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High performance computing

Break free from the overhead and limitations of your on-premises infrastructure. Tap into unlimited resources to scale your high performance computing (HPC) jobs—analyzing large-scale data, running simulations and financial models, and experimenting while reducing time to market.

Implement your high performance computing solution

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Use a Cray supercomputer

Run your most demanding workloads on a Cray supercomputer—near the Azure services you’re already using. Add a dedicated Cray supercomputer to your virtual network in Azure and innovate faster, access advanced services, and consolidate your IT footprint.

Learn how to get a Cray in Azure

Scale on demand, stay on budget

When the amount of data you have to ingest and process grows, tap into cloud resources for elastic extension of compute capabilities. Scale cost-effectively with the high performance computing (HPC) capabilities of Azure.

Democratize access to achieve fast results

As scientific experiments drive an explosion in data growth, the need to share, process, and protect that data grows too. Bring collaborative, scalable, and secure access from anywhere, at any time, to all users.

Reduce time to market

Add flexible compute resources to deliver more granularity and improved results faster. Ultimately, you’ll finish more projects and get more done.

Disrupt the market with new products

Whether re-inventing classic lines of business apps, re-architecting proven scenarios, or taking data-driven into overdrive, you need fast and flexible architectures. Use Azure to build architectures that expand, adapt, and shrink with the demand of customers.

ANSYS CFD software enables engineers to perform multi-physics analysis.

"ANSYS and Microsoft Azure have been working closely on a Pproof of Cconcept with a large customer to run ANSYS CFD workload on Azure"
Ray Milhem, Vice President of enterprise solutions at ANSYS

d3VIEW is hosted on Microsoft Azure, which provides thousands of virtual machines on demand.

"We look forward to using Azure to help customers use large-scale cloud computing for LS-DYNA® simulation-based product development."
Suri Bala, Founder and Chief Executive Officer

Excellent performance of the STAR-CCM+ container eliminates the need to have all software in-house.

"Combination of Microsoft Azure with UberCloud’s HPC having ANSYS FLUENT provided a strong platform to develop accurate virtual simulation model that involved complex geometries."

Solution architectures

Big compute with Azure Batch

  1. Overview
  2. Flow

Big compute and high performance computing (HPC) workloads are normally 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. Examples of Big Compute and HPC workloads include financial risk Monte Carlo simulations, image rendering, media transcoding, file processing, and engineering or scientific simulations.

This solution implements a cloud-native application with Azure Batch, which provides compute resource allocation and management, application installation, resource auto-scaling, 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 the Azure managed services—Virtual Machines, Storage, and Batch. These services run in a high-availability environment, patched and supported, allowing you to focus on your solution.

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

Use the applications and middleware that you love

Find HPC applications from our trusted partners in the Azure Marketplace and around the web.

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