GPU Type
GPU cloud servers can provide excellent floating-point computing capabilities, easily handling massive computational scenarios with high real-time and high concurrency requirements. Especially suitable for applications such as deep learning, scientific computing, CAE, 3D animation rendering, and CAD.
Currently, there are two major categories provided: Compute Acceleration and Graphics Acceleration.
Among them, the compute acceleration type of GPU cloud server currently supports both Nvidia and Ascend graphics cards; the graphics acceleration foundation type supports Nvidia graphics cards.
GPU Computing Accelerated
The GPU computing acceleration type of GPU cloud server utilizes GPU hardware pass-through technology, mainly suitable for scenarios such as AI deep learning training, inference, scientific computing, video transcoding, and graphic processing.
On Sale: PI7 and PI2
Features of Compute Acceleration GPU Cloud Servers
Specification Name | GPU Model | Quantity of GPUs | Single GPU Performance | Disk Type |
P8A | Nvidia Tesla A100 (40G PCIE) | 1,2,4 | 19.5 TFLOPS Single Precision Floating Point Calculation | Standard IO |
PI7 | Nvidia Tesla A10 | 1,2,4 | 31.2 TFLOPS Single Precision Floating Point Calculation | Standard IO |
P2V | Nvidia Tesla V100 | 1,2,4 | 14 TFLOPS Single Precision Floating Point Calculation | Standard IO |
P2Vs | Nvidia Tesla V100s | 1,2,4 | 16.4 TFLOPS Single Precision Floating Point Calculation | Standard IO |
PI2 | Nvidia Tesla T4 | 1,2,4 | 8.1 TFLOPS Single Precision Floating Point Calculation | Standard IO |
PAK1 | Atlas 300I pro | 1,2,4 | 70 TFLOPS Half Precision Floating Point Calculation | Standard IO |
P8A Type Cloud Server
The P8A model cloud server is equipped with an NVIDIA A100 40GB PCIe GPU and utilizes GPU pass-through technology. While providing the flexibility of a cloud server, it offers high-performance computing capabilities and excellent cost-effectiveness. A single card can provide up to 77.97 TFLOPS of half-precision floating-point computing power and 9.746 TFLOPS of double-precision floating-point computing power. The P8A model cloud server can provide ultra-high general computing capabilities, suitable for AI deep learning and scientific computing. It can demonstrate significant computational advantages in fields such as deep learning training, scientific computing, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, and genomics.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type | Maximum Bandwidth (Gbps) / Baseline Bandwidth (Gbps) | Number of NIC Queues | Maximum Packet Handling Capacity (in 10,000 PPS) |
p8a.6xlarge.4 | 24 | 96 | 1×A100 | 1×40GB | KVM | 30/11 | 8 | 300 |
p8a.12xlarge.4 | 48 | 192 | 2×A100 | 2×40GB | KVM | 36/23 | 16 | 600 |
p8a.24xlarge.4 | 96 | 384 | 4×A100 | 4×40GB | KVM | 47/45 | 32 | 1000 |
Common Software Compatibility List
The P8A model cloud server is primarily designed for compute-acceleration scenarios, such as deep learning training, inference, scientific computing, molecular modeling, seismic analysis, and other similar applications. If the application software utilizes the CUDA parallel computing capabilities of the GPU, the P8A model cloud server can be used. The common software support list is as follows:
Common deep learning frameworks: TensorFlow, Caffe, PyTorch, MXNet
RedShift for Autodesk 3dsMax, V-Ray for 3ds Max, and other CUDA-enabled GPU rendering software
Tips for Use
The P8A model cloud server currently supports the following versions of operating systems:
Windows Server 2019 Datacenter 64bit
Windows Server 2016 Datacenter 64bit
CentOS 8.1 64bit
CentOS 7.8 64bit
Ubuntu Server 20.04 64bit
Ubuntu Server 18.04 64bit
PI7 model cloud server
The PI7 model cloud server is equipped with the NVIDIA A10 Tensor Core GPU, which is specifically designed for AI inference. With GPU pass-through technology, it can provide extremely powerful real-time inference capabilities. The PI7 model elastic cloud server, with the help of the A10, can provide a maximum of 31.2 TFLOPS of FP32 computing power per card.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type | Maximum Bandwidth (Gbps) / Baseline Bandwidth (Gbps) | Number of NIC Queues | Maximum Packet Handling Capacity (in 10,000 PPS) |
pi7.4xlarge.4 | 16 | 64 | 1×A10 | 1×24GB | KVM | 17/7.5 | 8 | 200 |
pi7.8xlarge.4 | 32 | 128 | 2×A10 | 2×24GB | KVM | 25/15 | 16 | 400 |
pi7.16xlarge.4 | 64 | 256 | 4×A10 | 4×24GB | KVM | 47/45 | 32 | 800 |
Commonly Supported Software List
The PI7 model is primarily used for GPU inference computing scenarios, such as image recognition, speech recognition, natural language processing, and other similar applications. It can also support lightweight training scenarios and video encoding/decoding scenarios.
The common software support list is as follows:
Common deep learning frameworks: TensorFlow, Caffe, PyTorch, MXNet
RedShift for Autodesk 3dsMax, V-Ray for 3ds Max, and other CUDA-enabled GPU rendering software
Tips for Use
The PI7 model cloud server currently supports the following versions of operating systems:
Windows Server 2019 Datacenter 64bit
Windows Server 2016 Datacenter 64bit
CentOS 8.1 64bit
CentOS 7.8 64bit
Ubuntu Server 20.04 64bit
Ubuntu Server 18.04 64bit
P2V model cloud server
The P2V model cloud server is equipped with the NVIDIA Tesla V100 PCIe GPU and utilizes GPU pass-through technology. While offering the flexibility of a cloud server, it delivers high-performance computing capabilities and excellent cost-effectiveness. The P2V model cloud server can provide ultra-high general computing capabilities, suitable for AI deep learning and scientific computing. It can demonstrate significant computational advantages in fields such as deep learning training, scientific computing, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, and genomics.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type |
p2v.4xlarge.8 | 16 | 128 | 1*V100 | 1*32GB | KVM |
p2v.8xlarge.8 | 32 | 256 | 2*V100 | 2*32GB | KVM |
p2v.2xlarge.4 | 8 | 32 | 1*V100 | 1*32GB | KVM |
p2v.4xlarge.4 | 16 | 64 | 2*V100 | 2*32GB | KVM |
p2v.8xlarge.4 | 32 | 128 | 4*V100 | 4*32GB | KVM |
Common Software Compatibility List
The P2V model cloud server is primarily designed for compute-acceleration scenarios, such as deep learning training, inference, scientific computing, molecular modeling, seismic analysis, and other similar applications. If the application software utilizes the CUDA parallel computing capabilities of the GPU, the P2V model cloud server can be used. The common software support list is as follows:
Common deep learning frameworks: TensorFlow, Caffe, PyTorch, MXNet
RedShift for Autodesk 3dsMax, V-Ray for 3ds Max, and other CUDA-enabled GPU rendering software
Tips for Use
The P2V model cloud server currently supports the following versions of operating systems:
Windows Server 2019 Datacenter 64bit
Windows Server 2016 Datacenter 64bit
CentOS 8.1 64bit
CentOS 7.8 64bit
Ubuntu Server 20.04 64bit
Ubuntu Server 18.04 64bit
P2Vs model cloud server
The P2Vs model cloud server is equipped with the NVIDIA Tesla V100s PCIe GPU and utilizes GPU pass-through technology. While offering the flexibility of a cloud server, it delivers high-performance computing capabilities and excellent cost-effectiveness. The P2Vs model cloud server can provide ultra-high general computing capabilities, suitable for AI deep learning and scientific computing. It can demonstrate significant computational advantages in fields such as deep learning training, scientific computing, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, and genomics.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type |
p2vs.4xlarge.8 | 16 | 128 | 1*V100s | 1*32GB | KVM |
p2vs.8xlarge.8 | 32 | 256 | 2*V100s | 2*32GB | KVM |
Common Software Compatibility List
The P2Vs model cloud server is primarily designed for compute-acceleration scenarios, such as deep learning training, inference, scientific computing, molecular modeling, seismic analysis, and other similar applications. If the application software utilizes the CUDA parallel computing capabilities of the GPU, the P2Vs model cloud server can be used. The common software support list is as follows:
Common deep learning frameworks: TensorFlow, Caffe, PyTorch, MXNet
RedShift for Autodesk 3dsMax, V-Ray for 3ds Max, and other CUDA-enabled GPU rendering software
Tips for Use
The P2Vs model cloud server currently supports the following versions of operating systems:
Windows Server 2019 Datacenter 64bit
Windows Server 2016 Datacenter 64bit
CentOS 8.1 64bit
CentOS 7.8 64bit
Ubuntu Server 20.04 64bit
Ubuntu Server 18.04 64bit
PI2 model cloud server
The PI2 model cloud server is equipped with the NVIDIA Tesla T4 GPU, which is specifically designed for AI inference. With GPU pass-through technology, it can provide extremely powerful real-time inference capabilities. The PI2 model elastic cloud server, with the help of the T4's INT8 processor, can provide a maximum of 130
TOPS of INT8 computing power. The PI2 can also support lightweight training scenarios.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type |
pi2.2xlarge.4 | 8 | 32 | 1×T4 | 1×16GB | KVM |
pi2.4xlarge.4 | 16 | 64 | 2×T4 | 2×16GB | KVM |
pi2.8xlarge.4 | 32 | 128 | 4×T4 | 4×16GB | KVM |
Commonly Supported Software List
The PI2 model cloud server is primarily used for GPU inference computing scenarios, such as image recognition, speech recognition, natural language processing, and other similar applications. It can also support lightweight training scenarios.
The common software support list is as follows:
Common deep learning frameworks: TensorFlow, Caffe, PyTorch, MXNet
RedShift for Autodesk 3dsMax, V-Ray for 3ds Max, and other CUDA-enabled GPU rendering software
Tips for Use
The PI2 model cloud server currently supports the following versions of operating systems:
Windows Server 2019 Datacenter 64bit
Windows Server 2016 Datacenter 64bit
CentOS 8.1 64bit
CentOS 7.8 64bit
Ubuntu Server 20.04 64bit
Ubuntu Server 18.04 64bit
PAK1 model cloud server
The PAK1 model Ascend GPU cloud server, equipped with the Atlas 300I Pro accelerator card specifically designed for AI inference, and powered by domestically produced ARM architecture Kunpeng CPU, belongs to the compute acceleration (pass-through) specification. The cloud server has a CPU/memory ratio of 1:4, primarily suitable for inference scenarios such as search recommendation, content audit, and OCR systems.
Series | CPU | Memory | GPU Graphics Card Type | Graphics Memory | Maximum Bandwidth/Base Bandwidth (Gbit/s) | Number of Network Packages Sent and Received (10,000 PPS) | Multi-queue |
pak1.4xlarge.4 | 18 | 72 | Huawei Atlas 300I pro | 1*24G | 18/11.5 | 240 | 8 |
pak1.9xlarge.4 | 36 | 144 | Huawei Atlas 300I pro | 2*24G | 30/22.5 | 480 | 16 |
pak1.18xlarge.4 | 72 | 288 | Huawei Atlas 300I pro | 4*24G | 47/45 | 960 | 32 |
Supported Images
CTyunOS 2.0.1 64-bit ARM version
Note: The PAK1 model GPU cloud server's public images all come with the CANN 3.1.0 development kit package pre-installed by default, and the environment variables have been configured.
GPU image acceleration basic type
The Image Acceleration Basic Type GPU cloud server is based on NVIDIA GRID virtualization GPU technology. The public image integrates the GRID driver and includes the software License for NVIDIA GRID vWS. It can effectively reduce the usage cost for small-scale demands and is suitable for scenarios such as image rendering and small-scale AI inference.
On Sale: G7
Image Acceleration Basic Type GPU Cloud Server features:
Specification Name | GPU Model | Quantity of GPUs | Single GPU Performance | Disk Type |
G7 | Nvidia Tesla A10 | 1/4、1/2、1 | 31.2 TFLOPS Single Precision Floating Point Calculation | Standard IO |
G6 | Nvidia Tesla T4 | 1/4、1/2 | 31.2 TFLOPS Single Precision Floating Point Calculation | Standard IO |
G5 | Nvidia Tesla V100 | 1/16、1/8、1/4、1/2 | 14 TFLOPS Single Precision Floating Point Calculation | Standard IO |
G5s | Nvidia Tesla V100s | 1/16、1/8、1/4、1/2 | 16.4 TFLOPS Single Precision Floating Point Calculation | Standard IO |
G7 model cloud server
The G7 model cloud server, based on NVIDIA GRID virtualization GPU technology, is capable of providing comprehensive professional-level graphics acceleration capabilities. The G7 model cloud server uses the NVIDIA A10 Tensor Core GPU graphics card, capable of supporting DirectX, OpenGL, and Vulkan interfaces. It offers three video memory specifications of 6/12/24 GB and supports a resolution of 7680*4320, meeting the graphic processing needs from entry-level to professional-level.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type | Maximum Bandwidth (Gbps) / Baseline Bandwidth (Gbps) | Number of NIC Queues | Maximum Packet Handling Capacity (in 10,000 PPS) |
g7.2xlarge.4 | 8 | 32 | A10-6Q | 6 | KVM | 8/2.5 | 4 | 110 |
g7.4xlarge.4 | 16 | 64 | A10-12Q | 12 | KVM | 15/4.5 | 8 | 220 |
g7.8xlarge.4 | 32 | 128 | A10-24Q | 24 | KVM | 20/9 | 16 | 440 |
The G7 model cloud server features are as follows:
The processor-to-memory ratio is 1:4
Supports graphics acceleration interfaces:
DirectX 12, Direct2D, DirectX Video Acceleration(DXVA)
OpenGL 4.5
Vulkan 1.0
Supports CUDA and OpenCL
Supports Quadro vDWS features, providing acceleration for professional-grade graphics applications
Supports NVIDIA A10 GPU cards
Supports graphics acceleration applications
Provides GPU hardware virtualization (vGPU)
Provides the same application process as elastic cloud servers.
Automates the scheduling of G7 model elastic cloud servers to available zones equipped with NVIDIA A10 GPU cards
It can provide graphic and image processing capabilities with a maximum video memory of 24GB and a resolution of 7680*4320
Commonly Supported Software List
The G7 model cloud server is primarily used for graphics acceleration scenarios, such as image rendering, cloud laptop, and 3D visualization. Application software that relies on the DirectX and OpenGL hardware acceleration capabilities of the GPU can utilize the G7 model cloud server. The common graphics processing software support list is as follows:
AutoCAD
3DS MAX
MAYA
Agisoft PhotoScan
ContextCapture
Tips for Use
The G7 model cloud server currently supports the following versions of operating systems:
WindowsServer 2019 DataCenter 64bit
Windows Server 2016 DataCenter 64bit
Windows Server 2012 DataCenter 64bit
CentOS 8.1 64bit
CentOS 8.2 64bit
Ubuntu Server 20.04 64bit
G6 model cloud server
The G6 model cloud server, based on NVIDIA GRID virtualization GPU technology and equipped with the NVIDIA Tesla T4 GPU graphics card, supports DirectX, OpenGL, and Vulkan interfaces. It offers 8GiB of video memory and has a theoretical performance of a Pixel Rate of 101.8 GPixel/s and a Texture Rate of 254.4 GTexel/s, meeting the needs of professional-level graphics processing.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type |
g6.xlarge.4 | 4 | 16 | T4-4Q | 4 | KVM |
g6.2xlarge.4 | 8 | 32 | T4-8Q | 8 | KVM |
Commonly Supported Software List
The G6 model cloud server is primarily used for graphics acceleration scenarios, such as image rendering, cloud laptop, and 3D visualization. Application software that relies on the DirectX and OpenGL hardware acceleration capabilities of the GPU can utilize the G6 model cloud server. The common graphics processing software support list is as follows:
AutoCAD
3DS MAX
MAYA
Agisoft PhotoScan
ContextCapture
Tips for Use
The G6 model cloud server currently supports the following versions of operating systems:
Windows Server 2016 Standard 64bit
Windows Server 2012 Standard 64bit
CentOS 7.5 64bit
CentOS 7.6 64bit
Ubuntu Server 16.04 64bit
G5 model cloud server
The G5 model cloud server, based on NVIDIA GRID virtualization GPU technology, is capable of providing comprehensive professional-level graphics acceleration capabilities. The G5 model cloud server uses the NVIDIA Tesla V100 PCIe GPU graphics card, which supports DirectX, OpenGL, and Vulkan interfaces. It offers four video memory specifications: 2 GB, 4 GB, 8 GB, and 16 GB, and supports a maximum resolution of 4096*2160. This meets the graphic processing needs ranging from entry-level to professional-level.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type |
g5.2xlarge.2.1 | 8 | 16 | V100-2Q | 2 | KVM |
g5.2xlarge.2 | 8 | 32 | V100-4Q | 4 | KVM |
g5.2xlarge.8 | 8 | 64 | V100-16Q | 16 | KVM |
g5.4xlarge.4 | 16 | 64 | V100-8Q | 8 | KVM |
g5.8xlarge.4 | 32 | 128 | V100-16Q | 16 | KVM |
The G5 model cloud server features are as follows:
The processor-to-memory ratio is 1:4/1:2/1:8
Supports graphics acceleration interfaces:
DirectX 12, Direct2D, DirectX Video Acceleration(DXVA)
OpenGL 4.5
Vulkan 1.0
Supports CUDA and OpenCL
Supports Quadro vDWS features, providing acceleration for professional-grade graphics applications
Supports NVIDIA V100 GPU cards
Supports graphics acceleration applications
Provides GPU hardware virtualization (vGPU)
Provides the same application process as elastic cloud servers.
Automates the scheduling of G5 model elastic cloud servers to available zones equipped with NVIDIA V100 GPU cards
It can provide graphic processing capabilities with a maximum video memory of 16GB and a resolution of 4096×2160
Commonly Supported Software List
The G5 model cloud server is primarily used for graphics acceleration scenarios, such as image rendering, cloud laptop, and 3D visualization. Application software that relies on the DirectX and OpenGL hardware acceleration capabilities of the GPU can utilize the G5 model cloud server. The common graphics processing software support list is as follows:
AutoCAD
3DS MAX
MAYA
Agisoft PhotoScan
ContextCapture
Tips for Use
The G5 model cloud server currently supports the following versions of operating systems:
Windows Server 2016 Standard 64bit
Windows Server 2012 Standard 64bit
CentOS 7.5 64bit
CentOS 7.6 64bit
Ubuntu Server 16.04 64bit
G5s model cloud server
The G5s model cloud server, based on NVIDIA GRID virtualization GPU technology, is capable of providing comprehensive professional-level graphics acceleration capabilities. The G5s model cloud server uses the NVIDIA Tesla V100s PCIe GPU graphics card, which supports DirectX, OpenGL, and Vulkan interfaces. It offers four video memory specifications: 2 GB, 4 GB, 8 GB, and 16 GB, and supports a maximum resolution of 4096*2160. This meets the graphic processing needs ranging from entry-level to professional-level.
Specification Name | vCPU | Memory (GB) | GPU | Graphics Memory (GB) | Virtualization Type |
g5s.2xlarge.2.1 | 8 | 16 | V100s-2Q | 2 | KVM |
g5s.2xlarge.2 | 8 | 32 | V100s-4Q | 4 | KVM |
g5s.2xlarge.8 | 8 | 64 | V100s-16Q | 16 | KVM |
g5s.4xlarge.4 | 16 | 64 | V100s-8Q | 8 | KVM |
g5s.8xlarge.4 | 32 | 128 | V100s-16Q | 16 | KVM |
The G5s model cloud server features are as follows:
The processor-to-memory ratio is 1:4/1:2/1:8
Supports graphics acceleration interfaces:
DirectX 12, Direct2D, DirectX Video Acceleration(DXVA)
OpenGL 4.5
Vulkan 1.0
Supports CUDA and OpenCL
Supports Quadro vDWS features, providing acceleration for professional-grade graphics applications
Supports NVIDIA V100s GPU cards
Supports graphics acceleration applications
Provides GPU hardware virtualization (vGPU)
It offers the same application process as the elastic cloud server.
Automates the scheduling of G5s model elastic cloud servers to available zones equipped with NVIDIA V100s GPU cards
It can provide graphic processing capabilities with a maximum video memory of 16GB and a resolution of 4096×2160
Commonly Supported Software List
The G5s model cloud server is primarily used for graphics acceleration scenarios, such as image rendering, cloud laptop, and 3D visualization. Application software that relies on the DirectX and OpenGL hardware acceleration capabilities of the GPU can utilize the G5s model cloud server. The common graphics processing software support list is as follows:
AutoCAD
3DS MAX
MAYA
Agisoft PhotoScan
ContextCapture
Tips for Use
The G5s model cloud server currently supports the following versions of operating systems:
Windows Server 2016 Standard 64bit
Windows Server 2012 Standard 64bit
CentOS 7.5 64bit
CentOS 7.6 64bit
Ubuntu Server 16.04 64bit