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Overview

Last updated: 2022-04-19 16:46:18

    GPU Cloud Computing is a fast, stable and elastic GPU-based computing service. It's applicable to training or reasoning of deep learning, graphics and image processing, and scientific computing, etc. GPU Cloud Computing is easily managed in the same way as the CVMs. With the powerful computing performance of processing massive data, it can effectively relieve the computing pressure of users and improve the efficiency and competitiveness of business processing.

    Why GPU Cloud Computing?

    Comparison between GPU Cloud Computing and Self-built GPU Computing:

    Advantages
    GPU Cloud Computing
    Self-built GPU Computing
    Elastic
    • In just a few minutes, you can easily obtain one or more high-performance computing instances.
    • It can be customized flexibly as needed, and upgraded to an instance specification with higher performance and larger capacity with just one click, to achieve rapid, smooth expansion, and satisfy the requirement for fast business development.
    Fixed configuration makes it hard to satisfy the ever-changing requirements.
    High-performance
    • It supports GPU pass-through to make the most advantage of GPU.
    • Peak computing capacity for a single machine: 125.6T Flops for single-precision floating point computing and 62.4T Flops for double-precision floating point computing.
    • Users have to perform disaster recovery manually, depending on the robustness of hardware.
    • A single point of failure may occur on physical servers. Data security is uncontrollable.
    Easy-to-use
    • It can be seamlessly connected to CVM, CLB and many other Tencent Cloud products. Private network traffic is free of charge.
    • Designed for ease of use, it is managed in the same way as CVMs, without the need to use jump server for login.
    • It provides clear guides on installation and deployment of GPU driver to make it easier for users to get started with it.
    • Users must purchase installation management service to achieve automatic hardware expansion and driver installation.
    • Jump server is required for login with complicated operation procedures.
    Secure
    • Resources are completely isolated among different users to ensure the data security.
    • Complete security groups and network ACL settings allow you to control and securely filter the inbound and outbound network traffic to or from instances and subnets.
    • It can be seamlessly connected to Tencent Cloud security serices, just the same as CVM.
    • Resources are shared among different users, and data is not isolated.
    • Additional security protection services must be purchased.
    Low-cost
    • It supports monthly subscription. You can purchase physical servers without the need to make a huge one-off investment.
    • Hardware is updated with the mainstream GPU, eliminating the need to replace the hardware after each update.
    • With low server OPS cost, you can effectively reduce investment in infrastructure construction without the need to purchase and prepare hardware resources in advance.
    • High server investment and operating costs.
    • Due to high power consumption of devices, hardware modification is required.
    • Higher IT OPS cost is required to guarantee the stability of service.

    Comparison between GPU Cloud Computing and CPU Cloud Computing:

    Dimension GPU CPU
    Number of Kernels Thousands of accelerated kernels (dual ENI, M40, and up to 6,144 accelerated kernels) Dozens of kernels
    Product Features 1. Numerous efficient arithmetic logic units (ALU) support parallel processing
    2. Massively parallel throughput can be achieved using multiple threads
    3. Simple logic control
    1. Complex logic control unit
    2. Powerful ALUs
    3. Simple logic control
    Application Scenario Compute-intensive applications that support parallel processing Applications with logic control and serial arithmetic
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