High performance compute virtual machine sizes

The A8-A11 and H-series sizes are also known as compute-intensive instances. The hardware that runs these sizes is designed and optimized for compute-intensive and network-intensive applications, including high-performance computing (HPC) cluster applications, modeling, and simulations. The A8-A11 series uses Intel Xeon E5-2670 @ 2.6 GHZ and the H-series uses Intel Xeon E5-2667 v3 @ 3.2 GHz. This article provides information about the number of vCPUs, data disks and NICs as well as storage throughput and network bandwidth for each size in this grouping.

Azure H-series virtual machines are the next generation high performance computing VMs aimed at high end computational needs, like molecular modeling, and computational fluid dynamics. These 8 and 16 vCPU VMs are built on the Intel Haswell E5-2667 V3 processor technology featuring DDR4 memory and SSD-based temporary storage.

In addition to the substantial CPU power, the H-series offers diverse options for low latency RDMA networking using FDR InfiniBand and several memory configurations to support memory intensive computational requirements.


ACU: 290-300

Size vCPU Memory: GiB Temp storage (SSD) GiB Max data disks Max disk throughput: IOPS Max NICs
Standard_H8 8 56 1000 32 32 x 500 2
Standard_H16 16 112 2000 64 64 x 500 4
Standard_H8m 8 112 1000 32 32 x 500 2
Standard_H16m 16 224 2000 64 64 x 500 4
Standard_H16r 1 16 112 2000 64 64 x 500 4
Standard_H16mr 1 16 224 2000 64 64 x 500 4

1 For MPI applications, dedicated RDMA backend network is enabled by FDR InfiniBand network, which delivers ultra-low-latency and high bandwidth.

A-series - compute-intensive instances

ACU: 225

Size vCPU Memory: GiB Temp storage (HDD): GiB Max data disks Max data disk throughput: IOPS Max NICs
Standard_A8 1 8 56 382 32 32x500 2
Standard_A9 1 16 112 382 64 64x500 4
Standard_A10 8 56 382 32 32x500 2
Standard_A11 16 112 382 64 64x500 4

1For MPI applications, dedicated RDMA backend network is enabled by FDR InfiniBand network, which delivers ultra-low-latency and high bandwidth.

Size table definitions

  • Storage capacity is shown in units of GiB or 1024^3 bytes. When comparing disks measured in GB (1000^3 bytes) to disks measured in GiB (1024^3) remember that capacity numbers given in GiB may appear smaller. For example, 1023 GiB = 1098.4 GB
  • Disk throughput is measured in input/output operations per second (IOPS) and MBps where MBps = 10^6 bytes/sec.
  • Data disks can operate in cached or uncached modes. For cached data disk operation, the host cache mode is set to ReadOnly or ReadWrite. For uncached data disk operation, the host cache mode is set to None.
  • If you want to get the best performance for your VMs, you should limit the number of data disks to 2 disks per vCPU.
  • Expected network bandwidth is the maximum aggregated bandwidth allocated per VM type across all NICs, for all destinations. Upper limits are not guaranteed, but are intended to provide guidance for selecting the right VM type for the intended application. Actual network performance will depend on a variety of factors including network congestion, application loads, and network settings. For information on optimizing network throughput, see Optimizing network throughput for Windows and Linux. To achieve the expected network performance on Linux or Windows, it may be necessary to select a specific version or optimize your VM. For more information, see How to reliably test for virtual machine throughput.

  • † 16 vCPU performance will consistently reach the upper limit in an upcoming release.

Deployment considerations

  • Azure subscription – To deploy more than a few compute-intensive instances, consider a pay-as-you-go subscription or other purchase options. If you're using an Azure free account, you can use only a limited number of Azure compute cores.

  • Pricing and availability - These VM sizes are offered only in the Standard pricing tier. Check Products available by region for availability in Azure regions.

  • Cores quota – You might need to increase the cores quota in your Azure subscription from the default value. Your subscription might also limit the number of cores you can deploy in certain VM size families, including the H-series. To request a quota increase, open an online customer support request at no charge. (Default limits may vary depending on your subscription category.)


    Contact Azure Support if you have large-scale capacity needs. Azure quotas are credit limits, not capacity guarantees. Regardless of your quota, you are only charged for cores that you use.

  • Virtual network – An Azure virtual network is not required to use the compute-intensive instances. However, for many deployments you need at least a cloud-based Azure virtual network, or a site-to-site connection if you need to access on-premises resources. When needed, create a new virtual network to deploy the instances. Adding compute-intensive VMs to a virtual network in an affinity group is not supported.
  • Resizing – Because of their specialized hardware, you can only resize compute-intensive instances within the same size family (H-series or compute-intensive A-series). For example, you can only resize an H-series VM from one H-series size to another. In addition, resizing from a non-compute-intensive size to a compute-intensive size is not supported.

RDMA-capable instances

A subset of the compute-intensive instances (H16r, H16mr, A8, and A9) feature a network interface for remote direct memory access (RDMA) connectivity. This interface is in addition to the standard Azure network interface available to other VM sizes.

This interface allows the RDMA-capable instances to communicate over an InfiniBand network, operating at FDR rates for H16r and H16mr virtual machines, and QDR rates for A8 and A9 virtual machines. These RDMA capabilities can boost the scalability and performance of Message Passing Interface (MPI) applications running under Intel MPI 5.x or a later version.

Deploy the RDMA-capable VMs in the same availability set (when you use the Azure Resource Manager deployment model) or the same cloud service (when you use the classic deployment model). Additional requirements for RDMA-capable Linux VMs to access the Azure RDMA network follow.


Deploy a compute-intensive VM from one of the images in the Azure Marketplace that supports RDMA connectivity:

  • Ubuntu - Ubuntu Server 16.04 LTS. Configure RDMA drivers on the VM and register with Intel to download Intel MPI:

    1. Install dapl, rdmacm, ibverbs, and mlx4

      sudo apt-get update
      sudo apt-get install libdapl2 libmlx4-1
    2. In /etc/waagent.conf, enable RDMA by uncommenting the following configuration lines. You need root access to edit this file.

    3. Add or change the following memory settings in KB in the /etc/security/limits.conf file. You need root access to edit this file. For testing purposes you can set memlock to unlimited. For example: <User or group name> hard memlock unlimited.

      <User or group name> hard    memlock <memory required for your application in KB>
      <User or group name> soft    memlock <memory required for your application in KB>
    4. Install Intel MPI Library. Either purchase and download the library from Intel or download the free evaluation version.

      wget http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/11595/l_mpi_2017.3.196.tgz

      For installation steps, see the Intel MPI Library Installation Guide.

    5. Enable ptrace for non-root non-debugger processes (needed for the most recent versions of Intel MPI).

      echo 0 | sudo tee /proc/sys/kernel/yama/ptrace_scope
  • SUSE Linux Enterprise Server - SLES 12 SP3 for HPC, SLES 12 SP3 for HPC (Premium), SLES 12 SP1 for HPC, SLES 12 SP1 for HPC (Premium). RDMA drivers are installed and Intel MPI packages are distributed on the VM. Install MPI by running the following command:

    sudo rpm -v -i --nodeps /opt/intelMPI/intel_mpi_packages/*.rpm
  • CentOS-based HPC - CentOS-based 7.3 HPC, CentOS-based 7.1 HPC, CentOS-based 6.8 HPC, or CentOS-based 6.5 HPC (for H-series, version 7.1 or later is recommended). RDMA drivers and Intel MPI 5.1 are installed on the VM.


    On the CentOS-based HPC images, kernel updates are disabled in the yum configuration file. This is because the Linux RDMA drivers are distributed as an RPM package, and driver updates might not work if the kernel is updated.

Cluster configuration

Additional system configuration is needed to run MPI jobs on clustered VMs. For example, on a cluster of VMs, you need to establish trust among the compute nodes. For typical settings, see Set up a Linux RDMA cluster to run MPI applications.

Network topology considerations

  • On RDMA-enabled Linux VMs in Azure, Eth1 is reserved for RDMA network traffic. Do not change any Eth1 settings or any information in the configuration file referring to this network. Eth0 is reserved for regular Azure network traffic.

  • In Azure, IP over InfiniBand (IB) is not supported. Only RDMA over IB is supported.

Using HPC Pack

HPC Pack, Microsoft’s free HPC cluster and job management solution, is one option for you to use the compute-intensive instances with Linux. The latest releases of HPC Pack support several Linux distributions to run on compute nodes deployed in Azure VMs, managed by a Windows Server head node. With RDMA-capable Linux compute nodes running Intel MPI, HPC Pack can schedule and run Linux MPI applications that access the RDMA network. See Get started with Linux compute nodes in an HPC Pack cluster in Azure.

Other sizes

Next steps