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![© Microsoft Corporation
Most performant infrastructure
Specialized infrastructure
for Super Computing
“The bare performance figures [of Azure] are best
of all cases studied, even when compared with the
traditional supercomputing system of reference.”
HPC Benchmarking Study, Feb 2017, Exabyte Inc.
Virtual Machines, Cray in Azure
Performant hybrid
storage with Azure
Easy management with Batch and Azure CycleCloud](https://image.slidesharecdn.com/cruihpconazure-190306141918/85/HPC-on-Azure-for-Reserach-15-320.jpg)
Uploaded byJürgen Ambrosi
HPC on Azure for Reserach
The document discusses the advantages of high performance computing (HPC) in Azure, highlighting the static nature of traditional compute environments versus the dynamic needs of modern research and business. It emphasizes the benefits of transitioning to a cloud-based HPC, such as elasticity, optimized resource usage, and specialized infrastructure for various applications including machine learning and AI. Additionally, it details Azure's capabilities for managing HPC workloads, including hybrid solutions, advanced infrastructure, and robust governance and cost management features.
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Similar to HPC on Azure for Reserach
HPC on Azure for Reserach
- 1. High Performance Computing(HPC) Running compute-intensive workloads in Azure Silvia Spera Azure Infrastructure Technical Specialist CRUI Roma, 1 marzo 2019
- 2. © Microsoft Corporation Thechallenge of modern computing Your technical and business needs are dynamic, but your compute environment is static.
- 4. Research is theLifeblood of Scientific, Engineering, Health, Social, Technological Breakthroughs
- 5. Factory Layout Clinical Trial Simulation Rocket Design Self-driving Cars Harddisk design Materials Science Fundamental Science Architecture & Engineering Entertainment Genomics Drug Design Environment Impact Computational Chemistry Quantum computing Cancer Research Circuit Design Risk Management Diagnostics Crash Testing Machine Learning Product Design & Safety Security/ Encryption Logistics Data Science
- 6. © Microsoft Corporation Demandfor HPC infrastructure On-premises On-premises HPC
- 7. © Microsoft Corporation On-premisesHPC Demand for HPC infrastructure On-premises Challenges with Data analyticsAI IoT New business demands Regulations Keeping up with business demands Maximizing your investment Siloed environments limiting collaboration
- 8. © Microsoft Corporation Demandfor HPC infrastructure On-premises The HPC Cloud Opportunity Variable demand Fixed demand Expand your HPC environment to the Cloud The elasticity of the cloud provides the perfect accommodation for variable demands of compute resources.
- 9. © Microsoft Corporation Demandfor HPC infrastructure The HPC Cloud Opportunity All demand Build your HPC environment in the Cloud A fully native, cloud- based HPC environment ensures optimized business agility by accommodating an on- demand usage model for compute resources
- 10. © Microsoft Corporation Existing apps Clone tocloud Start using cloud without rewriting applications Hybrid workflows Simple to optimize infrastructure Cloud-native apps Create new services and modernize apps that matter Azure for every HPC pattern End-to-end workflows in the cloud Cloud workflows
- 11. © Microsoft Corporation Azurevalue for High Performance Computing Most performant infrastructure Granular cost control and governance Open and integrated
- 12. © Microsoft Corporation ProductiveTrustedHybrid Azure HPC Value Pillars
- 13.
- 15. © Microsoft Corporation Mostperformant infrastructure Specialized infrastructure for Super Computing “The bare performance figures [of Azure] are best of all cases studied, even when compared with the traditional supercomputing system of reference.” HPC Benchmarking Study, Feb 2017, Exabyte Inc. Virtual Machines, Cray in Azure Performant hybrid storage with Azure Easy management with Batch and Azure CycleCloud
- 16. © Microsoft Corporation Specializedinfrastructure for HPC and AI Cray in Azure IB Connected CPU/GPU/Storage available in cloud High-performance VMs Tightly coupled parallel jobs GPU-enabled VMs NV—Graphic-based applications NC—Advanced simulation ND—Artificial Intelligence (Deep Learning) H N Compute-optimized VMs Batch processing, Monte Carlo simulations F Large memory VMs Large databases M FPGA PGA Microservices— AI/Edge >80,000 IOPs - Premium Storage Low latency, high throughput apps Most performant infrastructure RDMA over …. For multi-node scaling
- 17. © Microsoft Corporation HPCResources on Azure Azure HPC VMs Azure GPUs Bare Metal
- 18. Specialized Compute Fleet VirtualMachines – HPC FPGA Microservices – AI/Edge IB Connected CPU/GPU/Storage available in cloud NC2 – Advanced Sim (P100-X) ND1 – AI Inferencing (P40) ND2* – AI Training (V100/V100 SXM) H N A D F G L
- 19. No-compromise CPU andGPU based resources • Up to 16 cores, 3.2 GHz E5-2667 V3 Haswell processor • Up to 224 GB DDR4 memory, 14GB per core • FDR InfiniBand @ 56 Gbps, 2.6 microsecond latency • 2 TB of local SSD • Up to 4 NVIDIA Tesla K80 GPUs • Up to 24 cores • Up to 224 GiB memory • Up to 1440 GiB of local SSD • FDR InfiniBand • Up to 4 NVIDIA Tesla M60 GPUs • Up to 24 cores • Up to 224 GiB memory • Up to 1440 GiB of local SSD • Up to 4 NVIDIA Pascal P40 GPUs • Up to 24 cores • Up to 448 GiB memory • Up to 3 TB of local SSD • FDR InfiniBand • Up to 4 NVIDIA Pascal P100 GPUs • Up to 24 cores • Up to 448 GiB memory • Up to 3 TB of local SSD • FDR InfiniBand • Up to 4 NVIDIA Volta V100 GPUs • Up to 24 cores • Up to 448 GiB memory • Up to 3 TB of local SSD • FDR InfiniBand HPC VMs on Azure • Up to 44 cores, Intel Xeon Platinum processor • Up to 352 GB DDR4 memory, 8GB per core • EDR InfiniBand @ 100 Gbps • 700 GB NVMe • Up to 60 cores, AMD EPYC processor • Up to 240 GB DDR4 memory, 4GB per core • EDR InfiniBand @ 100 Gbps • 700 GB NVMe • Up to 4 NVIDIA Tesla M60 GPUs • Up to 24 cores • Up to 448 GiB memory • Up to 2,948 GiB of local SSD H-Series: Most powerful CPU virtual machines with optional RDMA N-Series: GPU virtual machines specialized for graphic-intensive workloads
- 20. VM Scale Sets Deploy& manage groups of identical VMs at very large scale Scale multiple VM sets utilizing different VM types Automatically scale by policy without pre-provisioning Enjoy steep discounting with low priority VMs Simple ways to scale up your environment
- 21.
- 22. Rendering Deep-Learning/AIHPC/SimulationVisualization Oil &Gas and SciencesHealthcare & ResearchMedia, Entertainment & Gaming AerospaceAutomotive Financial Services RetailManufacturing
- 23. GPUs enable Endto End Workflows in the Cloud Storage & Shared Workspace CONSUME WorkstationsCompute Design & Create CREATE VM GPU Satellite officeDesign review Post-Processing 3D Print / Prototype Main office On the road Simulate & Render
- 24. • Excellent foraccelerating machine learning and HPC workloads • Volta SXM GPU instances – 8X NVIDIA V100 GPUs interconnected with NVLink mesh • Tensor Core technology to deliver over 100 TFLOPS of deep learning performance • Skylake based processor with premium storage support (SSD backed) • Specs: • 640 NVIDIA Tensor Core • FP64 - 7.8 TFLOPS of double precision floating point performance • FP32 – 15.7 TFLOPS of single precision performance • GPU Memory 16 GB • 300 GB/s GPU interconnect through NVLink ND v2 – Volta Generation GPU Compute ND40s_v3 Cores 40 cores GPU 8 x V100 SXM Memory 768 GB Local Disk ~1.3 TB SSD Network Azure Network + NVLink GPU interconnect http://aka.ms/AzureNDv2GPUs
- 25. • Get fasterresults for the your graphic intensive 2D and 3D applications with visualization optimized GPU instances featuring NVIDIA Tesla M60 GPUs • Broadwell based CPU processor with doubled memory from previous generation (up to 448 GB) • Premium storage support (SSD backed) • Grid license included with each GPU instance • Specs: • 2048 NVIDIA CUDA cores per GPU • 36 H.264 1080p30 streams • GPU Memory 8 GB/GPU NV v2 – Updated GPU Visualization Platform NV6s_v2 NV12s_v2 NV24s_v2 Cores 6 12 24 GPU 1 x M60 2 x M60 4 x M60 Memory 112 GB 224 GB 448 GB Local Disk ~700 GB SSD ~1.4 TB SSD ~3 TB SSD Network Azure Network Azure Network Azure Network GRID Licenses 1 2 4 http://aka.ms/AzureNVv2GPUs
- 26. GPU Accelerated ComputeFamily NC NC v2 NC v3 Cores 6, 12, 24 6, 12, 24 6, 12, 24 GPU 1, 2, or 4 K80 GPU 1, 2, or 4 P100 GPU 1, 2, or 4 V100 GPU Memory 56/112/224 GB 112/224/448 GB 112/224/448 GB Local Disk ~380/~680/~1.5 TB SSD ~700/~1.4/~3 TB SSD ~700/~1.4/~3 TB SSD Network Azure Network + InfiniBand (largest size only) GPU Accelerated Deep Learning Family GPU Visualization Family ND v1 ND v2 NV v1 Nv v2 Cores 6, 12, 24 40 6, 12, 24 6, 12, 24 GPU 1, 2, or 4 P40 GPU 8 V100 SXM GPU 1, 2, or 4 M60 GPU 1, 2, or 4 M60 GPU Memory 112/224/448 GB 768 GB 56/112/224 GB 112/224/448 GB Local Disk ~700/~1.4/~3 TB SSD ~1.3 TB SSD ~380/~680/~1.5 TB SSD ~700/~1.4/~3 TB SSD Network Azure Network + InfiniBand (largest size only) Azure Network + NVLink GPU interconnect Azure Network Azure Network
- 27. © Microsoft Corporation BareMetal options on Azure
- 28. A dedicated supercomputeron your virtual network Innovate faster to solve your toughest challenges Access to advanced cloud solutions and AI Bring your simulation data and services closer together Simplify the management of your infrastructure Cray in Azure
- 29. © Microsoft Corporation YourCray supercomputer running in Azure, close to your Azure services Rely on a dedicated, built- to-spec Cray XC or SC supercomputer for your most demanding workloads Connect to the broad range of Azure services on your Azure Virtual Network Access the Cray as a managed service in the cloud as OpEx instead of maintaining a specialized infrastructure with high up-front costs Most performant infrastructure Cray in Azure
- 30. Microsoft Azure DataCenter Customer’s Virtual Network OFFERINGOFFERING Dedicated XC or CS series with attached ClusterStor storage systems customized for each customer and installed in Microsoft owned data center, on the customer’s virtual network. Allows for capacity expansion without facilities management. Long term commitment required. Seamless connectivity to Azure Data Center network and all Azure services Cray provides sys admin, monitoring, maintenance & support via Cray’s (or Customer’s) Virtual Network on Azure Microsoft provide hosting, L1 support and Azure Data Center network to Azure services Customers access and run M&S and AI & Advanced Analytics workloads on XC’s an ExpressRoute connection Azure Services High Speed Network Microsoft Cray Customer Data LakeVM’s IOT Hub AI & ML Azure Support Cray Support Storage CycleActive Directory App Services
- 32. © Microsoft Corporation VirtualCompute Farm Avere Virtual FXT Bucket 1 Bucket 2 Bucket nAzure Blob Avere Physical FXT NAS Object Customer needs Azure delivers Low-latency file access Edge-core architecture Scalable performance and HA Scale-out clustering (3 to 24 nodes per cluster) Familiar NFS and SMB interfaces FlashCloud file system for object storage Manage as a single pool of storage Global namespace (GNS), FlashMove Data protection Cloud snapshots, FlashMirror High security AES-256 encryption (FIPS 140-2 compliant), KMIP Efficiency LZ4 compression Most performant infrastructure Performant hybrid storage with Azure
- 33. © Microsoft Corporation MicrosoftAvere vFXT Faster, more accessible data for Edge HPC High-performance file access for HPC applications Performance. Automatic identification and caching of hot data needed for demanding workloads, minimizing storage latency for heavy-read environments. Access. File-based applications can access Azure compute resources from either on-premises network-attached storage (NFS/SMB) or Azure Blob (REST) Flexibility. Get the flexibility of having the scale of Azure at your fingertips to support critical workloads Azure Marketplace Now in Preview Media & Entertainment | Life Sciences | Financial Services | Manufacturing | Oil & Gas | Government
- 34. Building a HybridCloud – Avere vFXT for Azure Virtual Network Subnet Your Azure Storage Account Mountpoint Address Range HPC Cluster Azure Blob Container Avere vFXT Cluster NFS 3 Storage Endpoint Azure subscription Mountpoint Aliases (RRDNS) Gateway Subnet Your Data Center ExpressRoute /export1 Network Attached Storage
- 35. © Microsoft Corporation Mostperformant infrastructure Fluent 280M Cell Open Race Car Model Benchmark Scaling on Microsoft Azure WallTime(s) Scale(X) 2000 1800 1600 1400 1200 1000 800 600 400 200 0 9.000 8.000 7.000 6.000 5.000 4.000 3.000 2.000 1.000 0.000 128 256 384 512 640 768 896 1024 Total Wall Time Scale Theoretical Cores
- 36. © Microsoft Corporation AzureCycleCloud running clusters Azure Batch running jobs Azure clusterHybrid/burstHPC as a service On-premises Client Client App or Web portal All HPC resources in the cloud Azure Batch Resourcepool Client Computenodes Head node Compute nodes Client Head node Compute nodes On-premises All HPC resources in the cloud Most performant infrastructure Services for workload management
- 37. © Microsoft Corporation AzureBatch API for creating pools of resources and the schedule jobs and tasks on them PaaS Cloud Services IaaS VM / VMSS Hardware Get and manage VMs Start the tasks Queue tasksMove task input and output Install task applications Scale up and downTask failure? Task frozen? Manage and authenticate users Azure Batch VM management and job scheduling
- 38. Access via APIs,CLIs, and UIs • .NET, Java, Node.js, Python, REST • PowerShell, x-plat Azure CLI • Azure Portal, Batch Labs x-plat client UI Choice of VMs • Windows or Linux. Choose the VM size most suited to your application • Standard or custom images • Automatically scale the number of VMs to maximize utilization • Windows pool can use AHUB • Use low-priority VMs Rich app management • Get apps from blobs, Batch app packages, package managers, custom VM images • Docker container images Job scheduling • Supports both embarrassingly parallel and tightly-coupled MPI jobs • Run > 1 task in parallel per node • Detect and retry failed tasks • Can set max execution time for jobs and tasks • Task dependencies • Job prep and cleanup tasks Monitoring • VM monitoring and auto-recover • Metrics and logs available via Portal and API Azure Batch Capabilities
- 39. © Microsoft Corporation AzureCycleCloud runs compute clusters IT management Link workflows for internal and external clouds Use Active Directory for authentication and authorization Provide secure and consistent access User empowerment Able to cloud-enable existing workflows Enable instant access to resources Provide auto-scaling, error handling Business management Able to link usage to spend Provide tools to manage and control costs
- 40. Hybrid/Clustered Big ComputeLifecycle Optimization Provisioning Cluster Configuration Monitoring Internal Admin Scope Configure Run on Cloud OptimizeUser
- 41. On-Premise Cluster for simulationand predictive analyses Gap #1: Hybrid / Migration Using templates to mirror the on-premise environment, CycleCloud provisions an identical environment into which the application can be loaded without rewriting User Apps & Scripts Filling the gaps in moving a strategic HPC application environment to Azure H Nc D, F vNet Avere vFXT Engineer, Quant, or Data Scientist Line of Business Manager Gap #2: Governance CycleCloud solves governance issues by providing a policy-based system for access, authorizations, cost controls, and compliance audit reporting. IT/Admin Azure CycleCloud Scenario:
- 42. Making Users andIT Successful LOB & User Inputs IT LOB Inputs Internal
- 43. • • • • • When to UseAzure Batch or CycleCloud Azure Batch – Running jobsCycleCloud – Running clusters
- 44. © Microsoft Corporation Openand integrated Robust partner ecosystem Microsoft and open source software support
- 45. © Microsoft Corporation Robustpartner ecosystem
- 46. © Microsoft Corporation Microsoftand open source software support .NET
- 47. Optimize cloud efficiency Monitor cloud spend Driveorganizational accountability With Cost Management, you can: Across your multi-cloud environment
- 48. © Microsoft Corporation Costsavings Ensures Reserved Instances for persistent infrastructure Offers flexible consumption and cost savings with low-priority VMs Provides per-second billing for VMs Azure services
- 49. © Microsoft Corporation Thelargest compliance portfolio in the industry
- 50. ENERGY & UTILITIES SeismicProcessing Reservoir Simulation Digital Oil Fields Smart Grids Market Use-Cases and Opportunities CYBER SECURITY Insider Threat Detection Continuous Monitoring Data Loss Monitoring and Analysis GOV’T AND DEFENSE National security High energy physics Civil engineering Material science FINANCIAL SERVICES Risk and Stress Testing Strategy Back Testing Anti Money Laundering KYC – Know Thy Customer EARTH SCIENCES Weather Prediction Climate change Oceanography Air Quality HEALTHCARE AND LIFE SCIENCES Personalized medicine Genomic sequencing Drug Discovery Early Disease Detection through Advanced Imaging MANUFACTURING Air Flow Modeling Crash Simulation Predictive analytics Autonomous vehicles HIGHER EDUCATION Astrophysics Molecular Modeling Computational chemistry Neuro informatics COMMUNICATIONS AND MEDIA Social media insights Network intelligence Image Classification CONSUMER-DRIVEN INDUSTRIES Consumer Sentiment Best Next Offer Analytics Customer Churn Supply Chain Optimization Dynamic Pricing Inventory Forecasting Unleashed by data and advanced computing, AI and Machine Learning are impacting every industry
- 51. We are committedto the Research community 51 We want the cloud to work the way the academic research community works. That’s why we’re waiving the Internet egress fee for qualified customers. • Ensures predictability and stability in cloud costs • Removes a significant barrier to cloud adoption, allowing researchers to move data freely • Paves the way for researchers to accelerate the pace of the important work they’re doing
- 52. Researchers in SaoPaolo, Brazil study how carbon dioxide, water, nitrogen, and other nutrients cycle through plants, animals, and microorganisms in this complex ecosystem using 700 sensors in 15 forest plots https://www.microsoft.com/en-us/research/blog/cloud- computing-helps-make-sense-of-cloud-forests/
- 53. Researchers at Universityof Texas used predictive modelling to calculate flood predictions to support the efforts of the first responders at risk of potential flooding. https://www.microsoft.com/en-us/research/blog/coping- with-floodsof-water-and-data/
- 54. Researchers in theparticle physics group at the University of Victoria created a flexible cloud system for large workloads such as high- energy physics computing. The system also streamlined user workflow, sparking collaboration in the research community. http://customers.microsoft.com/en-us/story/university- victoria-azure-cloud-services-canada-education
- 55. © Microsoft Corporation Financialservices Workloads Key partnerships
- 56. © Microsoft Corporation Financialservices workloads Monte Carlo simulations Risk analytics CCAR FRTB Regulatory reporting Scripts at scale Batch processing Code analysis Unit testing Regression testing
- 57. © Microsoft Corporation Keyfinancial services partners
- 58. © Microsoft Corporation Achievedconsistent experience in Azure on-premises with familiar tools and processes Gained cost savings of up to 55 percent and year-over-year infrastructure savings by scaling down unused compute Improved customer service with quicker data processing and faster results
- 59.
- 60. © Microsoft Corporation AzureHPC for the automotive industry Finite Element Analysis (FEA) Computational Fluid Dynamics (CFD) Multibody Dynamics (MBD) Simulation Program with Integrated Circuit Emphasis (SPICE) analysis Optimization HPC/Simulation Concept vehicle styling Digital concept vehicle Clay model replacement Marketing campaign Web, media, print Engineering Windshield cockpit glare Rendering Cloud-based engineering (cloud VDI) Cloud-based post visualization of simulations Visualization Autonomous driving Advanced Driver Assistance Systems (ADAS) Adaptive cruise control Auto parking Navigation systems Collision avoidance/warning Lane departure warning Deep Learning/AI
- 61. © Microsoft Corporation Keyautomotive partners
- 62. © Microsoft Corporation Stayahead of the competition by accessing a powerful infrastructure for real-time race simulations and deep analysis of track, driver and vehicle data Ensure significant cost savings versus building an on-premises HPC environment Provide rapid decision making using Azure Machine Learning and intelligent services
- 63. © Microsoft Corporation Oiland gas Workloads Key partnerships
- 64. © Microsoft Corporation Oiland gas workloads Process raw seismic data Perform bulk upload of seismic data Use in-house or commercial applications to process seismic data Seismic processing Reservoir simulations Remote Visualization and AI Accelerate onboarding and knowledge transfer Increase collaboration and productivity of field workers Create more accurate reservoir models, optimize drilling, and identify risks Evaluate production data to update models Optimize equipment and enable predictive maintenance Help provide development of new oil fields Ensure that simulation helps predict oil production and productivity Use commercial tools like Nexus or Intersect to run Reservoir simulation in Azure
- 65. © Microsoft Corporation Keyoil and gas partnerships
- 66. © Microsoft Corporation Mediaand entertainment Workloads Key partnerships
- 67. © Microsoft Corporation Mediaand entertainment workloads Hybrid/burst for peak demand Large-scale cloud-native workflows with Batch Rendering Remote visualization Shared workstations for collaboration
- 68. © Microsoft Corporation Keymedia and entertainment partners
- 69. © Microsoft Corporation Azurevalue for manufacturing Workloads Key partnerships
- 70. © Microsoft Corporation Manufacturingworkloads Finite Element Analysis (FEA) Computational Fluid Dynamics (CFD) Multibody Dynamics (MBD) Simulation Program with Integrated Circuit Emphasis (SPICE) analysis Optimization HPC/Simulation Digital concept product Physical models Marketing campaign Web, media, print Engineering Windshield cockpit glare Rendering Cloud-based engineering (cloud VDI) Cloud-based post visualization of simulations Visualization Image recognition for quality assurance Deep Learning/AI
- 71. © Microsoft Corporation Keymanufacturing partners
- 72.
- 73. © Microsoft Corporation OnlyMicrosoft has all the pieces to meet customers where they are in their HPC cloud journey Comprehensive portfolio Only cloud vendor to offer IaaS, PaaS, hybrid and supercomputer solutions for HPC Extensive partner ecosystem Unique programs & industry leaders ready to collaborate with your business Easy to Transition Tools for hybrid infrastructure, cloud clusters, data staging, and cloud apps Investment In HPC Dedicated HPC engineering and customer engagement teams Intelligent Cloud Join HPC with AI and IOT for Digital Twins and building next generation models
- 74. © Microsoft Corporation MakingHPC a reality HPC challenges Azure solves these Getting your workload into the cloud Simple, managed access to HPC Supporting hybrid use cases Azure CycleCloud and Avere vFXT for burst, including data and executables Moving data and apps Fast, repeatable, and scalable deployment Managing bandwidth, security and users Cost, user, and access controls Accessing the required technologies within the time given Strategic investments in HPC-specific technologies & service frameworks built into Azure Building cloud-native applications Azure Batch for resource provisioning and job scheduling
- 75. © Microsoft Corporation Nextsteps Learn more about Azure for HPC https://azure.microsoft.com/solutions/high-performance- computing/ Explore Azure solutions for your industry https://azure.microsoft.com/solutions/ Engage a partner to help implement your high- performance solution https://azure.microsoft.com/partners/directory/?solution=hi gh-performance-computing
- 76. © Copyright MicrosoftCorporation. All rights reserved.
- 77. Compute options forall types of apps
- 78. Compute options forall types of apps Intel Broadwell E5-2673 v4 Hyper-Threaded CPUs Up to 64 vCPU’s, 256GB RAM Intel® Xeon® Platinum 8168 processor (Skylake) Intel Haswell E5-2673 v3 Lowest cost, flexible CPUs Up to 8vCPUs, 32GB RAM AMD EPYC™7551 processor 8x1.9 TB SSDs
- 79. Intel Xeon E5-2673v4 (Broadwell) Hyper-Threaded CPUs Up to 64 vCPUs, 432GB RAM Intel Xeon E7-8890 v3 (Haswell) Largest VMs in Azure Up to 128 vCPUs, 4TB RAM Nvidia V100 SXM GPU Infiniband networking Deep learning, AI ‘ Compute options for all types of apps Nvidia M60 V100 PCIe ‘ Skylake Processor ‘
- 80. HPC Academia Automotive Oil & Gas Shipengineering Banking Insurance Energy Defense & Aerospace Pharmaceutical Food & beverages Healthcare Bio Science Oceaneering Weather forecasting Chemical engineering Engineering & construction Graphics & rendering Fluid dynamics Structural simulations Crash Simulations Deep Learning Genomics Molecular Modelling Risk Simulations
- 81. Most performant HPCVirtual machines Broadest GPU portfolio Largest compliance portfolio of any cloud Fastest Networking with InfiniBand and RDMA support Largest global footprint Per second billing for VMs Native integration into HPC client apps
- 82. © Microsoft Corporation Costcontrol and governance Provides monitoring Includes cost- saving features Offers the largest global footprint and compliance portfolio of any cloud Azure cost management