The convergence of HPC+AI has opened new pathways for companies and developers worldwide to develop innovative, transformative applications. While this presents a plethora of new business opportunities in fields like academic research, climate modeling, and energy sustainability, they also push the boundaries of compute, data, and process capabilities of the underlying infrastructure so they can perform the way they were intended.
Microsoft Azure is committed to providing those capabilities through a continual improvement cycle that incorporates the newest and fastest processors into the cloud. This spring, NVIDIA GTC will illustrate that commitment in detail, showcasing NVIDIA’s accelerated computing capabilities powering resources on Azure that highlight our ongoing commitment to HPC+AI computing across the spectrum of edge, on-premises, and the cloud, while extending data security and privacy capabilities to meet customer and business data needs.
Register for NVIDIA GTC, running March 21 through 24, 2022.
Get a chance to win an NVIDIA Jetson Nano
Two of our sessions give you the chance to win a SWAG box, complete with an HPC t-shirt and Jetson Nano developer kit. Attend these sessions and don’t forget to look for the special link to enter!
Supercomputer Performance, Meet Cloud Versatility.
Nidhi Chappell, Head of Product, Azure HPC/AI Microsoft; John Montgomery, Corporate Vice President Program Management, Azure AI- Microsoft,
Tuesday, March 22, 2022, 11:00 AM PDT.
The Azure HPC+AI platform enables a new era of innovative applications and services that leverage the versatility of the cloud with the power of supercomputing performance. The convergence of HPC and AI is a revolution, bringing dramatic acceleration to every kind of simulation, and advancing fields across science and industry. Whether you need to scale to over 80,000 cores for your message passing interface (MPI)-based workloads, or you are looking for AI supercomputing capabilities, Azure can support your needs with all of the versatility of the cloud. In this session, we will provide an overview of the Azure HPC+AI platform reviewing recent accomplishments, and cover in detail how the Azure HPC+AI portfolio can support your accelerator workload needs ranging from AI inferencing to deep learning and more.
Unlocking New Possibilities for Privacy-Preserving Data Analytics with Azure Confidential Computing.
Mark Russinovich, Azure CTO and Technical Fellow, Microsoft; Ian Buck, Vice President and General Manager of Accelerated Computing, NVIDIA.
In this session, Microsoft Azure CTO and Technical Fellow Mark Russinovich and NVIDIA Data Center VP Ian Buck discuss how Microsoft and NVIDIA are partnering together to integrate the latest GPU technology with Azure confidential computing to help customers process large data workloads such as AI and machine learning, multi-party analytics, and 3D rendering while keeping data private and secure. Currently, there is no comparable offering in the marketplace, and Azure is driving first to market with this game-changing technology in our quest to be the most secure cloud.
Preserving privacy with confidential computing
Organizations across industries are going through a major AI-led disruption. For example, in healthcare, hospitals, pharmaceuticals, and researchers are leveraging AI to accelerate research, refine diagnostics, and improve drug discovery and development. Yet, the democratization of AI is limited by concerns regarding share and use of personal data. For example, banks are often unable to collaborate on critical tasks such as fraud and money laundering detection.
Microsoft has pioneered several privacy-preserving technologies such as homomorphic encryption, confidential computing, and differential privacy to address these challenges.
Join us at NVIDIA GTC to learn more about how to unlock new possibilities for privacy-preserving data analytics with Azure confidential computing to help process large data workloads such as AI and machine learning, multi-party analytics, and 3D rendering, while keeping data private and secure. Learn about how confidential GPUs offer high efficiency and confidentiality and how customers and organizations across the world benefit from it.
Transforming AI and machine learning at the edge
According to IoT Signals, IoT and AI adoption isn’t slowing down with 90 percent of adopters stating that IoT is critical to their success and 79 percent of businesses indicating they were successfully adopting AI within their IoT solutions with top reasons including predictive maintenance at 67 percent and prescriptive maintenance at 65 percent. Additionally, 56 percent of organizations are combining AI and IoT to create a better user experience.
However, at the same time, 46 percent of businesses with AI strategies are struggling to get their projects past the proof-of-concept stage due to technical challenges and complexity. By shifting AI, analytics, and logic to edge devices, edge computing can help solve speed, latency, security, and reliability challenges within AI and IoT applications.
At NVIDIA GTC, learn more about how Nvidia and Microsoft are working together to Transform AI and machine learning at the Edge leveraging the power of the GPU at the edge combined with Azure AI and IoT services. Learn about accelerating AI and IoT solutions with Azure Percept, Azure Stack HCI, and other Azure IoT services.
For more information check out NVIDIA + Microsoft Accelerated Edge AI webpage.
NVIDIA DLI Training Powered by Azure
We’re proud to host NVIDIA’s Deep Learning Institute (DLI) training at NVIDIA GTC again this year, with instructor-led workshops around accelerated computing, accelerated data science, and deep learning. Hosted on Microsoft Azure, these sessions enable and empower you to leverage NVIDIA GPUs on the Microsoft Azure platform to solve the world’s most interesting and relevant problems. Register for a DLI workshop today.
Sensyne Health aids National Health Service in the COVID-19 struggle with Microsoft HPC and AI technologies.
In the midst of COVID-19 the need for a way to get faster test results, Sensyne Health developed its MagnifEye solution, a mobile app that uses a device’s camera to capture the lateral flow test (LFT) stick image and read it in tenths of seconds with a stunning 99.6 percent accuracy rate.