diff --git a/docs/ecs/umn/ALL_META.TXT.json b/docs/ecs/umn/ALL_META.TXT.json index b07fd670..2257ece7 100644 --- a/docs/ecs/umn/ALL_META.TXT.json +++ b/docs/ecs/umn/ALL_META.TXT.json @@ -1111,7 +1111,7 @@ "code":"59", "des":"To use graphics acceleration, such as OpenGL, DirectX, or Vulkan, install a GRID driver and separately purchase and configure a GRID license. The GRID driver with a vDWS ", "doc_type":"usermanual", - "kw":"Installing a GRID Driver on a GPU-accelerated ECS,Managing GPU Drivers of GPU-accelerated ECSs,User ", + "kw":"Manually Installing a GRID Driver on a GPU-accelerated ECS,Managing GPU Drivers of GPU-accelerated E", "search_title":"", "metedata":[ { @@ -1120,7 +1120,7 @@ "opensource":"false;true" } ], - "title":"Installing a GRID Driver on a GPU-accelerated ECS", + "title":"Manually Installing a GRID Driver on a GPU-accelerated ECS", "githuburl":"" }, { @@ -2023,7 +2023,7 @@ "code":"107", "des":"Note the following when using default security group rules:Inbound rules control incoming traffic to instances in the default security group. The instances can only commu", "doc_type":"usermanual", - "kw":"Default Security Group and Rules,Security Groups,User Guide", + "kw":"Default Security Groups and Rules,Security Groups,User Guide", "search_title":"", "metedata":[ { @@ -2032,7 +2032,7 @@ "opensource":"false;true" } ], - "title":"Default Security Group and Rules", + "title":"Default Security Groups and Rules", "githuburl":"" }, { @@ -2156,7 +2156,7 @@ "code":"114", "des":"HUAWEI CLOUD Help Center presents technical documents to help you quickly get started with HUAWEI CLOUD services. The technical documents include Service Overview, Price Details, Purchase Guide, User Guide, API Reference, Best Practices, FAQs, and Videos.", "doc_type":"usermanual", - "kw":"Passwords and Key Pairs", + "kw":"Passwords and Key Pairs Management", "search_title":"", "metedata":[ { @@ -2165,7 +2165,7 @@ "opensource":"false;true" } ], - "title":"Passwords and Key Pairs", + "title":"Passwords and Key Pairs Management", "githuburl":"" }, { diff --git a/docs/ecs/umn/CLASS.TXT.json b/docs/ecs/umn/CLASS.TXT.json index 9dfa52b2..7fa22a5d 100644 --- a/docs/ecs/umn/CLASS.TXT.json +++ b/docs/ecs/umn/CLASS.TXT.json @@ -524,7 +524,7 @@ { "desc":"To use graphics acceleration, such as OpenGL, DirectX, or Vulkan, install a GRID driver and separately purchase and configure a GRID license. The GRID driver with a vDWS ", "product_code":"ecs", - "title":"Installing a GRID Driver on a GPU-accelerated ECS", + "title":"Manually Installing a GRID Driver on a GPU-accelerated ECS", "uri":"en-us_topic_0149610914.html", "doc_type":"usermanual", "p_code":"56", @@ -956,7 +956,7 @@ { "desc":"Note the following when using default security group rules:Inbound rules control incoming traffic to instances in the default security group. The instances can only commu", "product_code":"ecs", - "title":"Default Security Group and Rules", + "title":"Default Security Groups and Rules", "uri":"en-us_topic_0140323154.html", "doc_type":"usermanual", "p_code":"105", @@ -1019,7 +1019,7 @@ { "desc":"HUAWEI CLOUD Help Center presents technical documents to help you quickly get started with HUAWEI CLOUD services. The technical documents include Service Overview, Price Details, Purchase Guide, User Guide, API Reference, Best Practices, FAQs, and Videos.", "product_code":"ecs", - "title":"Passwords and Key Pairs", + "title":"Passwords and Key Pairs Management", "uri":"en-us_topic_0140313881.html", "doc_type":"usermanual", "p_code":"", diff --git a/docs/ecs/umn/en-us_topic_0000001234175322.html b/docs/ecs/umn/en-us_topic_0000001234175322.html index b97488d9..7dae2776 100644 --- a/docs/ecs/umn/en-us_topic_0000001234175322.html +++ b/docs/ecs/umn/en-us_topic_0000001234175322.html @@ -21,7 +21,7 @@
-
Parent topic: Passwords and Key Pairs
+
Parent topic: Passwords and Key Pairs Management
diff --git a/docs/ecs/umn/en-us_topic_0031073513.html b/docs/ecs/umn/en-us_topic_0031073513.html index bd9a2063..7b1da2c8 100644 --- a/docs/ecs/umn/en-us_topic_0031073513.html +++ b/docs/ecs/umn/en-us_topic_0031073513.html @@ -15,7 +15,7 @@
-
Parent topic: Passwords and Key Pairs
+
Parent topic: Passwords and Key Pairs Management
diff --git a/docs/ecs/umn/en-us_topic_0041169567.html b/docs/ecs/umn/en-us_topic_0041169567.html index 1dbe94df..55f8349a 100644 --- a/docs/ecs/umn/en-us_topic_0041169567.html +++ b/docs/ecs/umn/en-us_topic_0041169567.html @@ -36,12 +36,6 @@

Searching for ECSs

-

2023-12-18

- -

Modified the following content:

- - -

2023-12-15

Modified the following content:

diff --git a/docs/ecs/umn/en-us_topic_0042400609.html b/docs/ecs/umn/en-us_topic_0042400609.html index eca622a1..6caf5bcc 100644 --- a/docs/ecs/umn/en-us_topic_0042400609.html +++ b/docs/ecs/umn/en-us_topic_0042400609.html @@ -191,7 +191,7 @@

Prerequisites

diff --git a/docs/ecs/umn/en-us_topic_0054121392.html b/docs/ecs/umn/en-us_topic_0054121392.html index 2775bf16..0d376e15 100644 --- a/docs/ecs/umn/en-us_topic_0054121392.html +++ b/docs/ecs/umn/en-us_topic_0054121392.html @@ -3,7 +3,7 @@

User Permissions

Two types of permissions are provided by default: user management and resource management.

-

For further details, see Permissions.

+

For further details, see Permissions.

diff --git a/docs/ecs/umn/en-us_topic_0097289624.html b/docs/ecs/umn/en-us_topic_0097289624.html index 1bff1178..bdf28d03 100644 --- a/docs/ecs/umn/en-us_topic_0097289624.html +++ b/docs/ecs/umn/en-us_topic_0097289624.html @@ -6,10 +6,10 @@

GPU-accelerated ECS Types

Recommended: Computing-accelerated P2s, Inference-accelerated Pi2, and GPU-accelerated Enhancement G6

Available now: All GPU models except the recommended ones. If available ECSs are sold out, use the recommended ones.

-
-

GPU-accelerated Enhancement G7v

Overview

-

G7v ECSs use NVIDIA A40 GPUs and support DirectX, Shader Model, OpenGL, and Vulkan. Each GPU provides 48 GiB of GPU memory. Theoretically, the peak FP32 is 37.4 TFLOPS and the peak TF32 tensor is 74.8 TFLOPS | 149.6 TFLOPS (sparsity enabled). They deliver two times the rendering performance and 1.4 times the graphics processing performance of RTX6000 GPUs to meet professional graphics processing requirements.

-

Select your desired GPU-accelerated ECS type and specifications.

-

Specifications

- -
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Table 2 G7v ECS specifications

Flavor

-

vCPUs

-

Memory

-

(GiB)

-

Max./Assured Bandwidth

-

(Gbit/s)

-

Max. PPS

-

(10,000)

-

Max. NIC Queues

-

Max. NICs

-

GPUs

-

GPU Memory

-

(GiB)

-

Virtualization

-

g7v.2xlarge.8

-

8

-

64

-

15/3

-

100

-

4

-

4

-

1 × NVIDIA-A40-8Q

-

8

-

KVM

-

g7v.4xlarge.8

-

16

-

128

-

20/6

-

150

-

8

-

8

-

1 × NVIDIA-A40-16Q

-

16

-

KVM

-

g7v.6xlarge.8

-

24

-

192

-

25/9

-

200

-

8

-

8

-

1 × NVIDIA-A40-24Q

-

24

-

KVM

-
-
-

G7v ECS Features

- -

Supported Common Software

-

G7v ECSs are used in graphics acceleration scenarios, such as video rendering, cloud desktop, and 3D visualization. If the software relies on GPU DirectX and OpenGL hardware acceleration, use G7v ECSs. G7v ECSs support the following commonly used graphics processing software:

- -

Notes

- -

Graphics-accelerated Enhancement G7

Overview

G7 ECSs use NVIDIA A40 GPUs and support DirectX, Shader Model, OpenGL, and Vulkan. Each GPU provides 48 GiB of GPU memory. Theoretically, the peak FP32 is 37.4 TFLOPS and the peak TF32 tensor is 74.8 TFLOPS | 149.6 TFLOPS (sparsity enabled). They deliver two times the rendering performance and 1.4 times the graphics processing performance of RTX6000 GPUs to meet professional graphics processing requirements.

Select your desired GPU-accelerated ECS type and specifications.

Specifications

-
Table 3 G7 ECS specifications

Flavor

+
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -274,93 +159,93 @@

Select your desired GPU-accelerated ECS type and specifications.

Specifications

-
Table 2 G7 ECS specifications

Flavor

vCPUs

+

vCPUs

Memory

+

Memory

(GiB)

Max./Assured Bandwidth

+

Max./Assured Bandwidth

(Gbit/s)

Max. PPS

+

Max. PPS

(10,000)

Max. NIC Queues

+

Max. NIC Queues

Max. NICs

+

Max. NICs

GPUs

+

GPUs

GPU Memory

+

GPU Memory

(GiB)

Virtualization

+

Virtualization

g7.12xlarge.8

+

g7.12xlarge.8

48

+

48

384

+

384

35/18

+

35/18

750

+

750

16

+

16

8

+

8

1 × NVIDIA-A40

+

1 × NVIDIA-A40

1 × 48

+

1 × 48

KVM

+

KVM

g7.24xlarge.8

+

g7.24xlarge.8

96

+

96

768

+

768

40/36

+

40/36

850

+

850

16

+

16

8

+

8

2 × NVIDIA-A40

+

2 × NVIDIA-A40

2 × 48

+

2 × 48

KVM

+

KVM
Table 4 G6 ECS specifications

Flavor

+
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -385,113 +270,113 @@

P3 ECSs use NVIDIA A100 GPUs and provide flexibility and ultra-high-performance computing. P3 ECSs have strengths in AI-based deep learning, scientific computing, Computational Fluid Dynamics (CFD), computing finance, seismic analysis, molecular modeling, and genomics. Theoretically, the FP32 is 19.5 TFLOPS and the TF32 tensor core is 156 TFLOPS | 312 TFLOPS (sparsity enabled).

Specifications

-
Table 3 G6 ECS specifications

Flavor

vCPUs

+

vCPUs

Memory

+

Memory

(GiB)

Max./Assured Bandwidth

+

Max./Assured Bandwidth

(Gbit/s)

Max. PPS

+

Max. PPS

(10,000)

Max. NIC Queues

+

Max. NIC Queues

Max. NICs

+

Max. NICs

GPUs

+

GPUs

GPU Memory

+

GPU Memory

(GiB)

Virtualization

+

Virtualization

g6.4xlarge.4

+

g6.4xlarge.4

16

+

16

64

+

64

25/15

+

25/15

200

+

200

8

+

8

8

+

8

1 × T4

+

1 × T4

16

+

16

KVM

+

KVM

g6.10xlarge.7

+

g6.10xlarge.7

40

+

40

280

+

280

25/15

+

25/15

200

+

200

16

+

16

8

+

8

1 × T4

+

1 × T4

16

+

16

KVM

+

KVM

g6.20xlarge.7

+

g6.20xlarge.7

80

+

80

560

+

560

30/30

+

30/30

400

+

400

32

+

32

16

+

16

2 × T4

+

2 × T4

32

+

32

KVM

+

KVM
Table 5 P3 ECS specifications

Flavor

+
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -505,8 +390,8 @@

Supported Common Software

P3 ECSs are used in computing acceleration scenarios, such as deep learning training, inference, scientific computing, molecular modeling, and seismic analysis. If the software is required to support GPU CUDA, use P3 ECSs. P3 ECSs support the following commonly used software:

  • Common deep learning frameworks, such as TensorFlow, Spark, PyTorch, MXNet, and Caffee
  • CUDA GPU rendering supported by RedShift for Autodesk 3dsMax and V-Ray for 3ds Max
  • Agisoft PhotoScan
  • MapD
  • More than 2,000 GPU-accelerated applications such as Amber, NAMD, and VASP
-

Notes

-
  • After a P3 ECS is stopped, basic resources (including vCPUs, memory, image, and GPUs) are not billed, but its system disk is billed based on the disk capacity. If other products, such as EVS disks, EIP, and bandwidth are associated with the ECS, these products are billed separately.

    Resources will be released after a P3 ECS is stopped. If resources are insufficient at the next start, the start may fail. If you want to use such an ECS for a long period of time, do not stop the ECS.

    +

    Notes

    +
    • After a P3 ECS is stopped, basic resources (including vCPUs, memory, image, and GPUs) are not billed, but its system disk is billed based on the disk capacity. If other products, such as EVS disks, EIP, and bandwidth are associated with the ECS, these products are billed separately.

      Resources will be released after a P3 ECS is stopped. If resources are insufficient at the next start, the start may fail. If you want to use such an ECS for a long period of time, do not stop the ECS.

    • If a P3 ECS is created using a private image, make sure that the Tesla driver was installed during the private image creation. If not, install the driver for computing acceleration after the ECS is created. For details, see Installing a Tesla Driver and CUDA Toolkit on a GPU-accelerated ECS.
    • GPU-accelerated ECSs differ greatly in general-purpose and heterogeneous computing power. Their specifications can only be changed to other specifications of the same instance type.
    @@ -514,129 +399,129 @@

    P2s ECSs use NVIDIA Tesla V100 GPUs to provide flexibility, high-performance computing, and cost-effectiveness. P2s ECSs provide outstanding general computing capabilities and have strengths in AI-based deep learning, scientific computing, Computational Fluid Dynamics (CFD), computing finance, seismic analysis, molecular modeling, and genomics.

    Specifications

    -
Table 4 P3 ECS specifications

Flavor

vCPUs

+

vCPUs

Memory

+

Memory

(GiB)

Max./Assured Bandwidth (Gbit/s)

+

Max./Assured Bandwidth (Gbit/s)

Max. PPS

+

Max. PPS

(10,000)

Max. NIC Queues

+

Max. NIC Queues

Max. NICs

+

Max. NICs

GPUs

+

GPUs

GPU Memory

+

GPU Memory

(GiB)

Virtualization

+

Virtualization

p3.2xlarge.8

+

p3.2xlarge.8

8

+

8

64

+

64

10/4

+

10/4

100

+

100

4

+

4

4

+

4

1 × NVIDIA A100 80GB

+

1 × NVIDIA A100 80GB

80

+

80

KVM

+

KVM

p3.4xlarge.8

+

p3.4xlarge.8

16

+

16

128

+

128

15/8

+

15/8

200

+

200

8

+

8

8

+

8

2 × NVIDIA A100 80GB

+

2 × NVIDIA A100 80GB

160

+

160

KVM

+

KVM

p3.8xlarge.8

+

p3.8xlarge.8

32

+

32

256

+

256

25/15

+

25/15

350

+

350

16

+

16

8

+

8

4 × NVIDIA A100 80GB

+

4 × NVIDIA A100 80GB

320

+

320

KVM

+

KVM

p3.16xlarge.8

+

p3.16xlarge.8

64

+

64

512

+

512

36/30

+

36/30

700

+

700

32

+

32

8

+

8

8 × NVIDIA A100 80GB

+

8 × NVIDIA A100 80GB

640

+

640

KVM

+

KVM
Table 6 P2s ECS specifications

Flavor

+
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -650,135 +535,135 @@

Supported Common Software

P2s ECSs are used in computing acceleration scenarios, such as deep learning training, inference, scientific computing, molecular modeling, and seismic analysis. If the software is required to support GPU CUDA, use P2s ECSs. P2s ECSs support the following commonly used software:
  • Common deep learning frameworks, such as TensorFlow, Caffe, PyTorch, and MXNet
  • CUDA GPU rendering supported by RedShift for Autodesk 3dsMax and V-Ray for 3ds Max
  • Agisoft PhotoScan
  • MapD
-
Notes
  • After a P2s ECS is stopped, basic resources (including vCPUs, memory, image, and GPUs) are not billed, but its system disk is billed based on the disk capacity. If other products, such as EVS disks, EIP, and bandwidth are associated with the ECS, these products are billed separately.

    Resources will be released after a P2s ECS is stopped. If resources are insufficient at the next start, the start may fail. If you want to use such an ECS for a long period of time, do not stop the ECS.

    +
    Notes
    • After a P2s ECS is stopped, basic resources (including vCPUs, memory, image, and GPUs) are not billed, but its system disk is billed based on the disk capacity. If other products, such as EVS disks, EIP, and bandwidth are associated with the ECS, these products are billed separately.

      Resources will be released after a P2s ECS is stopped. If resources are insufficient at the next start, the start may fail. If you want to use such an ECS for a long period of time, do not stop the ECS.

    • By default, P2s ECSs created using a Windows public image have the Tesla driver installed.
    • If a P2s ECS is created using a private image, make sure that the Tesla driver was installed during the private image creation. If not, install the driver for computing acceleration after the ECS is created. For details, see Installing a Tesla Driver and CUDA Toolkit on a GPU-accelerated ECS.
    • GPU-accelerated ECSs differ greatly in general-purpose and heterogeneous computing power. Their specifications can only be changed to other specifications of the same instance type.
    -

    Computing-accelerated P2v

    Overview

    +

    Computing-accelerated P2v

    Overview

    P2v ECSs use NVIDIA Tesla V100 GPUs and deliver high flexibility, high-performance computing, and high cost-effectiveness. These ECSs use GPU NVLink for direct communication between GPUs, improving data transmission efficiency. P2v ECSs provide outstanding general computing capabilities and have strengths in AI-based deep learning, scientific computing, Computational Fluid Dynamics (CFD), computing finance, seismic analysis, molecular modeling, and genomics.

    Specifications

    -
Table 5 P2s ECS specifications

Flavor

vCPUs

+

vCPUs

Memory

+

Memory

(GiB)

Max./Assured Bandwidth (Gbit/s)

+

Max./Assured Bandwidth (Gbit/s)

Max. PPS (10,000)

+

Max. PPS (10,000)

Max. NIC Queues

+

Max. NIC Queues

Max. NICs

+

Max. NICs

GPUs

+

GPUs

GPU Connection

+

GPU Connection

GPU Memory (GiB)

+

GPU Memory (GiB)

Virtualization

+

Virtualization

Hardware

+

Hardware

p2s.2xlarge.8

+

p2s.2xlarge.8

8

+

8

64

+

64

10/4

+

10/4

50

+

50

4

+

4

4

+

4

1 × V100

+

1 × V100

PCIe Gen3

+

PCIe Gen3

1 × 32 GiB

+

1 × 32 GiB

KVM

+

KVM

CPU: 2nd Generation Intel® Xeon® Scalable Processor 6278

+

CPU: 2nd Generation Intel® Xeon® Scalable Processor 6278

p2s.4xlarge.8

+

p2s.4xlarge.8

16

+

16

128

+

128

15/8

+

15/8

100

+

100

8

+

8

8

+

8

2 × V100

+

2 × V100

PCIe Gen3

+

PCIe Gen3

2 × 32 GiB

+

2 × 32 GiB

KVM

+

KVM

p2s.8xlarge.8

+

p2s.8xlarge.8

32

+

32

256

+

256

25/15

+

25/15

200

+

200

16

+

16

8

+

8

4 × V100

+

4 × V100

PCIe Gen3

+

PCIe Gen3

4 × 32 GiB

+

4 × 32 GiB

KVM

+

KVM

p2s.16xlarge.8

+

p2s.16xlarge.8

64

+

64

512

+

512

30/30

+

30/30

400

+

400

32

+

32

8

+

8

8 × V100

+

8 × V100

PCIe Gen3

+

PCIe Gen3

8 × 32 GiB

+

8 × 32 GiB

KVM

+

KVM
Table 7 P2v ECS specifications

Flavor

+
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - @@ -793,7 +678,7 @@

Supported Common Software

P2v ECSs are used in computing acceleration scenarios, such as deep learning training, inference, scientific computing, molecular modeling, and seismic analysis. If the software is required to support GPU CUDA, use P2v ECSs. P2v ECSs support the following commonly used software:
  • Common deep learning frameworks, such as TensorFlow, Caffe, PyTorch, and MXNet
  • CUDA GPU rendering supported by RedShift for Autodesk 3dsMax and V-Ray for 3ds Max
  • Agisoft PhotoScan
  • MapD
-
Notes
  • After a P2v ECS is stopped, basic resources (including vCPUs, memory, image, and GPUs) are not billed, but its system disk is billed based on the disk capacity. If other products, such as EVS disks, EIP, and bandwidth are associated with the ECS, these products are billed separately.

    Resources will be released after a P2v ECS is stopped. If resources are insufficient at the next start, the start may fail. If you want to use such an ECS for a long period of time, do not stop the ECS.

    +
    Notes
    • After a P2v ECS is stopped, basic resources (including vCPUs, memory, image, and GPUs) are not billed, but its system disk is billed based on the disk capacity. If other products, such as EVS disks, EIP, and bandwidth are associated with the ECS, these products are billed separately.

      Resources will be released after a P2v ECS is stopped. If resources are insufficient at the next start, the start may fail. If you want to use such an ECS for a long period of time, do not stop the ECS.

    • By default, P2v ECSs created using a Windows public image have the Tesla driver installed.
    • By default, P2v ECSs created using a Linux public image do not have a Tesla driver installed. After the ECS is created, install a driver on it for computing acceleration. For details, see Installing a Tesla Driver and CUDA Toolkit on a GPU-accelerated ECS.
    • If a P2v ECS is created using a private image, make sure that the Tesla driver was installed during the private image creation. If not, install the driver for computing acceleration after the ECS is created. For details, see Installing a Tesla Driver and CUDA Toolkit on a GPU-accelerated ECS.
    • GPU-accelerated ECSs differ greatly in general-purpose and heterogeneous computing power. Their specifications can only be changed to other specifications of the same instance type.
    @@ -802,151 +687,151 @@

    Pi2 ECSs use NVIDIA Tesla T4 GPUs dedicated for real-time AI inference. These ECSs use the T4 INT8 calculator for up to 130 TOPS of INT8 computing. The Pi2 ECSs can also be used for light-load training.

    Specifications

    -
Table 6 P2v ECS specifications

Flavor

vCPUs

+

vCPUs

Memory

+

Memory

(GiB)

Max./Assured Bandwidth (Gbit/s)

+

Max./Assured Bandwidth (Gbit/s)

Max. PPS (10,000)

+

Max. PPS (10,000)

Max. NIC Queues

+

Max. NIC Queues

Max. NICs

+

Max. NICs

GPUs

+

GPUs

GPU Connection

+

GPU Connection

GPU Memory

+

GPU Memory

(GiB)

Virtualization

+

Virtualization

Hardware

+

Hardware

p2v.2xlarge.8

+

p2v.2xlarge.8

8

+

8

64

+

64

10/4

+

10/4

50

+

50

4

+

4

4

+

4

1 × V100

+

1 × V100

N/A

+

N/A

1 × 16 GiB

+

1 × 16 GiB

KVM

+

KVM

CPU: Intel® Xeon® Skylake-SP Gold 6151 v5

+

CPU: Intel® Xeon® Skylake-SP Gold 6151 v5

p2v.4xlarge.8

+

p2v.4xlarge.8

16

+

16

128

+

128

15/8

+

15/8

100

+

100

8

+

8

8

+

8

2 × V100

+

2 × V100

NVLink

+

NVLink

2 × 16 GiB

+

2 × 16 GiB

KVM

+

KVM

p2v.8xlarge.8

+

p2v.8xlarge.8

32

+

32

256

+

256

25/15

+

25/15

200

+

200

16

+

16

8

+

8

4 × V100

+

4 × V100

NVLink

+

NVLink

4 × 16 GiB

+

4 × 16 GiB

KVM

+

KVM

p2v.16xlarge.8

+

p2v.16xlarge.8

64

+

64

512

+

512

30/30

+

30/30

400

+

400

32

+

32

8

+

8

8 × V100

+

8 × V100

NVLink

+

NVLink

8 × 16 GiB

+

8 × 16 GiB

KVM

+

KVM
Table 8 Pi2 ECS specifications

Flavor

+
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/docs/ecs/umn/en-us_topic_0133513874.html b/docs/ecs/umn/en-us_topic_0133513874.html index 351f2326..20d49355 100644 --- a/docs/ecs/umn/en-us_topic_0133513874.html +++ b/docs/ecs/umn/en-us_topic_0133513874.html @@ -9,7 +9,7 @@
  • Obtaining a Tesla Driver and CUDA Toolkit
    • -
  • Installing a GRID Driver on a GPU-accelerated ECS
    +
  • Manually Installing a GRID Driver on a GPU-accelerated ECS
  • Installing a Tesla Driver and CUDA Toolkit on a GPU-accelerated ECS
    • diff --git a/docs/ecs/umn/en-us_topic_0140313881.html b/docs/ecs/umn/en-us_topic_0140313881.html index 0a9a9cbd..1f291504 100644 --- a/docs/ecs/umn/en-us_topic_0140313881.html +++ b/docs/ecs/umn/en-us_topic_0140313881.html @@ -1,6 +1,6 @@ -

    Passwords and Key Pairs

    +

    Passwords and Key Pairs Management

    diff --git a/docs/ecs/umn/en-us_topic_0140323151.html b/docs/ecs/umn/en-us_topic_0140323151.html index 450070bd..56fa3e22 100644 --- a/docs/ecs/umn/en-us_topic_0140323151.html +++ b/docs/ecs/umn/en-us_topic_0140323151.html @@ -6,7 +6,7 @@
    • Overview
      • -
    • Default Security Group and Rules
      +
    • Default Security Groups and Rules
    • Security Group Configuration Examples
      • diff --git a/docs/ecs/umn/en-us_topic_0140323154.html b/docs/ecs/umn/en-us_topic_0140323154.html index 94f165c7..11b57823 100644 --- a/docs/ecs/umn/en-us_topic_0140323154.html +++ b/docs/ecs/umn/en-us_topic_0140323154.html @@ -1,6 +1,6 @@ -

      Default Security Group and Rules

      +

      Default Security Groups and Rules

      Note the following when using default security group rules:
      • Inbound rules control incoming traffic to instances in the default security group. The instances can only communicate with each other but cannot be accessed from external networks.
      • Outbound rules allow all traffic from the instances in the default security group to external networks.

      Figure 1 shows the default security group.

      diff --git a/docs/ecs/umn/en-us_topic_0140323157.html b/docs/ecs/umn/en-us_topic_0140323157.html index 5d57c2c7..c42c05e5 100644 --- a/docs/ecs/umn/en-us_topic_0140323157.html +++ b/docs/ecs/umn/en-us_topic_0140323157.html @@ -2,12 +2,12 @@

      Overview

      Security Group

      A security group is a collection of access control rules for ECSs that have the same security protection requirements and that are mutually trusted. After a security group is created, you can create various access rules for the security group, these rules will apply to all ECSs added to this security group.

      -

      You can also customize a security group or use the default one. The system provides a default security group for you, which permits all outbound traffic and denies inbound traffic. ECSs in a security group are accessible to each other. For details about the default security group, see Default Security Group and Rules.

      +

      You can also customize a security group or use the default one. The system provides a default security group for you, which permits all outbound traffic and denies inbound traffic. ECSs in a security group are accessible to each other. For details about the default security group, see Default Security Groups and Rules.

      If two ECSs are in the same security group but in different VPCs, the security group does not take effect. You can use a VPC peering connection to connect the two VPCs first.

      Security Group Rules

      After a security group is created, you can add rules to the security group. A rule applies either to inbound traffic (ingress) or outbound traffic (egress). After ECSs are added to the security group, they are protected by the rules of that group.

      -

      Each security group has default rules. For details, see Default Security Group and Rules. You can also customize security group rules. For details, see Configuring Security Group Rules.

      +

      Each security group has default rules. For details, see Default Security Groups and Rules. You can also customize security group rules. For details, see Configuring Security Group Rules.

      Notes and Constraints

      • By default, you can add up to 50 security group rules to a security group.
      diff --git a/docs/ecs/umn/en-us_topic_0149610914.html b/docs/ecs/umn/en-us_topic_0149610914.html index fc83d376..f1db85d0 100644 --- a/docs/ecs/umn/en-us_topic_0149610914.html +++ b/docs/ecs/umn/en-us_topic_0149610914.html @@ -1,6 +1,6 @@ -

      Installing a GRID Driver on a GPU-accelerated ECS

      +

      Manually Installing a GRID Driver on a GPU-accelerated ECS

      Scenarios

      To use graphics acceleration, such as OpenGL, DirectX, or Vulkan, install a GRID driver and separately purchase and configure a GRID license. The GRID driver with a vDWS license also supports CUDA for both computing and graphics acceleration.

      • A graphics-accelerated (G series) ECS created using a Windows public image has had a GRID driver of a specified version installed by default, but the GRID license must be purchased and configured separately.
      • A graphics-accelerated (G series) ECS created using a Linux public image does not have a GRID driver installed by default. You are required to install a GRID driver and purchase and configure a GRID license separately.
      • If a GPU-accelerated ECS is created using a private image, install a GRID driver and separately purchase and configure a GRID license.

      This section describes how to install a GRID driver, purchase or apply for a GRID license, and configure the license server.

      @@ -33,16 +33,7 @@ -
    - - - - - diff --git a/docs/ecs/umn/en-us_topic_0155136016.html b/docs/ecs/umn/en-us_topic_0155136016.html index ab0b8243..ce8d719e 100644 --- a/docs/ecs/umn/en-us_topic_0155136016.html +++ b/docs/ecs/umn/en-us_topic_0155136016.html @@ -90,7 +90,7 @@ Alias=myservice.service
    Figure 4 TightVNC client
  • Right-click on the blank area and choose Open in Terminal from the shortcut menu.
  • Run the following command on the terminal. If the graphics card information is displayed as follows, the driver is working properly.

    nvidia-settings

    Figure 5 Graphics card information
    -

    If a GPU-accelerated ECS has a GRID driver installed, you need to configure a license to use the GPU rendering capability. For details, see Installing a GRID Driver on a GPU-accelerated ECS.

    +

    If a GPU-accelerated ECS has a GRID driver installed, you need to configure a license to use the GPU rendering capability. For details, see Manually Installing a GRID Driver on a GPU-accelerated ECS.

    • diff --git a/docs/ecs/umn/en-us_topic_0177512565.html b/docs/ecs/umn/en-us_topic_0177512565.html index f8e78178..b7a5d189 100644 --- a/docs/ecs/umn/en-us_topic_0177512565.html +++ b/docs/ecs/umn/en-us_topic_0177512565.html @@ -3125,777 +3125,684 @@

    GPU-accelerated

    -
    Table 7 Pi2 ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth

    +

    Max./Assured Bandwidth

    (Gbit/s)

    Max. PPS

    +

    Max. PPS

    (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Memory

    +

    GPU Memory

    (GiB)

    Local Disks

    +

    Local Disks

    Virtualization

    +

    Virtualization

    Hardware

    +

    Hardware

    pi2.2xlarge.4

    +

    pi2.2xlarge.4

    8

    +

    8

    32

    +

    32

    10/4

    +

    10/4

    50

    +

    50

    4

    +

    4

    4

    +

    4

    1 × T4

    +

    1 × T4

    1 × 16 GiB

    +

    1 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    CPU: Intel® Xeon® Skylake 6151 3.0 GHz or Intel® Xeon® Cascade Lake 6278 2.6 GHz

    +

    CPU: Intel® Xeon® Skylake 6151 3.0 GHz or Intel® Xeon® Cascade Lake 6278 2.6 GHz

    pi2.3xlarge.4

    +

    pi2.3xlarge.4

    12

    +

    12

    48

    +

    48

    12/6

    +

    12/6

    80

    +

    80

    6

    +

    6

    6

    +

    6

    1 × T4

    +

    1 × T4

    1 × 16 GiB

    +

    1 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    pi2.4xlarge.4

    +

    pi2.4xlarge.4

    16

    +

    16

    64

    +

    64

    15/8

    +

    15/8

    100

    +

    100

    8

    +

    8

    8

    +

    8

    2 × T4

    +

    2 × T4

    2 × 16 GiB

    +

    2 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    pi2.8xlarge.4

    +

    pi2.8xlarge.4

    32

    +

    32

    128

    +

    128

    25/15

    +

    25/15

    200

    +

    200

    16

    +

    16

    8

    +

    8

    4 × T4

    +

    4 × T4

    4 × 16 GiB

    +

    4 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    pi2.16xlarge.4

    +

    pi2.16xlarge.4

    64

    +

    64

    256

    +

    256

    30/30

    +

    30/30

    400

    +

    400

    32

    +

    32

    8

    +

    8

    8 × T4

    +

    8 × T4

    8 × 16 GiB

    +

    8 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    G7v

    -

    GPU virtualization

    -

    GRID 13.0

    -

    x86_64

    -

    G7

    +

    G7

    GPU passthrough
    Table 14 G7v ECS specifications

    Flavor

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Table 14 G7 ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    -

    (GiB)

    -

    Max./Assured Bandwidth

    -

    (Gbit/s)

    -

    Max. PPS

    -

    (10,000)

    -

    Max. NIC Queues

    -

    Max. NICs

    -

    GPUs

    -

    GPU Memory

    -

    (GiB)

    -

    Virtualization

    -

    g7v.2xlarge.8

    -

    8

    -

    64

    -

    15/3

    -

    100

    -

    4

    -

    4

    -

    1 × NVIDIA-A40-8Q

    -

    8

    -

    KVM

    -

    g7v.4xlarge.8

    -

    16

    -

    128

    -

    20/6

    -

    150

    -

    8

    -

    8

    -

    1 × NVIDIA-A40-16Q

    -

    16

    -

    KVM

    -

    g7v.6xlarge.8

    -

    24

    -

    192

    -

    25/9

    -

    200

    -

    8

    -

    8

    -

    1 × NVIDIA-A40-24Q

    -

    24

    -

    KVM

    -
    -
    - -
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Table 15 G7 ECS specifications

    Flavor

    -

    vCPUs

    -

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth

    +

    Max./Assured Bandwidth

    (Gbit/s)

    Max. PPS

    +

    Max. PPS

    (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Memory

    +

    GPU Memory

    (GiB)

    Virtualization

    +

    Virtualization

    g7.12xlarge.8

    +

    g7.12xlarge.8

    48

    +

    48

    384

    +

    384

    35/18

    +

    35/18

    750

    +

    750

    16

    +

    16

    8

    +

    8

    1 × NVIDIA-A40

    +

    1 × NVIDIA-A40

    1 × 48

    +

    1 × 48

    KVM

    +

    KVM

    g7.24xlarge.8

    +

    g7.24xlarge.8

    96

    +

    96

    768

    +

    768

    40/36

    +

    40/36

    850

    +

    850

    16

    +

    16

    8

    +

    8

    2 × NVIDIA-A40

    +

    2 × NVIDIA-A40

    2 × 48

    +

    2 × 48

    KVM

    +

    KVM
    -
    Table 16 G6 ECS specifications

    Flavor

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Table 15 G6 ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth

    +

    Max./Assured Bandwidth

    (Gbit/s)

    Max. PPS

    +

    Max. PPS

    (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Memory

    +

    GPU Memory

    (GiB)

    Virtualization

    +

    Virtualization

    g6.4xlarge.4

    +

    g6.4xlarge.4

    16

    +

    16

    64

    +

    64

    25/15

    +

    25/15

    200

    +

    200

    8

    +

    8

    8

    +

    8

    1 × T4

    +

    1 × T4

    16

    +

    16

    KVM

    +

    KVM

    g6.10xlarge.7

    +

    g6.10xlarge.7

    40

    +

    40

    280

    +

    280

    25/15

    +

    25/15

    200

    +

    200

    16

    +

    16

    8

    +

    8

    1 × T4

    +

    1 × T4

    16

    +

    16

    KVM

    +

    KVM

    g6.20xlarge.7

    +

    g6.20xlarge.7

    80

    +

    80

    560

    +

    560

    30/30

    +

    30/30

    400

    +

    400

    32

    +

    32

    16

    +

    16

    2 × T4

    +

    2 × T4

    32

    +

    32

    KVM

    +

    KVM
    -
    Table 17 P3 ECS specifications

    Flavor

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Table 16 P3 ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth (Gbit/s)

    +

    Max./Assured Bandwidth (Gbit/s)

    Max. PPS

    +

    Max. PPS

    (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Memory

    +

    GPU Memory

    (GiB)

    Virtualization

    +

    Virtualization

    p3.2xlarge.8

    +

    p3.2xlarge.8

    8

    +

    8

    64

    +

    64

    10/4

    +

    10/4

    100

    +

    100

    4

    +

    4

    4

    +

    4

    1 × NVIDIA A100 80GB

    +

    1 × NVIDIA A100 80GB

    80

    +

    80

    KVM

    +

    KVM

    p3.4xlarge.8

    +

    p3.4xlarge.8

    16

    +

    16

    128

    +

    128

    15/8

    +

    15/8

    200

    +

    200

    8

    +

    8

    8

    +

    8

    2 × NVIDIA A100 80GB

    +

    2 × NVIDIA A100 80GB

    160

    +

    160

    KVM

    +

    KVM

    p3.8xlarge.8

    +

    p3.8xlarge.8

    32

    +

    32

    256

    +

    256

    25/15

    +

    25/15

    350

    +

    350

    16

    +

    16

    8

    +

    8

    4 × NVIDIA A100 80GB

    +

    4 × NVIDIA A100 80GB

    320

    +

    320

    KVM

    +

    KVM

    p3.16xlarge.8

    +

    p3.16xlarge.8

    64

    +

    64

    512

    +

    512

    36/30

    +

    36/30

    700

    +

    700

    32

    +

    32

    8

    +

    8

    8 × NVIDIA A100 80GB

    +

    8 × NVIDIA A100 80GB

    640

    +

    640

    KVM

    +

    KVM
    -
    Table 18 P2s ECS specifications

    Flavor

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Table 17 P2s ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth (Gbit/s)

    +

    Max./Assured Bandwidth (Gbit/s)

    Max. PPS (10,000)

    +

    Max. PPS (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Connection

    +

    GPU Connection

    GPU Memory (GiB)

    +

    GPU Memory (GiB)

    Virtualization

    +

    Virtualization

    Hardware

    +

    Hardware

    p2s.2xlarge.8

    +

    p2s.2xlarge.8

    8

    +

    8

    64

    +

    64

    10/4

    +

    10/4

    50

    +

    50

    4

    +

    4

    4

    +

    4

    1 × V100

    +

    1 × V100

    PCIe Gen3

    +

    PCIe Gen3

    1 × 32 GiB

    +

    1 × 32 GiB

    KVM

    +

    KVM

    CPU: 2nd Generation Intel® Xeon® Scalable Processor 6278

    +

    CPU: 2nd Generation Intel® Xeon® Scalable Processor 6278

    p2s.4xlarge.8

    +

    p2s.4xlarge.8

    16

    +

    16

    128

    +

    128

    15/8

    +

    15/8

    100

    +

    100

    8

    +

    8

    8

    +

    8

    2 × V100

    +

    2 × V100

    PCIe Gen3

    +

    PCIe Gen3

    2 × 32 GiB

    +

    2 × 32 GiB

    KVM

    +

    KVM

    p2s.8xlarge.8

    +

    p2s.8xlarge.8

    32

    +

    32

    256

    +

    256

    25/15

    +

    25/15

    200

    +

    200

    16

    +

    16

    8

    +

    8

    4 × V100

    +

    4 × V100

    PCIe Gen3

    +

    PCIe Gen3

    4 × 32 GiB

    +

    4 × 32 GiB

    KVM

    +

    KVM

    p2s.16xlarge.8

    +

    p2s.16xlarge.8

    64

    +

    64

    512

    +

    512

    30/30

    +

    30/30

    400

    +

    400

    32

    +

    32

    8

    +

    8

    8 × V100

    +

    8 × V100

    PCIe Gen3

    +

    PCIe Gen3

    8 × 32 GiB

    +

    8 × 32 GiB

    KVM

    +

    KVM
    -
    Table 19 P2v ECS specifications

    Flavor

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Table 18 P2v ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth (Gbit/s)

    +

    Max./Assured Bandwidth (Gbit/s)

    Max. PPS (10,000)

    +

    Max. PPS (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Connection

    +

    GPU Connection

    GPU Memory

    +

    GPU Memory

    (GiB)

    Virtualization

    +

    Virtualization

    Hardware

    +

    Hardware

    p2v.2xlarge.8

    +

    p2v.2xlarge.8

    8

    +

    8

    64

    +

    64

    10/4

    +

    10/4

    50

    +

    50

    4

    +

    4

    4

    +

    4

    1 × V100

    +

    1 × V100

    N/A

    +

    N/A

    1 × 16 GiB

    +

    1 × 16 GiB

    KVM

    +

    KVM

    CPU: Intel® Xeon® Skylake-SP Gold 6151 v5

    +

    CPU: Intel® Xeon® Skylake-SP Gold 6151 v5

    p2v.4xlarge.8

    +

    p2v.4xlarge.8

    16

    +

    16

    128

    +

    128

    15/8

    +

    15/8

    100

    +

    100

    8

    +

    8

    8

    +

    8

    2 × V100

    +

    2 × V100

    NVLink

    +

    NVLink

    2 × 16 GiB

    +

    2 × 16 GiB

    KVM

    +

    KVM

    p2v.8xlarge.8

    +

    p2v.8xlarge.8

    32

    +

    32

    256

    +

    256

    25/15

    +

    25/15

    200

    +

    200

    16

    +

    16

    8

    +

    8

    4 × V100

    +

    4 × V100

    NVLink

    +

    NVLink

    4 × 16 GiB

    +

    4 × 16 GiB

    KVM

    +

    KVM

    p2v.16xlarge.8

    +

    p2v.16xlarge.8

    64

    +

    64

    512

    +

    512

    30/30

    +

    30/30

    400

    +

    400

    32

    +

    32

    8

    +

    8

    8 × V100

    +

    8 × V100

    NVLink

    +

    NVLink

    8 × 16 GiB

    +

    8 × 16 GiB

    KVM

    +

    KVM
    -
    Table 20 Pi2 ECS specifications

    Flavor

    +
    - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/docs/ecs/umn/en-us_topic_0234802636.html b/docs/ecs/umn/en-us_topic_0234802636.html index 877b6995..c79bdf29 100644 --- a/docs/ecs/umn/en-us_topic_0234802636.html +++ b/docs/ecs/umn/en-us_topic_0234802636.html @@ -3,7 +3,7 @@

    GPU Driver

    Overview

    Before using a GPU-accelerated ECS, make sure that a GPU driver has been installed on the ECS for GPU acceleration.

    GPU-accelerated ECSs support GRID and Tesla drivers.

    -
    • To use graphics acceleration, such as OpenGL, DirectX, or Vulkan, install a GRID driver and separately purchase and configure a GRID license. The GRID driver with a vDWS license also supports CUDA for both computing and graphics acceleration.
      • A graphics-accelerated (G series) ECS created using a Windows public image has had a GRID driver of a specified version installed by default, but the GRID license must be purchased and configured separately. Before using such an ECS, check whether the desired driver has been installed on it and whether the version of the installed driver meets service requirements.
      • A graphics-accelerated (G series) ECS created using a Linux public image does not have a GRID driver installed by default. To install a GRID driver, see Installing a GRID Driver on a GPU-accelerated ECS.
      • To install a GRID driver on a GPU-accelerated ECS created using a private image, see Installing a GRID Driver on a GPU-accelerated ECS.
      +
      • To use graphics acceleration, such as OpenGL, DirectX, or Vulkan, install a GRID driver and separately purchase and configure a GRID license. The GRID driver with a vDWS license also supports CUDA for both computing and graphics acceleration.
        • A graphics-accelerated (G series) ECS created using a Windows public image has had a GRID driver of a specified version installed by default, but the GRID license must be purchased and configured separately. Before using such an ECS, check whether the desired driver has been installed on it and whether the version of the installed driver meets service requirements.
        • A graphics-accelerated (G series) ECS created using a Linux public image does not have a GRID driver installed by default. To install a GRID driver, see Manually Installing a GRID Driver on a GPU-accelerated ECS.
        • To install a GRID driver on a GPU-accelerated ECS created using a private image, see Manually Installing a GRID Driver on a GPU-accelerated ECS.
      • To use computing acceleration, install a Tesla driver.
    Table 19 Pi2 ECS specifications

    Flavor

    vCPUs

    +

    vCPUs

    Memory

    +

    Memory

    (GiB)

    Max./Assured Bandwidth

    +

    Max./Assured Bandwidth

    (Gbit/s)

    Max. PPS

    +

    Max. PPS

    (10,000)

    Max. NIC Queues

    +

    Max. NIC Queues

    Max. NICs

    +

    Max. NICs

    GPUs

    +

    GPUs

    GPU Memory

    +

    GPU Memory

    (GiB)

    Local Disks

    +

    Local Disks

    Virtualization

    +

    Virtualization

    Hardware

    +

    Hardware

    pi2.2xlarge.4

    +

    pi2.2xlarge.4

    8

    +

    8

    32

    +

    32

    10/4

    +

    10/4

    50

    +

    50

    4

    +

    4

    4

    +

    4

    1 × T4

    +

    1 × T4

    1 × 16 GiB

    +

    1 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    CPU: Intel® Xeon® Skylake 6151 3.0 GHz or Intel® Xeon® Cascade Lake 6278 2.6 GHz

    +

    CPU: Intel® Xeon® Skylake 6151 3.0 GHz or Intel® Xeon® Cascade Lake 6278 2.6 GHz

    pi2.3xlarge.4

    +

    pi2.3xlarge.4

    12

    +

    12

    48

    +

    48

    12/6

    +

    12/6

    80

    +

    80

    6

    +

    6

    6

    +

    6

    1 × T4

    +

    1 × T4

    1 × 16 GiB

    +

    1 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    pi2.4xlarge.4

    +

    pi2.4xlarge.4

    16

    +

    16

    64

    +

    64

    15/8

    +

    15/8

    100

    +

    100

    8

    +

    8

    8

    +

    8

    2 × T4

    +

    2 × T4

    2 × 16 GiB

    +

    2 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    pi2.8xlarge.4

    +

    pi2.8xlarge.4

    32

    +

    32

    128

    +

    128

    25/15

    +

    25/15

    200

    +

    200

    16

    +

    16

    8

    +

    8

    4 × T4

    +

    4 × T4

    4 × 16 GiB

    +

    4 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM

    pi2.16xlarge.4

    +

    pi2.16xlarge.4

    64

    +

    64

    256

    +

    256

    30/30

    +

    30/30

    400

    +

    400

    32

    +

    32

    8

    +

    8

    8 × T4

    +

    8 × T4

    8 × 16 GiB

    +

    8 × 16 GiB

    N/A

    +

    N/A

    KVM

    +

    KVM