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Table of Contents:

1. What is Computer-Aided Engineering (CAE)?


2. Why Moving CAE to Cloud? Cloud vs. On-Premises


3. What Makes Azure Special for CAE Workloads?


4. What Makes Azure Stand out Among Public Cloud Providers? “InfiniBand Interconnect”


5. Key CAE Workloads on Azure


6. Azure HPC VM Series for CAE Workloads


7. CAE Software Partnership “ISV’s”


8. Robust Ecosystem of System Integrator “SI” Partners


9. Real-World Use Case: Automotive Sector


10. Final Thoughts

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1. What is Computer-Aided Engineering “CAE”?

Computer-Aided Engineering (CAE) is a broad term that refers to the use of computer software to aid in engineering tasks. This includes simulation, validation, and optimization of products, processes, and manufacturing tools. CAE is integral to modern engineering, allowing engineers to explore ideas, validate concepts, and optimize designs before building physical prototypes. CAE encompasses various fields such as finite element analysis (FEA), computational fluid dynamics (CFD), and multibody dynamics (MBD) 

CAE tools are widely used in industries like automotive, aerospace, and manufacturing to improve product design and performance. For example, in the automotive industry, CAE tools help reduce product development costs and time while enhancing the safety, comfort, and durability of vehicles

CAE tools are often used to analyze and optimize designs created within CAD (Computer-Aided Design) software 

CAE systems typically involve three phases:

1. Pre-processing: Defining the model and environmental factors to be applied to it.


2. Analysis solver: Performing the analysis, usually on high-powered computers.


3. Post-processing: Visualizing the results 

In a world where product innovation moves faster than ever, Computer-Aided Engineering (CAE) has become a cornerstone of modern design and manufacturing. From simulating airflow over an F1 car to predicting stress in an aircraft fuselage, CAE allows engineers to explore ideas, validate concepts, and optimize designs—before a single prototype is built.

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2. Why Move CAE to Cloud? Cloud vs. On-Premises

Historically, CAE workloads were run on-premises due to their compute-intensive nature and large data requirements. Traditional CAE methods—dependent on expensive, on-premises HPC clusters—are facing a tipping point. Many organizations are now embracing cloud-based CAE.

When considering whether to use cloud or on-premises solutions, there are several factors to consider:

1. Cost and Maintenance: On-premises solutions require a large upfront investment in hardware and ongoing costs for maintenance and upgrades. Cloud solutions, on the other hand, spread costs over time and often result in lower total cost of ownership.

2. Security and Privacy: On-premises solutions offer control over security but require significant resources to manage. Cloud providers offer advanced security features and compliance certifications, often surpassing what individual companies can achieve on their own 

3. Scalability and Flexibility: Cloud solutions provide unmatched scalability and flexibility, allowing businesses to quickly adjust resources based on demand. On-premises solutions can be more rigid and require additional investments to scale 

4. Reliability and Availability: Cloud providers offer high availability and disaster recovery options, often with service level agreements (SLAs) guaranteeing uptime. On-premises solutions depend on the company’s infrastructure and may require additional investments for redundancy and disaster recovery 

5. Integration and Innovation: Cloud solutions often integrate seamlessly with other cloud services and offer continuous innovation through regular updates, new features, and run more simulations in parallel, reducing time-to-solution, accelerating product development cycle, and faster time to market. On-premises solutions may lag in terms of innovation and require manual integration efforts.

6. Global Access: Teams can collaborate and access data/models from anywhere. Cloud gives you global, on-demand supercomputing access without the physical, financial, and operational burden of traditional on-premise clusters.

In summary, the choice between cloud and on-premises solutions depends on various factors including cost, performance, security, maintenance, flexibility, and specific business needs. Cloud provides customers with global scalability, high availability, and a broad range of capabilities within a secure, integrated platform. It enables organizations to concentrate on core product innovation, accelerating their journey to market.

The following table shows Azure vs. on-premises for CAE Workloads:

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3. What Makes Azure Special for CAE Workloads?

Microsoft Azure: a cloud platform enabling scalable, secure, and high-performance CAE workflows across industries. Our goal in Azure is to provide the CAE field with a one-stop, best-in-class technology platform, rich with solution offerings and supported by a robust ecosystem of partners.

Azure offers several unique features and benefits that make it particularly well-suited for Computer-Aided Engineering (CAE) workloads:

1. GPU Acceleration: Azure provides powerful GPU options, such as NVIDIA GPUs, which significantly enhance the performance of leading CAE tools. This results in improved turnaround times, reduced power consumption, and lower hardware costs. For example, tools like Ansys Speos for lighting simulation and CPFD’s Barracuda Virtual Reactor have been optimized to take advantage of these GPUs.


2. High-Performance Computing (HPC): Azure offers specialized HPC solutions, such as the HBv3, HBv4/HX series, which are designed for high-performance workloads. These solutions provide the computational power needed for complex simulations and analyses.


3. Scalability and Flexibility: Azure’s cloud infrastructure allows for easy scaling of resources to meet the demands of CAE workloads. This flexibility ensures that you can handle varying levels of computational intensity without the need for significant upfront investment in hardware.


4. Integration with Industry Tools: Azure supports a wide range of CAE software and tools, making it easier to integrate existing workflows into the cloud environment. This includes certification and optimization of CAE tools on Azure.


5. Support for Hybrid Environments: Azure provides solutions for hybrid cloud environments, allowing you to seamlessly integrate on-premises resources with cloud resources. This is particularly useful for organizations transitioning to the cloud or requiring a hybrid setup for specific workloads.


6. Global Reach: As of April 2025, Microsoft Azure operates over 60 announced regions and more than 300 data centers worldwide, making it the most expansive cloud infrastructure among major providers. Azure ensures low latency and high availability for CAE workloads, regardless of where your team is located.

These features collectively make Azure a powerful and flexible platform for running CAE workloads, providing the computational power, scalability, and security needed to handle complex engineering simulations and analyses.

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4. What Makes Azure Stand out Among Public Cloud Providers? “InfiniBand Interconnect”

InfiniBand interconnect is one of the key differentiators that makes Microsoft Azure stand out among public cloud providers, especially for high-performance computing (HPC) and CAE workloads.

Here’s what makes InfiniBand a game changer, unique, and impactful on Azure:

a) Ultra-Low Latency & High Bandwidth

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  • InfiniBand on Azure delivers 200 Gbps (and up to 400 Gbps with HDR/NDR in some cases) interconnect speeds.
  
  
  • This ultra-low-latency, high-throughput network is ideal for tightly coupled parallel workloads, such as CFD, FEA, weather simulations, and molecular modeling.
  
  
  
  

b) RDMA (Remote Direct Memory Access) Support

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  • RDMA enables direct memory access between VMs, bypassing the CPU, which drastically reduces latency and increases application efficiency — a must for HPC workloads.
  
  
  
  

c) True HPC Fabric in the Cloud

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  • Azure is the only major public cloud provider that offers InfiniBand across multiple VM families like:
    
    
    
    • HBv3/4 (for CFD, FEA, Multiphysics, Molecular Dynamics)
    
    
    • HX-series (Structural Analysis)
    
    
    • ND (GPU + MPI)
    
    
    
    
  
  
  
  

• 
  
  
  
  • It allows scaling MPI workloads across thousands of cores — something typically limited to on-premises supercomputers.
  
  
  
  

d) Production-Grade Performance for CAE

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  • Solvers like ANSYS Fluent, STAR-CCM+, Abaqus, and MSC Nastran have benchmarked extremely well on Azure, thanks in large part to the InfiniBand-enabled infrastructure.
  
  
  
  

If you’re building CAE, HPC, or AI workloads that rely on ultra-fast communication between nodes, Azure’s InfiniBand-powered VM SKUs offer the best cloud-native alternative to on-prem HPC clusters.

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5. Key CAE Workloads on Azure:

CAE isn’t a one-size-fits-all domain. Azure supports a broad spectrum of CAE applications, such as:

• Computational Fluid Dynamics (CFD): ANSYS Fluent, Ansys CFX, Siemens Simcenter STAR-CCM+, Convergent Science CONVERGE CFD, Autodesk CFD, OpenFOAM, NUMECA Fine/Open, Altair ACuSolve, Simerics MP+, Cadence Fidelity CFD, COMSOL Multiphysics (CFD Module), Dassault Systeme XFlow, etc.


• Finite Element Analysis (FEA): ANSYS Mechanical, Dassault Systemes Abaqus, Altair OptiStruct, Siemens Simecenter 3D, MSC Nastran, Autodesk Fusion 360 Simulation, COMSOL Multiphysics (Structural Module), etc.


• Thermal & Electromagnetic Simulation: COMSOL Multiphysics, Ansys-HFSS, CST Studio Suite, Ansys Mechanical (Thermal Module), Siemens Simecenter 3D Thermal, Dassault Systemes Abaqus Thermal, etc.


• Crash & Impact Testing: Ansys LS-DYNA, Altair Radioss, ESI PAM-Crash, Siemens Simecenter Madymo, Dassault Systemes Abaqus “Explicit”, Ansys Autodyn, etc.

These applications require a combination of powerful CPUs, big memory footprint, high memory bandwidth, and low-latency interconnects, all of which are available in Azure’s purpose-built HPC VM families.

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6. Azure HPC VM Series for CAE Workloads

Azure offers specialized VM series tailored for CAE applications. These VMs support RDMA-enabled InfiniBand networking, critical for scaling CAE workloads across nodes in parallel simulations.

• CPU:
  
  
  
  • HBv3, HBv4 Series: Ideal for memory-intensive workloads like CFD and FEA, offering high memory bandwidth and low-latency interconnects.
  
  
  • HX Series: Optimized for structural analysis applications, providing significant performance boosts for solvers like MSC Nastran & others.
  
  
  
  

• GPU: ND Series: GPU-accelerated VMs optimized for CAE workloads, offering high double-precision compute, large memory bandwidth, and scalable performance with NVIDIA H100, H200, GB200 & AMD M300X GPUs.

The highest-performing compute-optimized CPU offering in Azure today is the HBv4/HX series, featuring 176 cores of 4th Gen AMD EPYC processors with 3D V-Cache technology (“Genoa-X”).

Below is a sample performance comparison of four different AMD SKU generations against the Intel “HCv1-Skylake” SKU, using the Ansys Fluent (F1 Racecar 140M cells) model.

Full performance & scalability of HBv4 and HX-Series VMs with Genoa-X CPUs is HERE.

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7. CAE Software Partnership “ISV’s”

Independent Software Vendors (ISVs) play a critical role on Azure by bringing trusted, industry-leading applications to the platform. Their solutions — spanning CAE, CFD, FEA, data analytics, AI, and more — are optimized to run efficiently on Azure’s scalable infrastructure. ISVs ensure that customers can seamlessly move their workloads to the cloud without sacrificing performance, compatibility, or technical support. They also drive innovation by collaborating with Azure engineering teams to deliver cloud-native, HPC-ready, and AI-enhanced capabilities, helping businesses accelerate product development, simulations, and decision-making.

Below is a partial list of these ISVs & their offerings on Azure:

• ANSYS Access: SaaS platform built on Azure, offering native cloud experiences for Fluent, Mechanical, LS-Dyna, HFSS, etc.


• Altair One: SaaS platform on Azure supporting Altair solvers such as HyperWorks, OptiStruct, Radioss, AcuSolve, etc.


• Siemens Simcenter: Validated on Azure for fluid, structural, and thermal simulation with solvers such as STAR-CCM+, NX, Femap


• Dassault Systèmes: Solvers such as Abaqus, CATIA, SIMULIA, XFlow


• COMSOL: For it sflagship solver “COMSOL Multiphysics”


• CPFD Software: CPFD Software has optimized its simulation tool “Barracuda Virtual Reactor” for Azure, enabling engineers to perform particle-fluid simulations efficiently.

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8. Robust Ecosystem of System Integrator “SI” Partners 

Azure CAE System Integrators (SIs) are specialized partners that assist organizations in deploying and managing CAE workloads on Microsoft Azure. These SIs provide expertise in cloud migration, HPC optimization, and integration of CAE applications, enabling businesses to leverage Azure’s scalable infrastructure for engineering simulations and analyses.

a) What Do Azure CAE System Integrators Offer?

Azure CAE SIs deliver a range of services tailored to the unique demands of engineering and simulation workloads:

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  • Cloud Migration: Transitioning on-premises CAE applications and data to Azure’s cloud environment.
  
  
  • HPC Optimization: Configuring Azure’s HPC resources to maximize performance for CAE tasks.
  
  
  • Application Integration: Ensuring compatibility and optimal performance of CAE software (e.g., ANSYS, Siemens, Altair, Abaqus) on Azure.
  
  
  • Managed Services: Ongoing support, monitoring, and maintenance of CAE environments on Azure.
  
  
  
  

b) Leading Azure CAE System Integrators 

Several SIs have been recognized for their capabilities in deploying CAE solutions on Azure. Partial list is below:

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  • Rescale, TotalCAE, Oakwood Systems, UberCloud “SIMR”, Capgemini, Accenture, Hexagon Manufacturing Intelligence.
  
  
  
  

c) Benefits of Collaborating with Azure CAE SIs

By partnering with Azure CAE System Integrators, organizations can effectively harness the power of cloud computing to enhance their engineering and simulation capabilities. Engaging with Azure CAE System Integrators can provide:

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  • Expertise: Access to professionals experienced in both CAE applications and Azure infrastructure.
  
  
  • Efficiency: Accelerated deployment and optimization of CAE workloads.
  
  
  • Scalability: Ability to scale resources up or down based on project requirements.
  
  
  • Cost Management: Optimized resource usage leading to potential cost savings.
  
  
  
  

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9. Real-World Use Case: Automotive Sector

One automotive company leveraged HBv4 VMs on Azure to simulate combustion and fluid dynamics for new engine designs. By scaling up CFD workloads using Azure’s 200 Gbps InfiniBand, they reduced simulation runtimes from 36 hours to under 9 hours, enabling faster design iterations and more competitive vehicles.

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10. The Future of CAE is Cloud-Native

The next frontier in CAE is not just lifting and shifting legacy solvers into the cloud—but enabling cloud-native simulation pipelines. List includes:

• AI-assisted simulation tuning


• Serverless pre/post-processing workflows


• Digital twins integrated with IoT data on Azure


• Cloud-based visualization with NVIDIA Omniverse

With advances in GPU acceleration, parallel file systems (like Azure Lustre), and intelligent job schedulers, Azure is enabling this next-gen CAE transformation today.

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11. Final Thoughts

Moving CAE to Azure is more than a tech upgrade—it’s a shift in mindset. It empowers engineering teams to simulate more, iterate faster, and design better—without being held back by hardware constraints.

If you’re still running CAE workloads on aging, capacity-constrained systems, now is the time to explore what Azure HPC can offer.

Let the cloud be your wind tunnel, your test track, your proving ground.

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Let’s Connect

Have questions or want to share how you’re using CAE in the cloud? Let’s start a conversation! 

We’d love to hear your thoughts! Leave a comment below and join the conversation. 👇

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