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Microsoft Discovery: The path to an agentic EDA environment
Generative AI has been the buzz across engineering, science and consumer applications, including EDA. It was the centerpiece of the keynotes at both SNUG and CadenceLive, and it will feature heavily at DAC. Very impressive task specific tools and capabilities powered by traditional and generative AI are being developed by both industry vendors and customers. However, all these solutions are point solutions addressing specific tasks. This leaves the question of how customers will tie it all together and how customers will be able to run and access the LLMs, AI and data resources needed to power these solutions. While our industry has experience developing, running, and maintaining high-performance EDA environments, an AI centric data center running GPUs and low latency interconnect like Infiniband, is not an environment many chip development companies already have or have experience executing. Unfortunately, because LLMs are so resource hungry, it’s difficult to “ease into” a deployment. The Agentic Platform for EDA At the Microsoft Build conference in May, Microsoft introduced the Microsoft Discovery Platform. This platform aims to accelerate R&D across several industry verticals, specifically Biology (Life science and drug discovery), Chemistry (materials and substance discovery), and Physics (semiconductors and multi-physics). Microsoft Discovery provides the platform and capabilities to help customers implement a complete agentic AI environment. Being a cloud-based solution means customers won’t need to manage the AI models or RAG solutions themselves. Running inside the customer’s cloud tenant, the AI models, the data they use, and the results they produce all remain under the customer's control and within the customer’s environment. No data goes back to the Internet and all learning remains with the customer. This gives customers the confidence that they can safely and easily deploy and use AI models while maintaining complete sovereignty over their data and IP. Customers are free to deploy any of the dozens of available AI models offered on Azure. Customers can also deploy and use Graph RAG solutions to improve context and get better LLM responses. This is all available without having to deploy additional hardware or manage a large, independent GPU deployment. Customers testing out generative AI solutions and starting to develop their flows, tools, and methodologies with this new technology can deploy and use these resources as needed. The Microsoft Discovery platform does not try to replace the EDA tools you already have. Instead, it allows you to incorporate those tools into an agentic environment. Without anthropomorphizing, these agents can be thought of as AI driven task engines that can reason and interact with each other or tools. They can be used to make decisions, analyze results, generate responses, take action, or even drive tools. Customers will be able to incorporate existing EDA tools into the platform and drive them with an agent. Microsoft Discovery will even be able to run agents from partners and help customers intelligently tie together multiple capabilities and help automate analysis and decision-making on the flow helping each engineering teams accomplish a greater number of tasks more quickly and achieve increased productivity. HPC Infrastructure for EDA Of course, to run EDA tools, customers need an effective environment to run those tools in. One of the things that has always been true in our industry but is often overlooked is that, as good as the algorithms in the tools are, they’re always limited by the infrastructure it runs on. No matter how fast your algorithm is, running on a slow processor means turn-around time is still going to be slow. No matter how fast your tools are and how new and shiny your servers are, if your file system is a bottleneck, your tool and server will have to wait for the data. The infrastructure you run on sets the speed limit for your job regardless of how fast an engine you have. Most of the AI solutions being discussed for EDA focus only on the engine and ignore the infrastructure. The Microsoft Discovery platform understands this and addresses the issue by having the Azure HPC environment at its core. The HPC core of the platform uses elements familiar to the EDA community. High performance file storage utilizes Azure NetApp Files (ANF). This shared file service uses the same NetApp technology and hardware that many in the EDA community already uses on-prem. ANF delivers unmatched performance for cloud-based file storage, especially for metadata heavy workloads, like EDA. This will help provide EDA workloads with a familiar pathway into the Discovery platform to make use of the AI capabilities for chip design. Customers will also have access to Azure’s fleet of high-performance compute, including the recently released Intel Emerald Rapids-based FXv2, which was developed with large, back-end EDA workloads in mind. FXv2 features 1.8TB of RAM and all core turbo clock speed of 4 GHz. Ideal for large STA, P&R, and PV workloads. For front-end and moderate sized back-end workloads, in addition to the existing HPC compute offerings, Microsoft recently updated the D and E series compute SKUs with Intel Emerald Rapids processors in the v6 versions of those systems, further pushing performance for smaller workloads. Design teams will have access to the required high-performance compute and storage resources to maximize their EDA tools while also taking advantage of the benefits of AI capabilities offered by the platform. The familiar EDA-friendly HPC environment makes migration of existing workloads easier and ensures that tools will run effectively and, more importantly, flows mesh more smoothly. Industry Standards and Interoperability Another aspect of the Microsoft Discovery platform that will be especially important for EDA customers is the fact that the platform will utilize A2A for agent-to-agent communication and MCP for agent-service communication. The reason this is important is because both A2A and MCP are industry standard protocols. Microsoft also expects to support the evolution of these and other newer standards that will emerge in this field, future-proofing your investment. Those of us who have been involved in the various standards and interoperability efforts in semiconductor and EDA over the years will understand that having the platform use industry standards-based interfaces makes adoption of new technology much easier for all users. With AI development rushing forward and everyone, customers and vendors alike, trying to capitalize on gen AI’s promises, there are already independent efforts by customers and vendors to develop capabilities quickly. In the past, this meant that everyone went off in different directions developing mutually exclusive solutions. Vendors would develop mutually exclusive solutions that customers would have to also develop customized solutions to leverage. The various solutions would all work slightly differently, making integration a painful process. The history of VMM, OVM, and UVM was an example of this. As the industry starts to develop AI and agentic environments, the same fragmentation is likely to also happen again. By starting with A2A and MCP, Microsoft is signaling for the industry to align around these industry standard protocols. This will make it easier for agents developed by customers and vendors to interoperate with each other and the Discovery platform. Vendor tools implementing a MCP server interface can directly communicate with customer agents using MCP as well as with the Discovery platform. This makes it easier for our industry to develop interoperable solutions. Similarly, agents that use the A2A protocol to interact with other agents can be more easily integrated if the other agents also communicate using A2A. If you’re going to be building agents for EDA or EDA tools or services that interact with agents, build them using A2A for inter-agent communication and MCP for agent-to-tool/service communication. Generative AI is likely to be the most transformative technology to impact EDA this decade. It likely will be at least as impactful, productivity wise, for us a synthesis, STA, and automatic place and route were in their own ways. To learn more about these innovations, come join the Microsoft team at the Design Automation Conference (DAC) in San Francisco on June 23. At DAC, the Microsoft team will go into depth about the Discovery platform and the larger impact that AI will have on the semiconductor industry. In his opening keynote discussion on Monday, Bill Chappell, Microsoft's CTO for the Microsoft Discovery and Quantum team will discuss AI's impact on science and the semiconductor industry. Serge Leef’s engineering track session will talk about generative AI in chip design, and don't miss Prashant Varshney's detailed explanation of the Microsoft Discovery platform in his Exhibitor Forum session. Visit the Microsoft booth (second floor, 2124) for more in-depth discussions with our team.
richpaw
Jun 20, 2025 Place Azure High Performance Computing (HPC) Blog
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Accelerating Genomic Pipelines with Nextflow on Microsoft Azure at the Nextflow Summit Boston 2025
Nextflow is one of the most widely adopted open-source workflow orchestrators in the scientific research domain. In genomics, a pipeline refers to a series of computational steps designed to analyze and interpret large-scale genomic data. These pipelines consist of multiple stages, each leveraging specialized bioinformatics tools and software to transform raw genomic inputs into meaningful biological insights. Running these pipelines efficiently requires significant computational power, parallel processing capabilities, and scalability—needs that are met by using a robust workflow orchestrator like Nextflow. This is precisely where Microsoft Azure HPC + AI services deliver strong value for scientists and bioinformaticians. With deep integrations between Nextflow and Azure cloud services, customers can build cloud-native infrastructures capable of handling multiple petabytes of genomic data from diverse sources. These integrations enable elastic pipeline scaling and seamless execution in hybrid or fully cloud-based environments. The Nextflow Summit Boston 2025 is an exciting gathering of scientists, bioinformaticians, data scientists, developers, and industry leaders from around the globe. It serves as a platform to shape the future of biotech research and development through community-driven innovation in data science and computational biology—all centered around a shared interest in Nextflow. This year, Microsoft is honored to participate in the summit with both a speaker session and a poster presentation, highlighting how Nextflow can run seamlessly in hybrid and fully cloud-native environments on Microsoft Azure. Join us on Thursday, May 15 at 4:00 PM for the session titled: “Running Nextflow on Microsoft Azure: Selecting Executors and Infrastructure Components” Presented by Wolfgang De Salvador, Venkat Malladi, and Jer-Ming Chia, this session offers a comprehensive overview of running Nextflow workflows in the cloud. It will explore the range of executor options available—including traditional schedulers, batch-managed services, and Kubernetes—as well as storage solutions spanning from file-based to object-based systems. This is a must-attend session for anyone looking to optimize infrastructure and boost performance for their Nextflow workflows on Azure. To register for Nextflow Summit Boston 2025 and access recordings after the event, visit the official Nextflow Summit website.
Fernando_Aznar
May 09, 2025 Place Azure High Performance Computing (HPC) Blog
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Session on-demand and highlights from NVIDIA GTC 2025
It was great to see you at the NVIDIA GTC AI Conference in San Jose, CA March 17 - 21! Microsoft sessions are now available on demand and here are highlights from our time at GTC 2025.
SarahYousuf
Apr 03, 2025 Place Azure High Performance Computing (HPC) Blog
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Accelerating the Intelligence Age with Azure AI Infrastructure and the GA of ND GB200 v6
Today we are thrilled to announce the General Availability of Azure's latest AI infrastructure Virtual Machines, the ND GB200 v6.
MattVegas1
Mar 19, 2025 Place Azure High Performance Computing (HPC) Blog
2.9KViews
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Daily schedule: Microsoft in-booth sessions at NVIDIA GTC
Visit Microsoft booth #514 at the NVIDIA GTC AI Conference for live information session from Azure, partner and customer AI experts. Read on for our daily schedule.
SarahYousuf
Mar 19, 2025 Place Azure High Performance Computing (HPC) Blog
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Unpacking the Performance of Microsoft Azure ND GB200 v6 Virtual Machines
For a comprehensive understanding of our benchmarking methodologies and detailed performance results, please refer to our benchmarking guide available on the official Azure GitHub repository: Azure AI Benchmarking Guide. Breakdown of Benchmark Tests GEMM Performance General Matrix Multiply (GEMM) operations form the backbone of AI models. We measured that more than 60% of the time spent inferencing or training an AI model is spent doing matrix multiplication. Thus, measuring their speed is key to understand the performance of a GPU-based virtual machine. Azure benchmark assesses matrix-to-matrix multiplication efficiency using NVIDIA’s CuBLASLt library with FP8 precision, ensuring results reflect enterprise AI workloads. We measured the peak theoretical performance of the NVIDIA GB200 Blackwell GPU to be 4,856 TFLOPS, representing a 2.45x increase in performance compared to peak theoretical 1,979 TFLOPS on the NVIDIA H100 GPU. This finding is in-line with NVIDIA’s announcement of a 2.5x performance increase at GTC 2024. The true performance gain of the NVIDIA GB200 Blackwell GPU over its predecessors emerges in real-life conditions. For example, using 10,000 warm-up iterations and randomly initialized matrices demonstrated a sustained 2,744 TFLOPS for FP8 workloads, which, while expectedly lower than the theoretical peak, is still double that of the H100. The impact of these improvements on real workloads indicates up to a 3x speedup on average for end-to-end training and inference workloads based on our early results. High-Bandwidth Memory (HBM) Bandwidth Memory bandwidth is the metric that governs data movements. Our benchmarks showed a peak memory bandwidth of 7.35 TB/s, achieving 92% of its theoretical peak of 7.9 TB/s. This efficiency mirrors that of the H100, which also operated close to its theoretical maximum, while reaching 2.5x faster data transfers. This speedup ensures that data-intensive tasks, such as training large-scale neural networks, are executed efficiently. NVBandwidth The ND GB200 v6 architecture significantly enhances AI workload performance with NVLink C2C, enabling a direct, high-speed connection between the GPU and host system. This design reduces latency and improves data transfer efficiency, making AI workloads faster and more scalable. Our NVBandwidth tests measured CPU-to-GPU and GPU-to-CPU transfer rates to be nearly 4× faster than the ND H100 v5. This improvement minimizes bottlenecks in data-intensive applications and optimizes data movement efficiency over previous GPU-powered virtual machines. In addition, it allows the GPU to readily access additional memory when needed, which can be quickly accessed via the C2C link. NCCL Bandwidth NVIDIA’s Collective Communications Library (NCCL) enables high-speed communication between GPUs within and across nodes. We built our tests to measure the speed of communication between GPUs over NVLink within one virtual machine. Hig-speed communication is instrumental as most enterprise workloads consist of large-scale distributed models. The ND GB200 v6’s NVLink achieved a bandwidth of approximately 680 GB/s, aligning with NVIDIA’s projections. Conclusion The ND GB200 v6 virtual machine, powered by the NVIDIA GB200 Blackwell GPUs, showcases substantial advancements in computational performance, memory bandwidth, and data transfer speeds compared to the previous generations of virtual machines. These improvements are pivotal for efficiently managing the increasing demands of AI workloads like generative and agentic use-cases. Following our Benchmarking Guide will provide early access to performance reviews of the innovations announced at GTC 2025, helping customers drive the next wave of AI on Azure’s purpose-built AI infrastructure.
HugoAffaticati
Mar 19, 2025 Place Azure High Performance Computing (HPC) Blog
1.2KViews
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Innovation starts here! Join Microsoft at NVIDIA GTC
Innovation starts here! Join Microsoft at the NVIDIA GTC AI Conference March 17 – 21 in San Jose, CA (or virtual) to explore the latest AI technology and solutions and discover Azure’s end-to-end AI platform.
SarahYousuf
Mar 13, 2025 Place Azure High Performance Computing (HPC) Blog
6.6KViews
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Join Microsoft Azure at SC24
Come visit Microsoft at Supercomputing 2024 Nov 17 – 22 where we’ll deep dive into HPC and AI solutions during a week of engaging sessions, hands on experiences and networking. We also have an exciting new Azure HPC announcement!
Michelle_R
Nov 19, 2024 Place Azure High Performance Computing (HPC) Blog
19KViews
1like
1Comment
Create the Future at Microsoft Azure HPC + AI Infrastructure Summit with AMD.
Discover how Microsoft, AMD, and your peers are revolutionizing their infrastructure with HPC+AI
Fernando_Aznar
May 20, 2024 Place Azure High Performance Computing (HPC) Blog
7.8KViews
2likes
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Deploying Open OnDemand Portal with Azure CycleCloud
This blog post presents an Azure CycleCloud project allowingthe deployment of an Open OnDemand portal, an efficient open-source web portal for job submission, job monitoring, file management and remote desktop/application sessions.
wolfgangdesalvador
May 09, 2024 Place Azure High Performance Computing (HPC) Blog
9.7KViews
1like
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auto;\r\n}\r\n.custom_widget_MicrosoftFooter_c-uhff-nav_1w55e_69 {\r\n margin: 0 auto;\r\n max-width: calc(100rem + 10%);\r\n padding: 0 5%;\r\n box-sizing: inherit;\r\n &:before,\r\n &:after {\r\n content: ' ';\r\n display: table;\r\n clear: left;\r\n }\r\n @media only screen and (max-width: 1083px) {\r\n padding-left: 0.75rem;\r\n }\r\n .custom_widget_MicrosoftFooter_c-heading-4_1w55e_97 {\r\n color: #616161;\r\n word-break: break-word;\r\n font-size: 0.9375rem;\r\n line-height: 1.25rem;\r\n padding: 2.25rem 0 0.25rem;\r\n font-weight: 600;\r\n }\r\n .custom_widget_MicrosoftFooter_c-uhff-nav-row_1w55e_113 {\r\n .custom_widget_MicrosoftFooter_c-uhff-nav-group_1w55e_115 {\r\n display: block;\r\n float: left;\r\n min-height: 0.0625rem;\r\n vertical-align: text-top;\r\n padding: 0 0.75rem;\r\n width: 100%;\r\n zoom: 1;\r\n &:first-child {\r\n padding-left: 0;\r\n @media only screen and (max-width: 1083px) {\r\n padding-left: 0.75rem;\r\n }\r\n }\r\n @media only screen and (min-width: 540px) and (max-width: 1082px) {\r\n width: 33.33333%;\r\n }\r\n @media only screen and (min-width: 1083px) {\r\n width: 16.6666666667%;\r\n }\r\n ul.custom_widget_MicrosoftFooter_c-list_1w55e_155.custom_widget_MicrosoftFooter_f-bare_1w55e_155 {\r\n font-size: 0.6875rem;\r\n line-height: 1rem;\r\n margin-top: 0;\r\n margin-bottom: 0;\r\n padding-left: 0;\r\n list-style-type: none;\r\n li {\r\n word-break: break-word;\r\n padding: 0.5rem 0;\r\n margin: 0;\r\n }\r\n }\r\n }\r\n }\r\n}\r\n.custom_widget_MicrosoftFooter_c-uhff-base_1w55e_187 {\r\n background: #f2f2f2;\r\n margin: 0 auto;\r\n max-width: calc(100rem + 10%);\r\n padding: 1.875rem 5% 1rem;\r\n &:before,\r\n &:after {\r\n content: ' ';\r\n display: table;\r\n }\r\n &:after {\r\n clear: both;\r\n }\r\n a.custom_widget_MicrosoftFooter_c-uhff-ccpa_1w55e_213 {\r\n font-size: 0.6875rem;\r\n line-height: 1rem;\r\n float: left;\r\n margin: 0.1875rem 0;\r\n }\r\n a.custom_widget_MicrosoftFooter_c-uhff-ccpa_1w55e_213:hover {\r\n text-decoration: underline;\r\n }\r\n ul.custom_widget_MicrosoftFooter_c-list_1w55e_155 {\r\n font-size: 0.6875rem;\r\n line-height: 1rem;\r\n float: right;\r\n margin: 0.1875rem 0;\r\n color: #616161;\r\n li {\r\n padding: 0 1.5rem 0.25rem 0;\r\n display: inline-block;\r\n }\r\n }\r\n .custom_widget_MicrosoftFooter_c-list_1w55e_155.custom_widget_MicrosoftFooter_f-bare_1w55e_155 {\r\n padding-left: 0;\r\n list-style-type: none;\r\n }\r\n @media only screen and (max-width: 1083px) {\r\n display: flex;\r\n flex-wrap: wrap;\r\n padding: 1.875rem 1.5rem 1rem;\r\n }\r\n}\r\n.custom_widget_MicrosoftFooter_social-share_1w55e_275 {\r\n position: fixed;\r\n top: 60%;\r\n transform: translateY(-50%);\r\n left: 0;\r\n z-index: 1000;\r\n}\r\n.custom_widget_MicrosoftFooter_sharing-options_1w55e_291 {\r\n list-style: none;\r\n padding: 0;\r\n margin: 0;\r\n display: block;\r\n flex-direction: column;\r\n background-color: white;\r\n width: 3.125rem;\r\n border-radius: 0 0.4375rem 0.4375rem 0;\r\n}\r\n.custom_widget_MicrosoftFooter_linkedin-icon_1w55e_311 {\r\n border-top-right-radius: 7px;\r\n}\r\n.custom_widget_MicrosoftFooter_linkedin-icon_1w55e_311:hover {\r\n border-radius: 0;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-email-image_1w55e_325:hover {\r\n border-radius: 0;\r\n}\r\n.custom_widget_MicrosoftFooter_social-link-footer_1w55e_333:hover .custom_widget_MicrosoftFooter_linkedin-icon_1w55e_311 {\r\n border-radius: 0;\r\n}\r\n.custom_widget_MicrosoftFooter_social-link-footer_1w55e_333:hover .custom_widget_MicrosoftFooter_social-share-email-image_1w55e_325 {\r\n border-radius: 0;\r\n}\r\n.custom_widget_MicrosoftFooter_social-link-footer_1w55e_333 img {\r\n width: 1.875rem;\r\n height: auto;\r\n transition: filter 0.3s ease;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list_1w55e_359 {\r\n width: 3.125rem;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-rss-image_1w55e_365 {\r\n width: 1.875rem;\r\n height: auto;\r\n transition: filter 0.3s ease;\r\n}\r\n.custom_widget_MicrosoftFooter_sharing-options_1w55e_291 li {\r\n width: 3.125rem;\r\n height: 3.125rem;\r\n padding: 0.5rem;\r\n box-sizing: border-box;\r\n border: 2px solid white;\r\n display: inline-block;\r\n text-align: center;\r\n opacity: 1;\r\n visibility: visible;\r\n transition: border 0.3s ease; /* Smooth transition effect */\r\n border-left: none;\r\n border-bottom: none; /* Apply bottom border to only last item */\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-linkedin_1w55e_405 {\r\n background-color: #0474b4;\r\n border-top-right-radius: 5px; /* Rounded top right corner of first item*/\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-facebook_1w55e_413 {\r\n background-color: #3c5c9c;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-xicon_1w55e_419 {\r\n background-color: #000;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-reddit_1w55e_425 {\r\n background-color: #fc4404;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-bluesky_1w55e_431 {\r\n background-color: #f0f2f5;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-rss_1w55e_437 {\r\n background-color: #ec7b1c;\r\n}\r\n.custom_widget_MicrosoftFooter_social-share-list-mail_1w55e_443 {\r\n background-color: #848484;\r\n border-bottom-right-radius: 5px; /* Rounded bottom right corner of last item*/\r\n}\r\n.custom_widget_MicrosoftFooter_sharing-options_1w55e_291 li.custom_widget_MicrosoftFooter_social-share-list-mail_1w55e_443 {\r\n border-bottom: 2px solid white; /* Add bottom border only to the last item */\r\n height: 3.25rem; /* Increase last child height to make in align with the hover label */\r\n}\r\n.custom_widget_MicrosoftFooter_x-icon_1w55e_459 {\r\n filter: invert(100%);\r\n transition: filter 0.3s ease;\r\n width: 1.25rem !important;\r\n height: auto;\r\n padding-top: 0.3125rem !important;\r\n}\r\n.custom_widget_MicrosoftFooter_bluesky-icon_1w55e_473 {\r\n filter: invert(20%) sepia(100%) saturate(3000%) hue-rotate(180deg);\r\n transition: filter 0.3s ease;\r\n padding-top: 0.3125rem !important;\r\n width: 1.5625rem !important;\r\n}\r\n.custom_widget_MicrosoftFooter_share-icon_1w55e_487 {\r\n border: 2px solid transparent;\r\n display: inline-block;\r\n position: relative;\r\n}\r\n.custom_widget_MicrosoftFooter_sharing-options_1w55e_291 li:hover {\r\n border: 2px solid white;\r\n border-left: none;\r\n border-bottom: none;\r\n border-radius: 0;\r\n}\r\n.custom_widget_MicrosoftFooter_sharing-options_1w55e_291 li.custom_widget_MicrosoftFooter_social-share-list-mail_1w55e_443:hover {\r\n border-bottom: 2px solid white; /* Add bottom border only to the last item */\r\n}\r\n.custom_widget_MicrosoftFooter_sharing-options_1w55e_291 li:hover .custom_widget_MicrosoftFooter_label_1w55e_519 {\r\n opacity: 1;\r\n visibility: visible;\r\n border: 2px solid white;\r\n box-sizing: border-box;\r\n border-left: 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Discovery: The path to an agentic EDA environment","conversation":{"__ref":"Conversation:conversation:4425992"},"id":"message:4425992","revisionNum":1,"uid":4425992,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:1302705"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"As AI-powered solutions increasingly take center stage at industry events like SNUG, CadenceLive, and the upcoming Design Automation Conference (DAC), it’s clear that generative AI will transform chip design. The question is how the industry can effectively harness generative AI. This article explores how the newly introduced Microsoft Discovery platform will facilitate a comprehensive industry-wide strategy to implement agentic EDA flows cohesively, leverage existing tools, and maintain interoperability.","metrics":{"__typename":"MessageMetrics","views":603},"postTime":"2025-06-20T12:24:14.505-07:00","lastPublishTime":"2025-06-20T12:24:14.505-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Generative AI has been the buzz across engineering, science and consumer applications, including EDA. It was the centerpiece of the keynotes at both SNUG and CadenceLive, and it will feature heavily at DAC. Very impressive task specific tools and capabilities powered by traditional and generative AI are being developed by both industry vendors and customers. However, all these solutions are point solutions addressing specific tasks. This leaves the question of how customers will tie it all together and how customers will be able to run and access the LLMs, AI and data resources needed to power these solutions. While our industry has experience developing, running, and maintaining high-performance EDA environments, an AI centric data center running GPUs and low latency interconnect like Infiniband, is not an environment many chip development companies already have or have experience executing. Unfortunately, because LLMs are so resource hungry, it’s difficult to “ease into” a deployment. \n The Agentic Platform for EDA \n At the Microsoft Build conference in May, Microsoft introduced the Microsoft Discovery Platform. This platform aims to accelerate R&D across several industry verticals, specifically Biology (Life science and drug discovery), Chemistry (materials and substance discovery), and Physics (semiconductors and multi-physics). \n Microsoft Discovery provides the platform and capabilities to help customers implement a complete agentic AI environment. Being a cloud-based solution means customers won’t need to manage the AI models or RAG solutions themselves. Running inside the customer’s cloud tenant, the AI models, the data they use, and the results they produce all remain under the customer's control and within the customer’s environment. No data goes back to the Internet and all learning remains with the customer. \n This gives customers the confidence that they can safely and easily deploy and use AI models while maintaining complete sovereignty over their data and IP. Customers are free to deploy any of the dozens of available AI models offered on Azure. Customers can also deploy and use Graph RAG solutions to improve context and get better LLM responses. This is all available without having to deploy additional hardware or manage a large, independent GPU deployment. Customers testing out generative AI solutions and starting to develop their flows, tools, and methodologies with this new technology can deploy and use these resources as needed. \n The Microsoft Discovery platform does not try to replace the EDA tools you already have. Instead, it allows you to incorporate those tools into an agentic environment. Without anthropomorphizing, these agents can be thought of as AI driven task engines that can reason and interact with each other or tools. They can be used to make decisions, analyze results, generate responses, take action, or even drive tools. Customers will be able to incorporate existing EDA tools into the platform and drive them with an agent. Microsoft Discovery will even be able to run agents from partners and help customers intelligently tie together multiple capabilities and help automate analysis and decision-making on the flow helping each engineering teams accomplish a greater number of tasks more quickly and achieve increased productivity. \n HPC Infrastructure for EDA \n Of course, to run EDA tools, customers need an effective environment to run those tools in. One of the things that has always been true in our industry but is often overlooked is that, as good as the algorithms in the tools are, they’re always limited by the infrastructure it runs on. No matter how fast your algorithm is, running on a slow processor means turn-around time is still going to be slow. No matter how fast your tools are and how new and shiny your servers are, if your file system is a bottleneck, your tool and server will have to wait for the data. The infrastructure you run on sets the speed limit for your job regardless of how fast an engine you have. Most of the AI solutions being discussed for EDA focus only on the engine and ignore the infrastructure. The Microsoft Discovery platform understands this and addresses the issue by having the Azure HPC environment at its core. \n The HPC core of the platform uses elements familiar to the EDA community. High performance file storage utilizes Azure NetApp Files (ANF). This shared file service uses the same NetApp technology and hardware that many in the EDA community already uses on-prem. ANF delivers unmatched performance for cloud-based file storage, especially for metadata heavy workloads, like EDA. This will help provide EDA workloads with a familiar pathway into the Discovery platform to make use of the AI capabilities for chip design. \n Customers will also have access to Azure’s fleet of high-performance compute, including the recently released Intel Emerald Rapids-based FXv2, which was developed with large, back-end EDA workloads in mind. FXv2 features 1.8TB of RAM and all core turbo clock speed of 4 GHz. Ideal for large STA, P&R, and PV workloads. For front-end and moderate sized back-end workloads, in addition to the existing HPC compute offerings, Microsoft recently updated the D and E series compute SKUs with Intel Emerald Rapids processors in the v6 versions of those systems, further pushing performance for smaller workloads. \n Design teams will have access to the required high-performance compute and storage resources to maximize their EDA tools while also taking advantage of the benefits of AI capabilities offered by the platform. The familiar EDA-friendly HPC environment makes migration of existing workloads easier and ensures that tools will run effectively and, more importantly, flows mesh more smoothly. \n Industry Standards and Interoperability \n Another aspect of the Microsoft Discovery platform that will be especially important for EDA customers is the fact that the platform will utilize A2A for agent-to-agent communication and MCP for agent-service communication. The reason this is important is because both A2A and MCP are industry standard protocols. Microsoft also expects to support the evolution of these and other newer standards that will emerge in this field, future-proofing your investment. \n Those of us who have been involved in the various standards and interoperability efforts in semiconductor and EDA over the years will understand that having the platform use industry standards-based interfaces makes adoption of new technology much easier for all users. With AI development rushing forward and everyone, customers and vendors alike, trying to capitalize on gen AI’s promises, there are already independent efforts by customers and vendors to develop capabilities quickly. \n In the past, this meant that everyone went off in different directions developing mutually exclusive solutions. Vendors would develop mutually exclusive solutions that customers would have to also develop customized solutions to leverage. The various solutions would all work slightly differently, making integration a painful process. The history of VMM, OVM, and UVM was an example of this. As the industry starts to develop AI and agentic environments, the same fragmentation is likely to also happen again. \n By starting with A2A and MCP, Microsoft is signaling for the industry to align around these industry standard protocols. This will make it easier for agents developed by customers and vendors to interoperate with each other and the Discovery platform. Vendor tools implementing a MCP server interface can directly communicate with customer agents using MCP as well as with the Discovery platform. This makes it easier for our industry to develop interoperable solutions. Similarly, agents that use the A2A protocol to interact with other agents can be more easily integrated if the other agents also communicate using A2A. If you’re going to be building agents for EDA or EDA tools or services that interact with agents, build them using A2A for inter-agent communication and MCP for agent-to-tool/service communication. \n Generative AI is likely to be the most transformative technology to impact EDA this decade. It likely will be at least as impactful, productivity wise, for us a synthesis, STA, and automatic place and route were in their own ways. To learn more about these innovations, come join the Microsoft team at the Design Automation Conference (DAC) in San Francisco on June 23. At DAC, the Microsoft team will go into depth about the Discovery platform and the larger impact that AI will have on the semiconductor industry. \n In his opening keynote discussion on Monday, Bill Chappell, Microsoft's CTO for the Microsoft Discovery and Quantum team will discuss AI's impact on science and the semiconductor industry. Serge Leef’s engineering track session will talk about generative AI in chip design, and don't miss Prashant Varshney's detailed explanation of the Microsoft Discovery platform in his Exhibitor Forum session. Visit the Microsoft booth (second floor, 2124) for more in-depth discussions with our team. 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In genomics, a pipeline refers to a series of computational steps designed to analyze and interpret large-scale genomic data. These pipelines consist of multiple stages, each leveraging specialized bioinformatics tools and software to transform raw genomic inputs into meaningful biological insights. \n \n Running these pipelines efficiently requires significant computational power, parallel processing capabilities, and scalability—needs that are met by using a robust workflow orchestrator like Nextflow. This is precisely where Microsoft Azure HPC + AI services deliver strong value for scientists and bioinformaticians. With deep integrations between Nextflow and Azure cloud services, customers can build cloud-native infrastructures capable of handling multiple petabytes of genomic data from diverse sources. These integrations enable elastic pipeline scaling and seamless execution in hybrid or fully cloud-based environments. \n \n The Nextflow Summit Boston 2025 is an exciting gathering of scientists, bioinformaticians, data scientists, developers, and industry leaders from around the globe. It serves as a platform to shape the future of biotech research and development through community-driven innovation in data science and computational biology—all centered around a shared interest in Nextflow. \n \n This year, Microsoft is honored to participate in the summit with both a speaker session and a poster presentation, highlighting how Nextflow can run seamlessly in hybrid and fully cloud-native environments on Microsoft Azure. \n \n Join us on Thursday, May 15 at 4:00 PM for the session titled: \n “Running Nextflow on Microsoft Azure: Selecting Executors and Infrastructure Components” \n Presented by Wolfgang De Salvador, Venkat Malladi, and Jer-Ming Chia, this session offers a comprehensive overview of running Nextflow workflows in the cloud. It will explore the range of executor options available—including traditional schedulers, batch-managed services, and Kubernetes—as well as storage solutions spanning from file-based to object-based systems. \n \n This is a must-attend session for anyone looking to optimize infrastructure and boost performance for their Nextflow workflows on Azure. \n \n To register for Nextflow Summit Boston 2025 and access recordings after the event, visit the official Nextflow Summit website. 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Microsoft sessions are now available on demand and here are highlights from our time at GTC 2025. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":199},"postTime":"2025-04-03T12:55:44.179-07:00","lastPublishTime":"2025-04-03T12:55:44.179-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" It was great to see you at the NVIDIA GTC AI Conference in San Jose, CA March 17 - 21! We hope you enjoyed Microsoft's social events and that our sessions and demos were informative and will help you on your AI transformation journey. \n Microsoft sessions are now available on demand and here are highlights from our time at GTC 2025. \n Microsoft announcements \n Together, Microsoft and NVIDIA are accelerating some of the most groundbreaking innovations in AI. This long-standing collaboration has been at the core of the AI revolution over the past few years, from bringing industry-leading supercomputing performance in the cloud to supporting breakthrough frontier models and solutions like ChatGPT in Microsoft Azure OpenAI Service and Microsoft Copilot. \n There are several new announcements from Microsoft and NVIDIA that further enhance the full stack collaboration to help shape the future of AI. This includes integrating the newest NVIDIA Blackwell platform with Azure AI services infrastructure, incorporating NVIDIA NIM microservices into Azure AI Foundry, and empowering developers, startups, and organizations of all sizes like NBA, BMW, Dentsu, Harvey and OriGen, to accelerate their innovations and solve the most challenging problems across domains. \n Read blog for full details: Microsoft and NVIDIA accelerate AI development and performance \n GTC Keynote \n NVIDIA CEO Jensen Huang highlighted Microsoft and NVIDIA's long-standing collaboration during his GTC keynote. \n \n Microsoft sessions on demand \n Get to know Azure’s end-to-end AI platform and learn how to innovate fast with the broadest choice in models and pre-trained AI services, comprehensive GenAIOps tools and the most scalable and performance infrastructure. Watch Microsoft talks and panels on demand. \n \n Build and run next generation AI on Azure’s proven AI Infrastructure platform \n Accelerate AI Innovation with NVIDIA and Azure AI Foundry \n AI Inferencing using NIM with Serverless GPUs \n Unlock AI Potential with Azure Infrastructure: Innovations, Best Practices \n Quantum Computing: Where We Are and Where We're Headed \n Building a 3D image-based search system for medical image \n GPU DiskANN: Accelerating Microsoft Vector Search with NVIDIA cuVS \n Accelerating AI Pipelines: How NVIDIA Tools Boost Bing Visual Search Efficiency \n Physical AI for the Next Frontier of Industrial Digitalization \n Wired for AI: Lessons from Networking 100K+ GPU AI Data Centers and Clouds \n Harnessing AI Agents for Enterprise Success: insights from AI Experts \n Build Secure and Scalable GenAI Applications with Databases and NVIDIA AI \n Explore AI-Assisted Developer Tools for Accelerated Computing App Development \n \n Live from GTC interview \n Learn about the latest in Azure AI advancements in this VentureBeat interview with Nidhi Chappell, VP of Azure AI and HPC Infrastructure. \n \n Learn more about Azure AI \n We look forward the next NVIDIA GTC AI Conference and hope we'll see you at Microsoft Buildin Seattle and online May 19 - 22. \n Explore Azure AI solutions \n Power your AI with Azure AI infrastructure ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"3144","kudosSumWeight":0,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzk4MzIyLW1Sdm54Mg?revision=18\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzk4MzIyLXZVZm5TeA?revision=18\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDM","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzk4MzIyLVdaVzZZbA?revision=18\"}"}}],"totalCount":3,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[{"__typename":"VideoEdge","cursor":"MHxodHRwczovL3lvdXR1LmJlL193YVB2T3dMOVo4P2xpc3Q9VExHR2I0eEVxdDFwQ3lrd01UQTBNakF5TlEvMTc0MzQ2NjIyNzE5MnwwfDI1OzI1fHw","node":{"__typename":"AssociatedVideo","videoTag":{"__typename":"VideoTag","vid":"https://youtu.be/_waPvOwL9Z8?list=TLGGb4xEqt1pCykwMTA0MjAyNQ/1743466227192","thumbnail":"https://i.ytimg.com/vi/_waPvOwL9Z8/hqdefault.jpg","uploading":false,"height":240,"width":320,"title":null},"videoAssociationType":"INLINE_BODY"}}],"totalCount":1,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":{"__typename":"UploadedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzk4MzIyLW1Sdm54Mg?revision=18"},"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4394575":{"__typename":"Conversation","id":"conversation:4394575","topic":{"__typename":"BlogTopicMessage","uid":4394575},"lastPostingActivityTime":"2025-03-19T12:26:53.147-07:00","solved":false},"User:user:199777":{"__typename":"User","uid":199777,"login":"MattVegas1","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/dS0xOTk3NzctN3hlOHJh?image-coordinates=0%2C0%2C800%2C800"},"id":"user:199777"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzk0NTc1LWRjOW9TNg?revision=8\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00Mzk0NTc1LWRjOW9TNg?revision=8","title":"Screenshot 2025-03-18 091137.png","associationType":"COVER","width":2265,"height":1011,"altText":""},"BlogTopicMessage:message:4394575":{"__typename":"BlogTopicMessage","subject":"Accelerating the Intelligence Age with Azure AI Infrastructure and the GA of ND GB200 v6","conversation":{"__ref":"Conversation:conversation:4394575"},"id":"message:4394575","revisionNum":8,"uid":4394575,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:199777"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" Today we are thrilled to announce the General Availability of Azure's latest AI infrastructure Virtual Machines, the ND GB200 v6. ","introduction":"By Matt Vegas, Principal Product Manager, Microsoft Azure","metrics":{"__typename":"MessageMetrics","views":2865},"postTime":"2025-03-18T13:00:38.017-07:00","lastPublishTime":"2025-03-19T12:26:53.147-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Today we are thrilled to announce the General Availability of Azure's latest AI infrastructure Virtual Machines, the ND GB200 v6. Azure is proud to be one of the first cloud service provider to launch a 4,000 NVIDIA GB200 Grace Blackwell powered supercomputing cluster for training state of the art models and accelerating production AI inference deployments at scale. These cutting-edge VMs, accelerated by NVIDIA Blackwell platform, represent the next frontier in AI supercomputing. \n AI reasoning models and Agentic AI — systems capable of critical thinking, problem solving, and task execution — are coevolving at an exponential rate and revolutionizing the ways organizations operate. From AI research labs on the frontier of AI algorithmic development to organizations that have adopted AI tools in their daily operations – we are leading an AI platform shift that requires infrastructure that delivers performance, cost-efficiency, reliability, and near instantaneous response time. \n This latest generation of AI supercomputer marks a quantum leap in hardware and infrastructure that will deliver unprecedented improvements in application performance for AI training and inferencing. They leverage a new rack-scale architecture that enables up to 72 Blackwell GPUs to act like a single exa-scale computer and liquid cooling in the datacenter to optimize performance and rack density. Furthermore, NVIDIA GB200 Grace Blackwell Superchips that connect ARM based NVIDIA Grace CPU with two NVIDIA Blackwell GPUs, with new high bandwidth NVIDIA NVLink-C2C interconnect; means the system is designed to deliver the next generation of AI and frontier models. \n \"As we push the boundaries of AI, our partnership with Azure and the introduction of the NVIDIA Blackwell platform represent a significant leap forward,\" said Ian Buck, Vice President of Hyperscale and HPC at NVIDIA. \"The NVIDIA GB200 NVL72, with its unparalleled performance and connectivity, tackles the most complex AI workloads, enabling businesses to innovate faster and more securely. By integrating this technology with Azure's secure infrastructure, we are unlocking the potential of reasoning AI.\" \n Microsoft Azure has also successfully proven the performance across these new AI supercomputing clusters and is pleased to share that using the LLAMA 70B model on the NVIDIA GB200 NVL72 on Azure, we can generate over 860,000 tokens/sec of throughput, a 9x increase per rack compared to last gen ND H100 v5 VMs. \n The next frontier of AI supercomputing - Azure launches ND GB200 v6 Virtual Machine Series: \n Today marks the general availability of our Azure ND GB200 v6 Virtual Machine (VM), powered by NVIDIA GB200 NVL72, that connects 36 Grace CPUs and 72 Blackwell GPUs into a single 72-GPU NVLink domain. This rack-scale system acts like a single massive exa-scale GPU delivering application performance gains and step function architectural improvements that are required to train and host the next generation of reasoning models, AI agents, and LLMs. \n \n NVIDIA Blackwell GPUs: The NVIDIA Blackwell architecture introduces the largest GPU ever built with 2.5x the transistors of Hopper GPUs, a new 2 nd generation transformer engine, and new FP4 datatype. It includes new HBM3e GPU memory with a 36% increase in High Bandwidth Memory (HBM) with 192GB and a 67% increase in HBM capacity with 8 TB/s per GPU compared to previous generation of Azure ND H200 v5 VMs. \n NVIDIA Grace CPU Superchip: High performance and power efficient Arm® Neoverse™ V2 cores connected with two Blackwell GPUs via the NVIDIA NVLink-C2C interface enabling high bandwidth access to CPU memory for checkpointing and offloading. \n 400 Gb/s dedicated bandwidth to each GPU with NVIDIA Quantum-2 InfiniBand networking with 1.6Tb/s per VM, and 28.8Tb/s per GB200 NVL72 hyper-computer in a non-blocking fat-tree network scaling to hundreds of thousands of GPUs. \n NVIDIA GB200 NVL72: Fifth generation NVLink with 1.8 TB/s per GPU of bidirectional bandwidth (2x Hopper), connecting 72 Blackwell GPUs per rack, enabling the system to operate as a single 72-GPU NVLink domain. This 72 GPU rack scale system comprised of groups of 18 compute nodes with NVIDIA GB200 Grace Blackwell Superchips delivers up to 1.4 Exa-FLOPS of FP4 Tensor Core throughput, 13.5 TB of shared high bandwidth memory, 130TB/s of cross sectional NVLink bandwidth, and 28.8Tb/s scale-out networking. \n \n To support the massive data demands of AI training and inferencing, the ND GB200 v6 is complemented by Azure Blob Storage, which provides exabytes of capacity and terabits of throughput. This ensures seamless access to the vast datasets needed to feed billion- or trillion-parameter models, empowering organizations to push the boundaries of AI without data bottlenecks. \n Customer momentum continues: \n Today we are working with some of the leading AI innovators to support their AI infrastructure needs, including Black Forest Labs. \n \"We are expanding our partnership with Microsoft Azure to combine BFL's unique research expertise in generative AI with Azure's powerful infrastructure. This collaboration enables us to build and deliver the best possible image and video models faster and at greater scale, providing our customers with state-of-the-art visual AI capabilities for media production, advertising, product design, content creation and beyond.\" - Robin Rombach, CEO \n End-to-end AI on Azure: \n Our software suite of Azure services and tools ensures that our customers can harness the true potential of Azure GB200 VMs to build, deploy and run AI workloads at scale to accelerate innovation while maintaining cost and resource efficiency. \n With Azure CycleCloud and Azure Batch, organizations can quickly set up and manage their AI training environments, focusing on innovation and achieving their business goals. Azure CycleCloud simplifies the management of HPC/AI environments, allowing users to set up clusters and adjust resources dynamically to meet workload demands. It integrates leading job schedulers and filesystems seamlessly with Azure's infrastructure, supporting a range of AI training workloads. Our groundbreaking Azure CycleCloud Workspace for Slurm allows users to effortlessly create, configure, and deploy pre-defined Slurm clusters with CycleCloud on Azure, all without requiring any prior knowledge of Azure or Slurm. \n Azure Batch enables large-scale parallel computing, handling thousands to millions of tasks per job and supporting containerized workloads. These platforms provide the tools and capabilities to efficiently scale AI training processes, letting organizations concentrate on core research and business objectives. \n With Kubernetes’ increasing popularity as a framework for running cloud native AI workloads, Azure Kubernetes Service offers an excellent choice for rapid deployment of Kubernetes clusters and management of containerized AI workloads at scale. We are building platform-specific optimizations including enhanced observability that will ensure that our customers have the reliability and performance necessary for running large scale AI workloads. \n Whether you are deploying Kubernetes or your own custom stack, Azure offers an integrated set of services and tools necessary for you to manage AI workloads at scale with high efficiency and reliability, maximizing the true potential of the GB200 infrastructure. \n Continued Partnership of Innovation with NVIDA: \n Leveraging our momentum on NVIDIA GB200 along with decades of building world class supercomputers, we are committed to always bring the latest NVIDIA platforms, including the newly announced NVIDIA GB300 NVL72, based on the NVIDIA Blackwell Ultra architecture, to the cloud, so stay tuned for more announcements like this at GTC from NVIDIA. \n Learn more: \n For more information and to request access to Microsoft's latest Virtual Machines for AI workloads, please register here. \n Learn more from our post on unpacking the performance of Microsoft Azure ND GB200 v6 Virtual Machines and how you can get started with our benchmarking guide. \n \n \n \n \n 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line.png","associationType":"BODY","width":2905,"height":2,"altText":""},"BlogTopicMessage:message:4386895":{"__typename":"BlogTopicMessage","subject":"Daily schedule: Microsoft in-booth sessions at NVIDIA GTC","conversation":{"__ref":"Conversation:conversation:4386895"},"id":"message:4386895","revisionNum":41,"uid":4386895,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:2105970"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n \n Visit Microsoft booth #514 at the NVIDIA GTC AI Conference for live information session from Azure, partner and customer AI experts. Read on for our daily schedule. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":1483},"postTime":"2025-03-06T08:28:51.462-08:00","lastPublishTime":"2025-03-19T09:48:10.091-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" We look forward to seeing you at the NVIDIA GTC AI Conference March 17 - 21 in San Jose, CA or virtually. Visit Microsoft booth #514 for daily informative sessions from Azure, partner and customer AI experts and discover the latest in AI services and technology that can help power your AI innovation. \n This blog post provides our daily in-booth sessions schedule. For Microsoft sessions in the GTC main conference program and our full presence at GTC, see Innovation starts here! Join Microsoft at NVIDIA GTC AI Conference. \n Live sessions in Microsoft booth #514 \n Mark your calendar and visit booth #514 to attend the below sessions. We'll be adding more sessions before March 17th, be sure to check back for the latest schedule. \n Tuesday, March 18 \n \n 1:40 pm - 2:00 pm PDT | March 18 \n Behind the scenes of building Azure AI infrastructure. Azure is leading innovation in systems design for next-generation AI hardware platforms, including NVIDIA's Blackwell. This presentation highlights the hardware systems at the foundation of Azure's advanced AI infrastructure. We'll discuss deployment of NVIDIA GPUs, Quantum-2 InfiniBand for high-speed interconnects, and advanced cooling solutions to ensure a sustainable and scalable foundation for systems development. Presenters: Akshat Nanda, Principal AI Hardware Product Manager, Microsoft \n \n 2:00 pm - 2:20 pm PDT | March 18 \n Navigating the Expanding Landscape of Large Language Models: Strategies for Optimal Model Selection in Azure AI Foundry. This session explores the evolving LLM landscape, offering insights on evaluating and selecting models for various applications. Attendees will learn key selection criteria, including performance metrics, Azure AI Foundry tools, and use case alignment. The goal is to equip participants with the knowledge to navigate the LLM ecosystem effectively and make informed AI decisions.  Presenters: Sharmila Chockalingam, Sr. Product Marketing Manager, Microsoft \n \n 2:30 pm - 2:50 pm PDT | March 18 \n Accelerate AI Inferencing using NIMs with Serverless GPUs. Discover the newest updates in NIMs and how serverless GPUs enable developers to streamline the deployment and management of AI solutions. Learn about the benefits of using serverless compute for custom model inferencing, and how to leverage Azure's serverless containers platform, Azure Container Apps, for building AI apps and agents.  Presenters: Cary Chai, Product Manager, Microsoft Azure Container Apps; Harry Li, Software Engineer, Microsoft Azure Container Apps \n \n 3:00 pm - 3:20 pm PDT | March 18 \n Software-Defined Factory: The New Frontier for Supply Chain and Manufacturing with NVIDIA Omniverse on Azure. As industries accelerate toward a software-defined future, AI-powered simulation is redefining product design and factory automation. With NVIDIA Omniverse on Azure, businesses can seamlessly integrate real-time collaboration, digital twins, and generative AI to drive efficiency, innovation, and scalability. Learn how enterprises are using advanced simulation to streamline manufacturing, enhance product lifecycles, and create next-generation consumer interactions. Presenters: Prasad Satyavol, Lead, Manufacturing Americas, Accenture \n \n 3:30 pm - 3:50 pm PDT | March 18 \n Catalysts: How Pangaea Data uses Azure AI Foundry to transform rare disease detection. Learn how Pangaea Data leverages AI to identify patients with rare diseases and aids in identifying candidates for clinical trials. Discover how Pangaea uses Azure Virtual Machines and Azure AI Services accelerated by NVIDIA GPUs to enhance the accuracy and speed of rare disease detection through advanced data analysis and privacy-compliant methodologies. Presenters: Abby Hamilton, Product Marketing Manager, AI for Science, Microsoft; Dr. Vibhor Gupta Founder, Pangaea Data \n \n 4:00 pm - 4:20 pm PDT | March 18 \n Agentic AI Orchestration Platform Powered by NVIDIA NIM and Microsoft Azure AI. This session highlights how to streamline autonomous AI pipelines using Azure’s compute, storage, and AI Studio’s MaaS, combined with NVIDIA’s GPU-accelerated inference. Discover how these technologies enable intelligent, efficient, and scalable AI solutions—designed for fast deployment, seamless integration, and enterprise-grade performance across cloud-native environments. Presenters: Shlomi Avigdor, Chief Product Officer, Dataloop \n \n 4:30 pm - 4:50 pm PDT | March 18 \n Small language model Inferencing for RAG applications --> Deploy DeepSeek R1 on Microsoft Azure PCIe H100 Infrastructure. Learn how to deploy models like DeepSeek R1 from the model catalog in Azure AI Foundry for cost optimized inferencing for your small language model and RAG applications. . Presenters: Rishab Verma, Senior Product Manager, HPC and AI Infrastructure, Microsoft \n \n 5:00 pm - 5:20 pm PDT | March 18 \n Introduction to Azure confidential GPUs and Azure AI confidential inferencing Discover Azure's industry-first confidential GPUs in the public cloud: the Azure NCC H100 v5 confidential VMs with NVIDIA H100 Tensor Core GPUs, generally available since September 2024. Explore the preview of Confidential inference for the Azure OpenAI Service Whisper model for speech to text transcription and learn how these innovations are setting new standards in secure and confidential AI. Presenters: Krishnaprasad Hande, Senior Technical Program Manager, Microsoft Azure Confidential Computing \n \n 5:30 pm - 5:50 pm PDT | March 18 \n Ansys, Microsoft & NVIDIA: Accelerating Innovation in Mobility Learn how Ansys’ industry-leading simulation tools, enhanced by NVIDIA and Microsoft Azure, are empowering automakers to streamline engineering workflows, optimize designs, and accelerate the development of next-generation vehicles. In this session we'll explore: AI-enhanced predictive modeling, seamless integration with NVIDIA Omniverse, cloud-based scalability with Microsoft Azure, and automation of complex analyses Presenters: Tony Karam Global Sales Director, Ansys \n \n 6:00 pm - 6:20 pm PDT | March 18 \n Pushing the boundaries of product design through AI with Azure and Neural Concept. During this session, you will learn how large engineering companies are leveraging AI and Microsoft Azure infrastructure to drastically speed up R&D cycles, and improve product performance, leading to massive competitiveness gains. . Presenters: Thomas von Tschammer, Co-founder and Managing Director US, Neural Concepts \n Wednesday, March 19 \n \n 12:00 pm - 12:20 pm PDT | March 19 \n Basecamp Research pushes scientific boundaries using Azure AI Foundry at the ends of the earth. Discover how Basecamp Research uses AI to create the world's largest biological database and learn how Basecamp leverages Azure Virtual Machines and Azure AI Services accelerated by NVIDIA GPUs to analyze and interpret complex biological data. This leads to the discovery of novel enzymes and proteins with potential applications in drug discovery and synthetic biology, driving groundbreaking scientific discoveries from remote locations and harnessing cutting-edge AI technologies to push the boundaries of bioscience. Presenters: Abby Hamilton, Product Marketing Manager, AI for Science, Microsoft; Gus Minto-Cowcher, Platform Engineering Lead, Basecamp Research \n \n 12:30 pm - 12:50 pm PDT | March 19 \n Measuring What Matters: Azure, GitHub Copilot, AI, and Engineering Transformation Join Faros AI at our theater session, where we’ll share how enterprises can maximize the impact of AI-powered development. We’ll cover real-world strategies to measure AI adoption, demonstrate its impact on engineering efficiency, and prevent bottlenecks in developer workflows. See our platform in action through a live demo, showcasing how data-driven insights can accelerate AI adoption at scale. Presenters: Shubha Nabar, Co-Founder, Faros AI \n \n 1:00 pm - 1:20 pm PDT | March 19 \n Build Generative AI models with NVIDIA NeMo on Azure and NVIDIA DGX Cloud Learn to build, customize, and deploy multimodal generative AI models with NVIDIA NeMo on Azure. This session covers state-of-the-art NeMo models, from billions to trillions of parameters, including Nemotron, PaxML, and LLAMA. Explore training, fine-tuning, and Azure's optimizations for on-premises performance in the cloud. Presenters: Hugo Affaticati, Cloud Infrastructure Engineer, Microsoft; Miro Enev, Solution Architect Manager & Principal Engineer, NVIDIA \n \n 1:30 pm - 1:50 pm PDT | March 19 \n Unify teams, sites, and systems with Azure’s adaptive cloud approach Learn to build, deploy, scale, and manage modern and critical workloads (including AI applications) from cloud to edge with Microsoft’s adaptive cloud approach. Understand how this innovative approach differentiates Azure for customers in their hybrid and multicloud journey. Presenters: Earl Valencia, Senior Product Marketing Manager, Microsoft; Julie Wang, Product Marketing Manager, Microsoft \n \n 2:00 pm - 2:20 pm PDT | March 19 \n Build Secure and Scalable Gen AI Applications with Azure Databases and NVIDIA AI Learn how to build secure and scalable Generative AI (GenAI) applications by integrating Azure Databases, SQL Server, and NVIDIA AI, how GPUs optimize AI workloads and how databases enhance AI pipelines. We’ll discuss best practices for enterprise-grade security, managing AI workloads at scale, and leveraging hybrid AI deployments and provide insights into future advancements. Presenters: Bob Ward, Principal Architect and Muazma Zahid, Data and AI Leader, Microsoft \n \n 2:30 pm - 2:50 pm PDT | March 19 \n Accelerating Snorkel AIML Research on Azure AI Infrastructure powered by NVIDIA GPUs. Snorkel researchers have contributed to over 170 papers on topics ranging from zero-shot robustification to enterprise alignment to fine-grained LLM evaluation. Join this session to learn how Snorkel is using reward model tuning to harness LLMs for high-level reasoning for agenitic systems and how designing projects on Azure AI infrastructure powered by NVIDIA GPUs helps Snorkel researchers deliver value for our customers and the OSS community even faster. Presenters: Ramya Ramakrishnan, Staff Applied Research Scientist, Snorkel AI \n \n 3:00 pm - 3:20 pm PDT | March 19 \n Evolution of AI: From AlphaGo to Agentic and Physical AI, all powered by Azure The AI journey that was sparked from a single move on a Go board to the emergence of agentic and physical AI underscores the incredible potential of AI to innovate, transform industries, and elevate human capabilities. Come learn how NVIDIA and Microsoft Azure are powering the next generation of AI capabilities through the entire AI stack from infrastructure to applications. \n Presenters: John Lee, Principal Program Manager, Microsoft \n \n 3:30 pm - 3:50 pm PDT | March 19 \n Innovating with AI Physics: Driving Breakthroughs in Engineering with NVIDIA and Microsoft Azure. Engineering and scientific teams are revolutionizing product design with AI-driven physics simulations across industries, from life sciences to aerospace. Join Rescale to explore real-world breakthroughs—from cardiovascular CFD to turbomachinery flows. See AI Physics on the Rescale platform, powered by NVIDIA and Microsoft Azure, in action. Watch a live demo showcasing GM Motosports seamless AI-driven simulations. Presenters: Madhu Vellakal, Solutions Engineering Manager, Rescale \n \n 4:00 pm - 4:20 pm PDT | March 19 \n Managed Deployments for AI Workloads on Azure Nvidia GPU VMs with Azure CycleCloud and CycleCloud Workspace. Discover how to efficiently manage and deploy AI workloads in Azure using Azure CycleCloud and CycleCloud Workspace for Slurm on Azure Nvidia GPU VMs. This session will cover how to deploy HPC environments at scale with CycleCloud, leveraging Slurm for workload management, and the benefits of using Azure Nvidia GPU VMs for AI deployments. Learn best practices, real-world use cases, and gain insights into optimizing your AI infrastructure for performance and scalability. Presenters: Param Shah, Technical Program Manager, Microsoft HPC & AI \n \n 4:30 pm - 4:50 pm PDT | March 19 \n Solving the Unsolvable with LLMs that Reason—Powered by Azure AI Foundry & NVIDIA The next wave of AI is here—models that don’t just generate, but reason, plan, and solve. With OpenAI’s O-series, DeepSeek’s R1, and other cutting-edge models, enterprises can tackle complex decision-making, strategic problem-solving, and AI-driven autonomy. Join this live demo session to see how Azure OpenAI Service and Azure AI Foundry empower developers to test, compare, and deploy these next-gen models at scale. Presenters: Andy Beatman, Director, Product Marketing, Microsoft Azure AI Foundry \n \n 5:00 pm - 5:20 pm PDT | March 19 \n The Power of horizontal intelligence in a Omniverse on Azure Digital Twin World Traditional data models create silos, limiting collaboration and efficiency. With 3D digital twins, organizations can enable Horizontal Intelligence. Explore how integrating real-time operational and enterprise data in a Omniverse on Azure environment fosters better decision-making, predictive insights, and cross-functional collaboration. Presenters: Pratap Gulabrao, Vice President - Industry Solutions Lead, Celebal Technologies \n \n 5:30 pm - 5:50 pm PDT | March 19 \n Enabling Trustworthy AI with Microsoft Azure AI Foundry and Azure OpenAI Service At Microsoft, we believe AI should be powerful, responsible, and secure. Discover the latest trust and safety innovations across Azure AI Foundry, Azure OpenAI Service, and Microsoft Copilot - designed to help enterprises deploy AI with privacy, security, and governance from the start. See live demos of enterprise safety controls, content filtering, and compliance features. This session will equip you with the tools to build and deploy AI you can trust. Presenters: Andy Beatman, Director, Product Marketing, Microsoft Azure AI Foundry \n \n 6:00 pm - 6:20 pm PDT | March 19 \n Using Robotic Automation Insights to Revolutionize Server and GPU design with Omniverse Kit App Streaming on Microsoft Azure. Supercharge Server and GPU design & assembly for higher yields through robotic automation. Learn how Bright Machines is delivering Design for Automated Assembly (DFAA) and Digital Twin solutions enabled by Omniverse Kit App Streaming (OKAS) and Microsoft Azure. Presenters: Hari Ramachandran, VP Product, Bright Machines; Sashank Ganti, Principal Product Manager, Bright Machines \n Thursday, March 20 \n \n 12:00 pm - 12:20 pm PDT | March 20 \n Accelerating AI Innovation with NVIDIA Inference Microservices on Azure AI Foundry Discover how NVIDIA and Microsoft Azure are transforming AI deployments with NVIDIA Inference Microservices (NVIDIA NIM) on Azure AI Foundry. Learn how NVIDIA NIM simplifies deployment of foundation models across diverse AI use cases, leveraging Azure’s NVIDIA GPU-accelerated infrastructure for unmatched performance, scalability, and reduced TCO. Presenters: Rajesh Vasireddy, Director, Partner Tech Strategy, NVIDIA; Raj Nemani, Director, Partner Tech Strategy NVIDIA \n \n 12:30 pm - 12:50 pm PDT | March 20 \n Accelerating Medical Innovation with an End-to-End Imaging and Video Data Management Platform on Azure. Discover how Flywheel’s end-to-end imaging and video data management platform, powered by NVIDIA GPUs and Microsoft Azure, enables Pharmaceutical, Medical-Device, and Healthcare organizations to accelerate innovation. See firsthand how Flywheel’s cloud-native, modular architecture streamlines ingestion, curation, and analysis of complex datasets—transforming raw images into analysis-ready data for multi-center studies, AI model training, clinical trials, and translational research while ensuring regulatory compliance and operational efficiency. Presenters: Dan Rafter, MD, Flywheel \n \n 1:00 pm - 1:20 pm PDT | March 20 \n Transform Product Design with Cloud-Based NX X and AI using Azure HPC and NVIDIA GPUs. In this session you'll learn about Siemens NX on Azure Virtual Desktop, integrated with NVIDIA GPUs, Azure Nvidia NV series Machines, and Microsoft AI capabilities, offer customers enhanced collaboration, design efficiency, increased security, and significant cost savings. With the help of multi-session capability, you can now experience GPU-accelerated performance. In this session, we'll introduce Siemens' SaaS offering, NX X, now powered by copilot, featuring automated coding and proactive problem solving. Presenters: Taylor Anderson Director, NX Product Management, Siemens \n \n 1:30 pm - 1:50 pm PDT | March 20 \n Transforming Scientific Workflows with Generative AI on Azure Batch and NVIDIA GPUs This session will showcase the automated execution of a genomics workflow representing a complex genetic variant analysis pipeline on Azure Batch, as well as an AI-powered assistant tool developed on NVIDIA GPUs highlighting how AI enhances research precision, speed, and operational excellence. Whether you're a researcher, practitioner, or AI industry expert, this session is essential for anyone looking to transform and make their scientific workflows more efficient. Presenters: Seetha Subramanium, Senior Product Manager, Microsoft \n \n 2:00 pm - 2:20 pm PDT | March 20 \n Mastering Model Customization: Fine-Tuning Azure OpenAI Service Models with Weights & Biases. As businesses increasingly seek AI models tailored to their unique needs, fine-tuning Large Language Models (LLMs) has emerged as a powerful customization strategy—enhancing accuracy, efficiency, and domain relevance. Learn how fine-tuning such as hyperparameter tuning, model evaluation, and performance monitoring can ensure optimal results. Presenters: Anish Shah, AI Solutions Engineer, Weights and Biases \n \n 2:30 pm - 2:50 pm PDT | March 20 \n From Dribble to Deluge: Supercharging AI with WEKA’s Game-Changing Architecture on Azure. In the era of AI reasoning and agents, data infrastructure bottlenecks are holding back innovation. Enter the WEKA Data Platform, a high-performance, scalable storage system, optimized for AI in Azure. Join us for a demonstration of the performance and scale WEKA provides for your AI workloads in Azure. We’ll dive into WEKA capabilities to provide sub-millisecond latency and high throughput at petabyte scale, bridging the gap between compute performance and data storage. These capabilities are critical to the success of next-generation infrastructure deployments supporting AI model training, tuning and inference. Presenters: Sheen Austin, Sr Director of AI Platforms, Weka.IO \n \n 4:00 pm - 4:20 pm PDT | March 20 \n Microsoft for Startups & NVIDIA Inception: Identifying and Supporting the World's Best Startups. RAG systems depend on contextually relevant data. But how do you make sure that the data you're using is always relevant? Join Pinecone to discuss vector retrieval plus reranking models and how using them together will boost the reliability and effectiveness of your RAG application. Presenters: Cory Waddingham, Staff Partner Engineer, Pinecone \n \n 4:30 pm - 4:50 pm PDT | March 20 \n Introducing Azure NetApp Files (ANF) for AI Azure NetApp Files (ANF) is a high-performance file storage service by Microsoft, integrated with NetApp technology. Dive into how it's new GenAI Toolkit seamlessly integrated with Azure OpenAI Service models, simplifies GenAI services deployment, enhances LLM accuracy, and facilitates retrieval-augmented generation (RAG) for precise outputs by leveraging proprietary data stored in ANF for superior inference capabilities and business continuity. Presenters: Andy Chan, Principal Product Manager, Azure Netapp Files HPC/EDA, NetApp \n \n 5:30 pm - 5:50 pm PDT | March 20 \n Building Competitive Advantage in Automotive with A2MAC1 on Microsoft Azure This session explores how automotive OEMs and suppliers can gain a competitive edge by leveraging the A2MAC1 Solutions Platform on Microsoft Azure. It highlights the latest advancements in automated costing and CO2 management, the productivity and outcome improvements driven by benchmarking copilot and virtual benchmarking, and the value of next-generation market insights in discovering and understanding the latest innovations and trends in the automotive industry. Presenters: Timothy Kiester, Customer Engagement Manager, A2MAC1 \n \n 6:00 pm - 6:20 pm PDT | March 20 \n Beyond Vibe Checks: Building Reliable GenAI with an Eval-First Approach In this session, you will learn how to move beyond intuition-based “vibe checks” toward a structured Eval-First approach, enabling you to build reliable, trustworthy, and scalable generative AI applications. Discover how embedding automated evaluations early and consistently across your development lifecycle helps avoid costly mistakes, accelerates deployment, and aligns AI outputs more closely with business goals and user expectations. Presenters: Roie Schwaber-Cohen, Principal Developer Advocate, Galileo \n Microsoft Azure at NVIDIA GTC \n We look forward to seeing you at the NVIDIA GTC AI Conference. Visit our Innovation starts here! Join Microsoft at NVIDIA GTC AI Conference blog post to learn how to engage with Microsoft Azure at GTC and discover Azure's end-to-end platform for AI innovation. \n \n #AzureGTC25 #AzureAI 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the Performance of Microsoft Azure ND GB200 v6 Virtual Machines","conversation":{"__ref":"Conversation:conversation:4390442"},"id":"message:4390442","revisionNum":6,"uid":4390442,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:1467620"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":"","introduction":"As AI workloads continue to push the boundaries of computing, the NVIDIA GB200 NVL72 stands at the forefront of high-performance acceleration. By examining the foundational metrics, we provide insights into how Azure’s infrastructure optimally supports AI training and inference workloads. Thus, in this deep dive, we analyze the performance of Azure’s ND GB200 v6 Virtual Machines one component at a time using Azure microbenchmarks. Whether you’re fine-tuning deep learning models or scaling enterprise workloads, this analysis will help you understand what to expect from the NVIDIA GB200 Superchip on Azure. ","metrics":{"__typename":"MessageMetrics","views":1200},"postTime":"2025-03-17T10:03:16.674-07:00","lastPublishTime":"2025-03-18T21:12:20.402-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" For a comprehensive understanding of our benchmarking methodologies and detailed performance results, please refer to our benchmarking guide available on the official Azure GitHub repository: Azure AI Benchmarking Guide. \n Breakdown of Benchmark Tests \n GEMM Performance \n General Matrix Multiply (GEMM) operations form the backbone of AI models. We measured that more than 60% of the time spent inferencing or training an AI model is spent doing matrix multiplication. Thus, measuring their speed is key to understand the performance of a GPU-based virtual machine. Azure benchmark assesses matrix-to-matrix multiplication efficiency using NVIDIA’s CuBLASLt library with FP8 precision, ensuring results reflect enterprise AI workloads. We measured the peak theoretical performance of the NVIDIA GB200 Blackwell GPU to be 4,856 TFLOPS, representing a 2.45x increase in performance compared to peak theoretical 1,979 TFLOPS on the NVIDIA H100 GPU. This finding is in-line with NVIDIA’s announcement of a 2.5x performance increase at GTC 2024. \n The true performance gain of the NVIDIA GB200 Blackwell GPU over its predecessors emerges in real-life conditions. For example, using 10,000 warm-up iterations and randomly initialized matrices demonstrated a sustained 2,744 TFLOPS for FP8 workloads, which, while expectedly lower than the theoretical peak, is still double that of the H100. The impact of these improvements on real workloads indicates up to a 3x speedup on average for end-to-end training and inference workloads based on our early results. \n High-Bandwidth Memory (HBM) Bandwidth \n Memory bandwidth is the metric that governs data movements. Our benchmarks showed a peak memory bandwidth of 7.35 TB/s, achieving 92% of its theoretical peak of 7.9 TB/s. This efficiency mirrors that of the H100, which also operated close to its theoretical maximum, while reaching 2.5x faster data transfers. This speedup ensures that data-intensive tasks, such as training large-scale neural networks, are executed efficiently. \n NVBandwidth \n The ND GB200 v6 architecture significantly enhances AI workload performance with NVLink C2C, enabling a direct, high-speed connection between the GPU and host system. This design reduces latency and improves data transfer efficiency, making AI workloads faster and more scalable. \n Our NVBandwidth tests measured CPU-to-GPU and GPU-to-CPU transfer rates to be nearly 4× faster than the ND H100 v5. This improvement minimizes bottlenecks in data-intensive applications and optimizes data movement efficiency over previous GPU-powered virtual machines. In addition, it allows the GPU to readily access additional memory when needed, which can be quickly accessed via the C2C link. \n NCCL Bandwidth \n NVIDIA’s Collective Communications Library (NCCL) enables high-speed communication between GPUs within and across nodes. We built our tests to measure the speed of communication between GPUs over NVLink within one virtual machine. Hig-speed communication is instrumental as most enterprise workloads consist of large-scale distributed models. The ND GB200 v6’s NVLink achieved a bandwidth of approximately 680 GB/s, aligning with NVIDIA’s projections. \n Conclusion \n The ND GB200 v6 virtual machine, powered by the NVIDIA GB200 Blackwell GPUs, showcases substantial advancements in computational performance, memory bandwidth, and data transfer speeds compared to the previous generations of virtual machines. These improvements are pivotal for efficiently managing the increasing demands of AI workloads like generative and agentic use-cases. Following our Benchmarking Guide will provide early access to performance reviews of the innovations announced at GTC 2025, helping customers drive the next wave of AI on Azure’s purpose-built AI infrastructure. \n \n \n ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"3920","kudosSumWeight":1,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkwNDQyLVMyZWY2ag?revision=6\"}"}}],"totalCount":1,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":{"__typename":"UploadedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzkwNDQyLVMyZWY2ag?revision=6"},"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4372488":{"__typename":"Conversation","id":"conversation:4372488","topic":{"__typename":"BlogTopicMessage","uid":4372488},"lastPostingActivityTime":"2025-03-13T11:21:26.967-07:00","solved":false},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LW9GcDdoVQ?revision=99\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LW9GcDdoVQ?revision=99","title":"Tech Comm blog header_Azure GTC25.png","associationType":"COVER","width":806,"height":503,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LXBBTkF3dA?revision=99\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LXBBTkF3dA?revision=99","title":"Tech Comm blog header for main page.png","associationType":"TEASER","width":806,"height":503,"altText":""},"BlogTopicMessage:message:4372488":{"__typename":"BlogTopicMessage","subject":"Innovation starts here! Join Microsoft at NVIDIA GTC","conversation":{"__ref":"Conversation:conversation:4372488"},"id":"message:4372488","revisionNum":99,"uid":4372488,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:2105970"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Innovation starts here! Join Microsoft at the NVIDIA GTC AI Conference March 17 – 21 in San Jose, CA (or virtual) to explore the latest AI technology and solutions and discover Azure’s end-to-end AI platform. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":6630},"postTime":"2025-02-12T17:57:04.671-08:00","lastPublishTime":"2025-03-13T11:21:26.967-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Calling all AI innovators, champions, and pioneers... \n The impact of AI on businesses is profound and Microsoft is committed to helping every company, regardless of its size, and everyone, regardless of their role, leverage the full potential of AI to advance their business objectives. \n Join Microsoft at the NVIDIA GTC AI Conference March 17 – 21 in San Jose, CA (or virtual) to explore the latest AI technology and solutions and discover how Azure’s end-to-end AI platform can accelerate your AI innovation. From live Microsoft sessions to hands-on experiences and networking events, you can connect with and learn from Microsoft AI experts, partners, customers and your peers. \n Register today and Read on to schedule your time with us! \n _______________________________________________________________________________________________ \n Attend Microsoft talks and panels \n Get to know Azure’s end-to-end AI platform and learn how to innovate fast with the broadest choice in models and pre-trained AI services, comprehensive GenAIOps tools and the most scalable and performance infrastructure. Attend Microsoft talks and panels in the GTC main program. Click on session titles to add to your GTC schedule. \n Featured sessions \n S74600: Unlock AI Potential with Azure Infrastructure: Innovations, Best Practices Tuesday, March 18, on demand Kanchan Mehrotra, Group Technical Manager, Azure HPC & AI Kyle Esecson, Head of Commercial Strategy, Wayve \n S74606: Build and run next generation AI on Azure’s proven AI Infrastructure platform Wednesday, March 19, 10:00 AM - 10:40 AM Nidhi Chappell, Vice President and Head of AI infra for Azure; Omar Khan, VP, Azure Infrastructure Marketing \n S74611: Accelerate AI Innovation with NVIDIA and Azure AI Foundry Wednesday, March 19, 2:00 PM- 2:40 PM Mike Hulme, General Manager, Azure Digital and App Innovation \n S74603: AI Inferencing using NIM with Serverless GPUs Thursday, March 20, 9:00 AM - 9:40 AM Devanshi Joshi, Sr. Product Marketing Manager, Azure Digital Applications Harry Li, Software Engineer, Microsoft Cary Chai, Product Manager, Azure Digital Applications \n Quantum day \n S74495: Quantum Computing: Where We Are and Where We’re Headed Thursday, March 20 | 10:00 AM - 12:00 PM Jensen Huang, Founder and CEO, NVIDIA Krysta Svore, Technical Fellow, Microsoft and more... \n Talks and panels \n S72436: Building a 3D image-based search system for medical images Monday, March 17, 1:00 PM to 1:40 PM \n S72905: GPU DiskANN: Accelerating Microsoft Vector Search with NVIDIA cuVS Monday, March 17, 1:00 PM - 1:40 PM \n S71676: Accelerating AI Pipelines: How NVIDIA Tools Boost Bing Visual Search Efficiency Monday, March 17, 4:00 PM - 4:40 PM \n S73232: Physical AI for the Next Frontier of Industrial Digitalization Tuesday, March 18, 2:00 PM to 3:00 PM \n S71145: Wired for AI: Lessons from Networking 100K+ GPU AI Data Centers and Clouds Tuesday, March 18, 4:00 PM to 5:00 PM \n S72355: Harnessing AI Agents for Enterprise Success: insights from AI Experts Wednesday, March 19, 9:00 AM to 10:00 AM \n S71521: Build Secure and Scalable GenAI Applications with Databases and NVIDIA AI Thursday, March 20, 4:00 - 4:40 PM \n S72435: Explore AI-Assisted Developer Tools for Accelerated Computing App Development Friday, March 21, 9:00 AM- 10:00 AM \n Daily sessions in booth #514 \n Visit Microsoft booth #514 for daily live information sessions. See our daily schedule. \n Hands-on lab \n S72435: Connecting Industrial Data to Digital Twins with Microsoft Power BI, NVIDIA Omniverse, and OpenUSD Thursday, March 20, 1:00 PM- 2:45 PM \n Visit Microsoft booth #514 \n Come and experience the latest in Azure AI. Join live discussion sessions at Microsoft's in-booth theater, connect with Microsoft and partner AI experts, and try out the latest AI technology and hardware. Stop by Microsoft booth #514 daily to: \n \n Attend in-booth information sessions. \n Get hands-on with the latest AI solutions in our demo pods. \n Check our latest AI technology in our hardware bar. \n Take a break in our lounge area and enjoy free coffee served by Artly, the barista bot. \n Enter for a chance to win cool stuff! \n \n In-booth information sessions Dive deeper into Azure AI solutions and infrastructure. Attend daily informative sessions in our booth #514 with Azure, customer, and partner experts. See our daily schedule. \n Demo stations Get hands-on with the latest AI solutions from Microsoft Azure and partners. Visit booth #514 to experience: \n \n Azure AI Foundry \n Azure AI infrastructure \n NVIDIA on Azure \n Innovation with Azure startups \n \n Hardware bar Discover the latest AI technology and hardware from Microsoft and NVIDIA. Come by our hardware bar in booth #514. \n Get social \n Connect Microsoft executives and AI experts and your peers at our social events at GTC. Enjoy drinks, food and networking. Microsoft and NVIDIA will host an invitation-only AI Innovators Circle executive dinner and Automotive mixer Tuesday March 18; a Networking AI & Tech mixer and NVIDIA Quantum evening on Wednesday March 19; AI Exchange roundtable luncheons on March 19 and 20, and a The Innovators' Circle: Brunch for women in technology on Thursday, March 20. Contact your Microsoft representative to request an invitation these special events! Space is limited. \n Learn more about Azure AI \n Azure AI Platform—Cloud AI Platform \n Azure AI Infrastructure \n Microsoft for Startups #AzureGTC25 #AzureAI ","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})@stringLength":"5577","kudosSumWeight":1,"repliesCount":0,"readOnly":false,"images":{"__typename":"AssociatedImageConnection","edges":[{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDE","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LW9GcDdoVQ?revision=99\"}"}},{"__typename":"AssociatedImageEdge","cursor":"MjUuM3wyLjF8b3wyNXxfTlZffDI","node":{"__ref":"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LXBBTkF3dA?revision=99\"}"}}],"totalCount":2,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"videos":{"__typename":"VideoConnection","edges":[],"totalCount":0,"pageInfo":{"__typename":"PageInfo","hasNextPage":false,"endCursor":null,"hasPreviousPage":false,"startCursor":null}},"coverImage":{"__typename":"UploadedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MzcyNDg4LW9GcDdoVQ?revision=99"},"coverImageProperties":{"__typename":"CoverImageProperties","style":"STANDARD","titlePosition":"BOTTOM","altText":""}},"Conversation:conversation:4235774":{"__typename":"Conversation","id":"conversation:4235774","topic":{"__typename":"BlogTopicMessage","uid":4235774},"lastPostingActivityTime":"2024-11-19T15:42:51.915-08:00","solved":false},"User:user:565461":{"__typename":"User","uid":565461,"login":"Michelle_R","registrationData":{"__typename":"RegistrationData","status":null},"deleted":false,"avatar":{"__typename":"UserAvatar","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/m_assets/avatars/default/avatar-7.svg?time=0"},"id":"user:565461"},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjM1Nzc0LTJ2U25TdA?revision=110\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjM1Nzc0LTJ2U25TdA?revision=110","title":"Michelle_R_0-1729119743539.png","associationType":"COVER","width":750,"height":422,"altText":""},"AssociatedImage:{\"url\":\"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjM1Nzc0LTYyOTgwMGkwNDk5QUE4MjE5RTcxQkQz?revision=110\"}":{"__typename":"AssociatedImage","url":"https://techcommunity.microsoft.com/t5/s/gxcuf89792/images/bS00MjM1Nzc0LTYyOTgwMGkwNDk5QUE4MjE5RTcxQkQz?revision=110","title":"Michelle_R_0-1729119743539.png","associationType":"TEASER","width":2000,"height":1125,"altText":"Michelle_R_0-1729119743539.png"},"BlogTopicMessage:message:4235774":{"__typename":"BlogTopicMessage","subject":"Join Microsoft Azure at SC24","conversation":{"__ref":"Conversation:conversation:4235774"},"id":"message:4235774","revisionNum":110,"uid":4235774,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:565461"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Come visit Microsoft at Supercomputing 2024 Nov 17 – 22 where we’ll deep dive into HPC and AI solutions during a week of engaging sessions, hands on experiences and networking. We also have an exciting new Azure HPC announcement! \n \n \n ","introduction":"","metrics":{"__typename":"MessageMetrics","views":18892},"postTime":"2024-10-18T12:14:20.154-07:00","lastPublishTime":"2024-11-19T15:42:51.915-08:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Come visit Microsoft at Supercomputing 2024 (SC24), Atlanta, Georgia, November 17 – 22 where we’ll deep dive into high-performance computing (HPC) and AI solutions during a week of engaging sessions, hands on experiences and networking. We also have an exciting new Azure HPC announcement! Come by booth #1905 on November 19 for the unveiling of a major leap forward in high-performance computing. \n SC24 Main Conference Sessions featuring Microsoft speakers \n Don't miss Microsoft sessions in the SC24 program. Click titles below for full details and to add to your SC24 calendar. \n \n \n \n \n \n \n \n Date / Time (EST) \n \n \n Type \n \n \n Title \n \n \n Speakers/Panelists \n \n \n \n \n Sun, Nov 17 8:30 am - 5 pm \n \n \n Tutorial \n \n \n Delivering HPC: Procurement, Cost Models, Metrics, and Value \n \n \n Microsoft Azure, Stanford University, Mitre, Red Oak Consulting \n \n \n \n \n Mon, Nov 18 8:30 am - 5 pm \n \n \n Tutorial \n \n \n Parallel I/O In Practice \n \n \n Microsoft Azure, Argonne National Laboratory (ANL), Google \n \n \n \n \n Tues, Nov 19 10:30 am - 12 pm \n \n \n Panel \n \n \n How the Convergence of HPC and AI Is Accelerating Innovation \n \n \n Microsoft Azure, AMD, Minds AI, Purdue University, d3VIEW \n \n \n \n \n Tues, Nov 19 3:30 pm - 5 pm \n \n \n Panel \n \n \n Impact of Advances in Lower Precision Performance on HPC Simulation Codes \n \n \n Microsoft Azure, NERSC at LBNL, NVIDIA, AMD, Chevron \n \n \n \n \n Tues, Nov 19 5:15 pm - 6:45 pm \n \n \n Birds of a Feather \n \n \n Benchmarking: A Key Driver for AI Innovation \n \n \n Microsoft Azure, AMD, NVIDIA, Oracle, Snorkel AI \n \n \n \n \n Tues, Nov 19 5:15 pm - 6:45 pm \n \n \n Birds of a Feather \n \n \n LUSTRE Community BOF: Lustre in HPC, AI, and the Cloud \n \n \n Microsoft, Whamcloud, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, Oak Ridge National Laboratory, University of Cambridge \n \n \n \n Wed, Nov 20 11 am - 11:30 am \n \n Paper \n \n \n RecFlex: Enabling Feature Heterogeneity-Aware Optimization for Deep Recommendation Models with Flexible Schedules \n \n \n Microsoft, Renmin University of China, University of California San Diego \n \n \n \n \n Wed, Nov 20 12:15 pm - 1:15 pm \n \n \n Birds of a Feather \n \n \n The Future of Benchmarks in Supercomputing \n \n \n Microsoft Azure, NVIDIA, HPE \n \n \n \n \n Wed, Nov 20 2 pm - 2:30 pm \n \n \n Paper \n \n \n LoRAStencil: Low-Rank Adaptation of Stencil Computation on Tensor Core \n \n \n Microsoft Research, UCAS, Tsinghua University, CAS \n \n \n \n \n Wed, Nov 20 5:15 PM - 6:45pm \n \n \n Birds of a Feather \n \n \n Converged HPC and Cloud Computing in the Era of Generative AI \n \n \n Microsoft Azure, Lawrence Livermore National Laboratory, Barcelona Supercomputing Center, USC Information Sciences Institute, IBM TJ Watson Research Center, Google, University of Tennessee, University of Delaware \n \n \n \n \n Wed, Nov 20 5:15 pm - 6:45 pm \n \n \n Birds of a Feather \n \n \n The National Artificial Intelligence Research Resource (NAIRR) Pilot User Experience BOF \n \n \n Microsoft, University of Colorado Boulder, Slippery Rock University of Pennsylvania, SambaNova Systems, Arizona State University \n \n \n \n \n Thurs, Nov 21 9:30 am - 10am \n \n \n Paper \n \n \n Long Exposure: Accelerating Parameter-Efficient Fine-Tuning for LLMs under Shadowy Sparsity \n \n \n Microsoft Research, Tsinghua University \n \n \n \n \n Fri, Nov 22 11:30 am - 12 pm \n \n \n Workshop \n \n \n HPCAdvisor: A Tool for Assisting Users in Selecting HPC Resources in the Cloud \n \n \n Microsoft \n \n \n \n \n \n \n Meet with Azure Engineering \n Request a private briefing with the Azure Engineering team at SC24. Reach out to your Microsoft account manager to schedule. \n Visit Microsoft Booth #1905 \n Stop by Microsoft booth #1905 daily to... \n \n engage with Microsoft Azure HPC and AI experts and our amazing partners. \n learn the latest advancements during our in-booth information sessions. \n get hands-on with our demo pods for HPC and AI. \n enjoy our hardware bar featuring our newest technology. \n take a break in our lounge area and enjoy free coffee served by Artly, the barista bot - sponsored by NVIDIA. \n enter for a chance to win cool stuff! \n \n Booth theater sessions \n Discover the latest in HPC and AI from Microsoft Azure and partners. Attend our daily information sessions in booth #1905. \n \n \n \n \n \n \n Date/Time (EST) \n \n \n Session Title \n \n \n Abstract \n \n \n Presenter \n \n \n \n \n Mon, Nov 18 \n 7:40 pm - 8:00 pm \n \n \n Accelerating AI Innovation: Microsoft and NVIDIA Bring the Power of GB200 Superchip to Azure \n \n \n \n Microsoft and NVIDIA are bringing the NVIDIA Grace Blackwell 200 (GB200) Superchip to Azure, enabling businesses to handle large-scale AI, data processing, and high-performance tasks with faster performance. This collaboration optimizes GPUs for advanced AI models, improving accuracy, efficiency, and scalability. Paired with upcoming NVIDIA's Quantum-X800 networking platform, this powerful infrastructure helps companies boost AI workloads and stay competitive with cutting-edge technology. \n \n \n NVIDIA, Microsoft \n \n \n \n \n Mon, Nov 18 \n 8:10 pm - 8:30 pm \n \n \n Revolutionizing Computational Science: AI-Driven Solutions on Rescale and Microsoft \n \n \n Learn how innovative AI capabilities, such as Rescale’s compute recommendation engine and AI Physics raise the bar for what's possible in R&D. We'll discuss how AI on Azure is solving challenges in areas such as Molecular Dynamics, Biomechanics, CFD and more... \n \n \n Rescale, Microsoft \n \n \n \n \n Tue, Nov 19 \n 9:30 am - 11:30 am \n \n \n Ignite 2024 Keynote \n \n \n Live stream of Microsoft CEO, Satya Nadella's Ignite 2024 keynote presentation. \n \n \n Microsoft \n \n \n \n \n Tue, Nov 19 \n 11:30 am - 12:30 pm \n \n \n Special Azure HPC announcement \n \n \n Join us for a special announcement where we’ll unveil a major leap forward in high-performance computing. \n \n \n Microsoft Azure, AMD \n \n \n \n \n Tue, Nov 19 \n 12:40 pm - 1:00 pm \n \n \n Together We Advance Cloud HPC \n \n \n With Azure H-series infrastructure, based on AMD EPYC processors, Azure customers have access to super computing resources in the cloud. Join this session to learn how to reduce cost per job by using the latest H-series VMs. \n \n \n AMD \n \n \n \n \n Tue, Nov 19 \n 1:10 pm - 1:30 pm \n \n \n Fast and efficient processing of complex AI workloads with ND MI300X v5 \n \n \n Join us for an in-depth exploration of the Azure ND MI300X v5 VM series, a groundbreaking addition to Azure’s AI infrastructure. Learn how these VMs meet the demands of advanced AI workflows. \n \n \n AMD \n \n \n \n \n Tue, Nov 19 \n 1:40 pm - 2:00 pm \n \n \n Case Studies in Digital Product Innovation with TotalCAE on Azure \n \n \n TotalCAE makes Computer-Aided Engineering (CAE), Life Sciences, and AI applications easy to use on Azure in just a few clicks with TotalCAE-managed HPC services and the TotalCAE platform on Azure. Learn through several public customer case studies how clients are adopting Azure HPC optimized H series instances to accelerate their product designs and transform their HPC workflows with award-winning deployments in manufacturing, automotive, and life sciences. \n \n \n TotalCAE, Microsoft \n \n \n \n \n Tue, Nov 19 \n 2:10 pm - 2:30 pm \n \n \n Ansys & Azure: How to leverage the power of Azure to accelerate Ansys workloads \n \n \n Learn how Ansys and Microsoft leverage the compute power of Azure and the solving power of Ansys to accelerate the pace of innovation. This session will focus on the migration of Ansys workloads to Azure cloud infrastructure and Ansys Access on Microsoft Azure™. \n \n \n Ansys, Microsoft \n \n \n \n \n Tue, Nov 19 \n 2:40 pm - 3:00 pm \n \n \n Accelerating Hybrid Quantum-Classical Computing with Microsoft & Quantinuum \n \n \n This session will cover recent announcements and advancements by Quantinuum and Microsoft in quantum computing and applications. \n \n \n Quantinuum, Microsoft \n \n \n \n \n Tue, Nov 19 3:10 pm - 3:30 pm \n \n \n Rescale & Microsoft: Simplifying Advanced Computing to Scale Digital Engineering & AI Innovation \n \n \n Join our session to learn how Microsoft and Rescale simplify HPC, enhancing collaboration between engineers, data scientists, and IT leaders to power innovation. \n \n \n Rescale, Microsoft \n \n \n \n \n Tue, Nov 19 \n 3:40 pm - 4:00 pm \n \n \n Hurricane Modeling in Public Cloud \n \n \n In this session, we'll explore how the 2024 Hurricane Analysis and Forecast System (HAFS) Ensemble in Real-time on the Cloud (HERC) experiment showcased NOAA’s ability to run advanced hurricane models seamlessly on the cloud. \n \n \n Parallel Works, Microsoft \n \n \n \n \n Tue, Nov 19 \n 4:10 pm - 4:30 pm \n \n \n Revolutionizing HPC Workflows with Generative AI assistants \n \n \n Explore how advanced generative AI is revolutionizing high-performance computing (HPC) workflows. Discover an AI-driven tool designed to streamline HPC processes by reducing manual intervention, with a featured use case in genomics and health sciences. \n \n \n Microsoft Azure \n \n \n \n \n Tue, Nov 19 \n 4:40 pm - 5:00 pm \n \n \n Accelerating AI for Science on Supercomputers using DeepSpeed and Megatron \n \n \n Join this session to learn about Microsoft AI for Science and how Microsoft's AI models for science leverage deepspeed frameworks together with megatron for diverse scientific domains. \n \n \n Microsoft Research \n \n \n \n \n Tue, Nov 19 \n 5:10 pm - 5:30 pm \n \n \n Azure Storage for AI Supercomputers \n \n \n This is an overview session covering the various announcements in Azure storage products which cater to modern AI workloads. \n \n \n Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 10:10 am - 10:30 am \n \n \n \n Accelerating EDA workloads on Azure – Best Practice and benchmark on Intel EMR CPU \n \n \n Learn best practices for running EDA on Azure, including recommended architecture, optimal compute VMs, and high-performance NFS storage solutions. And benchmark results for EDA tools on Azure and Azure VMs with 5th Gen Intel® Xeon® Platinum 8537C processor. \n \n \n Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 10:40 am - 11:00 am \n \n \n Azure CycleCloud and the WEKA Data Platform Integration \n \n \n The integration of Azure CycleCloud with the WEKA Data Platform empowers businesses to achieve high performance, scalability, and efficiency in their high-performance computing (HPC) environments. CycleCloud orchestrates and manages HPC clusters in Azure, providing autoscaling and configuration management for complex deployments. With WEKA, users gain a high-performance file system optimized for low-latency and high-throughput workloads, ideal for AI, analytics, and machine learning applications. This session will describe the solution and demonstrate the advantages with a live demo. \n \n \n Weka, Microsoft \n \n \n \n \n Wed, Nov 20 \n 11:10 am - 11:30 am \n \n \n A Full Stack Approach to Accelerated Computing \n \n \n This session will discuss how NVIDIA and Azure are partnering to provide accelerated computing for HPC and AI workloads. Ashraf will highlight NVIDIA's latest innovations in GPUs and software, showcasing how they are used in supercomputing platforms to address the opportunities and challenges faced by scientists, institutions, and governments worldwide. Listeners will gain insights into how Microsoft and NVIDIA are collaborating to deliver a comprehensive, full-stack solution to these challenges. \n \n \n \n NVIDIA, Microsoft \n \n \n \n \n Wed, Nov 20 \n 11:40 am - 12:00 pm \n \n \n Deploy HPC & AI Infrastructure at Scale on Azure in Minutes! – Part 1 \n \n \n Join us for an engaging demonstration on how to build your HPC and AI solutions with ease using Microsoft Azure CycleCloud Workspace for Slurm (CCWS). Learn key features that can bring up HPC workloads in minutes and significantly boost productivity and efficiency. \n \n \n Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 12:10 pm - 12:30 pm \n \n \n Accelerating Enterprise Computing with Altair Workload Managers and Azure CycleCloud \n \n \n Altair's workload managers and cloud enablement solutions, in synergy with Azure CycleCloud, empower Azure HPC/AI users with unmatched performance and agility. This presentation will showcase the seamless integration of our cutting-edge scheduling solutions—Altair PBS Professional and Altair Grid Engine —within Azure's purpose-built HPC/AI infrastructure. Join us to witness firsthand how this collaboration transforms efficiency and accelerates innovation in high-performance computing and artificial intelligence. \n \n \n Altair, Microsoft \n \n \n \n \n Wed, Nov 20 \n 12:40 pm - 1:00 pm \n \n \n Running Small Language model inference on Azure NC series VMs \n \n \n Join us for a live demonstration of deploying small language models using Azure’s NC H100 v5 VMs. Discover how to leverage open-source tools like Ollama to deploy the Phi3 Mini model, showcasing the seamless integration of NVIDIA H100 GPUs with Azure’s powerful infrastructure. Learn the streamlined deployment process, performance optimization techniques, and best practices for managing NLP projects on Azure. Whether you’re an AI developer or data scientist, this session will provide the essential skills to efficiently deploy and run language models on Azure’s NC series. Don’t miss this opportunity to enhance your AI initiatives with Azure’s advanced GPU offerings! \n \n \n NVIDIA, Microsoft \n \n \n \n \n Wed, Nov 20 \n 1:40 pm - 2:00 pm \n \n \n Increase Cryo-EM performance, discover more at impossibly small scale \n \n \n See how global pharma companies are working with Hammerspace and running on AMD powered instances in Azure to offer users the ability to scale their infrastructure as needed to meet the changing requirements of Cryo-EM and their research. \n \n \n Hammerspace, Microsoft \n \n \n \n \n Wed, Nov 20 \n 2:10 pm - 2:30 pm \n \n \n High Performance Computing with AMD EPYC Processors on Azure H-series VMs \n \n \n Come get an update on how to get the most out of your HPC applications using Azure’s HB-series VMs with AMD EPYC Processors. \n \n \n Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 2:40 pm - 3:00 pm \n \n \n The European Environment for Scientific Software Installations (EESSI) \n \n \n Have you ever wished that all the scientific software you use was available on all the resources you have access to without having to go through the pain of installing it the way you want/need? In this talk, we will introduce the European Environment for Scientific Software Installations (EESSI — pronounced \"easy\") as a common stack of optimized scientific software installations for HPC systems and beyond all around the globe. \n \n \n EESSI, Microsoft \n \n \n \n \n Wed, Nov 20 \n 3:10 pm - 3:30 pm \n \n \n Esri using Reality Capture for Climate Science in the City of Stuttgart. \n \n \n Learn how Esri's ArcGIS Pro, powered by Azure and NVIDIA, is used for Climate Science to predict and mitigate flooding in the City of Stuttgart. We'll demonstrate how high-resolution 3D models of the city are created and analyzed. \n \n \n NVIDIA, Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 3:40 pm - 4:00 pm \n \n \n Deploy HPC & AI Infrastructure at Scale on Azure in Minutes – Part 2! \n \n \n This is a continuation of Part 1 session on deploying a full HPC/AI infrastructure using Azure CycleCloud Workspace for Slurm (CCWS). Get a full walkthrough demo on how to deploy and scale your OSS toolchain including familiar tooling, like Open OnDemandand and Linux VDI from with ThinLinc from Cendio. \n \n \n Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 4:10 pm - 4:30 pm \n \n \n Deploying small-to-medium AI workloads on Azure’s PCIe GPUs \n \n \n Discover how Azure's NC and NV series VMs are revolutionizing the deployment of small-to-medium AI workloads by optimizing performance, scalability, and insights. We’ll introduce you to Azure’s comprehensive PCIe GPU portfolio and the ideal GPU solutions. \n \n \n Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 4:40 pm - 5:00 pm \n \n \n Empowering Workforce Development through AI-Powered Power BI Training \n \n \n Presenting examines how Azure AI and Power BI are integrated into Emory University’s workforce development curriculum, equipping professionals with skills in AI-driven data analytics. Using tools like sentiment analysis, keyword extraction, and vision recognition, participants generate actionable insights and visualize data in Power BI. \n \n \n Emory University, Microsoft Azure \n \n \n \n \n Wed, Nov 20 \n 5:10 pm - 5:30 pm \n \n \n Azure Storage solutions for your most demanding HPC and AI training workloads \n \n \n This is an overview session covering the various announcements in Azure storage products which cater to modern AI workloads. \n \n \n Microsoft Azure \n \n \n \n \n Thurs, Nov 20 \n 10:40 am - 11:00am \n \n \n \n Introducing SimOps and how to build and operate and optimal and cost-efficient HPC/AI infrastructure on Azure \n \n \n By collaborating with Azure and manufacturing customers like Rimac Automobili, FLSmidth, and others, Wolfgang from Simr will share insights gained from Azure clients and demonstrate how these lessons have been transformed into SimOps Best Practices. They will outline the SimOps Framework, explaining how it can be used to build, operate, and manage HPC/AI infrastructures in a way that is both efficient and cost-effective \n \n \n Simr, Microsoft Azure \n \n \n \n \n Thurs, Nov 20 \n 11:10 am - 11:30am \n \n \n \n \n Azure NetApp Files, boosting HPC productive with Innovation \n \n \n In this session, we will explore the pivotal role of file systems in optimizing High-Performance Computing (HPC) at an Azure scale, utilizing tens of thousands of compute cores working in unison to tackle the most advanced HPC challenges. The key solution is Azure NetApp Files (ANF), which Microsoft Azure customers are leveraging with remarkable efficacy today. Thanks to ANF’s low latency, high throughput, and simplified management, users are experiencing significant productivity gains by eliminating the hardware constraints traditionally associated with running HPC workloads. \n \n \n NetApp, Microsoft Azure \n \n \n \n \n Thurs, Nov 20 \n 12:10pm- 12:30pm \n \n \n Qumulo Global Data Platform: Removing data boundaries to deliver infinite possibilities \n \n \n Imagine if you could share your data - globally, securely and efficiently - to accelerate time-to-results and insights. Imagine if you could elastically scale cloud performance and capacity on-demand to meet your application demands. Learn how Qumulo Global Data Platform unlocks the value of your data to enable faster time-to-results and enables transformative opportunities in accelerated computing. In this presentation you will discover how Qumulo Run Anywhere with Global Namespace enables you to the choice to host your data on-premise or in the cloud, while ensuring your data can be accessed anywhere, whether in the cloud or in your data center, while maintaining control of your most valuable asset; your data. \n \n \n Qumulo, Microsoft \n \n \n \n \n \n Thurs, Nov 20 \n 2:10pm- 2:30pm \n \n \n \n Quantum & AI to Accelerate Scientific Discovery \n \n \n AI and quantum computing have the potential to help solve some of the most pressing challenges of our time -- from the climate crisis to world hunger to finding cures for disease. As we continue to improve the fidelity and scale of quantum machines, we will first be able to unlock scientific quantum advantage, solving a growing class of complex and intractable problems. As we scale to quantum supercomputers, we will be able to achieve commercial quantum advantage and solve the world’s most pressing challenges through quantum-enabled advances in chemistry, biochemistry, and materials science. This session will explain Microsoft’s latest advancements in quantum computing and how Microsoft is building a new science platform using AI, HPC, and quantum to accelerate scientific discovery in chemistry, biology, and physics. \n \n \n Azure Quantum \n \n \n \n \n \n \n \n Demos \n Get hands-on with HPC and AI demos in booth #1905. \n \n \n \n \n \n \n Date \n \n \n Start \n \n \n Demo \n \n \n \n \n Mon Nov 18 \n \n \n 7:00 am EST – 9:00 AM \n \n \n NVIDIA demo \n \n \n \n \n Tues Nov 19 \n \n \n FULL DAY \n \n \n AMD demo \n \n \n \n \n Wed Nov 20 \n \n \n 10:00 AM – 2:00 PM \n \n \n NVIDIA demo \n \n \n \n \n Wed Nov 20 \n \n \n 2:00 PM – 4:00 PM \n \n \n Rescale demo \n \n \n \n \n Wed Nov 20 \n \n \n 4:00 PM – 6:00 PM \n \n \n Ansys demo \n \n \n \n \n \n \n Hardware bar \n Discover the latest Azure HPC and AI technology featuring hardware from AMD and NVIDIA at our hardware bar in booth #1905. \n Get social at our special events \n Request an invitation to our after-hour events for networking, drinks, food, and fun! \n Social Mixer \n Microsoft and AMD are hosting a high-end tailgate mixer the evening of November 19. This social event will feature exciting announcements, a special guest appearance, and fabulous food and drinks. Space is limited! Registration approval and email confirmation (e-ticket) required to attend. Request your invite today. \n \n \n 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AMD.","conversation":{"__ref":"Conversation:conversation:4130931"},"id":"message:4130931","revisionNum":25,"uid":4130931,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:2446399"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Discover how Microsoft, AMD, and your peers are revolutionizing their infrastructure with HPC+AI ","introduction":"","metrics":{"__typename":"MessageMetrics","views":7785},"postTime":"2024-05-03T12:51:36.238-07:00","lastPublishTime":"2024-05-20T11:40:36.532-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" \n \n Discover how Microsoft, AMD, and your peers are revolutionizing their infrastructure with HPC+AI \n \nClick Here to Register Now to Secure Your Spot! \n \n \n Join us for the “HPC + AI Infrastructure Summit with Microsoft and AMD,” a premier event designed to elevate your understanding and capabilities in HPC and AI. This 3-day summit will open doors to not only broaden your knowledge but also to harness the potential of cutting-edge innovations in HPC and AI. \n This is an unmissable opportunity to hear from top industry leaders like Nidhi Chappell, VP of Azure HPC + AI Infrastructure and recipient of a recipient of the HPCWire’s 2023 People to Watch, and Andrew Jones, who leads our Future HPC + AI Capabilities. They, along with other distinguished speakers from AMD and our industry partners, will provide invaluable insights into the advancements driving our sector forward. \n \n \n Who should attend \n \n This event is designed for IT decision-makers, engineers, data scientists, and tech leaders focused on implementing cutting-edge technology solutions within their organizations. \n \n Why attend \n \n \n \n \n \n Discover technological advances \n Customize your experience \n Engage in hands-on learning \n Gain real-world insights \n Expand your network \n \n \n Learn the latest HPC and AI innovations to accelerate your projects. \n Choose your own adventure with multiple product and industry tracks. \n Participate in labs, demos, and technical deep dives to gain practical skills. \n Hear firsthand from customers on how HPC and AI are reshaping industries. \n Connect with industry leaders and peers during networking sessions. \n \n \n \n \n \n Featured speakers \n Don’t miss exciting keynotes and sessions from HPC thought leaders. \n \n \n \n \n Nidhi Chappell \n Microsoft \n Vice President Azure HPC + AI Infrastructure \n \n Day 1 – June 4 9:15-10:00 AM \n Keynote: Vision and Customer Highlights \n \n \n \n \n Andrew Jones \n Microsoft \n Leader Azure Future HPC + AI Capabilities \n \n Day 1 – June 4 10:00-10:40 AM \n Keynote: Future of Supercomputing and Roadmap \n \n \n \n \n Aung Oo \n Microsoft \n General Manager Azure Storage Engineering \n \n Day 1 – June 4 11:00-11:40 AM \n Plenary: Storage for HPC + AI Infrastructure \n \n \n \n \n Robert Hormuth \n AMD \n Corporate Vice President Architecture & Strategy DCS \n \n Day 2 – June 5 9:10-9:40 AM \n Keynote: AMD Vision and Roadmap \n \n \n \n \n Dr. Prith Banerjee \n Ansys \n Chief Technical Officer \n \n \n Day 1 – June 4 9:15-10:00 AM \n Keynote: Vision and Customer Highlights \n \n \n \n \n Kiran Bhageshpur \n Qumulo \n Chief Technical Officer \n \n \n Day 1 – June 4 11:00-11:40 AM \n Plenary: Storage for HPC + AI Infrastructure \n \n \n \n \n Tailor your summit journey \n Customize your event experience with sessions for automotive, financial, energy, life sciences, and manufacturing sectors, including relevant cross-industry solutions. \n \n \n \n \n Key benefits of attending \n \n Learn from the best: Direct insights from industry leaders. \n Hands-on technology exposure: Get up close with the latest innovations; bring your device to work out solutions labs. \n Expand your network: Meet potential collaborators and industry peers. \n Industry-relevant sessions: Tailored insights that apply directly to your sector. \n \n \n \n Day 1 Agenda Overview – June 4 \n \n \n \n Start \n End \n Session \n Speakers \n \n \n 8:00 \n 9:00 \n Registration & Breakfast in the Event Lobby \n \n \n 9:00 \n 9:15 \n Executive Welcome to Summit \n Erin Chapple CVP Azure Core Product and Design \n \n \n 9:15 \n 10:00 \n Keynote: Vision and Customer Highlights \n Nidhi Chappell VP Azure HPC + AI Infrastructure and Dr. Prith Banerjee Ansys CTO \n \n \n 10:00 \n 10:40 \n Keynote: Future of Supercomputing and Roadmap \n Andrew Jones Azure Future HPC + AI Capabilities Leader \n \n \n 10:40 \n 11:00 \n Break – 20 mins \n \n \n 11:00 \n 11:40 \n Storage for HPC + AI Infrastructure \n Aung Oo Microsoft Partner General Manager Azure Storage Engineering, Kiran Bhageshpur Qumulo CTO \n \n \n 11:40 \n 12:15 \n Fireside Chat with Microsoft CVPs \n Erin Chapple CVP Azure Core Product and Design, Eric Lockard CVP Azure Specialized Workloads, hosted by Andrew Jones Azure Future HPC + AI Capabilities Leader \n \n \n 12:15 \n 1:15 \n Catered Lunch – 60 mins \n \n \n 1:15 \n 2:30 \n Azure HPC + AI Infra Portfolio - Intro and Teasers: H N Viz SW Linux VDI \n Microsoft Product Engineering Team \n \n \n 2:45 \n 3:45 \n 3x Product Breakouts + 3x Industry Breakouts \n \n \n \n 3:45 \n 4:00 \n Break – 15 mins \n \n \n 4:00 \n 5:00 \n Interactive Customer Panel \n Moderated by Andrew Jones Azure Future HPC + AI Capabilities Leader \n \n \n 5:00 \n 7:00 \n Summit Technologists Networking Reception – All attendees welcome \n \n \n \n Subject to change \n Day 1 Product Breakouts – June 4 2:45 PM-3:45 PM \n \n \n \n Start \n End \n Track 1 \n Track 2 \n Track 3 \n \n \n 2:45 \n 3:45 \n In-depth: Azure VM Products - H (HPC Infra) including (1) and (2) InfiniBand \n Reliable Deployments and Diagnostics \n In-depth session: Batch & CycleCloud \n \n \n 2:45 \n 3:45 \n Discussion & Customer Inputs: Observability and performance metrics \n Deploy Slurm on Azure from your remote Linux desktop in minutes with Linux VDI and Cycle Cloud Slurm Workspace \n \n \n \n \n Subject to change \n Day 1 Industry Breakouts – June 4 2:45-3:45 PM \n \n \n \n Start \n End \n Track 1 \n Track 2 \n Track 3 \n \n \n 2:45 \n 3:15 \n Healthcare & Life Sciences The future of Healthcare: Genomics Sequencing Integration of Workflow Schedulers in Azure Visualization and beyond Presented by: Roberto Lleras Microsoft \n Manufacturing Panel: Revolutionizing Product Development: Azure's Compute Power Meets Generative AI Executive: Tim Ryder Microsoft Moderator: Andy Chan Microsoft Panelists: Dr. Erik Berg Microsoft Nathan Chang AMD Srikanth Gubbala Applied Materials Brian Andrus LAM Research \n Energy Top AI Use Cases in the Energy Sector Powered By HPC Presented by: Hema Prapoo Microsoft \n \n \n 3:15 \n 3:45 \n Healthcare & Life Sciences Azure Quantum Elements—Transforming R&D in Pharma with HPC + AI Presented by: Gorka Madariaga Microsoft \n \n Energy AMD Accelerated Compute for Energy Presented by: Varun Selvaraj AMD \n \n \n \n Subject to change \n Day 2 Agenda Overview – June 5 \n \n \n \n Start \n End \n Session \n Speakers \n \n \n 8:00 \n 9:00 \n Registration & Breakfast \n \n \n 9:00 \n 9:10 \n Executive Welcome Day 2 \n Henrik Gutle GM Azure Business Group Americas \n \n \n 9:10 \n 9:40 \n Keynote: AMD Vision and Roadmap \n Robert Hormuth AMD CVP Architecture & Strategy Data Center Solutions \n \n \n 9:40 \n 10:10 \n Best practices for successfully leveraging HPC AI Infrastructure on Azure \n Kanchan Mehrotra Principal Group PM Manager \n \n \n 10:10 \n 10:45 \n HPC Support and CSA Enablement \n Bill Paxson Support Engineer Manager, Brian Timpe Sr. HPC Cloud Solution Architect \n \n \n 10:45 \n 11:00 \n Break 15 mins \n \n \n 11:00 \n 11:30 \n Application Performance and Benchmarks \n Joe Greenseid Principal HPC + AI Product Engineering \n \n \n 11:30 \n 12:15 \n Industry Panel \n Moderated by Desiree Campbell Americas Azure HPC + AI Managing Director \n \n \n 12:15 \n 1:15 \n Catered Networking Lunch – 60 mins \n \n \n 1:15 \n 2:15 \n 3x Product Breakouts + 3x Industry Breakouts \n \n \n \n 2:15 \n 2:30 \n Break 15 mins \n \n \n 2:30 \n 3:30 \n 3x Product Breakouts + 3x Industry Breakouts \n \n \n \n 3:30 \n 3:45 \n Break 15 mins \n \n \n 3:45 \n 4:30 \n Open Mic / AMA with Microsoft Product Leaders \n \n \n \n 4:30 \n 5:00 \n HPC & AI Technology Futures Roundtable \n Led by Alan More Managing Director of Microsoft Met Office Program, Dr. Erik Berg Azure Sr Principal Engineer, Evan Burness Azure HPC Platforms & Infrastructure Lead, Phil Steinke AMD Fellow CAD Infrastructure and Physical Design \n \n \n 5:00 \n 5:10 \n Closing and Thank You \n Desiree Campbell Americas Azure HPC + AI Managing Director \n \n \n \n Subject to change \n Day 2 Product Breakouts – June 5 1:15-3:30 PM \n \n \n \n Start \n End \n Track 1 \n Track 2 \n Track 3 \n \n \n 1:15 \n 1:45 \n In-depth: Azure VM Products - N (AI Infra) (AMD) \n Managed HPC services in Azure? Lessons from mission critical HPC in Azure? \n In-depth session: Azure HPC Linux distros \n \n \n 1:45 \n 2:15 \n In-depth: Azure VM Products - N (AI Infra) (NVIDIA) \n Anatomy of a customer journey on Azure HPC: Vestas \n Discussion & Customer Inputs: HPC Software Stack incl. Convergence of HPC & AI \n \n \n 2:30 \n 3:00 \n Video Processing with Azure NM-series \n In-depth best practice and key tips for HPC with Azure \n Sessions require an NDA Azure AMD Roadmap HPC/AI Software Roadmap Discussion & Customer Inputs: Future product directions \n \n \n 3:00 \n 3:30 \n Visualization with Azure NV* series \n Reduce development costs with Copilots for HPC workload management \n \n \n \n \n Subject to change \n Day 2 Industry Breakouts – June 5 1:15-3:30 PM \n \n \n \n Start \n End \n Track 1 \n Track 2 \n Track 3 \n \n \n 1:15 \n 1:45 \n Financial Services HPC Risk Workloads and Azure Presented by: Kent Altena Microsoft, Herman Nakamura AMD, Rick Hughson AMD \n Automotive & Mobility Autonomous Vehicles- Past Present & Future. Presented by: Danny Atsmon Cognata, Kurt Niebuhr Microsoft \n Energy WEKA product demonstration Presented by: Raj Sharma WEKA \n \n \n 1:45 \n 2:15 \n Financial Services Optimizing HPC Workloads in Azure for Financial Services Presented by: Kent Altena Microsoft, Herman Nakamura AMD, Rick Hughson AMD, Shaun Welsh Moody’s Analytics \n Manufacturing Next-gen CAE modeling and Digital Twinning for industrial/Manufacturing Presented by: Pieter Fountain Microsoft, Rick Knoechel AMD, Andy Byers Ansys \n Cross-Industry Building a True Global Namespace for Cloud AI and Data Pipelines Presented by: Neeloy Bhattacharyya VAST Data \n \n \n 2:30 \n 3:00 \n Financial Services Unleashing the Power of HPC Grids in FSI: Overcoming Storage Hurdles Presented by: Kent Altena Microsoft, Adam Ginsberg NetApp \n Automotive & Mobility Panel: Transforming Automotive Industry Through AI Panel: Industry leaders from Microsoft, AMD, and Neutral Concept \n Energy & Manufacturing Azure Quantum Elements—Transforming R&D for chemistry processes with HPC + AI Presented by: Gorka Madariaga Microsoft \n \n \n 3:00 \n 3:30 \n Cross-Industry Breaking the speed limit with WEKA: Getting the most out of Azure BLOB Storage Presented by: Kent Altena Microsoft, Raj Sharma WEKA \n Automotive & Mobility Advancing the Automotive Future with Digital Engineering Presented by: Dr. Ahmed Taha Microsoft, Rick Knoechel AMD, Andy Byers Ansys \n \n \n \n \n Subject to change \n Day 3 Agenda Overview – June 6 \n \n \n \n Start \n End \n Session \n \n \n 8:00 \n 9:00 \n Registration & Breakfast \n \n \n 9:00 \n 10:00 \n 3x Hand-On Labs / Demo Sessions \n \n \n 10:00 \n 10:15 \n 15 min Break \n \n \n 10:15 \n 11:15 \n 3x Hand-On Labs / Demo Sessions \n \n \n 11:15 \n 11:30 \n 15 min Break \n \n \n 11:30 \n 12:30 \n 3x Hand-On Labs / Demo Sessions \n \n \n 12:30 \n 1:30 \n Catered Lunch 60 mins \n \n \n \n Subject to change \n Day 3 Hand-on Labs and Solutions Demonstrations – June 6 9:00 AM-12:30 PM \n \n \n \n Start \n End \n Track 1 \n Track 2 \n Track 3 \n \n \n 9:00 \n 10:00 \n e2e HPC Environment on Azure–Lift & Shift Facilitated by: Hugo Meiland Microsoft, Ben George Microsoft \n AMD Innovation Lab with Ansys Focus Application developed by Oakwood Presented by: Dan Cooke Oakwood, Jason Scheffelmaer Microsoft \n Integrating Azure Native Qumulo with Microsoft Copilot Facilitated by: Kevin McDonald Qumulo \n \n \n 10:15 \n 11:15 \n e2e HPC environment on Azure (cloud native and SaaS) Facilitated by: Marco Netto Microsoft, Sonal Doomra Microsoft \n Ansys Access Technical Session Presented by: JJ Jones Ansys, Krishna Samavedam Ansys, Hugo Meiland Microsoft \n Altair Engineering Tech Presentation/Demo Presented by: Shaun Kroeger Altair \n \n \n 11:30 \n 12:30 \n Rescale: Harnessing the Data Explosion for New Insights in Engineering & Scientific Computing Presented by: Madhu Vellakal Rescale, Eric Schieferstein Rescale \n Azure Quantum Elements Technical deep dive demonstration and hands-on lab Presented by: Microsoft Azure Quantum Elements Team \n Siemens NX on AVD + StarCCM hands-on lab Presented by: Siemens, Sunita Phanse Microsoft \n \n \n \n Subject to change \n \n \n Event Partners \n Learn more about our Event Partner Sponsors and meet them during the Networking Technologist Reception at the end of Day 1. \n\n Platinum Partners \n \n \n \n \n \n \n \n Hardware Provider \n AMD drives innovation in computing graphics and AI supporting billions of users and top companies worldwide. At the forefront of technology for over 50 years AMD delivers high-performance solutions that enhance daily life and business. \n Key contributions to Azure HPC + AI Infrastructure: \n \n AMD Instinct MI300X accelerators: Featured in Azure's new ND MI300x v5 VMs optimized for AI workloads providing unmatched efficiency and scalability. \n 4th Gen AMD EPYC processors: Powering new general purpose memory-intensive and compute-optimized VMs delivering up to 20% better performance and 2x the CPU performance for compute tasks. \n Azure NGads V620 Series VMs: GPU-accelerated VMs for visualization workloads powered by AMD Radeon™ PRO V620 GPUs and 3rd Gen AMD EPYC CPUs supporting demanding applications like gaming and rendering. \n \n Supporting resources: AMD Brings New AI and Compute Capabilities to Microsoft Customers \n Sessions not to miss! \n \n Day 2 – June 5 4:30-5:00 PM Keynote: AMD Vision and Roadmap with Robert Hormuth CVP Architecture & Strategy \n Day 3 – June 6 9:00-10:00 AM AMD Innovation Lab with Oakwood and a focus on Ansys \n \n Check out the new AMD Healthcare Solutions site where you will find lots of resources including this White Paper: 4th Gen AMD EPYC™ Processors for Healthcare and Life Sciences \n \n \n \n \n\n Gold Partners \n \n \n \n \n \n \n \n Software Provider for HPC & AI \n Ansys Access on Microsoft Azure is now available in the Microsoft Azure Marketplace enabling fast flexible and scalable access to Ansys’ world-leading engineering simulation technology. Customers can use their existing Microsoft Azure tenants ensuring maximum data integrity and security while leveraging existing commercial agreements for Ansys software and Microsoft Azure infrastructure. With minimal initial setup customers can access pre-configured Ansys simulation tools in the cloud via an intuitive easy-to-use web interface. In addition Ansys Access on Microsoft Azure is an open platform allowing customers to configure their own workflows by manually incorporating third party applications. Meet your engineering budget and goals with the speed and scale of Ansys access on Microsoft Azure. \n Learn more at Ansys Access for Microsoft Azure \n \n \n \n \n \n \n \n Data Storage & Management \n Qumulo provides elastic high-performance file storage solutions designed for large volumes of unstructured data offering disruptively low prices. Integrated with Microsoft Azure as a fully managed service Azure Native Qumulo supports data-intensive HPC and AI workloads offering simple management at exabyte scale and unlimited performance. Ideal for industries like healthcare / life sciences energy manufacturing media and finance Qumulo helps businesses maximize their Azure HPC + AI infrastructure with reliable and scalable storage. \n Learn more at Azure Native Qumulo \n Announcements: \n \n Qumulo announces integration with Microsoft Copilot. \n Qumulo announces industry’s fastest AI benchmark for HPC storage. \n \n Learn more here. \n \n \n \n \n\n Silver Partners \n \n \n \n \n \n \n \n Data Storage & Management \n NetApp is the intelligent data infrastructure company, delivering silo-free infrastructure, harnessing observability and AI to enable the best data management everywhere. Azure NetApp Files (ANF) is the high performance, native, first party file service delivering consistent, high-throughput, low-latency access to CIFS and NFS shares hosted on NetApp-engineered, all-flash file server clusters resident in Microsoft Azure’s regional data centers. Learn more Azure data services – Azure cloud migration & Azure storage | NetApp \n Check out our partnership video Microsoft AMD and NetApp EDA \n \n \n \n \n \n \n \n Cloud & Infrastructure Services \n As a distinguished Microsoft Solutions Partner Oakwood is a leading provider of transformative Cloud & Infrastructure Services Custom Application Development Data & Analytics AI and Managed IT Services. Leveraging the power of Microsoft Azure Oakwood specializes in optimizing HPC and AI workloads enabling businesses to accelerate innovation and drive performance. Our comprehensive solutions ensure seamless integration scalability and enhanced data management empowering organizations to achieve their digital transformation goals with confidence and efficiency. \n Learn more at Oakwood Azure HPC Services \n \n \n \n \n \n \n \n Cloud & Infrastructure Services \n Rescale in partnership with Microsoft empowers organizations to accelerate engineering simulations by 10000X while reducing their operational R&D costs by more than 80% by combining the best of Azure HPC+AI in a centralized HPC platform. Rescale’s HPC Built for the Cloud platform enables engineers and technology leaders to harness the latest technologies and discover new product breakthroughs. Innovators from the automotive to life sciences industries use Rescale to equip their R&D teams with the world’s largest library of simulation applications and specialized computing architectures leading security and compliance and intelligent automation. Rescale is recognized by Deloitte as a Technology Fast 500 company and by the World Economic Forum as a Global Innovator Unicorn. \n Learn more at Rescale on Azure \n \n \n \n \n\n Bronze Partners \n \n \n \n \n \n \n \n Software Provider for HPC & AI \n Altair is a global leader in computational intelligence that provides software and cloud solutions in simulation HPC data analytics and AI. Altair enables organizations across all industries to compete more effectively and drive smarter decisions in an increasingly connected world – all while creating a greener more sustainable future. \n Learn more at Altair.com \n \n \n \n \n \n \n \n Data Storage & Management \n Hammerspace is radically changing how unstructured data is used and preserved. Our software unifies unstructured data across sites clouds and any storage provides extreme parallel performance for AI GPUs and high-speed data analytics and automates data placement non-disruptively with data orchestration. This creates a Global Data Environment that eliminates data silos and makes data an instantly accessible resource for users applications and compute clusters no matter where they are located. \n Learn more at Hammerspace \n \n \n \n \n \n \n \n Data Storage & Management \n VAST Data offers a groundbreaking data platform designed for AI-driven businesses combining the high-performance capabilities of HPC systems with the simplicity of Enterprise NAS. This unified multi-protocol solution seamlessly supports AI and HPC workloads across data centers various data types and protocols. Its innovative disaggregated shared everything architecture can scale to exabytes and facilitates always-online system upgrades and expansions to compute and capacity without downtime delivering continuous operations. Focused on unlocking insights and accelerating innovation VAST Data helps organizations rapidly make informed decisions reducing business risks linked to data management. \n Learn more at VAST Data \n \n \n \n \n \n \n \n Data Storage & Management \n WEKA is a data platform provider for AI and other performance-intensive workloads helping data-driven organizations seamlessly and sustainably store process and manage their data across edge core cloud hybrid and multicloud environments. \n Learn more at WEKA \n \n \n \n \n \n Thank you to our event partners: A heartfelt thank you to AMD and all our sponsors for their pivotal roles in shaping this summit, providing invaluable insights into the latest HPC technology. \n \n Click Here to Reserve Your Spot Today! \n \n For more information: Please contact Lisa Downey, Americas HPC GTM Business Lead \n Registration deadline: May 28, 2024 \n \n \n 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Open OnDemand Portal with Azure CycleCloud","conversation":{"__ref":"Conversation:conversation:4136231"},"id":"message:4136231","revisionNum":3,"uid":4136231,"depth":0,"board":{"__ref":"Blog:board:AzureHighPerformanceComputingBlog"},"author":{"__ref":"User:user:1563537"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" This blog post presents an Azure CycleCloud project allowingthe deployment of an Open OnDemand portal, an efficient open-source web portal for job submission, job monitoring, file management and remote desktop/application sessions. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":9729},"postTime":"2024-05-09T12:33:25.013-07:00","lastPublishTime":"2024-05-09T12:33:25.013-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Dr. Wolfgang De Salvador - EMEA GBB HPC/AI Infrastructure Senior Specialist \n Dr. Darko Mocelj - EMEA GBB HPC/AI Infrastructure Senior Specialist \n \n \n \n Resources and references used in this article: \n \n Repository of the Azure CycleCloud OnDemand project \n Open OnDemand Portal \n Open OnDemand Portal Documentation \n OnDemand Job template for OpenFOAM \n \n \n Visit us at ISC24 - Microsoft Booth #F30 for a live demo of this integration on Wednesday, the 15th | 9 AM - 12.30 PM \n \n Introduction \n As of today, several tools, frameworks and automations allow the deployment of HPC infrastructures in a cloud environment. \n \n Azure CycleCloud enables users and IT administrators to run cloud-only or hybrid (bursting) clusters leveraging traditional HPC schedulers like OpenPBS, SGE, Altair PBS Professional and Slurm. \n \n Azure CycleCloud provides the possibility to preserve standard submission interfaces from on-premises HPC systems, without the need to re-architect or alter by any means the standard simulation workflows. In this way, end users can keep running and using their standard applications without any disruption. \n \n Azure CycleCloud provides out of the box the possibility for interaction and cluster operations only using a standard SSH connection for the end users or scheduler default APIs (e.g. Slurm APIs). \n \n This blog post presents an Azure CycleCloud project allowing to deploy an Open OnDemand portal, an efficient open-source web portal for job submission, job monitoring, file management and remote desktop/application sessions. \n \n This project allows to deploy an Open OnDemand Portal like az-hop, but allowing the user to just deploy a single VM with a portal to be attached to an already existing and configured Azure CycleCloud cluster. \n \n What is required as prerequisites \n \n The project requires a working installation of Azure CycleCloud. \n At the same time, Open OnDemand portal is meant to be attached to an existing Slurm or OpenPBS cluster deployed in Azure CycleCloud. Support for additional schedulers is planned to be available in future releases. \n The deployment relies on an Azure Key Vault and a Managed Identity for secret access during the deployment. The following elements need to be uploaded depending on the selected SSL and authentication mechanism need in the Azure Key Vault:\n \n SSL certificate Required to avoid using self-signed certificate. \n Secret for the OIDC Client This is required in case the authentication mechanism is OIDC. This will require an Entra ID app registration \n LDAPS CA Certificate This is required only in case of OIDC Dex LDAP if the LDAPS server requires a dedicated certification authority for SSL connections \n LDAP Service Account BIND password This is required only in case of OIDC Dex LDAP among with a read only account \n \n \n \n Basic authentication option and self-signed SSL certificates should be considered only for test/development purpose, away from production systems because of the security concerns \n \n How to deploy \n The project can be deployed following the step-by-step guide provided in the README of the GitHub repository. \n The steps involved in getting the project accessible inside Azure CycleCloud are: \n \n Definition of a custom cluster-init project source in Azure CycleCloud \n Import of the OnDemand Portal template in Azure CycleCloud \n \n \n What the project will deliver \n The project will deploy a single sever hosting an Open OnDemand portal allowing the users to specify: \n \n The general server configuration in terms of Azure VM Size, Virtual Network, IP Address and server name. \n The cluster to which the OnDemand Portal should be attached in terms of scheduler type (OpenPBS/Slurm) and scheduler version \n The shared NFS file system to be attached in /shared and /sched as common shared file systems for users and file management \n The OnDemand Portal configuration in terms of:\n \n Authentication\n \n OIDC \n OIDC Dex LDAP \n Basic PAM (insecure) \n \n \n SSL termination\n \n Bring-your-own certificate \n Self-signed (insecure) \n \n \n \n \n \n All the secrets and certificates involved in the configuration are safely stored inside an Azure Key Vault which is accessed by the Azure CycleCloud nodes through a Managed Identity. \n After the cluster is successfully deployed, the user will be able to have a basic interface to access the main OnDemand functionality: \n \n In-browser SSH connection \n \n \n \n \n Ability to upload/download files \n \n \n \n \n Possibility to customize the OnDemand portal configuration with dedicated Interactive Apps templates. \n \n \n Additional considerations \n Open OnDemand portal must be able to map the username provided by an external authentication mechanism like OIDC or OIDC Dex LDAP to a local Linux user account. This will be the Linux account that will be impersonating the user and interacting with the cluster through Open OnDemand. \n This is something that remains responsibility of the user following the Open OnDemand documentation. \n \n An easy way to realize this is to enable Azure CycleCloud EntraID and using the following additional configuration in Open OnDemand Portal: \n \n \n user_map_match: '^([^@]+)@example.com$'\noidc_remote_user_claim: \"email\" \n \n \n This will map the users authenticated from EntraID directly to a local user in the system. The configuration above can be inputted directly from Azure CycleCloud UI and respectively: \n \n the user map match in the additional configuration \n the OIDC Remote user claim in the authentication section \n \n \n Creation of Interactive Desktop Sessions with auto-scaling in Azure CycleCloud \n As already extensively implemented and developed in az-hop, Open OnDemand allows to create on-demand interactive Desktop Session or Interactive App session with nodes dynamically allocated by Azure CycleCloud. \n \n The underlying concept is that a Desktop session will be submitted as a job to the scheduler and Azure CycleCloud will allocate the required nodes for the session duration. \n \n In order to get this up in OnDemand, the steps are: \n \n Defining a dedicated nodearray in Azure CycleCloud for the purpose. There is an example of a Slurm cluster template based on 3.0.6 version of the CycleCloud project inside the repository. \n Building a dedicated OS image on Azure with the required Desktop environment. An example script for non-accelerated GPU environments is available in the repository. For GPU accelerated environment it is possible to install also the dedicated driver and VirtualGL. \n Configuring Open OnDemand portal Desktop form attributes and enabling reverse proxy. \n \n There is the plan in a future project release to integrate this configuration also in an automation. \n \n Creation of a submission batch application \n In a similar way of interactive session, Open OnDemand allows to define submission forms for specific batch submission logics. \n \n For example, here an example of integrating OpenFOAM submission in the OpenOnDemand portal: \n \n \n \n Once the job is finished, it can be visualized using a Desktop session GPU accelerated: \n \n \n \n \n \n \n Visit us at ISC24 - Microsoft Booth #F30 for a live demo of this integration on Wednesday, the 15th | 9 AM - 12.30 PM \n 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