About H-series and compute-intensive A-series VMs
Here is background information and some considerations for using the newer Azure H-series and the earlier A8, A9, A10, and A11 instances, also known as compute-intensive instances. This article focuses on using these instances for Windows VMs. This article is also available for Linux VMs.
High-performance hardware – These instances are designed and optimized for compute-intensive and network-intensive applications, including high-performance computing (HPC) and batch applications, modeling, and large-scale simulations.
For basic specs, storage capacities, and disk details, see Sizes for virtual machines. Details about the Intel Xeon E5-2667 v3 processor (used in the H-series) and Intel Xeon E5-2670 processor (in A8 - A11), including supported instruction set extensions, are at the Intel.com website.
Designed for HPC clusters – Deploy multiple compute-intensive instances in Azure to create a stand-alone HPC cluster or to add capacity to an on-premises cluster. If you want to, deploy cluster management and job scheduling tools. Or, use the instances for compute-intensive work in another Azure service such as Azure Batch.
RDMA network connection for MPI applications – A subset of the compute-intensive instances (H16r, H16mr, A8, and A9) feature a second 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 RDMA-capable instances to communicate with each other over an InfiniBand network, operating at FDR rates for H16r and H16mr virtual machines, and QDR rates for A8 and A9 virtual machines. The RDMA capabilities exposed in these virtual machines can boost the scalability and performance of certain Linux and Windows Message Passing Interface (MPI) applications. See Access to the RDMA network in this article for requirements.
Azure subscription – If you want to deploy more than a small number of 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 - The compute-intensive 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 of 20 cores per subscription (if you use the classic deployment model) or 20 cores per region (if you use the Resource Manager deployment model). 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.)
Virtual network – An Azure virtual network is not required to use the compute-intensive instances. However, you may need at least a cloud-based Azure virtual network for many deployment scenarios, or a site-to-site connection if you need to access on-premises resources such as an application license server. If one is 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.
Cloud service or availability set – To use the Azure RDMA network, deploy the RDMA-capable VMs in the same cloud service (if you use the classic deployment model) or the same availability set (if you use the Azure Resource Manager deployment model). If you use Azure Batch, the RDMA-capable VMs must be in the same pool.
Resizing – Because of the specialized hardware used in the compute-intensive instances, 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 network address space - The RDMA network in Azure reserves the address space 172.16.0.0/16. To run MPI applications on instances deployed in an Azure virtual network, make sure that the virtual network address space does not overlap the RDMA network.
You can create clusters of RDMA-capable Windows Server instances and deploy one of the supported MPI implementations to take advantage of the Azure RDMA network. This low-latency, high-throughput network is reserved for MPI traffic only.
- Virtual machines - Windows Server 2012 R2, Windows Server 2012
- Cloud services - Windows Server 2012 R2, Windows Server 2012, Windows Server 2008 R2 Guest OS family
MPI - Microsoft MPI (MS-MPI) 2012 R2 or later, Intel MPI Library 5.x
Supported MPI implementations use the Microsoft Network Direct interface to communicate between instances. See Set up a Windows RDMA cluster with HPC Pack to run MPI applications and Use multi-instance tasks to run Message Passing Interface (MPI) applications in Azure Batch for deployment options and sample configuration steps.
On RDMA-capable compute-intensive VMs, the HpcVmDrivers extension must be added to the VMs to install Windows network device drivers that are needed for RDMA connectivity. In most deployments, the HpcVmDrivers extension is added automatically. If you need to add the extension yourself, see Manage VM extensions.
Microsoft HPC Pack, Microsoft’s free HPC cluster and job management solution, is not required for you to use the compute-intensive instances with Windows Server. However, it is one option for you to create a compute cluster in Azure to run Windows-based MPI applications and other HPC workloads. HPC Pack 2012 R2 and later versions include a runtime environment for MS-MPI that can use the Azure RDMA network when deployed on RDMA-capable VMs.
For more information and checklists to use the compute-intensive instances with HPC Pack on Windows Server, see Set up a Windows RDMA cluster with HPC Pack to run MPI applications.
For storage capacities and disk details, see Sizes for virtual machines.
To get started deploying and using compute-intensive instances with HPC Pack on Windows, see Set up a Windows RDMA cluster with HPC Pack to run MPI applications.
For information about using A8 and A9 instances to run MPI applications with Azure Batch, see Use multi-instance tasks to run Message Passing Interface (MPI) applications in Azure Batch.