This topic describes the features of GPU-accelerated virtualization instance families and lists the instance types of each family.

To use a GPU-accelerated virtualization instance, you must install a GRID driver on the instance. Click here to go to the NVIDIA official website and purchase a GRID license. After you create an instance, you can manually install the GRID driver and activate the license.

vgn6i, lightweight GPU-accelerated compute optimized instance family

vgn6i is in invitational preview. To use vgn6i, submit a ticket.

Features
  • Is an instance family in which all instances are I/O optimized.
  • Supports standard SSDs and ultra disks only.
  • Uses NVIDIA T4 GPU computing accelerators.
  • Contains virtual GPUs generated from GPU slice virtualization.
    • Supports the 1/4 and 1/2 computing capacity of NVIDIA Tesla T4 GPUs.
    • Supports 4 GB and 8 GB of GPU video memory.
  • Offers a CPU-to-memory ratio of 1:5.
  • Uses 2.5 GHz Intel ® Xeon ® Platinum 8163 (Skylake) processors.
  • Provides high network performance based on large computing capacity.
  • Applies to the following scenarios:
    • Real-time rendering for cloud games
    • Real-time rendering for AR and VR applications
    • AI (deep learning and machine learning) inference for elastic Internet service deployment
    • Educational environment of deep learning
    • Modeling experiment environment of deep learning
Instance types
Instance type vCPU Memory (GiB) Local storage (GiB) GPU GPU memory (GB) Bandwidth (Gbit/s) Packet forwarding rate (Kpps) IPv6 support NIC queues ENIs (including one primary ENI) Private IP addresses per ENI
ecs.vgn6i-m4.xlarge 4 23.0 None T4*1/4 4 3.0 500 Yes 2 4 10
ecs.vgn6i-m8.2xlarge 10 46.0 None T4*1/2 8 4.0 800 Yes 4 5 20
Note

vgn5i, lightweight GPU-accelerated compute optimized instance family

Features
  • Is an instance family in which all instances are I/O optimized.
  • Supports standard SSDs and ultra disks only.
  • Uses NVIDIA P4 GPU computing accelerators.
  • Contains virtual GPUs generated from GPU slice virtualization.
    • Supports the 1/8, 1/4, 1/2, and 1/1 computing capacity of NVIDIA Tesla P4 GPUs.
    • Supports 1 GB, 2 GB, 4 GB, and 8 GB of GPU video memory.
  • Offers a CPU-to-memory ratio of 1:3.
  • Uses 2.5 GHz Intel ® Xeon ® E5-2682 v4 (Broadwell) processors.
  • Provides high network performance based on large computing capacity.
  • Applies to the following scenarios:
    • Real-time rendering for cloud games
    • Real-time rendering for AR and VR applications
    • AI (deep learning and machine learning) inference for elastic Internet service deployment
    • Educational environment of deep learning
    • Modeling experiment environment of deep learning
Instance types
Instance type vCPU Memory (GiB) Local storage (GiB) GPU GPU memory (GB) Bandwidth (Gbit/s) Packet forwarding rate (Kpps) IPv6 support NIC queues ENIs (including one primary ENI) Private IP addresses per ENI
ecs.vgn5i-m1.large 2 6.0 None P4*1/8 1 1.0 300 Yes 2 2 6
ecs.vgn5i-m2.xlarge 4 12.0 None P4*1/4 2 2.0 500 Yes 2 3 10
ecs.vgn5i-m4.2xlarge 8 24.0 None P4*1/2 4 3.0 800 Yes 2 4 10
ecs.vgn5i-m8.4xlarge 16 48.0 None P4*1 8 5.0 1,000 Yes 4 5 20
Note