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Elastic GPU Service:vGPU-accelerated instance families (vgn and sgn series)

Last Updated:Dec 09, 2024

Instances of vGPU-accelerated instance families provide high-performance graphics processing and GPU-accelerated computing capabilities. vGPU-accelerated instances are suitable for graphics acceleration and rendering scenarios and general-purpose computing scenarios. This topic describes the features of vGPU-accelerated instance families of Elastic Compute Service (ECS) and lists the instance types of each instance family.

sgn7i-vws, vGPU-accelerated instance family with shared CPUs

  • Introduction:

    • This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data storage and model loading can be performed more quickly.

    • Instances of this instance family share CPU and network resources to maximize the utilization of underlying resources. Each instance has exclusive access to its memory and GPU memory to provide data isolation and performance assurance.

      Note

      If you want to use exclusive CPU resources, select the vgn7i-vws instance family.

    • This instance family comes with an NVIDIA GRID vWS license and provides certified graphics acceleration capabilities for Computer Aided Design (CAD) software to meet the requirements of professional graphic design. Instances of this instance family can serve as lightweight GPU-accelerated compute-optimized instances to reduce the costs of small-scale AI inference tasks.

  • Supported scenarios:

    • Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification

    • Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming

    • 3D modeling in fields that require the use of Ice Lake processors, such as animation and film production, cloud gaming, and mechanical design

  • Compute:

    • Uses NVIDIA A10 GPUs that have the following features:

      • Innovative NVIDIA Ampere architecture

      • Support for acceleration features, such as vGPU, RTX, and TensorRT, to provide diversified business support

    • Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.

  • Storage:

    • Is an instance family in which all instances are I/O optimized.

    • Supports Enterprise SSDs (ESSDs) and ESSD AutoPL disks.

  • Network:

    • Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.

    • Provides high network performance based on large computing capacity.

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network baseline/burst bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IPv4 addresses per ENI

IPv6 addresses per ENI

ecs.sgn7i-vws-m2.xlarge

4

15.5

NVIDIA A10 * 1/12

24GB * 1/12

1.5/5

500,000

4

2

2

1

ecs.sgn7i-vws-m4.2xlarge

8

31

NVIDIA A10 * 1/6

24GB * 1/6

2.5/10

1,000,000

4

4

6

1

ecs.sgn7i-vws-m8.4xlarge

16

62

NVIDIA A10 * 1/3

24GB * 1/3

5/20

2,000,000

8

4

10

1

ecs.sgn7i-vws-m2s.xlarge

4

8

NVIDIA A10 * 1/12

24GB * 1/12

1.5/5

500,000

4

2

2

1

ecs.sgn7i-vws-m4s.2xlarge

8

16

NVIDIA A10 * 1/6

24GB * 1/6

2.5/10

1,000,000

4

4

6

1

ecs.sgn7i-vws-m8s.4xlarge

16

32

NVIDIA A10 * 1/3

24GB * 1/3

5/20

2,000,000

8

4

10

1

Note

The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:

NVIDIA A10 * 1/12. NVIDIA A10 is the GPU model. 1/12 indicates that a GPU is sliced into 12 GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.

vgn7i-vws, vGPU-accelerated instance family

  • Introduction:

    • This instance family uses the third-generation SHENLONG architecture to provide predictable and consistent ultra-high performance. This instance family utilizes fast path acceleration on chips to improve storage performance, network performance, and computing stability by an order of magnitude. This way, data storage and model loading can be performed more quickly.

    • This instance family comes with an NVIDIA GRID vWS license and provides certified graphics acceleration capabilities for CAD software to meet the requirements of professional graphic design. Instances of this instance family can serve as lightweight GPU-accelerated compute-optimized instances to reduce the costs of small-scale AI inference tasks.

  • Supported scenarios:

    • Concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification

    • Compute-intensive graphics processing tasks that require high-performance 3D graphics virtualization capabilities, such as remote graphic design and cloud gaming

    • 3D modeling in fields that require the use of Ice Lake processors, such as animation and film production, cloud gaming, and mechanical design

  • Compute:

    • Uses NVIDIA A10 GPUs that have the following features:

      • Innovative NVIDIA Ampere architecture

      • Support for acceleration features, such as vGPU, RTX, and TensorRT, to provide diversified business support

    • Uses 2.9 GHz Intel® Xeon® Scalable (Ice Lake) processors that deliver an all-core turbo frequency of 3.5 GHz.

  • Storage:

    • Is an instance family in which all instances are I/O optimized.

    • Supports ESSDs and ESSD AutoPL disks.

  • Network:

    • Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.

    • Provides high network performance based on large computing capacity.

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network baseline bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IPv4 addresses per ENI

IPv6 addresses per ENI

ecs.vgn7i-vws-m4.xlarge

4

30

NVIDIA A10 * 1/6

24GB * 1/6

3

1,000,000

4

4

10

1

ecs.vgn7i-vws-m8.2xlarge

10

62

NVIDIA A10 * 1/3

24GB * 1/3

5

2,000,000

8

6

10

1

ecs.vgn7i-vws-m12.3xlarge

14

93

NVIDIA A10 * 1/2

24GB * 1/2

8

3,000,000

8

6

15

1

ecs.vgn7i-vws-m24.7xlarge

30

186

NVIDIA A10 * 1

24GB * 1

16

6,000,000

12

8

30

1

Note

The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:

NVIDIA A10 * 1/6. NVIDIA A10 is the GPU model. 1/6 indicates that a GPU is sliced into six GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.

vgn6i-vws, vGPU-accelerated instance family

Important
  • In light of the NVIDIA GRID driver upgrade, Alibaba Cloud upgrades the vgn6i instance family to the vgn6i-vws instance family. The vgn6i-vws instance family uses the latest NVIDIA GRID driver and provides an NVIDIA GRID vWS license. To apply for free images for which the NVIDIA GRID driver is pre-installed, submit a ticket.

  • To use other public images or custom images that do not contain an NVIDIA GRID driver, submit a ticket to apply for the GRID driver file and install the NVIDIA GRID driver. Alibaba Cloud does not charge additional license fees for the GRID driver.

  • Supported scenarios:

    • Real-time rendering for cloud gaming

    • Real-time rendering for Augmented Reality (AR) and Virtual Reality (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

  • Compute:

    • Uses NVIDIA T4 GPUs.

    • Uses vGPUs.

      • Supports the 1/4 and 1/2 compute capacity of NVIDIA Tesla T4 GPUs.

      • Supports 4 GB and 8 GB of GPU memory.

    • Offers a CPU-to-memory ratio of 1:5.

    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors.

  • Storage:

    • Is an instance family in which all instances are I/O optimized.

    • Supports standard SSDs and ultra disks.

  • Network:

    • Supports IPv4 and IPv6. For information about IPv6 communication, see IPv6 communication.

    • Provides high network performance based on large computing capacity.

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network baseline bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IPv4 addresses per ENI

IPv6 addresses per ENI

ecs.vgn6i-m4-vws.xlarge

4

23

NVIDIA T4 * 1/4

16GB * 1/4

2

500,000

4/2

3

10

1

ecs.vgn6i-m8-vws.2xlarge

10

46

NVIDIA T4 * 1/2

16GB * 1/2

4

800,000

8/2

4

10

1

ecs.vgn6i-m16-vws.5xlarge

20

92

NVIDIA T4 * 1

16GB * 1

7.5

1,200,000

6

4

10

1

Note

The GPU column in the preceding table indicates the GPU model and GPU slicing information for each instance type. Each GPU can be sliced into multiple GPU partitions, and each GPU partition can be allocated as a vGPU to an instance. Example:

NVIDIA T4 * 1/4. NVIDIA T4 is the GPU model. 1/4 indicates that a GPU is sliced into four GPU partitions, and each GPU partition can be allocated as a vGPU to an instance.