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Elastic Compute Service:GPU-accelerated compute-optimized and vGPU-accelerated instance families

Last Updated:Feb 02, 2024

This topic describes the features of GPU-accelerated compute-optimized and 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

Features:

  • 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. Memory and GPU memory are provided in exclusive mode 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 a 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.

  • Compute:

    • Uses NVIDIA A10 GPUs that have the following features:

      • Innovative 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:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • 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

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network baseline/burst bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

ecs.sgn7i-vws-m2.xlarge

4

15.5

NVIDIA A10 * 1/12

24GB * 1/12

1.5/5

500,000

4

2

ecs.sgn7i-vws-m4.2xlarge

8

31

NVIDIA A10 * 1/6

24GB * 1/6

2.5/10

1,000,000

4

4

ecs.sgn7i-vws-m8.4xlarge

16

62

NVIDIA A10 * 1/3

24GB * 1/3

5/20

2,000,000

8

4

ecs.sgn7i-vws-m2s.xlarge

4

8

NVIDIA A10 * 1/12

24GB * 1/12

1.5/5

500,000

4

2

ecs.sgn7i-vws-m4s.2xlarge

8

16

NVIDIA A10 * 1/6

24GB * 1/6

2.5/10

1,000,000

4

4

ecs.sgn7i-vws-m8s.4xlarge

16

32

NVIDIA A10 * 1/3

24GB * 1/3

5/20

2,000,000

8

4

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 is allocated as a vGPU to an instance.

  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

vgn7i-vws, vGPU-accelerated instance family

Features:

  • 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 a 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.

  • Compute:

    • Uses NVIDIA A10 GPUs that have the following features:

      • Innovative 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:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • 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

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

ecs.vgn7i-vws-m4.xlarge

4

30

NVIDIA A10 * 1/6

24GB * 1/6

3

1,000,000

4

4

ecs.vgn7i-vws-m8.2xlarge

10

62

NVIDIA A10 * 1/3

24GB * 1/3

5

2,000,000

8

6

ecs.vgn7i-vws-m12.3xlarge

14

93

NVIDIA A10 * 1/2

24GB * 1/2

8

3,000,000

8

6

ecs.vgn7i-vws-m24.7xlarge

30

186

NVIDIA A10 * 1

24GB * 1

16

6,000,000

12

8

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 is allocated as a vGPU to an instance.

  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn7e, GPU-accelerated compute-optimized instance family

Features:

  • You can specify different numbers of GPUs and vCPUs in AI scenarios to meet your business requirements.

  • This instance family uses the third-generation SHENLONG architecture and doubles the average bandwidths of virtual private clouds (VPCs), networks, and disks compared with instance families of the previous generation.

  • Storage:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Small- and medium-scale AI training

    • High-performance computing (HPC) business accelerated by using Compute Unified Device Architecture (CUDA)

    • AI inference tasks that require high GPU processing capabilities or large amounts of GPU memory

    • Deep learning applications such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition.

    • Scientific computing applications that require robust GPU computing capabilities such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics

    Important

    When you use AI training services that feature a high communication load, such as transformer models, you must enable NVLink for GPU-to-GPU communication. Otherwise, data may be damaged due to unpredictable failures that are caused by large-scale data transmission over Peripheral Component Interconnect Express (PCIe) links. If you do not understand the topology of the communication links that are used for AI training services, submit a ticket to obtain technical support.

Instance types

Instance type

vCPU

Memory (GiB)

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn7e-c16g1.4xlarge

16

125

80GB * 1

8

3,000,000

8

8

10

ecs.gn7e-c16g1.16xlarge

64

500

80GB * 4

32

12,000,000

32

8

10

ecs.gn7e-c16g1.32xlarge

128

1000

80GB * 8

64

24,000,000

32

16

15

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn7i, GPU-accelerated compute-optimized instance family

Features:

  • 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.

  • Compute:

    • Uses NVIDIA A10 GPUs that have the following features:

      • Innovative Ampere architecture

      • Support for acceleration features such as RTX and TensorRT

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

    • Provides up to 752 GiB of memory, which is much larger than the memory sizes of the gn6i instance family.

  • Storage:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • 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

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn7i-c8g1.2xlarge

8

30

NVIDIA A10 * 1

24GB * 1

16

1,600,000

8

4

5

ecs.gn7i-c16g1.4xlarge

16

60

NVIDIA A10 * 1

24GB * 1

16

3,000,000

8

8

5

ecs.gn7i-c32g1.8xlarge

32

188

NVIDIA A10 * 1

24GB * 1

16

6,000,000

12

8

5

ecs.gn7i-c32g1.16xlarge

64

376

NVIDIA A10 * 2

24GB * 2

32

12,000,000

16

15

5

ecs.gn7i-c32g1.32xlarge

128

752

NVIDIA A10 * 4

24GB * 4

64

24,000,000

32

15

10

ecs.gn7i-c48g1.12xlarge

48

310

NVIDIA A10 * 1

24GB * 1

16

9,000,000

16

8

8

ecs.gn7i-c56g1.14xlarge

56

346

NVIDIA A10 * 1

24GB * 1

16

12,000,000

16

12

8

ecs.gn7i-2x.8xlarge

32

128

NVIDIA A10 * 2

24GB * 2

16

6,000,000

16

8

30

ecs.gn7i-4x.8xlarge

32

128

NVIDIA A10 * 4

24GB * 4

16

6,000,000

16

8

30

ecs.gn7i-4x.16xlarge

64

256

NVIDIA A10 * 4

24GB * 4

32

12,000,000

32

8

30

ecs.gn7i-8x.32xlarge

128

512

NVIDIA A10 * 8

24GB * 8

64

24,000,000

32

16

30

ecs.gn7i-8x.16xlarge

64

256

NVIDIA A10 * 8

24GB * 8

32

12,000,000

32

8

30

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • You can change the following instance types only to ecs.gn7i-c8g1.2xlarge or ecs.gn7i-c16g1.4xlarge: ecs.gn7i-2x.8xlarge, ecs.gn7i-4x.8xlarge, ecs.gn7i-4x.16xlarge, ecs.gn7i-8x.32xlarge, and ecs.gn7i-8x.16xlarge.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn7s, GPU-accelerated compute-optimized instance family

Features:

  • This instance family uses the latest Intel Ice Lake processors and NVIDIA A30 GPUs that are based on NVIDIA Ampere architecture. You can specify custom GPUs and CPUs to meet your AI business requirements.

  • This instance family uses the third-generation SHENLONG architecture and doubles the average bandwidths of VPCs, networks, and disks compared with instance families of the previous generation.

  • Compute:

    • Uses NVIDIA A30 GPUs that have the following features:

      • Innovative NVIDIA Ampere architecture

      • Support for the multi-instance GPU (MIG) feature and acceleration features (based on second-generation Tensor cores) 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.

    • Improves memory sizes significantly from instance families of the previous generation.

  • Storage: supports enhanced SSDs (ESSDs) and ESSD AutoPL disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios: concurrent AI inference tasks that require high-performance CPUs, memory, and GPUs, such as image recognition, speech recognition, and behavior identification.

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

IPv6 addresses per ENI

NIC queues

ENIs

ecs.gn7s-c8g1.2xlarge

8

60

NVIDIA A30 * 1

24GB * 1

16

6,000,000

1

12

8

ecs.gn7s-c16g1.4xlarge

16

120

NVIDIA A30 * 1

24GB * 1

16

6,000,000

1

12

8

ecs.gn7s-c32g1.8xlarge

32

250

NVIDIA A30 * 1

24GB * 1

16

6,000,000

1

12

8

ecs.gn7s-c32g1.16xlarge

64

500

NVIDIA A30 * 2

24GB * 2

32

12,000,000

1

16

15

ecs.gn7s-c32g1.32xlarge

128

1000

NVIDIA A30 * 4

24GB * 4

64

24,000,000

1

32

15

ecs.gn7s-c48g1.12xlarge

48

380

NVIDIA A30 * 1

24GB * 1

16

6,000,000

1

12

8

ecs.gn7s-c56g1.14xlarge

56

440

NVIDIA A30 * 1

24GB * 1

16

6,000,000

1

12

8

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn7, GPU-accelerated compute-optimized instance family

Features:

  • Storage:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Deep learning applications such as training applications of AI algorithms used in image classification, autonomous vehicles, and speech recognition.

    • Scientific computing applications that require robust GPU computing capabilities such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics

Instance types

Instance type

vCPU

Memory (GiB)

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

ecs.gn7-c12g1.3xlarge

12

94

40GB * 1

4

2,500,000

4

8

ecs.gn7-c13g1.13xlarge

52

378

40GB * 4

16

9,000,000

16

8

ecs.gn7-c13g1.26xlarge

104

756

40GB * 8

30

18,000,000

16

15

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

vgn6i and vgn6i-vws, vGPU-accelerated instance families

vgn6i-vws:

  • In light of the NVIDIA GRID driver upgrade, Alibaba Cloud upgrades the vgn6i instance family to vgn6i-vws instance family. The vgn6i-vws instance family uses the latest NVIDIA GRID driver and provides a NVIDIA GRID vWS license. If you want to apply for free images that have the NVIDIA GRID driver pre-installed, submit a ticket.

  • To use other public images or custom images that do not contain a 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.

vgn6i:

  • If you want your vgn6i instance to support graphics features such as Open Graphics Library (OpenGL), you must purchase a GRID license from NVIDIA. After the instance is created, install a GRID driver and activate the license.

  • 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:

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

    • Supports standard SSDs and ultra disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • 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

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues (primary NICI/secondary NIC)

ENIs

Private IP addresses per ENI

ecs.vgn6i-m4.xlarge

4

23

NVIDIA T4 * 1/4

16GB * 1/4

2

500,000

4/2

3

10

ecs.vgn6i-m8.2xlarge

10

46

NVIDIA T4 * 1/2

16GB * 1/2

4

800,000

8/2

4

10

ecs.vgn6i-m4-vws.xlarge

4

23

NVIDIA T4 * 1/4

16GB * 1/4

2

500,000

4/2

3

10

ecs.vgn6i-m8-vws.2xlarge

10

46

NVIDIA T4 * 1/2

16GB * 1/2

4

800,000

8/2

4

10

ecs.vgn6i-m16-vws.5xlarge

20

92

NVIDIA T4 * 1

16GB * 1

7.5

1,200,000

6

4

10

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 is allocated as a vGPU to an instance.

  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn6i, GPU-accelerated compute-optimized instance family

Features:

  • Compute:

    • Uses NVIDIA T4 GPUs that have the following features:

      • Innovative NVIDIA Turing architecture

      • 16 GB memory (320 GB/s bandwidth) per GPU

      • 2,560 CUDA cores per GPU

      • Up to 320 Turing Tensor cores per GPU

      • Mixed-precision Tensor cores that support 65 FP16 TFLOPS, 130 INT8 TOPS, and 260 INT4 TOPS

    • Offers a CPU-to-memory ratio of 1:4.

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

  • Storage:

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

    • Supports ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • AI (deep learning and machine learning) inference for computer vision, speech recognition, speech synthesis, natural language processing (NLP), machine translation, and recommendation systems

    • Real-time rendering for cloud gaming

    • Real-time rendering for AR and VR applications

    • Graphics workstations or overloaded graphics computing

    • GPU-accelerated databases

    • High-performance computing

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

Storage baseline IOPS

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn6i-c4g1.xlarge

4

15

NVIDIA T4 * 1

16GB * 1

4

500,000

N/A

2

2

10

ecs.gn6i-c8g1.2xlarge

8

31

NVIDIA T4 * 1

16GB * 1

5

800,000

N/A

2

2

10

ecs.gn6i-c16g1.4xlarge

16

62

NVIDIA T4 * 1

16GB * 1

6

1,000,000

N/A

4

3

10

ecs.gn6i-c24g1.6xlarge

24

93

NVIDIA T4 * 1

16GB * 1

7.5

1,200,000

N/A

6

4

10

ecs.gn6i-c40g1.10xlarge

40

155

NVIDIA T4 * 1

16GB * 1

10

1,600,000

N/A

16

10

10

ecs.gn6i-c24g1.12xlarge

48

186

NVIDIA T4 * 2

16GB * 2

15

2,400,000

N/A

12

6

10

ecs.gn6i-c24g1.24xlarge

96

372

NVIDIA T4 * 4

16GB * 4

30

4,800,000

250,000

24

8

10

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn6e, GPU-accelerated compute-optimized instance family

Features:

  • Compute:

    • Uses NVIDIA V100 GPUs that each has 32 GB of GPU memory and support NVLink.

    • Uses NVIDIA V100 GPUs (SXM2-based) that have the following features:

      • Innovative NVIDIA Volta architecture

      • 32 GB HBM2 memory (900 GB/s bandwidth) per GPU

      • 5,120 CUDA cores per GPU

      • Up to 640 Tensor cores per GPU

      • Support for up to six NVLink bidirectional connections, which each provide a bandwidth of 25 GB/s in each direction for a total bandwidth of 300 GB/s (6 × 25 × 2 = 300)

    • Offers a CPU-to-memory ratio of 1:8.

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

  • Storage:

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

    • Supports ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Deep learning applications such as the training and inference applications of AI algorithms used in image classification, autonomous driving, and speech recognition

    • Scientific computing applications, such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn6e-c12g1.3xlarge

12

92

NVIDIA V100 * 1

32GB * 1

5

800,000

8

6

10

ecs.gn6e-c12g1.12xlarge

48

368

NVIDIA V100 * 4

32GB * 4

16

2,400,000

8

8

20

ecs.gn6e-c12g1.24xlarge

96

736

NVIDIA V100 * 8

32GB * 8

32

4,800,000

16

8

20

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn6v, GPU-accelerated compute-optimized instance family

Features:

  • Compute:

    • Uses NVIDIA V100 GPUs.

    • Uses NVIDIA V100 GPUs (SXM2-based) that have the following features:

      • Innovative NVIDIA Volta architecture

      • 16 GB HBM2 memory (900 GB/s bandwidth) per GPU

      • 5,120 CUDA cores per GPU

      • Up to 640 Tensor cores per GPU

      • Support for up to six NVLink bidirectional connections, which each provide a bandwidth of 25 GB/s in each direction for a total bandwidth of 300 GB/s (6 × 25 × 2 = 300)

    • Offers a CPU-to-memory ratio of 1:4.

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

  • Storage:

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

    • Supports ESSDs, ESSD AutoPL disks, standard SSDs, and ultra disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Deep learning applications such as the training and inference applications of AI algorithms used in image classification, autonomous driving, and speech recognition

    • Scientific computing applications, such as computational fluid dynamics, computational finance, molecular dynamics, and environmental analytics

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

Storage baseline IOPS

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn6v-c8g1.2xlarge

8

32

NVIDIA V100 * 1

16GB * 1

2.5

800,000

N/A

4

4

10

ecs.gn6v-c8g1.8xlarge

32

128

NVIDIA V100 * 4

16GB * 4

10

2,000,000

N/A

8

8

20

ecs.gn6v-c8g1.16xlarge

64

256

NVIDIA V100 * 8

16GB * 8

20

2,500,000

N/A

16

8

20

ecs.gn6v-c10g1.20xlarge

82

336

NVIDIA V100 * 8

16GB * 8

32

4,500,000

250,000

16

8

20

Note

vgn5i, vGPU-accelerated instance family

Features:

  • If you want the vgn5i instance to support graphics features such as OpenGL, you must purchase a GRID license from the NVIDIA, install the GRID driver, and activate the license after you create the instance.

  • Compute:

    • Uses NVIDIA P4 GPUs.

    • Uses vGPUs.

      • Supports the 1/8, 1/4, 1/2, and 1/1 compute capacity of NVIDIA Tesla P4 GPUs.

      • Supports 1 GB, 2 GB, 4 GB, and 8 GB of GPU memory.

    • Offers a CPU-to-memory ratio of 1:3.

    • Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.

  • Storage:

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

    • Supports standard SSDs and ultra disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Real-time rendering for cloud gaming

    • 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)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.vgn5i-m1.large

2

6

NVIDIA P4 * 1/8

8GB * 1/8

1

300,000

2

2

6

ecs.vgn5i-m2.xlarge

4

12

NVIDIA P4 * 1/4

8GB * 1/4

2

500,000

2

3

10

ecs.vgn5i-m4.2xlarge

8

24

NVIDIA P4 * 1/2

8GB * 1/2

3

800,000

2

4

10

ecs.vgn5i-m8.4xlarge

16

48

NVIDIA P4 * 1

8GB * 1

5

1,000,000

4

5

20

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 P4 * 1/8. NVIDIA P4 is the GPU model. 1/8 indicates that a GPU is sliced into eight GPU partitions and each GPU partition is allocated as a vGPU to an instance.

  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn5, GPU-accelerated compute-optimized instance family

Features:

  • Compute:

    • Uses NVIDIA P100 GPUs.

    • Offers multiple CPU-to-memory ratios.

    • Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.

  • Storage:

    • Supports high-performance local Non-Volatile Memory Express (NVMe) SSDs.

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

    • Supports standard SSDs and ultra disks.

  • Network:

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Deep learning

    • Scientific computing applications, such as computational fluid dynamics, computational finance, genomics, and environmental analytics

    • Server-side GPU compute workloads such as high-performance computing, rendering, and multi-media encoding and decoding

Instance types

Instance type

vCPU

Memory (GiB)

Local storage (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn5-c4g1.xlarge

4

30

440

NVIDIA P100 * 1

16GB * 1

3

300,000

1

3

10

ecs.gn5-c8g1.2xlarge

8

60

440

NVIDIA P100 * 1

16GB * 1

3

400,000

1

4

10

ecs.gn5-c4g1.2xlarge

8

60

880

NVIDIA P100 * 2

16GB * 2

5

1,000,000

2

4

10

ecs.gn5-c8g1.4xlarge

16

120

880

NVIDIA P100 * 2

16GB * 2

5

1,000,000

4

8

20

ecs.gn5-c28g1.7xlarge

28

112

440

NVIDIA P100 * 1

16GB * 1

5

1,000,000

8

8

20

ecs.gn5-c8g1.8xlarge

32

240

1760

NVIDIA P100 * 4

16GB * 4

10

2,000,000

8

8

20

ecs.gn5-c28g1.14xlarge

56

224

880

NVIDIA P100 * 2

16GB * 2

10

2,000,000

14

8

20

ecs.gn5-c8g1.14xlarge

54

480

3520

NVIDIA P100 * 8

16GB * 8

25

4,000,000

14

8

20

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.

gn5i, GPU-accelerated compute-optimized instance family

Features:

  • Compute:

    • Uses NVIDIA P4 GPUs.

    • Offers a CPU-to-memory ratio of 1:4.

    • Uses 2.5 GHz Intel® Xeon® E5-2682 v4 (Broadwell) processors.

  • Storage:

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

    • Supports standard SSDs and ultra disks.

  • Network:

    • Supports IPv6.

    • Provides high network performance based on large computing capacity.

  • Supported scenarios:

    • Deep learning inference.

    • Server-side GPU compute workloads such as multi-media encoding and decoding

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.gn5i-c2g1.large

2

8

NVIDIA P4 * 1

8GB * 1

1

100,000

2

2

6

ecs.gn5i-c4g1.xlarge

4

16

NVIDIA P4 * 1

8GB * 1

1.5

200,000

2

3

10

ecs.gn5i-c8g1.2xlarge

8

32

NVIDIA P4 * 1

8GB * 1

2

400,000

4

4

10

ecs.gn5i-c16g1.4xlarge

16

64

NVIDIA P4 * 1

8GB * 1

3

800,000

4

8

20

ecs.gn5i-c16g1.8xlarge

32

128

NVIDIA P4 * 2

8GB * 2

6

1,200,000

8

8

20

ecs.gn5i-c28g1.14xlarge

56

224

NVIDIA P4 * 2

8GB * 2

10

2,000,000

14

8

20

Note
  • You can go to the ECS Instance Types Available for Each Region page to view the instance types available in each region.

  • For more information about these specifications, see the "Instance type specifications" section in Overview of instance families. Packet forwarding rates vary significantly based on business scenarios. We recommend that you perform business stress tests on instances to choose appropriate instance types.