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Elastic GPU Service:GPU-accelerated compute-optimized instance families

Last Updated:Dec 28, 2023

GPU-accelerated compute-optimized instances provide high performance and high parallel computing capabilities, and are suitable for large-scale parallel computing scenarios. You can use GPU-accelerated compute-optimized instances to achieve improved computing performance and efficiency for your business. This topic describes the features of GPU-accelerated compute-optimized instance families of Elastic Compute Service (ECS) and lists the instance specifications of each instance family.

gn7e, GPU-accelerated compute-optimized instance family

Features:

  • This instance family uses Intel Ice lake processors that are interconnected by using NVSwitches. You can choose an appropriate mix of GPUs and CPU resources to meet various AI 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:

    • Is 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

vCPUs

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

When you create or restart a gn7e instance in the ECS console, the Multi-Instance GPU (MIG) feature of the instance is automatically disabled. For more information about MIG, see NVIDIA Multi-Instance GPU User Guide.

The following table describes whether the MIG feature is supported by the instance types in the gn7e instance family.

Instance type

MIG

Description

ecs.gn7e-c16g1.4xlarge

Yes

The MIG feature is supported by single-GPU instances.

ecs.gn7e-c16g1.16xlarge

No

The MIG feature is not supported by multi-GPU instances for security reasons.

ecs.gn7e-c16g1.32xlarge

No

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 NVIDIA 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:

    • Is 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

vCPUs

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

Note

gn7s, GPU-accelerated compute-optimized instance family

Features:

  • This instance family uses new Intel Ice lake processors and NVIDIA A30 GPUs that are based on NVIDIA Ampere architecture. You can choose an appropriate mix of GPUs and CPU resources to meet various 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

vCPUs

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

gn7, GPU-accelerated compute-optimized instance family

Features:

  • Storage:

    • Is 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

vCPUs

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

When you create or restart a gn7 instance in the ECS console, the MIG feature of the instance is automatically disabled. For more information about MIG, see NVIDIA Multi-Instance GPU User Guide.

The following table describes whether the MIG feature is supported by the instance types in the gn7 instance family.

Instance type

MIG

Description

ecs.gn7-c12g1.3xlarge

Yes

The MIG feature is supported by single-GPU instances.

ecs.gn7-c13g1.13xlarge

No

The MIG feature is not supported by multi-GPU instances for security reasons.

ecs.gn7-c13g1.26xlarge

No

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:

    • Is 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 graphics-heavy computing

    • GPU-accelerated databases

    • High-performance computing

Instance types

Instance type

vCPUs

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

None

2

2

10

ecs.gn6i-c8g1.2xlarge

8

31

NVIDIA T4 * 1

16GB * 1

5

800,000

None

2

2

10

ecs.gn6i-c16g1.4xlarge

16

62

NVIDIA T4 * 1

16GB * 1

6

1,000,000

None

4

3

10

ecs.gn6i-c24g1.6xlarge

24

93

NVIDIA T4 * 1

16GB * 1

7.5

1,200,000

None

6

4

10

ecs.gn6i-c40g1.10xlarge

40

155

NVIDIA T4 * 1

16GB * 1

10

1,600,000

None

16

10

10

ecs.gn6i-c24g1.12xlarge

48

186

NVIDIA T4 * 2

16GB * 2

15

2,400,000

None

12

6

10

ecs.gn6i-c24g1.24xlarge

96

372

NVIDIA T4 * 4

16GB * 4

30

4,800,000

250,000

24

8

10

Note

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:

    • Is 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

vCPUs

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

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:

    • Is 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

vCPUs

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

None

4

4

10

ecs.gn6v-c8g1.8xlarge

32

128

NVIDIA V100 * 4

16GB * 4

10

2,000,000

None

8

8

20

ecs.gn6v-c8g1.16xlarge

64

256

NVIDIA V100 * 8

16GB * 8

20

2,500,000

None

16

8

20

ecs.gn6v-c10g1.20xlarge

82

336

NVIDIA V100 * 8

16GB * 8

32

4,500,000

250,000

16

8

20

Note

ebmgn7e, GPU-accelerated compute-optimized ECS Bare Metal Instance family

Features:

  • This instance family uses the SHENLONG architecture to provide flexible and powerful software-defined compute.

  • Storage:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides ultra-high network performance with a packet forwarding rate of 24,000,000 pps.

  • Supported scenarios:

    • Deep learning training and development

    • High-performance computing (HPC) and simulations

    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 (Primary NIC/Secondary NIC)

ENIs

ecs.ebmgn7e.32xlarge

128

1024

80GB * 8

64

24,000,000

32/12

32

Note

You must check the status of the MIG feature and enable or disable the MIG feature after you start an ebmgn7e instance. For more information about MIG, see NVIDIA Multi-Instance GPU User Guide.

The following table describes whether the MIG feature is supported by the instance types in the ebmgn7e instance family.

Instance type

MIG

Description

ecs.ebmgn7e.32xlarge

Yes

The MIG feature is supported by ebmgn7e instances.

ebmgn7i, GPU-accelerated compute optimized ECS Bare Metal Instance family

Features:

  • This instance family uses the SHENLONG architecture to provide flexible and powerful software-defined compute.

  • Compute:

    • Uses NVIDIA A10 GPUs that have the following features:

      • Innovative NVIDIA Ampere architecture

      • Support for acceleration features such as vGPU, RTX technology, and TensorRT inference engine

    • 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.

    • ESSDs and ESSD AutoPL disks are supported.

  • Network:

    • Supports IPv6.

    • Provides ultra-high network performance with a packet forwarding rate of 24,000,000 pps.

  • 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

    • Scenarios that require high network bandwidth and disk bandwidth, such as the creation of high-performance render farms

    • Small-scale deep learning and training applications that require high network bandwidth

Instance types

Instance type

vCPU

Memory (GiB)

GPU

GPU memory

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

ecs.ebmgn7i.32xlarge

128

768

NVIDIA A10 * 4

24GB * 4

64

24,000,000

32

32

Note

ebmgn7, GPU-accelerated compute-optimized ECS Bare Metal Instance family

Features:

  • This instance family uses the SHENLONG architecture to provide flexible and powerful software-defined compute.

  • Storage:

    • Is 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)

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

NIC queues

ENIs

Private IP addresses per ENI

ecs.ebmgn7.26xlarge

104

768

30

18,000,000

16

15

10

Note

You must manually check the status of the MIG feature and enable or disable the MIG feature after you start an ebmgn7 instance. For more information about MIG, see NVIDIA Multi-Instance GPU User Guide.

The following table describes whether the MIG feature is supported by the instance types in the ebmgn7 instance family.

Instance type

MIG

Description

ecs.ebmgn7.26xlarge

Yes

The MIG feature is supported by ebmgn7 instances.

ebmgn6ia, GPU-accelerated compute-optimized ECS Bare Metal Instance family

The instance family is in invitational preview. To use the instance family, submit a ticket.

Features:

  • This instance family uses the third-generation SHENLONG architecture and fast path acceleration on chips to provide predictable and consistent ultra-high computing, storage, and network performance.

  • This instance family uses NVIDIA T4 GPUs to offer GPU acceleration capabilities for graphics and AI applications and adopts container technology to start up to 60 virtual Android devices and provide hardware-accelerated video transcoding.

  • Compute:

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

    • Uses 2.8 GHz Ampere® Altra® Arm-based processors that deliver a turbo frequency of 3.0 GHz and provides high performance and high compatibility with applications for Android servers.

  • Storage:

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

    • ESSDs and ESSD AutoPL disks are supported.

  • Network: supports IPv6.

  • Supported scenarios: remote application services based on Android, such as always-on cloud-based services, cloud-based mobile games, cloud-based mobile phones, and Android service crawlers.

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.ebmgn6ia.20xlarge

80

256

NVIDIA T4 * 2

16GB * 2

32

24,000,000

32

15

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.

  • Ampere® Altra® processors have specific requirements on the kernels of operating systems. Instances of the preceding instance type can use Alibaba Cloud Linux 3 images and CentOS 8.4 or later images. We recommend that you use Alibaba Cloud Linux 3 images on the instances. If you want to use another operating system distribution, patch the kernel of an instance that runs an operating system of that distribution, create a custom image from the instance, and then use the custom image to create instances of the instance type. For information about kernel patches, visit Ampere Altra (TM) Linux Kernel Porting Guide.

  • The CPU monitoring information about ECS bare metal instances cannot be obtained. To obtain the CPU monitoring information about an ECS bare metal instance, install the CloudMonitor agent on the instance. For more information, see Install and uninstall the CloudMonitor agent for C++.

ebmgn6e, GPU-accelerated compute-optimized ECS Bare Metal Instance family

Features:

  • This instance family uses the SHENLONG architecture to provide flexible and powerful software-defined compute.

  • This instance family uses NVIDIA V100 GPUs that each has 32 GB of GPU memory and support NVLink.

  • This instance family uses NVIDIA V100 GPUs (SXM2-based) that have the following features:

    • Innovative NVIDIA Volta architecture.

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

    • 5,120 CUDA cores per GPU.

    • 640 Tensor cores per GPU.

    • Support for up to six NVLink connections. Each NVLink connection provides a bandwidth of 25 GB/s in each direction for a total bandwidth of 300 GB/s (6 × 25 × 2 = 300).

  • Compute:

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

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

  • Storage:

    • Is 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 training and inference applications of AI algorithms used in image classification, autonomous vehicles, 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.ebmgn6e.24xlarge

96

768

NVIDIA V100 * 8

32GB * 8

32

4,800,000

16

15

10

Note

ebmgn6v, GPU-accelerated compute-optimized ECS Bare Metal Instance family

Features:

  • This instance family uses the SHENLONG architecture to provide flexible and powerful software-defined compute.

  • This instance family uses NVIDIA V100 GPUs.

  • This instance family uses NVIDIA V100 GPUs (SXM2-based) that have the following features:

    • Innovative NVIDIA Volta architecture.

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

    • 5,120 CUDA cores per GPU.

    • 640 Tensor cores per GPU.

    • Support for up to six NVLink connections. Each NVLink connection provides a bandwidth of 25 GB/s in each direction for a total bandwidth of 300 GB/s (6 × 25 × 2 = 300).

  • Compute:

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

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

  • Storage:

    • Is 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 training and inference applications of AI algorithms used in image classification, autonomous vehicles, 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.ebmgn6v.24xlarge

96

384

NVIDIA V100 * 8

16GB * 8

30

4,500,000

8

32

10

Note

ebmgn6i, GPU-accelerated compute-optimized ECS Bare Metal Instance family

Features:

  • This instance family uses the SHENLONG architecture to provide flexible and powerful software-defined compute.

  • This instance family uses NVIDIA T4 GPUs that have the following features:

    • Innovative NVIDIA Turing architecture

    • 16 GB of 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

  • Compute:

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

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

  • Storage:

    • Is 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, voice recognition, speech synthesis, natural language processing (NLP), machine translation, and reference systems

    • Real-time rendering for cloud games

    • Real-time rendering for AR and VR applications

    • Graphics workstations or graphics-heavy 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)

NIC queues

ENIs

Private IP addresses per ENI

ecs.ebmgn6i.24xlarge

96

384

NVIDIA T4 * 4

16GB * 4

30

4,500,000

8

32

10

Note

sccgn6e, GPU-accelerated compute-optimized SCC instance family

To use it, submit a ticket.

Features:

  • This instance family provides all features of ECS Bare Metal Instance. For more information, see Overview of ECS Bare Metal Instance families.

  • Compute:

    • This instance family uses NVIDIA V100 GPUs (SXM2-based) that have the following features:

      • Innovative NVIDIA Volta architecture

      • 32 GB of HBM2 GPU memory

      • 5,120 CUDA cores

      • 640 Tensor cores

      • GPU memory bandwidth of up to 900 GB/s

      • Support for up to six bidirectional NVLink connections, which each have a unidirectional bandwidth of 25 GB/s for a total bandwidth of 300 GB/s

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

    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors for consistent computing performance.

  • Storage:

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

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

    • Supports high-performance Cloud Paralleled File System (CPFS).

  • Network:

    • Supports IPv6.

    • Supports VPCs.

    • Supports RoCE v2 networks, which are dedicated to low-latency RDMA communication.

  • Supported scenarios:

    • Ultra-large-scale training for machine learning on distributed GPU clusters

    • Large-scale high-performance scientific computing and simulation calculation

    • Large-scale data analytics, batch processing, and video encoding

Instance types

Instance type

vCPUs

Memory (GiB)

GPU

GPU memory (GB)

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

RoCE bandwidth (Gbit/s)

NIC queues

ENIs

Private IP addresses per ENI

ecs.sccgn6e.24xlarge

96

768.0

NVIDIA V100 * 8

32GB * 8

32

4,800,000

50

8

32

10

Note

sccgn6, GPU-accelerated compute-optimized SCC instance family

Features:

  • This instance family provides all features of ECS Bare Metal Instance. For more information, see Overview of ECS Bare Metal Instance families.

  • Compute:

    • This instance family uses NVIDIA V100 GPUs (SXM2-based) that have the following features:

      • Innovative NVIDIA Volta architecture

      • 16 GB of HBM2 GPU memory

      • 5,120 CUDA cores

      • 640 Tensor cores

      • GPU memory bandwidth of up to 900 GB/s

      • Support for up to six bidirectional NVLink connections, which each have a unidirectional bandwidth of 25 GB/s for a total bandwidth of 300 GB/s

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

    • Uses 2.5 GHz Intel® Xeon® Platinum 8163 (Skylake) processors for consistent computing performance.

  • Storage:

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

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

    • Supports high-performance CPFS.

  • Network:

    • Supports IPv6.

    • Supports VPCs.

    • Supports RoCE v2 networks, which are dedicated to low-latency RDMA communication.

  • Supported scenarios:

    • Ultra-large-scale training for machine learning on distributed GPU clusters

    • Large-scale high-performance scientific computing and simulation calculation

    • Large-scale data analytics, batch processing, and video encoding

Instance types

Instance type

vCPUs

Memory (GiB)

GPU

Network bandwidth (Gbit/s)

Packet forwarding rate (pps)

RoCE bandwidth (Gbit/s)

NIC queues

ENIs

Private IP addresses per ENI

ecs.sccgn6.24xlarge

96

384.0

NVIDIA V100 * 8

30

4,500,000

50

8

32

10

Note

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.

    • Is 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

vCPUs

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

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:

    • Is 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

vCPUs

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