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 modelling 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

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

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

Visualisation

Visualisation of your workspaces and applications on virtual PCs to securely minimise 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 rearchitecting 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 centre.

InfiniBand

ExpressRoute

Optimised 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

Storage

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 optimise 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 vehicle 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.

Financial risk modelling

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 modelling

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 modelling 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 optimisation insights.

Finite element analysis (FEA)

Improve FEA accuracies and element behaviour 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 vehicle 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 optimisation

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 modelling

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 such as:

  • Dedicated, customised, 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 optimisation on Azure

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

Application workload scaling using either HPC-optimised 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 rearchitecting your applications.

Learn more

On-demand bursting though API/CLI pathways for democratised 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

Training

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.

Getting 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

AXA

“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

NeuroInitiative

“Before every race or test, we have to compile a report for sending 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 got 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 modelling application INTERSECT, on Azure.

Read the story

Schlumberger

“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

Media and entertainment rendering architectureThis 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.123456778
  1. Overview
  2. Flow

Media and entertainment rendering architecture

Overview

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.

Flow

  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, licence 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 auto-starts render farm nodes in Virtual Machines Scale Sets with location, SKU and configuration customised 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.
Big compute with Azure BatchBig 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.123456
  1. Overview
  2. Flow

Big compute with Azure Batch

Overview

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.

Flow

  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.
Arquitetura de análise de risco híbridaEsta solução de análise de risco de modelo utiliza computação HPC do Azure e máquinas virtuais de GPU (VMs) para expandir a computação local do Tibco GridServer para o Azure através do Azure CycleCloud para integração de dimensionamento automático. O trabalho é executado no local e na cloud através da colocação em cache rápida do Avere vFXT e do acesso NFS nativo aos dados de mercado disponíveis no local.