Today, Azure announces the general availability of Azure ND A100 v4 Cloud GPU instances—powered by NVIDIA A100 Tensor Core GPUs—achieving leadership-class supercomputing scalability in a public cloud. For demanding customers chasing the next frontier of AI and high-performance computing (HPC), scalability is the key to unlocking improved Total Cost of Solution and Time-to-Solution.
Simply put, ND A100 v4—powered by NVIDIA A100 GPUs—is designed to let our most demanding customers scale up and scale out without slowing down.
Benchmarking with 164 ND A100 v4 virtual machines on a pre-release public supercomputing cluster yielded a High-Performance Linpack (HPL) result of 16.59 petaflops. This HPL result, delivered on public cloud infrastructure, would fall within the Top 20 of the November 2020 Top 500 list of the fastest supercomputers in the world, or top 10 in Europe, based on the region where the job was run.
Measured via HPL-AI, an artificial intelligence (AI) and machine learning (ML)-focused High-Performance Linpack variant, the same 164-VM pool achieved a 142.8 Petaflop result, placing it among the world’s Top 5 fastest known AI supercomputers as measured by the official HPL-AI benchmark list. These HPL results, utilizing only a fraction of a single public Azure cluster, rank with the most powerful dedicated, on-premises supercomputing
Over the past year, it’s become clear that businesses navigating these unprecedented times require a new level of agility. Core to this agility is achieving a level of software development excellence that was once thought unimaginable. When it comes to empowering all developers with limitless scale, choice, and possibilities, Microsoft Azure has their back.
Our commitment to developers is to make Azure the best cloud for developing intelligent applications that harness the power of data and AI. At Microsoft Build, we are announcing several exciting new capabilities and offers that make it easy and cost-effective for developers to get started with Azure data and AI services.
Innovate with Azure database services
We are announcing several new capabilities that empower developers to innovate with Azure’s database services. Azure SQL Database’s ledger capability, in preview, provides cryptographic verification for sensitive records. Customers like British Petroleum are already benefiting from this exciting feature. Azure Synapse Link for Microsoft Dataverse provides immediate insights from Microsoft Dynamics 365 and Microsoft Power Platform applications, while Microsoft Power BI streaming dataflows remove any bottleneck from signals to insights. There are also several updates to Azure Cosmos DB to help developers build and modernize high-performance applications at any scale,
Over the past year, Microsoft has teamed with Ball Aerospace to develop the prototype for the Commercially Augmented Space Inter Networked Operations (CASINO) Program Office, facilitated by the Defense Innovation Unit, demonstrating agile cloud processing capabilities in support of the United States Space Force.
The rising number of satellites proliferating in low earth orbit (LEO) presents a new data challenge for the ground segment of missions—a segment that is often overlooked. For increasingly distributed mission environments, Microsoft Azure delivers the processing power and analysis necessary for these large datasets.
The CASINO Program Office demonstrated fast, flexible, and extensible commercial capabilities for ground processing in support of defense missions. The project also confirmed the potential to transform the analysis of space data across a wide array of industries, including agriculture, ecological study, sustainability, and disaster response.
Microsoft-Ball Aerospace team demonstrates a new method of space analytics
This project represents a huge leap forward in reducing the time to actionable insight—if you are on the ground in a tactical edge vehicle or located at a command center, users can obtain necessary information accurately, quickly, and securely.
To execute the demonstrations, the team transmitted simulated overhead persistent infrared (OPIR) data through
Azure Health Bot empowers developers in healthcare organizations to build and deploy artificial intelligence (AI)-powered, compliant, conversational healthcare experiences at scale. It combines built-in medical intelligence with natural language capabilities to understand clinical terminology and can be easily customized to support clinical and operational use cases. The service enables healthcare organizations to comply with industry requirements, including HIPAA and HITRUST. For example, Trinity Health, one of the largest healthcare systems in the U.S., caring for more than 30 million people across 22 states, has effectively utilized Azure Health Bot to make it easier for patients to quickly connect to the care they need.
Today, we are bringing Azure Health Bot to eight new regions:
West U.S. 2 East U.S. 2 South Central U.S. UK South North Europe Southeast Asia Australia East India Central
In response to the surge of COVID-19 cases in India, we are also adding India Central to support the pandemic response efforts in the region. In addition to East U.S. and West Europe, these new regions bring the general availability of Azure Health Bot to a total of 10 regions across three continents.
Our customers have been using Azure Health Bot to drive engagement
Customers around the world rely on Microsoft Azure to drive innovations related to our environment, public health, energy sustainability, weather modeling, economic growth, and more. Finding solutions to these important challenges requires huge amounts of focused computing power. Customers are increasingly finding the best way to access such high-performance computing (HPC) through the agility, scale, security, and leading-edge performance of Azure’s purpose-built HPC and AI cloud services.
Azure’s market-leading vision for HPC and AI is based on a core of genuine and recognized HPC expertise, using proven HPC technology and design principles, enhanced with the best features of the cloud. The result is a capability that delivers performance, scale, and value, unlike any other cloud. This means applications are scaling 12 times higher than other public clouds. It means higher application performance per node. It means powering AI workloads for one customer with a supercomputer fit to be among the top five in the world. It also means delivering massive compute power into the hands of medical researchers over a weekend to prove out life-saving innovations in the fight against COVID-19.
This year during NVIDIA GTC 21, we’re spotlighting some of the most transformational applications powered by NVIDIA accelerated
Keeping up with the rapid pace of technology innovation today requires equal advances in the pace of development of new microelectronics. At the same time, customers are increasingly focused on securing the technology supply chain all the way to the silicon. To sustain U.S. strength and leadership in the microelectronics field, we and our partners are committed to enabling a microelectronics supply chain that meets stringent security, protection, and compliance requirements.
Commercially, the microelectronics industry uses Azure to accelerate the development of new circuits and chips to improve both the design and the manufacturing process. We work closely with semiconductor design and foundry partners, and electronic design automation (EDA) vendors, to develop finely tuned solutions running on Azure High Performance Computing (HPC), Internet of Things (IoT) and Edge infrastructures, utilizing Azure Artificial Intelligence and Machine Learning to accelerate the silicon development cycle.
These capabilities also enable U.S. Government customers to ensure compliance with the stringent supply chain requirements for defense and critical infrastructure. Today we’re announcing our collaboration with the Department of Defense (DoD) to strengthen U.S. microelectronics supply chain through our work on the Rapid Assured Microelectronics Prototypes (RAMP) using Advanced Commercial Capabilities Project. This work extends our
Whether you’re a new student, thriving startup, or the largest enterprise, you have financial constraints, and you need to know what you’re spending, where, and how to plan for the future. Nobody wants a surprise when it comes to the bill, and this is where Azure Cost Management and Billing comes in.
We’re always looking for ways to learn more about your challenges and how Azure Cost Management and Billing can help you better understand where you’re accruing costs in the cloud, identify and prevent bad spending patterns, and optimize costs to empower you to do more with less. Here are a few of the latest improvements and updates based on your feedback:
Introducing the Azure Advisor Score Create subscriptions with ARM templates Tell us what you need when verifying billed charges What’s new in Cost Management Labs New ways to save money with Azure New videos and learning opportunities Documentation updates
Let’s dig into the details.
Introducing the Azure Advisor Score
Wouldn’t it be great to have some assurances that you’re running your workloads in a cost-efficient manner? That’s exactly what Azure Advisor gives you and now, with the Advisor Score, it’s easier than ever for you
Organizations today are striving to build agility and resilience to the fast-changing environment we live in. AI and machine learning innovation can help tackle these emerging challenges and enable cost efficiencies. However, organizations still encounter barriers to adopting and deploying machine learning at scale. Recently at Microsoft Ignite, Azure Machine Learning made a number of announcements that help organizations harness machine learning more easily, securely, and at scale. This includes capabilities like designer and automated machine learning UI, now generally available, that simplify machine learning for beginners and professionals alike. Advanced role-based access control (RBAC) and private IP link, in preview, make it possible to build machine learning solutions more securely. In addition, we are merging the Azure Machine Learning Enterprise and Basic Editions to deliver greater value at no extra cost.
“With Azure Machine Learning, we’re increasing speed-to-value while reducing cost-to-value.” – Sarah Dods, Head of Advanced Analytics, AGL. Read the story.
Machine learning simplified
Azure Machine Learning designer provides a drag-and-drop canvas to build no-code models with ease. Built-in modules help preprocess data and build and train models using machine learning and deep learning algorithms, including computer vision, text analytics, recommendation, anomaly detection, and
Organizations around the world are gearing up for a future powered by artificial intelligence (AI). From supply chain systems to genomics, and from predictive maintenance to autonomous systems, every aspect of the transformation is making use of AI. This raises a very important question: How are we making sure that the AI systems and models show the right ethical behavior and deliver results that can be explained and backed with data?
This week at Spark + AI Summit, we talked about Microsoft’s commitment to the advancement of AI and machine learning driven by principles that put people first.
Understand, protect, and control your machine learning solution
Over the past several years, machine learning has moved out of research labs and into the mainstream and has grown from a niche discipline for data scientists with PhDs to one where all developers are empowered to participate. With power comes responsibility. As the audience for machine learning expands, practitioners are increasingly asked to build AI systems that are easy to explain and that comply with privacy regulations.
The demand for artificial intelligence (AI) and data science roles continues to rise. According to LinkedIn’s Emerging Jobs Report for 2020, AI specialist roles are most sought after with a 74 percent annual growth rate in hiring over the last four years. Additionally, the current global health pandemic has powered a shift towards remote working as well as an increased interest in professional training resources. To address this demand, we’re announcing our collaboration with Udacity to launch new machine learning courses for both beginners and advanced users, as well as a scholarship program.
Through these new offerings, Microsoft aims to help expand the talent pool of data scientists and improve access to education and resources to anyone interested. I recently sat down for a chat with Udacity CEO, Gabe Dalporto, to talk about this collaboration.
Udacity is a digital education platform with over 250,000 currently active students. Their students have expressed continued interest in introductory machine learning (ML) content that doesn’t require advanced programming knowledge. In response, Microsoft Azure and Udacity have created a unique free course based on Azure Machine Learning. This Introduction to machine learning on Azure course will help students learn the basics of ML through