tencent cloud

Cloud GPU Service

Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads.

Strengths
Ultimate Parallel Computing Capabilities
Ultimate Parallel Computing Capabilities

Improve your business efficiency and competitiveness with high-performance parallel computing capabilities

Quick Environment Deployment
Quick Environment Deployment

Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images

Native Acceleration Engine
Native Acceleration Engine

Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud

Specification Recommendation
spot instance
GPU Computing GN7
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
$0.204
/hour
Buy Now
GPU Computing GN7
spot instance
$0.204
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
Pay-As-You-Go
GPU Computing GN10Xp
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
$23.54
/hour
Buy Now
GPU Computing GN10Xp
Pay-As-You-Go
$23.54
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
Pay-As-You-Go
GPU Computing GN10Xp
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
$23.54
/hour
Buy Now
GPU Computing GN10Xp
Pay-As-You-Go
$23.54
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
spot instance
GPU Computing GN7
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
$0.204
/hour
Buy Now
GPU Computing GN7
spot instance
$0.204
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
spot instance
GPU Rendering GN7vw
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
16-core
Memory
64GB
GPU
1
Packet sending/receiving capabilities
1.5 million PPS
$0.242
/hour
Buy Now
GPU Rendering GN7vw
spot instance
$0.242
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
16-core
Memory
64GB
GPU
1
Packet sending/receiving capabilities
1.5 million PPS
spot instance
GPU Computing GN7
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
$0.204
/hour
Buy Now
GPU Computing GN7
spot instance
$0.204
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
Pay-As-You-Go
GPU Computing GN10Xp
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
$23.54
/hour
Buy Now
GPU Computing GN10Xp
Pay-As-You-Go
$23.54
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
Pay-As-You-Go
GPU Computing GN10Xp
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
$23.54
/hour
Buy Now
GPU Computing GN10Xp
Pay-As-You-Go
$23.54
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla® V100 NVLink 32GB
CPU
80-core
Memory
320GB
GPU
8
Packet sending/receiving capabilities
4.9 million PPS
spot instance
GPU Computing GN7
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
$0.204
/hour
Buy Now
GPU Computing GN7
spot instance
$0.204
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
8-core
Memory
32GB
GPU
1
Packet sending/receiving capabilities
600,000 PPS
spot instance
GPU Rendering GN7vw
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
16-core
Memory
64GB
GPU
1
Packet sending/receiving capabilities
1.5 million PPS
$0.242
/hour
Buy Now
GPU Rendering GN7vw
spot instance
$0.242
/hour
Buy Now
Intel Xeon Cascade Lake 8255C(2.5 GHz) + NVIDIA® Tesla T4
CPU
16-core
Memory
64GB
GPU
1
Packet sending/receiving capabilities
1.5 million PPS
Solutions

All-True Internet Solution

For rendering, gaming, virtual humans, and NFT art

Rendering Solution

Ease of use, workflow automation, and comprehensive monitoring

AI-Enabled Moderation Solution for Game Live Streaming Platform

Rapidly scale up to meet your business requirements

Autonomous Driving Solution

Proccess massive data in the most cost-effective way

All-True Internet Solution

All-True Internet Solution

Customer challenges:

To deliver a highly immersive and vivid experience, virtual worlds rely on powerful computing for rendering and other highly demanding workloads. However, most mobile phones and other end-user devices don't have the hardware performance to sustain intense rendering. Moreover, software packages that contain the required rendering engines and other various materials often reach gigabytes in size, occupying massive storage space on the user’s device.

Solution:

With Tencent Cloud's powerful GPU computing power, this solution integrates enterprise-grade rendering, qGPU-based container-level resource splitting and virtualization technologies, video encoding and decoding technologies, and cloud-based streaming solutions. It delivers high computing power for rendering in the cloud, so end users only need to connect to the network to access high-performance rendering. This frees up the resources and storage on end-user devices and delivers a smooth cloud-edge integration experience.

Benefits of cloud deployment:

The cloud native-based solution allows for canary release and rapid launch of your business. Elastic scaling allows you to schedule massive numbers of resources, so you can easily scale your business to adapt to peak and off-peak hours. Combined with the qGPU virtualization sharing technology featuring GPU computing power and VRAM isolation, it can greatly increase GPU utilization while reducing your enterprise costs.

The new-generation Cloud GPU Service provides high-density encoding computing power and a higher network performance. Joining hands with NVIDIA, it is China's first one-stop CloudXR solution and guarantees smooth, lightweight user experience for VR applications.

Related Products

Rendering Solution

Rendering Solution

Customer challenges:

In industries such as movie, TV, advertising, and architectural planning, content creators and post-production teams rely on a large number of machines to complete the rendering work related to visual effects, 3D animations, and design sketches.

Traditional IDC resources often struggle to meet high rendering demands during occasional peak hours, and idle resources are wasted during off-peak hours. This means that upfront investment costs are very high, while return on investment is slow, making it difficult for the enterprise business to expand.

Solution:

Tencent provides various professional GPU Rendering instances, which work with BatchCompute to enable teams to automate their content rendering workflows. Creative and technical professionals can build their own rendering-dependent processes by leveraging Cloud GPU Service's massive computing resources and BatchCompute's job scheduling capabilities to complete their visual creation projects more efficiently.

Benefits of cloud deployment:

Cloud GPU Service allows you to quickly create and manage clusters and select the GPU models and quantities you need to fully sustain your rendering needs.

Jobs are configurable, easy to use, and reusable. You can set up a job flow that is specifically tailored to your process and rendering logic, all in the cloud.

Cloud GPU Service provides a multidimensional job and resource monitoring system, eliminating the need to worry about Ops at the IaaS layer.

Related Products

AI-Enabled Moderation Solution for Game Live Streaming Platform

AI-Enabled Moderation Solution for Game Live Streaming Platform

Customer challenges:

The business was growing, and the self-built cluster had a long scaling period, which could hardly sustain the ever-increasing video moderation tasks.

The hardware devices in the self-built cluster were old, and the computing, storage, and network performance could no longer sustain the business's requirements for high concurrency and low latency.


Solution:

The large-scale GPU-based inference cluster supports a massive number of data samples. A cluster can be scaled quickly to sustain a high number of concurrent requests, eliminating performance bottlenecks.

The high-performance training cluster works with Turbo high-throughput storage to quickly train and iterate models, increasing the video moderation accuracy as well as the moderation success rate.


Benefits of cloud deployment:

Cloud GPU Service supports elastic scaling, so you can quickly adjust the service scale based on your current business needs. You can purchase and utilize computing power when you need it, allowing you to vastly reduce your upfront investment costs.

Related Products

Autonomous Driving Solution

Autonomous Driving Solution

Customer challenges:

Autonomous driving systems collect data through in-vehicle sensors and cameras, which generate several terabytes of data every day. These massive amounts of data need to be analyzed and processed quickly and stored persistently. Therefore, a large-scale computing cluster with high-IOPS, high-performance storage, and high-bandwidth network infrastructure is required to fully satisfy the computing and storage needs at different stages such as annotation, training, and simulation.


Solution:

Cloud GPU Service provides a CPM High-Performance Computing cluster enabled by powerful V100 and A100 GPUs, which allow it to sustain the high-performance computing required by autonomous driving systems.

The High-Performance Computing cluster supports interconnection over a 100 GiB RDMA network. It can be used with GooseFS to improve the efficiency of large-scale distributed clusters used for training.

COS stores data in a cross-infrastructure, multi-device, and redundant manner and provides remote disaster recovery and resource isolation capabilities to guarantee data durability and security.


Benefits of cloud deployment:

Cloud GPU Service allows you to run large-scale parallel simulations with high-elasticity and cost-effective storage. It provides full-linkage services that enable automakers and R&D teams to develop and optimize autonomous driving technology more quickly at lower costs.

Related Products
Solutions
All-True Internet Solution

Customer challenges:

To deliver a highly immersive and vivid experience, virtual worlds rely on powerful computing for rendering and other highly demanding workloads. However, most mobile phones and other end-user devices don't have the hardware performance to sustain intense rendering. Moreover, software packages that contain the required rendering engines and other various materials often reach gigabytes in size, occupying massive storage space on the user’s device.

Solution:

With Tencent Cloud's powerful GPU computing power, this solution integrates enterprise-grade rendering, qGPU-based container-level resource splitting and virtualization technologies, video encoding and decoding technologies, and cloud-based streaming solutions. It delivers high computing power for rendering in the cloud, so end users only need to connect to the network to access high-performance rendering. This frees up the resources and storage on end-user devices and delivers a smooth cloud-edge integration experience.

Benefits of cloud deployment:

The cloud native-based solution allows for canary release and rapid launch of your business. Elastic scaling allows you to schedule massive numbers of resources, so you can easily scale your business to adapt to peak and off-peak hours. Combined with the qGPU virtualization sharing technology featuring GPU computing power and VRAM isolation, it can greatly increase GPU utilization while reducing your enterprise costs.

The new-generation Cloud GPU Service provides high-density encoding computing power and a higher network performance. Joining hands with NVIDIA, it is China's first one-stop CloudXR solution and guarantees smooth, lightweight user experience for VR applications.

Related Products
Rendering Solution

Customer challenges:

In industries such as movie, TV, advertising, and architectural planning, content creators and post-production teams rely on a large number of machines to complete the rendering work related to visual effects, 3D animations, and design sketches.

Traditional IDC resources often struggle to meet high rendering demands during occasional peak hours, and idle resources are wasted during off-peak hours. This means that upfront investment costs are very high, while return on investment is slow, making it difficult for the enterprise business to expand.

Solution:

Tencent provides various professional GPU Rendering instances, which work with BatchCompute to enable teams to automate their content rendering workflows. Creative and technical professionals can build their own rendering-dependent processes by leveraging Cloud GPU Service's massive computing resources and BatchCompute's job scheduling capabilities to complete their visual creation projects more efficiently.

Benefits of cloud deployment:

Cloud GPU Service allows you to quickly create and manage clusters and select the GPU models and quantities you need to fully sustain your rendering needs.

Jobs are configurable, easy to use, and reusable. You can set up a job flow that is specifically tailored to your process and rendering logic, all in the cloud.

Cloud GPU Service provides a multidimensional job and resource monitoring system, eliminating the need to worry about Ops at the IaaS layer.

Related Products
AI-Enabled Moderation Solution for Game Live Streaming Platform

Customer challenges:

The business was growing, and the self-built cluster had a long scaling period, which could hardly sustain the ever-increasing video moderation tasks.

The hardware devices in the self-built cluster were old, and the computing, storage, and network performance could no longer sustain the business's requirements for high concurrency and low latency.


Solution:

The large-scale GPU-based inference cluster supports a massive number of data samples. A cluster can be scaled quickly to sustain a high number of concurrent requests, eliminating performance bottlenecks.

The high-performance training cluster works with Turbo high-throughput storage to quickly train and iterate models, increasing the video moderation accuracy as well as the moderation success rate.


Benefits of cloud deployment:

Cloud GPU Service supports elastic scaling, so you can quickly adjust the service scale based on your current business needs. You can purchase and utilize computing power when you need it, allowing you to vastly reduce your upfront investment costs.

Related Products
Autonomous Driving Solution

Customer challenges:

Autonomous driving systems collect data through in-vehicle sensors and cameras, which generate several terabytes of data every day. These massive amounts of data need to be analyzed and processed quickly and stored persistently. Therefore, a large-scale computing cluster with high-IOPS, high-performance storage, and high-bandwidth network infrastructure is required to fully satisfy the computing and storage needs at different stages such as annotation, training, and simulation.


Solution:

Cloud GPU Service provides a CPM High-Performance Computing cluster enabled by powerful V100 and A100 GPUs, which allow it to sustain the high-performance computing required by autonomous driving systems.

The High-Performance Computing cluster supports interconnection over a 100 GiB RDMA network. It can be used with GooseFS to improve the efficiency of large-scale distributed clusters used for training.

COS stores data in a cross-infrastructure, multi-device, and redundant manner and provides remote disaster recovery and resource isolation capabilities to guarantee data durability and security.


Benefits of cloud deployment:

Cloud GPU Service allows you to run large-scale parallel simulations with high-elasticity and cost-effective storage. It provides full-linkage services that enable automakers and R&D teams to develop and optimize autonomous driving technology more quickly at lower costs.

Related Products
Success Stories

Cloud GPU Service is an elastic computing service that provides GPU computing power and has high-performance parallel computing capabilities. It offers easily accessible computing power, effectively relieving your computing pressure, improving your business efficiency and competitiveness, and empowering your business success.

Ubitus
Ubitus
Ubitus' cloud game service leverages a distributed service-oriented architecture to accelerate high numbers of compute-intensive tasks in the cloud, such as multimedia conversion and game image compression. Tencent Cloud provides diverse GPU instance specifications and storage resources to adapt to Ubitus' business load, helping it increase the utilization and achieve operating goals at lower costs.
WeBank
WeBank
WeBank's face recognition-based identity verification technology relies on Cloud GPU Service, which deploys large-scale inference clusters to respond to verification requests in real time. This well solves the biggest problem in financial service efficiency optimization.
WeChat
WeChat
The massive amount of data on WeChat makes the compute resource usage and training time soar. The original CPU clusters generally would need several hours to complete a training task, seriously compromising the service iteration speed. In contrast, by using multi-instance multi-card distributed GPU training, a task can be completed in minutes now.
FAQs
In what cases should I use a GPU instance?
How do I select a GPU instance model?
How do I select a driver based on the instance model and scenario?
Does Cloud GPU Service allow you to adjust the configuration of an instance?
What should I do if the resources are sold out when I purchase an instance?
How are GPU instances billed?
How can I get the estimated price of GPU instances?
What is the difference between a private IP and a public IP of a GPU instance?
What is an EIP?
What storage options does Cloud GPU Service offer?
What storage options does a CPM GPU instance offer?
How do I back up data in a GPU instance?
What is a region?
How do I select an appropriate region?
How are AZs isolated from each other?
Where can I find more information on security?
How do I prevent others from viewing my system?
How do I troubleshoot security issues?
Does Cloud GPU Service provide images with a preinstalled GPU driver?
What types of images are available?
What is a shared image?
How many users can I share an image with?
Tencent Cloud GPU Service

An Ultimate Parallel Computing Capabilities and Professional Computing Acceleration Service. We are committed to providing you with a personalized presales consultation service.