HPC system and big-compute solutions

Storage Accounts
Virtual Machines

Solution ideas

This article is a solution idea. If you'd like us to expand the content with more information, such as potential use cases, alternative services, implementation considerations, or pricing guidance, let us know by providing GitHub feedback.

This article describes a cloud-native application that uses Azure Batch. Batch provides compute resource allocation and management, application installation, resource autoscaling, and more.


Architecture Diagram

Download an SVG of this architecture.


  1. Upload input files and the applications to your Azure Storage account.
  2. Create a Batch pool of compute nodes, a job to run the workload on the pool, and the tasks in the job.
  3. Batch downloads input files and applications.
  4. Batch monitors the task execution.
  5. Batch uploads the task output.
  6. Download the output files.


Scenario details

Big compute and high performance computing (HPC) workloads are typically compute-intensive and can be run in parallel, taking advantage of the scale and flexibility of the cloud. The workloads are often run asynchronously using batch processing, with compute resources required to run the work and job scheduling required to specify the work.

This solution implements a cloud-native application with Azure Batch, which provides compute resource allocation and management, application installation, resource autoscaling, and job scheduling as a platform service. Batch also offers higher-level workload accelerators specifically for running R in parallel, AI training, and rendering workloads.

This solution is built on managed services including Virtual Machines, Storage, and Batch. These Azure services run in a high-availability environment, patched and supported, allowing you to focus on your solution.

Potential use cases

This solution is ideal for the finance, media, entertainment, energy, and environment industries. It's optimized for the following scenarios:

  • Financial risk Monte Carlo simulations (finance and portfolio)
  • Image rendering
  • Media transcoding
  • File processing
  • Engineering or scientific simulations (energy and environment)

Next steps

The following links provide documentation on deploying and managing the Azure products listed in the solution architecture: