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17 TopicsJoin Microsoft @ SC25: Experience HPC and AI Innovation
Supercomputing 2025 is coming to St. Louis, MO, November 16–21! Visit Microsoft Booth #1627 to explore cutting-edge HPC and AI solutions, connect with experts, and experience interactive demos that showcase the future of compute. Whether you’re attending technical sessions, stopping by for a coffee, or joining our partner events, we’ve got something for everyone. Booth Highlights Alpine Formula 1 Showcar: Snap a photo with a real Alpine F1 car and learn how high-performance computing drives innovation in motorsports. Silicon Wall: Discover silicon diversity—featuring chips from our partners AMD and NVIDIA, alongside Microsoft’s own first-party silicon: Maia, Cobalt, and Majorana. NVIDIA Weather Modeling Demo: See how AI and HPC predict extreme weather events with Tomorrow.io and NVIDIA technology. Coffee Bar with Barista: Enjoy a handcrafted coffee while you connect with our experts. Immersive Screens: Watch live demos and visual stories about HPC breakthroughs and AI innovation. Hardware Bar: Explore AMD EPYC™ and NVIDIA GB200 systems powering next-generation workloads. Whether you’re attending technical sessions, stopping by for a coffee and chat with our team, or joining our partner events, we’ve got something for everyone. Conference Details Conference week: Sun, Nov 16 – Fri, Nov 21 Expo hours (CST): Mon, Nov 17: 7:00–9:00 PM (Opening Night) Tue, Nov 18: 10:00 AM–6:00 PM Wed, Nov 19: 10:00 AM–6:00 PM Thu, Nov 20: 10:00 AM–3:00 PM Customer meeting rooms: Four Seasons Hotel Quick links RSVP — Microsoft + AMD Networking Reception (Tue, Nov 18): https://aka.ms/MicrosoftAMD-Mixer RSVP — Microsoft + NVIDIA Panel Luncheon (Wed, Nov 19): Luncheon is now closed as the event is fully booked. Earned Sessions (Technical Program) Sunday, Nov 16 Session Type Time (CST) Title Microsoft Contributor(s) Location Tutorial 8:30 AM–5:00 PM Delivering HPC: Procurement, Cost Models, Metrics, Value, and More Andrew Jones Room 132 Tutorial 8:30 AM–5:00 PM Modern High Performance I/O: Leveraging Object Stores Glenn Lockwood Room 120 Workshop 2:00–5:30 PM 14th International Workshop on Runtime and Operating Systems for Supercomputers (ROSS 2025) Torsten Hoefler Room 265 Monday, Nov 17 Session Type Time (CST) Title Microsoft Contributor(s) Location Early Career Program 3:30–4:45 PM Voices from the Field: Navigating Careers in Academia, Government, and Industry Joe Greenseid Room 262 Workshop 3:50–4:20 PM Towards Enabling Hostile Multi-tenancy in Kubernetes Ali Kanso; Elzeiny Mostafa; Gurpreet Virdi; Slava Oks Room 275 Workshop 5:00–5:30 PM On the Performance and Scalability of Cloud Supercomputers: Insights from Eagle and Reindeer Amirreza Rastegari; Prabhat Ram; Michael F. Ringenburg Room 267 Tuesday, Nov 18 Session Type Time (CST) Title Microsoft Contributor(s) Location BOF 12:15–1:15 PM High Performance Software Foundation BoF Joe Greenseid Room 230 Poster 5:30–7:00 PM Compute System Simulator: Modeling the Impact of Allocation Policy and Hardware Reliability on HPC Cloud Resource Utilization Jarrod Leddy; Huseyin Yildiz Second Floor Atrium Wednesday, Nov 19 Session Type Time (CST) Title Microsoft Contributor(s) Location BOF 12:15–1:15 PM The Future of Python on HPC Systems Michael Droettboom Room 125 BOF 12:15–1:15 PM Autonomous Science Network: Interconnected Autonomous Science Labs Empowered by HPC and Intelligent Agents Joe Tostenrude Room 131 Paper 1:30–1:52 PM Uno: A One‑Stop Solution for Inter‑ and Intra‑Data Center Congestion Control and Reliable Connectivity Abdul Kabbani; Ahmad Ghalayini; Nadeen Gebara; Terry Lam Rooms 260–267 Paper 2:14–2:36 PM SDR‑RDMA: Software‑Defined Reliability Architecture for Planetary‑Scale RDMA Communication Abdul Kabbani; Jie Zhang; Jithin Jose; Konstantin Taranov; Mahmoud Elhaddad; Scott Moe; Sreevatsa Anantharamu; Zhuolong Yu Rooms 260–267 Panel 3:30–5:00 PM CPUs Have a Memory Problem — Designing CPU‑Based HPC Systems with Very High Memory Bandwidth Joe Greenseid Rooms 231–232 Paper 4:36–4:58 PM SparStencil: Retargeting Sparse Tensor Cores to Scientific Stencil Computations Kun Li; Liang Yuan; Ting Cao; Mao Yang Rooms 260–267 Thursday, Nov 20 Session Type Time (CST) Title Microsoft Contributor(s) Location BOF 12:15–1:15 PM Super(computing)heroes Laura Parry Rooms 261–266 Paper 3:30–3:52 PM Workload Intelligence: Workload‑Aware IaaS Abstraction for Cloud Efficiency Anjaly Parayil; Chetan Bansal; Eli Cortez; Íñigo Goiri; Jim Kleewein; Jue Zhang; Pantea Zardoshti; Pulkit Misra; Raphael Ghelman; Ricardo Bianchini; Rodrigo Fonseca; Saravan Rajmohan; Xiaoting Qin Room 275 Paper 4:14–4:36 PM From Deep Learning to Deep Science: AI Accelerators Scaling Quantum Chemistry Beyond Limits Fusong Ju; Kun Li; Mao Yang Rooms 260–267 Friday, Nov 21 Session Type Time (CST) Title Microsoft Contributor(s) Location Workshop 9:00 AM–12:30 PM Eleventh International Workshop on Heterogeneous High‑performance Reconfigurable Computing (H2RC 2025) Torsten Hoefler Room 263 Booth Theater Sessions Monday, Nov 17 — 7:00 PM–9:00 PM Time (CST) Session Title Presenter(s) 8:00–8:20 PM Inside the World’s Most Powerful AI Data Center Chris Jones 8:30–8:50 PM Transforming Science and Engineering — Driven by Agentic AI, Powered by HPC Joe Tostenrude Tuesday, Nov 18 — 10:00 AM–6:00 PM Time (CST) Session Title Presenter(s) 11:00–11:50 AM Ignite Keynotes 12:00–12:20 PM Accelerating AI workloads with Azure Storage Sachin Sheth; Wolfgang De Salvador 12:30–12:50 PM Accelerate Memory Bandwidth‑Bound Workloads with Azure HBv5, now GA Jyothi Venkatesh 1:00–1:20 PM Radiation & Health Companion: AI‑Driven Flight‑Dose Awareness Olesya Sarajlic 1:30–1:50 PM Ascend HPC Lab: Your On‑Ramp to GPU‑Powered Innovation Daniel Cooke (Oakwood) 2:00–2:20 PM Azure AMD HBv5: Redefining CFD Performance and Value in the Cloud Rick Knoechel (AMD) 2:30–2:50 PM Empowering High Performance Life Sciences Workloads on Azure Qumulo 3:00–3:20 PM Transforming Science and Engineering — Driven by Agentic AI, Powered by HPC Joe Tostenrude 4:00–4:20 PM Unleashing AMD EPYC on Azure: Scalable HPC for Energy and Manufacturing Varun Selvaraj (AMD) 4:30–4:50 PM Automating HPC Workflows with Copilot Agents Xavier Pillons 5:00–5:20 PM Scaling the Future: NVIDIA’s GB300 NVL72 Rack for Next‑Generation AI Inference Kirthi Devleker (NVIDIA) 5:30–5:50 PM Enabling AI and HPC Workloads in the Cloud with Azure NetApp Files Andy Chan Wednesday, Nov 19 — 10:00 AM–6:00 PM Time (CST) Session Title Presenter(s) 10:30–10:50 AM AI‑Powered Digital Twins for Industrial Engineering John Linford (NVIDIA) 11:00–11:20 AM Advancing 5 Generations of HPC Innovation with AMD on Azure Allen Leibovitch (AMD) 11:30–11:50 AM Intro to LoRA Fine‑Tuning on Azure Christin Pohl 12:00–12:20 PM VAST + Microsoft: Building the Foundation for Agentic AI Lior Genzel (VAST Data) 12:30–12:50 PM Inside the World’s Most Powerful AI Data Center Chris Jones 1:00–1:20 PM Supervised GenAI Simulation – Stroke Prognosis (NVads V710 v5) Kurt Niebuhr 1:30–1:50 PM What You Don’t See: How Azure Defines VM Families Anshul Jain 2:00–2:20 PM Hammerspace Tier 0: Unleashing GPU Storage Performance on Azure Raj Sharma (Hammerspace) 2:30–2:50 PM GM Motorsports: Accelerating Race Performance with AI Physics on Rescale Bernardo Mendez (Rescale) 3:00–3:20 PM Hurricane Analysis and Forecasting on the Azure Cloud Salar Adili (Microsoft); Unni Kirandumkara (GDIT); Stefan Gary (Parallel Works) 3:30–3:50 PM Performance at Scale: Accelerating HPC & AI Workloads with WEKA on Azure Desiree Campbell; Wolfgang De Salvador 4:00–4:20 PM Pushing the Limits of Performance: Supercomputing on Azure AI Infrastructure Biju Thankachen; Ojasvi Bhalerao 4:30–4:50 PM Accelerating Momentum: Powering AI & HPC with AMD Instinct™ GPUs Jay Cayton (AMD) Thursday, Nov 20 — 10:00 AM–3:00 PM Time (CST) Session Title Presenter(s) 11:30–11:50 AM Intro to LoRA Fine‑Tuning on Azure Christin Pohl 12:00–12:20 PM Accelerating HPC Workflows with Ansys Access on Microsoft Azure Dr. John Baker (Ansys) 12:30–12:50 PM Accelerate Memory Bandwidth‑Bound Workloads with Azure HBv5, now GA Jyothi Venkatesh 1:00–1:20 PM Pushing the Limits: Supercomputing on Azure AI Infrastructure Biju Thankachen; Ojasvi Bhalerao 1:30–1:50 PM The High Performance Software Foundation Todd Gamblin (HPSF) 2:00–2:20 PM Heidi AI — Deploying Azure Cloud Environments for Higher‑Ed Students & Researchers James Verona (Adaptive Computing); Dr. Sameer Shende (UO/ParaTools) Partner Session Schedule Tuesday, Nov 18 Date Time (CST) Title Microsoft Contributor(s) Location Nov 18 11:00 AM–11:50 AM Cloud Computing for Engineering Simulation Joe Greenseid Ansys Booth Nov 18 1:00 PM–1:30 PM Revolutionizing Simulation with Artificial Intelligence Joe Tostenrude Ansys Booth Nov 18 4:30 PM–5:00 PM [HBv5] Jyothi Venkatesh AMD Booth Wednesday, Nov 19 Date Time (CST) Title Microsoft Contributor(s) Location Nov 19 11:30 AM–1:30 PM Accelerating Discovery: How HPC and AI Are Shaping the Future of Science (Lunch Panel) Andrew Jones (Moderator); Joe Greenseid (Panelist) Ruth's Chris Steak House Nov 19 1:00 PM–1:30 PM VAST and Microsoft Kanchan Mehrotra VAST Booth Demo Pods at Microsoft Booth Azure HPC & AI Infrastructure Explore how Azure delivers high-performance computing and AI workloads at scale. Learn about VM families, networking, and storage optimized for HPC. Agentic AI for Science See how autonomous agents accelerate scientific workflows, from simulation to analysis, using Azure AI and HPC resources. Hybrid HPC with Azure Arc Discover how Azure Arc enables hybrid HPC environments, integrating on-prem clusters with cloud resources for flexibility and scale. Ancillary Events (RSVP Required) Microsoft + AMD Networking Reception — Tuesday Night When: Tue, Nov 18, 6:30–10:00 PM (CST) Where: UMB Champions Club, Busch Stadium RSVP: https://aka.ms/MicrosoftAMD-Mixer Microsoft + NVIDIA Panel Luncheon — Wednesday When: Wed, Nov 19, 11:30 AM–1:30 PM (CST) Where: Ruth’s Chris Steak House Topic: Accelerating Discovery: How AI and HPC Are Shaping the Future of Science Panelists: Dan Ernst (NVIDIA); Rollin Thomas (NERSC); Joe Greenseid (Microsoft); Antonia Maar (Intersect360 Research); Fernanda Foertter (University of Alabama) RSVP: Luncheon is now closed as the event is fully booked. Conclusion We’re excited to connect with you at SC25! Whether you’re exploring our booth demos, attending technical sessions, or joining one of our partner events, this is your opportunity to experience how Microsoft is driving innovation in HPC and AI. Stop by Booth #1627 to see the Alpine F1 showcar, explore the Silicon Wall featuring AMD, NVIDIA, and Microsoft’s own chips, and enjoy a coffee from our barista while networking with experts. Don’t forget to RSVP for our Microsoft + AMD Network Reception and Microsoft + NVIDIA Panel Luncheon See you in St. Louis!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.