NVIDIA GPU GN* instances provide powerful computing capabilities to help you process a large number of concurrent computing tasks in real time. NVIDIA GPU instances are not only suitable for general computing scenarios such as deep learning and scientific computing, but also graphic and image processing such as 3D rendering and video encoding and decoding. Tencent Cloud GPU Cloud Computing (GCC) provides a fast, stable, and elastic computing service and allows you to manage NVIDIA GPU instances the same way you manage CVM instances.
NVIDIA GPU instances are categorized into rendering and computing types:
GCC provides the following types of NVIDIA GPU instances:
Type | NVIDIA GPU instance |
GPU type | GPU performance | Availability zone |
---|---|---|---|---|
Computing | GN10X or GN10Xp | Tesla V100 NVLink 32GB |
|
|
GN8 | Tesla P40 |
|
Hong Kong (China), Guangzhou, Shanghai, Beijing, Chengdu, Chongqing, and Silicon Valley | |
GN7 | Tesla T4 |
|
Guangzhou, Shanghai, Nanjing, Beijing, Chengdu, Chongqing, Singapore, and Silicon Valley | |
GN6 or GN6S | Tesla P4 |
|
|
|
GN2 | Tesla M40 |
|
Guangzhou, Shanghai, and Beijing | |
Rendering | GN7vw | Tesla T4 |
|
- |
Note:
Availability zone: accurate to the city level. For more information, please see the instance configuration information below.
Tencent Cloud provides NVIDIA GPU instances to meet business needs in different scenarios. Refer to the following tables to select an NVIDIA GPU instance as needed.
The table below lists recommended NVIDIA GPU instances provided by GCC. A tick (✓) indicates that the NVIDIA GPU instance supports the corresponding feature. A pentagram (★) indicates that the NVIDIA GPU instance is recommended.
Feature\Instance | GN2 | GN6 or GN6S | GN7 | GN8 | GN10X or GN10Xp |
---|---|---|---|---|---|
Graphic and image processing | - | ✓ | ✓ | ✓ | ✓ |
Video encoding and decoding | ✓ | ✓ | ★ | ✓ | ✓ |
Deep learning training | ✓ | ✓ | ✓ | ★ | ★ |
Deep learning inference | ✓ | ★ | ★ | ★ | ✓ |
Scientific computing | ✓ | - | - | - | ★ |
Note:
GN2 supports video encoding and decoding in H.264 format, but not H.265. For more information, please see Video Encode and Decode GPU Support Matrix.
Except for GN2, other types of NVIDIA GN* instances allow you to install a GRID driver to process graphics and images. To use the GRID driver, you must purchase a license.
Recommended instance: GN7. GN7 uses T4 GPU. It features high performance and the lowest cost for transcoding a single video, making it suitable for video encoding and decoding.
Recommended instance: GN8, GN10X, or GN10Xp. GN8 and GN10X use P40 or V100 mid- to high-end GPU. They feature powerful single-precision floating-point computing capabilities and large on-board memories, making them ideal for deep learning training.
Recommended instance: GN6, GN6S, GN7, or GN8. These instances use P4, T4, or P40 GPU. They feature INT8 computing capabilities and cost-efficiency, making them suitable for mass deployment.
Recommended instance: GN10X or GN10Xp. GN10X and GN10Xp use V100 GPU. They feature powerful double-precision floating-point computing capabilities and provide optimal acceleration for computational science and engineering applications.
Note:
- These recommendations are for reference only. Please select an appropriate instance based on your needs.
- To use NVIDIA GPU instances for general computing tasks, you must install the Tesla driver and CUDA toolkit. For more information, please see Installing NVIDIA Driver and Installing CUDA Toolkit.
- To use NVIDIA GPU instances for 3D rendering tasks such as high-performance graphic processing and video encoding and decoding, you must install a GRID driver and configure a license server.
NVIDIA GPU instances GN10X and GN10Xp support not only general GPU computing tasks such as deep learning and scientific computing, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
GN10X and GN10Xp feature powerful double-precision floating-point computing capabilities. They are applicable to the following scenarios:
GN10X and GN10Xp instances provide the following configurations:
Model | GPU (NVIDIA Tesla V100 NVLink 32GB) |
GPU memory (HBM2) |
vCPU | Memory (DDR4) |
Private network bandwidth | Packet forwarding rate (PPS) | Number of queues | Availability zone |
---|---|---|---|---|---|---|---|---|
GN10X.2XLARGE40 | 1 | 1 * 32 GB | 8 cores | 40 GB | 4 Gbps | 800,000 | 2 | Guangzhou Zone 3, Guangzhou Zone 4, Shanghai Zone 2, Shanghai Zone 3, Nanjing Zone 1, Beijing Zone 4, Beijing Zone 5, Chengdu Zone 1, Chongqing Zone 1, Singapore Zone 1, and Silicon Valley Zone 2 |
GN10X.9XLARGE160 | 4 | 4 * 32 GB | 36 cores | 160 GB | 13 Gbps | 2.5 million | 9 | |
GN10X.18XLARGE320 | 8 | 8 * 32 GB | 72 cores | 320 GB | 25 Gbps | 4.9 million | 16 | |
GN10X.4XLARGE80 | 2 | 2 * 32 GB | 18 cores | 80 GB | 7 Gbps | 1.5 million | 4 | Guangzhou Zone 3, Guangzhou Zone 4, Nanjing Zone 1, Chengdu Zone 1, and Chongqing Zone 1 |
GN10X.MEDIUM10 | 1/4 | 8 GB vGPU | 2 cores | 10 GB | 1 Gbps | 200,000 | 2 | - |
GN10X.LARGE20 | 1/2 | 16 GB vGPU | 4 cores | 20 GB | 2 Gbps | 400,000 | 2 | |
GN10Xp.2XLARGE40 | 1 | 1 * 32 GB | 10 cores | 40 GB | 4 Gbps | 800,000 | 10 | Guangzhou Zone 3, Guangzhou Zone 4, Shanghai Zone 2, Nanjing Zone 1, Beijing Zone 5, Chengdu Zone 1, and Chongqing Zone 1 |
GN10Xp.5XLARGE80 | 2 | 2 * 32 GB | 20 cores | 80 GB | 7 Gbps | 1.5 million | 16 | |
GN10Xp.10XLARGE160 | 4 | 4 * 32 GB | 40 cores | 160 GB | 13 Gbps | 2.5 million | 16 | |
GN10Xp.20XLARGE320 | 8 | 8 * 32 GB | 80 cores | 320 GB | 25 Gbps | 4.9 million | 16 |
Note:
vGPU: GN10X instance cluster provides vGPU-based instances, which are currently in beta. The vGPU type is vComputeServer, which only supports CUDA APIs.
NVIDIA GPU instance GN8 supports not only general GPU computing tasks such as deep learning, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
GN8 is applicable to the following scenarios:
GN8 instance provides the following configurations:
Model | GPU (NVIDIA Tesla P40) |
GPU memory (GDDR5) |
vCPU | Memory (DDR4) |
Private network bandwidth | Packet forwarding rate (PPS) | Number of queues | Availability zone |
---|---|---|---|---|---|---|---|---|
GN8.LARGE56 | 1 | 24 GB | 6 cores | 56 GB | 1.5 Gbps | 450,000 | 6 | Hong Kong Zone 2, Guangzhou Zone 3, Shanghai Zone 3, Beijing Zone 2, Beijing Zone 4, Chengdu Zone 1, Chongqing Zone 1, and Silicon Valley Zone 1 |
GN8.3XLARGE112 | 2 | 48 GB | 14 cores | 112 GB | 2.5 Gbps | 500,000 | 8 | |
GN8.7XLARGE224 | 4 | 96 GB | 28 cores | 224 GB | 5 Gbps | 700,000 | 8 | |
GN8.14XLARGE448 | 8 | 192 GB | 56 cores | 448 GB | 10 Gbps | 700,000 | 8 |
NVIDIA GPU instance GN7 supports not only general GPU computing tasks such as deep learning, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
GN7 is cost-effective and applicable to the following scenarios:
GN7 instance provides the following configurations:
Model | GPU (NVIDIA Tesla T4) |
GPU memory (GDDR6) |
vCPU | Memory (DDR4) |
Private network bandwidth | Packet forwarding rate (PPS) | Number of queues | Availability zone |
---|---|---|---|---|---|---|---|---|
GN7.LARGE20 | 1/4 | 4 GB vGPU | 4 cores | 20 GB | 2 Gbps | 500,000 | 4 | Guangzhou Zone 3, Guangzhou Zone 4, Shanghai Zone 2, Shanghai Zone 4, Nanjing Zone 1, Nanjing Zone 2, Beijing Zone 3, Beijing Zone 5, Chengdu Zone 1, Chongqing Zone 1, and Silicon Valley Zone 2 |
GN7.2XLARGE40 | 1/2 | 8 GB vGPU | 10 cores | 40 GB | 4 Gbps | 700,000 | 10 | |
GN7.2XLARGE32 | 1 | 1 * 16 GB | 8 cores | 32 GB | 7 Gbps | 600,000 | 8 | Guangzhou Zone 3, Guangzhou Zone 4, Shanghai Zone 2, Shanghai Zone 4, Nanjing Zone 1, Nanjing Zone 2, Beijing Zone 3, Beijing Zone 5, Chengdu Zone 1, Chongqing Zone 1, Singapore Zone 1, and Silicon Valley Zone 2 |
GN7.5XLARGE80 | 1 | 1 * 16 GB | 20 cores | 80 GB | 7 Gbps | 1.4 million | 16 | |
GN7.8XLARGE128 | 1 | 1 * 16 GB | 32 cores | 128 GB | 7 Gbps | 2.4 million | 16 | |
GN7.10XLARGE160 | 2 | 2 * 16 GB | 40 cores | 160 GB | 13 Gbps | 2.8 million | 16 | |
GN7.20XLARGE320 | 4 | 4 * 16 GB | 80 cores | 320 GB | 25 Gbps | 5.6 million | 16 |
Note:
vGPU: GN7 instance cluster provides vGPU-based instances. The vGPU type is vComputeServer, which only supports CUDA APIs.
NVIDIA GPU instances GN6 and GN6S support not only general GPU computing tasks such as deep learning, but also graphic and image processing tasks such as 3D rendering and video encoding and decoding.
GN6 and GN6S are cost-effective and applicable to the following scenarios:
GN6 and GN6S instances provide the following configurations:
Model | GPU (NVIDIA Tesla P4) |
GPU memory (GDDR5) |
vCPU | Memory (DDR4) |
Private network bandwidth | Packet forwarding rate (PPS) | Number of queues | Availability zone |
---|---|---|---|---|---|---|---|---|
GN6.7XLARGE48 | 1 | 8 GB | 28 cores | 48 GB | 5 Gbps | 1.2 million | 16 | Chengdu Zone 1 |
GN6.14XLARGE96 | 2 | 16 GB | 56 cores | 96 GB | 10 Gbps | 1.2 million | 16 | |
GN6S.LARGE20 | 1 | 8 GB | 4 cores | 20 GB | 7 Gbps | 500,000 | 2 | Guangzhou Zone 3, Shanghai Zone 2, Shanghai Zone 3, Shanghai Zone 4, Beijing Zone 4, and Beijing Zone 5 |
GN6S.2XLARGE40 | 2 | 16 GB | 8 cores | 40 GB | 13 Gbps | 800,000 | 2 |
NVIDIA GPU instance GN2 supports not only general GPU computing tasks such as deep learning and scientific computing, but also graphic and image processing tasks such as video encoding and decoding.
GN2 is applicable to deep learning training and inference as well as scientific computing scenarios, such as:
GN2 is also applicable to graphic and image processing scenarios. For example, GN2 supports video encoding and decoding in H.264 format, but not H.265. For more information, please see Video Encode and Decode GPU Support Matrix.
GN2 instance provides the following configurations:
Model | GPU (NVIDIA Tesla M40) |
GPU memory (GDDR5) |
vCPU | Memory (DDR4) |
Private network bandwidth | Packet forwarding rate (PPS) | Number of queues | Availability zone |
---|---|---|---|---|---|---|---|---|
GN2.7XLARGE48 | 1 | 24 GB | 28 cores | 48 GB | 5 Gbps | 400,000 | 8 | Guangzhou Zone 3, Beijing Zone 2, and Shanghai Zone 2 |
GN2.14XLARGE96 | 2 | 48 GB | 56 cores | 96 GB | 10 Gbps | 700,000 | 8 | |
GN2.7XLARGE56 | 1 | 24 GB | 28 cores | 56 GB | 5 Gbps | 400,000 | 8 | Guangzhou Zone 3, Beijing Zone 2, and Shanghai Zone 2 |
GN2.14XLARGE112 | 2 | 48 GB | 56 cores | 112 GB | 10 Gbps | 700,000 | 8 |
GN7vw is applicable to graphic and image processing scenarios, such as:
Was this page helpful?