HBv4-series
Applies to: ✔️ Linux VMs ✔️ Windows VMs ✔️ Flexible scale sets ✔️ Uniform scale sets
HBv4-series VMs are optimized for various HPC workloads such as computational fluid dynamics, finite element analysis, frontend and backend EDA, rendering, molecular dynamics, computational geoscience, weather simulation, and financial risk analysis. HBv4 VMs feature up to 176 AMD EPYC™ 9V33X ("Genoa-X") CPU cores with AMD's 3D V-Cache, clock frequencies up to 3.7 GHz, and no simultaneous multithreading. HBv4-series VMs also provide 768 GB of RAM, 2.3 GB L3 cache. The 2.3 GB L3 cache per VM can deliver up to 5.7 TB/s of bandwidth to amplify up to 780 GB/s of bandwidth from DRAM, for a blended average of 1.2 TB/s of effective memory bandwidth across a broad range of customer workloads. The VMs also provide up to 12 GB/s (reads) and 7 GB/s (writes) of block device SSD performance.
All HBv4-series VMs feature 400 Gb/s NDR InfiniBand from NVIDIA Networking to enable supercomputer-scale MPI workloads. These VMs are connected in a non-blocking fat tree for optimized and consistent RDMA performance. NDR continues to support features like Adaptive Routing and the Dynamically Connected Transport (DCT). This newest generation of InfiniBand also brings greater support for offload of MPI collectives, optimized real-world latencies due to congestion control intelligence, and enhanced adaptive routing capabilities. These features enhance application performance, scalability, and consistency, and their usage is recommended.
Premium Storage: Supported
Premium Storage caching: Supported
Ultra Disks: Supported (Learn more about availability, usage and performance)
Live Migration: Not Supported
Memory Preserving Updates: Not Supported
VM Generation Support: Generation 2
Accelerated Networking
Ephemeral OS Disks: Supported
Size | Physical CPU cores | Processor | Memory (GB) | Memory bandwidth (GB/s) | Base CPU frequency (GHz) | Single-core frequency (GHz, peak) | RDMA performance (Gb/s) | MPI support | Temp storage (TB) | Max data disks | Max Ethernet vNICs |
---|---|---|---|---|---|---|---|---|---|---|---|
Standard_HB176rs_v4 | 176 | AMD EPYC 9V33X (Genoa-X) | 768 | 780 | 2.4 | 3.7 | 400 | All | 2 * 1.8 | 32 | 8 |
Standard_HB176-144rs_v4 | 144 | AMD EPYC 9V33X (Genoa-X) | 768 | 780 | 2.4 | 3.7 | 400 | All | 2 * 1.8 | 32 | 8 |
Standard_HB176-96rs_v4 | 96 | AMD EPYC 9V33X (Genoa-X) | 768 | 780 | 2.4 | 3.7 | 400 | All | 2 * 1.8 | 32 | 8 |
Standard_HB176-48rs_v4 | 48 | AMD EPYC 9V33X (Genoa-X) | 768 | 780 | 2.4 | 3.7 | 400 | All | 2 * 1.8 | 32 | 8 |
Standard_HB176-24rs_v4 | 24 | AMD EPYC 9V33X (Genoa-X) | 768 | 780 | 2.4 | 3.7 | 400 | All | 2 * 1.8 | 32 | 8 |
Get started
- Overview of HPC on InfiniBand-enabled HB-series and N-series VMs.
- Configuring VMs and supported OS and VM Images.
- Enabling InfiniBand with HPC VM images, VM extensions or manual installation.
- Setting up MPI, including code snippets and recommendations.
- Cluster configuration options.
- Deployment considerations.
Size table definitions
Storage capacity is shown in units of GiB or 1024^3 bytes. When you compare 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.
To learn how to get the best storage performance for your VMs, see Virtual machine and disk performance.
Expected network bandwidth is the maximum aggregated bandwidth allocated per VM type across all NICs, for all destinations. For more information, see Virtual machine network bandwidth.
Upper limits aren't guaranteed. Limits offer guidance for selecting the right VM type for the intended application. Actual network performance will depend on several factors including network congestion, application loads, and network settings. For information on optimizing network throughput, see Optimize network throughput for Azure virtual machines. To achieve the expected network performance on Linux or Windows, you may need to select a specific version or optimize your VM. For more information, see Bandwidth/Throughput testing (NTTTCP).
Other sizes and information
- General purpose
- Memory optimized
- Storage optimized
- GPU optimized
- High performance compute
- Previous generations
Pricing Calculator: Pricing Calculator
For more information on disk types, see What disk types are available in Azure?
Next steps
- Read about the latest announcements, HPC workload examples, and performance results at the Azure Compute Tech Community Blogs.
- For a higher level architectural view of running HPC workloads, see High Performance Computing (HPC) on Azure.
- Learn more about how Azure compute units (ACU) can help you compare compute performance across Azure SKUs.
Athugasemdir
https://aka.ms/ContentUserFeedback.
Væntanlegt: Á árinu 2024 munum við hætta með GitHub-mál sem ábendingaleið fyrir efni og skipta því út fyrir nýtt ábendingakerfi. Frekari upplýsingar er að finna hér:Senda inn og skoða endurgjöf fyrir