GPU-accelerated ECSs

GPU-accelerated ECS Types

Recommended: Computing-accelerated P2s and Inference-accelerated Pi2

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

• G series
  • GPU-accelerated Enhancement G6
  • Graphics-accelerated Enhancement G5
  • Graphics-accelerated Enhancement G3
• P series
  • Computing-accelerated P2s (recommended)
  • Computing-accelerated P2
  • Inference-accelerated Pi2 (recommended)

Images Supported by GPU-accelerated ECSs

GPU-accelerated Enhancement G6

Overview

G6 ECSs use NVIDIA Tesla T4 GPUs to support DirectX, OpenGL, and Vulkan and provide 16 GiB of GPU memory. The theoretical Pixel rate is 101.8 Gpixel/s and Texture rate 254.4 GTexel/s, meeting professional graphics processing requirements.

Select your desired GPU-accelerated ECS type and specifications.

Specifications

G6 ECS Features

• CPU: 2nd Generation Intel® Xeon® Scalable 6266 processors (3.0 GHz of base frequency and 3.4 GHz of turbo frequency)
• Graphics acceleration APIs
  • DirectX 12, Direct2D, and DirectX Video Acceleration (DXVA)
  • OpenGL 4.5
  • Vulkan 1.0
• CUDA and OpenCL
• NVIDIA T4 GPUs
• Graphics applications accelerated
• Heavy-load CPU inference
• Automatic scheduling of G6 ECSs to AZs where NVIDIA T4 GPUs are used
• One NVENC engine and two NVDEC engines embedded

Supported Common Software

G6 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 G6 ECSs. G6 ECSs support the following commonly used graphics processing software:

• AutoCAD
• 3DS MAX
• MAYA
• Agisoft PhotoScan
• ContextCapture

Notes

• After a G6 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 G6 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.

• G6 ECSs created using a public image have had the GRID driver of a specific version installed by default. However, you need to purchase and configure a GRID license by yourself. Ensure that the GRID driver version meets service requirements.

  For details about how to configure a GRID license, see Installing a GRID Driver on a GPU-accelerated ECS.

• If a G6 ECS is created using a private image, make sure that the GRID driver was installed during the private image creation. If not, install the driver for graphics acceleration after the ECS is created.

  For details, see Installing a GRID Driver 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.

GPU-accelerated Enhancement G5

Overview

G5 ECSs use NVIDIA GRID vGPUs and provide comprehensive, professional graphics acceleration. They use NVIDIA Tesla V100 GPUs and support DirectX, OpenGL, and Vulkan. These ECSs provide 1 GiB of GPU memory, meeting requirements from entry-level through professional graphics processing.

Select your desired GPU-accelerated ECS type and specifications.

V100-xQ indicates that V100 GPUs are virtualized to vGPUs with different specifications and models using GRID. x specifies the vGPU memory, and Q indicates that the vGPU of this type is designed to work in workstations and desktop scenarios. For more details about GRID vGPUs, see GRID VIRTUAL GPU User Guide.

Supported Common Software

Notes

• After a G5 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 G5 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.

• When the Windows OS running on a G5 ECS is started, the GRID driver is loaded by default, and vGPUs are used for video output by default. In such a case, the remote login function provided on the management console is not supported. To access such an ECS, use RDP, such as Windows MSTSC. Then, install a third-party VDI tool on the ECS for remote login, such as VNC.
• For G5 ECSs, you need to configure the GRID license after the ECS is created.
• G5 ECSs created using a public image have had the GRID driver of a specific version installed by default. However, you need to purchase and configure a GRID license by yourself. Ensure that the GRID driver version meets service requirements.

  For details about how to configure a GRID license, see Installing a GRID Driver on a GPU-accelerated ECS.

• If a G5 ECS is created using a private image, make sure that the GRID driver was installed during the private image creation. If not, install the driver for graphics acceleration after the ECS is created.

  For details, see Installing a GRID Driver 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.

GPU-accelerated Enhancement G3

Overview

G3 ECSs are based on PCI passthrough and exclusively use GPUs for professional graphics acceleration. In addition, G3 ECSs use NVIDIA Tesla M60 GPUs and support DirectX and OpenGL with up to 16 GiB of GPU memory and 4096 x 2160 resolution. They are ideal for professional graphics workstations.

Notes

• After a G3 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 G3 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.

• When the Windows OS running on a G3 ECS is started, the GRID driver is loaded by default, and vGPUs are used for video output by default. In such a case, the remote login function provided on the management console is not supported. To access such an ECS, use RDP, such as Windows MSTSC. Then, install a third-party VDI tool on the ECS for remote login, such as VNC.
• By default, G3 ECSs created using a public image have had the GRID driver of a specific version installed.
• If a G3 ECS is created using a private image, make sure that the GRID driver was installed during the private image creation. If not, install the driver for graphics acceleration after the ECS is created. For details, see Installing a GRID Driver 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 P2s

Overview

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

Supported Common Software

Computing-accelerated P2

Overview

P2 ECSs use NVIDIA Tesla V100 GPUs, which have improved both single- and double-precision computing capabilities by 50% than the performance of the previous-generation GPUs and offer 112 TFLOPS of deep learning.

Specifications

Supported Common Software

Inference-accelerated Pi2

Overview

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

Pi2 ECS Features

• CPU: 2nd Generation Intel® Xeon® Scalable 6278 processors (2.6 GHz of base frequency and 3.5 GHz of turbo frequency), or Intel® Xeon® Scalable 6151 processors (3.0 GHz of base frequency and 3.4 GHz of turbo frequency)
• Up to four NVIDIA Tesla T4 GPUs on an ECS
• GPU hardware passthrough
• Up to 8.1 TFLOPS of single-precision computing on a single GPU
• Up to 130 TOPS of INT8 computing on a single GPU
• 16 GiB of GDDR6 GPU memory with a bandwidth of 320 GiB/s on a single GPU
• One NVENC engine and two NVDEC engines embedded

Supported Common Software

Pi2 ECSs are used in GPU-based inference computing scenarios, such as image recognition, speech recognition, and natural language processing. The Pi2 ECSs can also be used for light-load training.

Pi2 ECSs support the following commonly used software:

• Deep learning frameworks, such as TensorFlow, Caffe, PyTorch, and MXNet

Notes

• After a Pi2 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 Pi2 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.

• Pi2 ECSs support automatic recovery when the hosts accommodating such ECSs become faulty.
• By default, Pi2 ECSs created using a public image have the Tesla driver installed.
• If a Pi2 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.