, Kindle, Fire tablets,
Fire TV, Amazon Echo, and Alexa are some of the products and
services pioneered by Amazon. For more information, visit
amazon.com/about and follow @AmazonNews.
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