HPC, Batch, and Big Compute solutions using Azure VMs

Organizations have large-scale computing needs. These Big Compute workloads include engineering design and analysis, financial risk calculations, image rendering, complex modeling, Monte Carlo simulations, and more.

Use the Azure cloud to efficiently run compute-intensive Linux and Windows workloads, from parallel batch jobs to traditional HPC simulations. Run your HPC and batch workloads on Azure infrastructure, with your choice of compute services, grid managers, Marketplace solutions, and vendor-hosted (SaaS) applications. Azure provides flexible solutions to distribute work and scale to thousands of VMs or cores and then scale down when you need fewer resources.

Solution options

The following sections provide more information about the supporting technologies and links to guidance.

Marketplace solutions

Visit the Azure Marketplace for Linux and Windows VM images and solutions designed for HPC. Examples include:

HPC applications

Run custom or commercial HPC applications in Azure. Several examples in this section are benchmarked to scale efficiently with additional VMs or compute cores. Visit the Azure Marketplace for ready-to-deploy solutions.


Check with the vendor of any commercial application for licensing or other restrictions for running in the cloud. Not all vendors offer pay-as-you-go licensing. You might need a licensing server in the cloud for your solution, or connect to an on-premises license server.

Engineering applications

Graphics and rendering

  • Rendering applications on Azure Batch, including Autodesk Maya, 3ds Max, and Arnold, Chaos Group V-Ray, and Blender

AI and deep learning

HPC and GPU VM sizes

Azure offers a range of sizes for Linux and Windows VMs, including sizes designed for compute-intensive workloads. For example, H16r and H16mr VMs can connect to a high throughput back-end RDMA network. This cloud network can improve the performance of tightly coupled parallel applications running under Microsoft MPI or Intel MPI.

N-series VMs feature NVIDIA GPUs designed for compute-intensive or graphics-intensive applications including artificial intelligence (AI) learning and visualization.

Learn more:

Azure CycleCloud

Effectively manage common workloads with ease while creating and optimizing HPC clusters on Azure VMs with Azure CycleCloud.

Learn how to:

Azure Batch

Batch is a platform service for running large-scale parallel and high-performance computing (HPC) applications efficiently in the cloud. Azure Batch schedules compute-intensive work to run on a managed pool of virtual machines, and can automatically scale compute resources to meet the needs of your jobs.

SaaS providers or developers can use the Batch SDKs and tools to integrate HPC applications or container workloads with Azure, stage data to Azure, and build job execution pipelines.

Learn how to:

Workload managers

The following are examples of cluster and workload managers that can run in Azure infrastructure. Create stand-alone clusters in Azure VMs or burst to Azure VMs from an on-premises cluster.

HPC storage

Large-scale Batch and HPC workloads have demands for data storage and access that exceed the capabilities of traditional cloud file systems.

Learn more:

Azure virtual machines, virtual machine scale sets, Batch, and related compute services are the foundation of most Azure HPC solutions. However, your solution can take advantage of many related Azure services. Here is a partial list:


Data and analytics

AI and machine learning



Customer stories

Examples of customers that have solved business problems with Azure HPC solutions:

Next steps