High-performance computing

Achieve your unique business objectives with enterprise-grade agility, scale, performance, and security with the Microsoft Azure HPC portfolio.

Powerful versatility

Designed for HPC workloads. Whether it’s computational fluid dynamics, finite or infinite element analysis, Monte Carlo simulations, reservoir modeling, or autonomous vehicle development, get the HPC models and tools you need, at the scale you need, from Azure.

Extend your HPC environments to the cloud. Extend your HPC beyond your on-premises boundaries by adding new capabilities, including bursting to the cloud, AI and machine learning, or even full migration.

HPC core application patterns

Based on customer adoption patterns, the Azure HPC portfolio is commonly used across four application patterns. Discover a new generation of powerful, scalable Azure applications and processes designed to empower engineers, scientists, and researchers to innovate beyond traditional HPC scenarios.


Simulation for highly efficient research and development message passing interface (MPI) workflows in manufacturing, engineering, life sciences, financial services, and energy.

Computational fluid dynamics (CFD) simulations

Deep learning

Deep learning workloads incorporating Azure AI and machine learning technologies for predictive analytics and insights for smart IoT devices, increased productivity, and deeper collaboration.

Machine learning diagram and overview


Rendering processes for workloads in media production and engineering design that deliver intended results in a fraction of the time it normally takes.

Rendering architecture scenario diagrams


Visualization of your workspaces and applications on virtual PCs to securely minimize client PC investments, scale-up on demand, and reduce IT support issues.

Fast networking

Azure is the only public cloud with support for InfiniBand, which provides the interconnect speed and bandwidth necessary to support all MPI types and versions, including Open MPI, MVAPICH2, Platform MPI, Intel MPI, and SparkRDMA.

Powerful infrastructure

Get extraordinary versatility and scalability with high memory virtual machines (VMs), graphic-intensive GPUs, high IOPS storage, or a fully managed, dedicated supercomputing service on Cray.

Seamless orchestration

Avoid the time and expense of re-architecting your applications for the cloud by simply extending the HPC resource environment you already have to Azure. Clone your clusters to the cloud with Azure Cycle and manage your application workflows with Azure Batch.

Azure HPC platform services

Get vast compute resources with a cloud platform built for global scale and outfitted with services specifically geared towards handling HPC workloads.

HPC workflow services

Take advantage of end-to-end application workload management and orchestration services that make Azure a logical extension of your HPC environment or application.

Azure CycleCloud

Azure Batch

Transformative services

Innovate the next generation of applications with predictive analysis and machine learning model training against large HPC data sets.

Azure Machine Learning service

Azure Data Lake

Fast, secure networking

Establish private, secure tunnels for hybrid cloud connectivity, and take advantage of Linux RDMA with InfiniBand for MPI workloads within your data center.



Optimized infrastructure and data

Find the right resources at nearly unlimited scale to keep up with your HPC apps, including CPU- and GPU-based virtual machines, automatic scaling, and fast storage.

Azure H-series VMs

Azure N-series VMs


Cray in Azure

Avere vFXT

Azure HPC for industries

Autonomous driving

Design and build autonomous driving vehicles without the hassle of computing bottlenecks from processing big data sets.

Advanced driver assistance systems (ADAS)

Accelerate time to market by using simulations to optimize sensor and algorithm performance.

Crash test simulation

Reduce the costs associated with real crash testing and gain deeper insights from your data output.

Learn how to set up an Azure HPC cluster for automotive engineering simulations by reading the free Run Star-CCM+ in an Azure HPC Cluster white paper.

Download now

Risk compute and analytics (FRTB)

Focus on risk analysis and related regulatory compliance requirements in a flexible, security-enhanced manner.

Trade modulation and simulation

Test the effectiveness of your trading strategy without putting real money at risk.

Risk reporting

Speed up processing and get faster results that are perfectly aligned with rapidly changing market conditions.

Learn more about enabling the financial services risk lifecycle with Azure and R.

Actuarial risk modeling

Run what used to be thousands of hours of analysis in just minutes so that you have more time to review, evaluate, and validate results.

Catastrophic risk modeling

Better predict and mitigate risk from catastrophes and natural disasters using probabilistic or deterministic models.

Risk analytics

Accelerate and streamline your risk processes while adapting to changing practices, demands, and regulations.

Learn more about enabling the financial services risk lifecycle with Azure and R.

Genomic analysis

Get the computational power you need for DNA sequencing and analysis workloads with data management for large data sets.

NONMEM clinical trial simulation

Create population pharmacokinetic and pharmacokinetic-pharmacodynamic modeling workloads.

Molecular dynamics

Increase the accuracy of mathematical formulas used in simulated atom and particle movement analysis.

Computational fluid dynamics (CFD)

Dramatically accelerate your time to results for mechanical design improvements and optimization insights.

Finite element analysis (FEA)

Improve FEA accuracies and element behavior predictability for physical effects such as mechanical stress, fatigue, and fluid flow.

Computational chemistry

Discover possibilities for molecular manufacturing with atomic precision and accurately model/predict properties of new materials.

Learn how to set up an Azure HPC cluster for automotive engineering simulations by reading the free Run Star-CCM+ in an Azure HPC Cluster white paper.

Download now

Fast media rendering

Greatly reduce the time required for 3D-to-2D image conversion with video, film, or imagery content from non-linear editing and production systems.

Scalable post-production

Take advantage of the most computationally intensive VFX tools and processes without missing tight production and market deadlines.

Content optimization

Improve consistency and discoverability of new media content with remote content ingestion, in-line transcoding, speech indexing, and metadata tagging.

Learn more about how to use Azure for media rendering workflows.

Reservoir modeling

Produce more informative, upscale grids using single-node jobs, tightly coupled multi-node jobs, or dedicated supercomputing workloads.

Seismic processing and imaging

Quickly process and deliver results from increasingly growing sets of seismic data.

Computational chemistry

Simulate physical properties of streams, use improved sensitivity analysis, and better describe new compounds and materials.

Learn more about how the oil and gas industry is using Azure Batch to accelerate ROI and minimize risk.

Fully managed supercomputing service on Azure

Get a dedicated, fully managed, single tenancy Cray XC series or Cray CS series supercomputer. Take advantage of ClusterStor high-performance storage with your Cray deployment or with Azure H-series VMs. Experience great features like:

  • Dedicated, customized, fully managed supercomputers.
  • Single tenancy on bare metal for complete control and privacy over your computing environment.
  • No data movement. Your data stays on the same Azure network as your RDMA/GPU/FPGA VMs.
  • Transformative services such as AI, deep learning, and advanced analytics.

Learn more about Cray in Azure

Workflow optimization on Azure

Achieve more with proven processing and operational tools and services for HPC application workflows, including:

Application workload scaling using either HPC-optimized CPU, GPU, or FPGA-based VMs, or with dedicated, single tenant environments for hyperscale class applications.

Learn more

Cluster and environment scaling with built-in orchestration and management, saving you the time and cost of re-architecting your applications.

Learn more

On-demand bursting though API/CLI pathways for democratized access to cloud-scale HPC resources.

Learn more

Low-latency hybrid storage access to allow you to easily manage your work in the cloud across resources.

Learn more

Documentation, training, and demos


Learn how to run large-scale parallel and HPC applications efficiently in the cloud with Azure Batch in this free 45-minute learning module from Microsoft Learn.

Get started

Learn what customers are doing with Azure HPC

“The ability to do large-scale computing is essential if you’re looking at something like hurricane risk, because it’s a complex event affecting an extremely large geography. With Azure, we have the computing power to model such events and provide more accurate information to our clients. As a result, they can get better coverage.”

Simon Blaquière, Reinsurance Actuarial Manager, AXA Global P & C

Read the story


“Our simulation tool, powered by HPC resources in Azure, has the potential to cut today’s 12-to-20-year drug development period in half.”

Andy Lee, Cofounder and Chief Technology Officer, NeuroInitiative LLC

Read the story


“Before every race or test, we have to compile a report for shipping parts to and from the event so that we can ensure that every single part will get to the track on time. That report used to take someone a week to compile, but we’ve gotten that down to a fraction of that time now—just a few hours.”

Mark Everest, IS Development Manager, Renault Sport Formula 1 Team

Read the story

Renault Sport

Microsoft partnered up with oil and gas giant Schlumberger to launch the company’s first fully commercial SaaS offering, the high-resolution reservoir modeling application INTERSECT, on Azure.

Read the story


“With the scalability we now have with Microsoft Avere vFXT for Azure, we can predict demand more accurately than ever before and respond to it much better, especially when dealing with last-minute changes.”

Dave Blommers, Global Head of Technology, Mr. X

Read the story

Mr X

Solution architectures

Arquitetura de composição de multimédia e entretenimentoEsta arquitetura de solução de composição de multimédia HPC mostra o Azure CycleCloud a monitorizar um gestor de pipelines do Pixar Tractor e a orquestrar o aumento da capacidade de nós de computação a pedido mediante a utilização de Conjuntos de Dimensionamento de Máquinas Virtuais de baixa prioridade do Azure. Uma cache do Avere vFXT disponibiliza os dados do sistema de ficheiros e do armazenamento de Blobs do Azure já existentes aos nós de computação no Azure.123456778
  1. Overview
  2. Flow

Media and entertainment rendering architecture


This HPC media rendering solution architecture shows Azure CycleCloud monitoring a Pixar Tractor pipeline manager and orchestrating burst compute node capacity on-demand using Azure low-priority Virtual Machines Scale Sets. An Avere vFXT cache makes data from the existing on-premises filesystem and Azure Blob storage available to compute nodes in Azure.


  1. 1 Operations team uses Azure CycleCloud to configure and launch rendering pipeline cluster.
  2. 2 Azure CycleCloud orchestrates virtual machine (VM) creation and software configuration for head nodes, license servers, and Avere vFXT Cache.
  3. 3 Artist submits a render job to the Pixar Tractor pipeline manager.
  4. 4 Azure CycleCloud detects the change in job queue depth and autostarts render farm nodes in Virtual Machines Scale Sets with location, SKU, and configuration customized by job requirements.
  5. 5 Render pipeline manager (head nodes) executes render jobs on the new render farm VMs.
  6. 6 Render jobs pull artifacts from on-premises and Azure Blob storage as needed from NFS-mounted Avere vFXT.
  7. 7 As each job finishes rendering, resulting artifacts are written back to storage through the Avere vFXT.
  8. 8 As job queue empties, Azure CycleCloud auto-stops render farm VMs to reduce cost.
Macrocomputação com o Azure BatchAs cargas de trabalho de macrocomputação e de computação de alto desempenho (HPC) são, normalmente, de computação intensiva e podem ser executadas em paralelo, ao tirar partido das capacidades de dimensionamento e da flexibilidade da cloud. As cargas de trabalho são, muitas vezes, executadas de forma assíncrona com processamento em lotes, com os recursos de computação necessários para executar o trabalho e o agendamento de tarefas necessário para especificar o trabalho. Exemplos de cargas de trabalho de Macrocomputação e de HPC incluem simulações Monte Carlo de risco financeiro, composição de imagens, transcodificação de multimédia, processamento de ficheiros e simulações científicas ou de engenharia.123456
  1. Overview
  2. Flow

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. 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.
Hybrid risk analysis architectureThis templated risk analysis solution uses Azure HPC compute and GPU virtual machines (VMs) to expand on-premises Tibco GridServer compute to Azure using Azure CycleCloud for auto-scaling integration. The job executes both on-premises and in the cloud by using Avere vFXT fast caching and native NFS access to market data available on-premises.