New Amazon EC2 instances featuring Gaudi
accelerators from Habana Labs deliver up to 40% better price
performance for training machine learning models compared to the
latest GPU-based Amazon EC2 instances
Seagate Technology, Intel, and Leidos among
customers using Amazon EC2 DL1 instances
Today, Amazon Web Services, Inc. (AWS), an Amazon.com, Inc.
company (NASDAQ: AMZN), announced general availability of Amazon
Elastic Compute Cloud (Amazon EC2) DL1 instances, a new instance
type designed for training machine learning models. DL1 instances
are powered by Gaudi accelerators from Habana Labs (an Intel
company) to provide up to 40% better price performance for training
machine learning models than the latest GPU-powered Amazon EC2
instances. With DL1 instances, customers can train their machine
learning models faster and more cost effectively for use cases like
natural language processing, object detection and classification,
fraud detection, recommendation and personalization engines,
intelligent document processing, business forecasting, and more.
DL1 instances are available on demand via a low-cost pay-as-you-go
usage model with no upfront commitments. To get started with DL1
instances, visit aws.amazon.com/ec2/instance-types/dl1.
Machine learning has become mainstream as customers have
realized tangible business impact from deploying machine learning
models at scale in the cloud. To use machine learning in their
business applications, customers start by building and training a
model to recognize patterns by learning from sample data, and then
apply the model on new data to make predictions. For example, a
machine learning model trained on large numbers of contact center
transcripts can make predictions to provide real-time personalized
assistance to customers through a conversational chatbot. To
improve a model's prediction accuracy, data scientists and machine
learning engineers are building increasingly larger and more
complex models. To maintain prediction accuracy and high quality of
the models, these engineers need to tune and retrain their models
frequently. This requires a considerable amount of high-performance
compute resources, resulting in increased infrastructure costs.
These costs can be prohibitive for customers to retrain their
models at the frequency they need to maintain high-accuracy
predictions, while also posing an obstacle to customers that want
to begin experimenting with machine learning.
New DL1 instances use Gaudi accelerators built specifically to
accelerate machine learning model training by delivering higher
compute efficiency at a lower cost compared to general purpose
GPUs. DL1 instances feature up to eight Gaudi accelerators, 256 GB
of high-bandwidth memory, 768 GB of system memory, 2nd generation
Amazon custom Intel Xeon Scalable (Cascade Lake) processors, 400
Gbps of networking throughput, and up to 4 TB of local NVMe
storage. Together, these innovations translate to up to 40% better
price performance than the latest GPU-powered Amazon EC2 instances
for training common machine learning models. Customers can quickly
and easily get started with DL1 instances using the included Habana
SynapseAI SDK, which is integrated with leading machine learning
frameworks (e.g. TensorFlow and PyTorch), helping customers to
seamlessly migrate their existing machine learning models currently
running on GPU-based or CPU-based instances onto DL1 instances,
with minimal code changes. Developers and data scientists can also
start with reference models optimized for Gaudi accelerators
available in Habana’s GitHub repository, which includes popular
models for diverse applications, including image classification,
object detection, natural language processing, and recommendation
systems.
“The use of machine learning has skyrocketed. One of the
challenges with training machine learning models, however, is that
it is computationally intensive and can get expensive as customers
refine and retrain their models,” said David Brown, Vice President,
of Amazon EC2, at AWS. “AWS already has the broadest choice of
powerful compute for any machine learning project or application.
The addition of DL1 instances featuring Gaudi accelerators provides
the most cost-effective alternative to GPU-based instances in the
cloud to date. Their optimal combination of price and performance
makes it possible for customers to reduce the cost to train, train
more models, and innovate faster.”
Customers can launch DL1 instances using AWS Deep Learning AMIs
or using Amazon Elastic Kubernetes Service (Amazon EKS) or Amazon
Elastic Container Service (Amazon ECS) for containerized
applications. For a more managed experience, customers can access
DL1 instances through Amazon SageMaker, making it even easier and
faster for developers and data scientists to build, train, and
deploy machine learning models in the cloud and at the edge. DL1
instances benefit from the AWS Nitro System, a collection of
building blocks that offload many of the traditional virtualization
functions to dedicated hardware and software to deliver high
performance, high availability, and high security while also
reducing virtualization overhead. DL1 instances are available for
purchase as On-Demand Instances, with Savings Plans, as Reserved
Instances, or as Spot Instances. DL1 instances are currently
available in the US East (N. Virginia) and US West (Oregon) AWS
Regions.
Seagate Technology has been a global leader offering data
storage and management solutions for over 40 years. Seagate’s data
science and machine learning engineers have built an advanced deep
learning (DL) defect detection system and deployed it globally
across the company’s manufacturing facilities. In a recent proof of
concept project, Habana Gaudi exceeded the performance targets for
training one of the DL semantic segmentation models currently used
in Seagate’s production. “We expect the significant price
performance advantage of Amazon EC2 DL1 instances, powered by
Habana Gaudi accelerators, could make a compelling future addition
to AWS compute clusters,” said Darrell Louder, Senior Engineering
Director of Operations, Technology and Advanced Analytics, at
Seagate. “As Habana Labs continues to evolve and enables broader
coverage of operators, there is potential for expanding to
additional enterprise use cases, and thereby harnessing additional
cost savings.”
Intel has created 3D Athlete Tracking technology that analyzes
athlete-in-action video in real time to inform performance training
processes and enhance audience experiences during competitions.
“Training our models on Amazon EC2 DL1 instances, powered by Gaudi
accelerators from Habana Labs, will enable us to accurately and
reliably process thousands of videos and generate associated
performance data, while lowering training cost,” said Rick
Echevarria, Vice President, Sales and Marketing Group, Intel. “With
DL1 instances, we can now train at the speed and cost required to
productively serve athletes, teams, and broadcasters of all levels
across a variety of sports.”
Riskfuel provides real-time valuations and risk sensitivities to
companies managing financial portfolios, helping them increase
trading accuracy and performance. “Two factors drew us to Amazon
EC2 DL1 instances based on Habana Gaudi AI accelerators,” said Ryan
Ferguson, CEO of Riskfuel. “First, we want to make sure our banking
and insurance clients can run Riskfuel models that take advantage
of the newest hardware. We found migrating our models to DL1
instances to be simple and straightforward—really, it was just a
matter of changing a few lines of code. Second, training costs are
a big component of our spending, and the promise of up to 40%
improvement in price performance offers potentially substantial
benefit to our bottom line.”
Leidos is recognized as a top 10 health IT provider delivering a
broad range of customizable, scalable solutions to hospitals and
health systems, biomedical organizations, and every U.S. federal
agency focused on health. “One of the numerous technologies we are
enabling to advance healthcare today is the use of machine learning
and deep learning for disease diagnosis based on medical imaging
data. Our massive data sets require timely and efficient training
to aid researchers seeking to solve some of the most urgent medical
mysteries,” said Chetan Paul, CTO Health and Human Services at
Leidos. “Given Leidos’ and its customers’ need for quick, easy, and
cost-effective training for deep learning models, we are excited to
have begun this journey with Intel and AWS to use Amazon EC2 DL1
instances based on Habana Gaudi AI processors. Using DL1 instances,
we expect an increase in model training speed and efficiency, with
a subsequent reduction in risk and cost of research and
development.”
Fractal is a global leader in artificial intelligence and
analytics, powering decisions in Fortune 500 companies. “AI and
deep learning are at the core of our healthcare imaging business,
enabling customers to make better medical decisions. In order to
improve accuracy, medical datasets are becoming larger and more
complex, requiring more training and retraining of models, and
driving the need for improved computing price performance,” said
Srikanth Velamakanni, Group CEO of Fractal. “The new Amazon EC2 DL1
instances promise significantly lower cost training than GPU-based
EC2 instances, which can help us contain costs and make AI
decision-making more accessible to a broader array of
customers.”
About Amazon Web Services
For over 15 years, Amazon Web Services has been the world’s most
comprehensive and broadly adopted cloud offering. AWS has been
continually expanding its services to support virtually any cloud
workload, and it now has more than 200 fully featured services for
compute, storage, databases, networking, analytics, 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 81 Availability Zones (AZs) within 25 geographic
regions, with announced plans for 24 more Availability Zones and
eight more AWS Regions in Australia, India, Indonesia, Israel, New
Zealand, Spain, Switzerland, and the United Arab Emirates. 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. Amazon strives to
be Earth’s Most Customer-Centric Company, Earth’s Best Employer,
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