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
View solution architecturesUse 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.
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.
Success stories from partners like you
ANSYS CFD software enables engineers to perform multi-physics analysis
"ANSYS and Microsoft Azure have been working closely on a proof of concept 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."
CD-adapco
MUFG's international securities business offers a comprehensive product suite to clients around the world.
"Instead of leasing a big new datacenter, we put several thousand cores on an ongoing basis in Azure, which gives us the ability to scale almost instantaneously in case of a market event."
Robert Griffiths, Head of High Performance Computing at MUFG Securities
Computer scientists at Virginia Tech developed an on-demand, cloud-computing model using the Microsoft Azure HDInsight Service.
"Life scientists and their institutions no longer have to find millions of dollars to establish their own supercomputing center."
Wu Feng, Professor of Computer Science at Virginia Tech
Willis Towers Watson uses Microsoft Azure to gain a competitive advantage, save costs, and broaden the market for its solutions.
"Usage-based insurance can be an opportunity or a threat to insurers. With a cost-effective UBI service hosted in Azure, we’re ensuring that they can see it as an opportunity."
Andy Lingard, Global Leader of General Insurance Software Dev
EFS is creating a solution powered by Microsoft Azure that analyzes pictures taken from a car’s front-facing high-resolution 2D camera.
"As part of our autonomous driving research for Audi, we proved that it’s possible to use deep learning to analyze roads. That is a really big deal. As far as we know, EFS is the first company to do it on such a large scale."
Max Jesch, Software Developer at EFS
Solution architectures
Big compute with Azure Batch
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 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 task execution.
- 5 Batch uploads task output.
- 6 Download output files.
Hybrid HPC in Azure with HPC Pack
Microsoft HPC Pack is a free high performance computing (HPC) solution built on Microsoft Azure and Windows Server technologies. HPC Pack combines a comprehensive set of deployment, administration, job scheduling, and monitoring tools for your Windows and Linux HPC cluster environment, providing a flexible platform for developing and running HPC applications on premises and in Azure.
This solution shows the process for using HPC Pack to create a hybrid (on-premises and Azure) HPC environment.
- 1 Log into on-premises head node
- 2 Add Azure compute nodes to the cluster
- 3 Start the compute nodes
- 4 Submit jobs to the cluster
- 5 HPC Pack sends jobs to on-premises and Azure nodes based upon the node group selected
- 6 Monitor job progress
- 7 Stop the compute nodes or configure auto-scaling
Use the applications and middleware that you love
Find HPC applications from our trusted partners in the Azure Marketplace and around the web.
Find a solution partner
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